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Sustainable and Resilient Infrastructure (23789689) 10(1)pp. 40-62
Extreme dust storms (EDSs) are high-impact low-probability natural disasters, and their occurrence in humid climates can damage the power distribution systems (PDSs) as a critical infrastructure. In this paper, proposed a bi-level stochastic framework for simultaneously hardening substations and distribution lines. In the first level, total capital cost is addressed for PDS hardening under the financial constraints, while in the second level, the expected operating costs are minimized in the case of an EDS under the operating constraints. In the proposed model, the location of remote-controled switches (RCSs) is determined based on the PDS hardening planning results, and the decisions at each level depend on the planning results of the other level. The simulation results at different budget levels show that simultaneous hardening planning of distribution lines and substations considering network reconfiguration can not only reduce expected operating costs, but also can reducing total capital cost to PDS resilience enhancement. © 2024 Informa UK Limited, trading as Taylor & Francis Group.
IET Generation, Transmission and Distribution (17518687) 19(1)
Peak load management is a pivotal aspect of power generation and distribution, representing one of the primary challenges for power companies. A key feature of smart grids is their capability to manage available resources effectively to mitigate peak load while accounting for the inherent uncertainties in load demand and the generation of all renewable energy sources. Thereby, this paper proposes a two-stage coordination approach that integrates price-based demand response (PBDR) and energy storage systems, encompassing Battery Energy Storage Systems (BESS) and Compressed Air Energy Storage (CAES). This approach integrates CAES with BESSs to optimise the charging and discharging processes while minimising degradation costs. Specifically, it aims to address the substantial degradation expenses of BESSs by strategically utilising CAES as a complementary storage solution. The objective is to minimise operational costs while controlling peak demand load in smart microgrids. Moreover, to simultaneously address the inherent uncertainties associated with the demanded load and the generating power of renewable energy sources, a method incorporating scenario generation and reduction is introduced to improve scheduling accuracy and enhance the reliability of energy management. To tackle this multifaceted challenge, a novel scenario-based Developed Two-Stage Interval Optimisation (DTSIO) model has been proposed to effectively address uncertainty. By employing the scenario generation method in conjunction with the k-means technique to reduce scenarios with low probabilities of occurrence, the analysis process is optimised for better problem-solving efficiency. The proposed model's efficacy is validated through its implementation on a 33 and 69 bus microgrid, showcasing its ability to enhance profitability, manage peak load, reduce reliance on the upstream grid, and lower carbon dioxide emissions. © 2025 The Author(s). IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.
Reliability Engineering and System Safety (18790836) 254
With the escalating dependence on electricity and natural gas infrastructure, ensuring both reliability and economic efficiency becomes paramount. It necessitates reliability centric measures to mitigate disruptions that could cascade between these interconnected systems. To address this challenges, this paper introduces a reliability-constrained two-stage stochastic model to optimize power-to-gas (P2 G) and gas-to-power (G2P) unit placement and sizing, aiming to enhance the reliability of both systems under stochastic scenarios. The proposed model, employing Sequential Monte Carlo (SMC) within its optimization framework, seeks to minimize investment, operation, and reliability costs. By addressing temporal uncertainties in component outages for both systems and considering uncertainties in power and gas system loads with a high temporal resolution and annual load growth, the model provides a comprehensive reliability perspective. Furthermore, sensitivity analysis is conducted to explore the impact of varying Values of Lost Load (VOLL) on the planning results. Numerical evaluation, using two integrated energy systems including IEEE 14-bus-10-gas node, and large-scale energy systems including IEEE 118-bus-85-gas node integrated power-gas system (IPGS), demonstrates a significant 12.53 % improvement in overall system reliability. Furthermore, a 2.81 % reduction in operation costs and a substantial 26.3 % reduction in reliability costs, validating the effectiveness of the proposed model. © 2024 Elsevier Ltd
Shabanian-poodeh, M. ,
Hoshmand, R. ,
Shafie-khah, M. ,
Siano, P. IEEE Access (21693536) 13pp. 67301-67322
Energy systems and their related technologies are susceptible to natural extreme events, categorized as high-impact low-probability (HILP) events, posing a significant threat to their reliable functioning. Gas-to-power (G2P) and power-to-gas (P2G) technologies establish a bidirectional interface between these energy systems, leading to the creation of integrated power and natural gas systems (IPGS) as energy systems. Due to their extensive geographical coverage, energy systems are particularly vulnerable to severe damage from natural calamities. Given the growing interest and research focus on energy systems resilience, this comprehensive review meticulously navigates the intricate terrain of resilience differentiation, offering a detailed roadmap fortified by insights from significant instances of grid failures and weather-driven contingencies. The review examines preemptive cyber security fortifications and strategic planning imperatives, scrutinizing each aspect with conviction and clarity. Temporally stratified into long-term and short-term horizons, it not only delineates prevailing approaches and methodologies but also identifies emerging trends poised to shape the future landscape of resilience enhancement. This paper provides an exhaustive review of existing research on the resilience of energy systems, introducing a visual framework for comparing different studies and facilitating easy understanding through multiple figures. Since uncertainties play a crucial role in decision-making within this field, this paper broadly explores methods for addressing them as presented in previous studies. Furthermore, the literature is meticulously classified to offer a clear and organized overview, highlighting the impact of HILP events, such as natural disasters and cyber-attacks, on energy systems resilience. This review underscores the critical need to fortify energy systems, emphasizing its importance as a crucial component of integrated energy systems in preparing for the continuous impact of natural disasters in future research. © 2013 IEEE.
Journal of Modern Power Systems and Clean Energy (21965420) 13(1)pp. 228-240
The increase in the number of sensitive loads in power systems has made power quality, particularly voltage sag, a prominent problem due to its effects on consumers from both the utility and customer perspectives. Thus, to evaluate the effects of voltage sag caused by short circuits, it is necessary to determine the areas of vulnerability (AOVs). In this paper, a new method is proposed for the AOV determination that is applicable to large-scale networks. The false position method (FPM) is proposed for the precise calculation of the critical points of the system lines. Furthermore, a new method is proposed for the voltage sag monitor (VSM) placement to detect the fault locations. A systematic placement scheme is used to provide the highest fault location detection (FLD) index at buses and lines for various short-circuit fault types. To assess the efficiency of the proposed methods for AOV determination and VSM placement, simulations are conducted in IEEE standard systems. The results demonstrate the accuracy of the proposed method for AOV determination. In addition, through VSM placement, the fault locations at buses and lines are detected. © 2013 State Grid Electric Power Research Institute.
International Journal of Critical Infrastructure Protection (18745482) 44
In the recent years, dust storms (DSs) pose a serious threat to critical infrastructure such as power distribution networks (PDNs). During DSs, the contamination of insulators, increases the possibility of damage to the PDNs insulation system and flashover induced power outage may occur. Power outages disrupt the performance of other urban infrastructures and, in addition to heavy financial losses, cause public dissatisfaction. Although this issue is of particular importance in areas with humid climate, a few studies have been reported on PDNs resilience improvement against DSs. This paper proposes a novel cost-based optimization model to make PDNs more resilient to DSs considering uncertainties. The proposed model is based on the two-stage stochastic mixed-integer programming (SMIP). In the first stage, decisions are made to equip repair crews (RCs) with insulator washing machines, hardening distribution lines with silicone-rubber insulators (SIs), and deploy backup distributed generators (DGs). Decisions in the second stage include network reconfiguration, RCs routing, DGs power dispatch, and load shedding as the critical options for PDN outage management during/after DSs. Case studies are evaluated in the IEEE 69-bus test system and a real 209-bus PDN in Khuzestan province, a coastal province in southwestern Iran. The simulation results at different budget levels have confirmed the efficiency of the proposed model for cost-optimal resilience enhancement planning of PDNs against DSs. © 2023 Elsevier B.V.
Today, power quality is a crucial issue that greatly impacts distribution networks. Short-term and long-term power quality phenomena play a significant role in the overall performance of the network. Voltage sag, a type of short-term power quality issue, has higher occurrence rate compared to other power quality phenomena. The primary sources of voltage sag include transient symmetrical/asymmetrical faults, starting large motors, and transformer energizing. Although Numerous methods have been suggested for identifying the root cause of voltage sag incidents, the impact of noise and measurement error is often overlooked. In this paper, an assessment of the impact of noise and measurement error on voltage sag source localization methods is provided. Firstly, four of the most important methods proposed in this regard are described, and then the performance of each of them is examined with and without considering noise and potential measurement errors. Simulation conducted on the standard IEEE 33-bus network illustrate that methods utilizing a set of measurement data are robust to noise and measurement error. In contrast, methods using individual measurement data samples are vulnerable to noise and measurement error, leading to mistake conclusions. © 2024 IEEE.
IET Generation, Transmission and Distribution (17518687) 18(17)pp. 2776-2792
By increasing the number of electric vehicles (EVs) to achieve a less carbon environment, not only they consume power from the grid to be charged, but also do they deliver power to the grid, and this can play a significant role in load frequency control. However, EVs take part in frequency regulation based on their state of charge (SoC) which will cause uncertainties. In order to manage these uncertainties, EV aggregator (EVA) concept has been introduced. The EV owner participates in the demand response program provided by the EVA arbitrarily considering her/his requirements. Accordingly, EVA calculates the up and down power reserve for the power system operator. Following any frequency deviation, EVA sends the proper commands to each EV to consume or to inject power to the system. There are also communication delays between different parts, uncertainties, and non-linearities that existed in the power system. To overcome these issues, this study proposes a new robust load frequency controller based on feedback theory and artificial neural network which is designed through the non-linear multi-machine power system. Simulation results on IEEE 39-bus power system show that the proposed controller regulates frequency more desirably in comparison with other methods. © 2024 The Author(s). IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.
Electrical Engineering (14320487) 106(1)pp. 93-109
One of the most prevalent and destructive types of cyber-attacks on power systems is the false data injection (FDI) attack. In a false data injection attack, the attacker inflicts large damages on the network by manipulating the measurements. The pivotal solution to opposing this type of cyber-attack is to use phasor measurement units (PMUs). In this paper, a new method is presented to confront the FDI attack by using the optimal placement of PMU instruments. In the proposed algorithm at the beginning, all PMUs placements that achieve network observability are determined using the tabu search (TS) algorithm. Then, from the observable placement vectors, the placements that minimize the possibility of a cyber-attack on the network is identified. For this purpose, a new attack criterion is presented, which is obtained from the adversary strategy in the attack scheme. Since the measurements obtained from the PMUs must be transferred to a phasor data concentrator (PDC) center, the PDC placement also must be determined. In this paper, the optimal placement of PDC is presented by considering the cost of communication infrastructure, because the cost of communication infrastructure between PMUs and PDC is significant. For this purpose, we have used the Kruskal algorithm. The simulations performed on the IEEE 30-bus and 118-bus test system confirm the effectiveness of the proposed method for opposing cyber-attacks and reducing the cost of communication infrastructure. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023.
IET Generation, Transmission and Distribution (17518687) 18(20)pp. 3234-3246
In response to growing reliance on electricity and gas systems, this paper introduces a stochastic bi-level model for the optimized integration of these systems. This integration is achieved through sizing and allocating of power-to-gas (P2G) and gas-to-power (G2P) units. The first level of the model focuses on decisions related to P2G and G2P unit installations, while the second level addresses optimal system operation considering decisions made from first level and stochastic scenarios. The primary aim is to enhance energy-sharing capabilities through coupling devices and mitigate wind generation curtailment. An economic evaluation assesses the model's effectiveness in reducing costs. N − 1 contingency analysis gauges the integrated system's ability to supply load under emergency conditions. Two new indices, performance of the electricity system and performance of the natural gas system, are proposed for N − 1 contingency analysis. These indices quantify the proportion of the supplied load to the total load, thereby illustrating the system's capacity to meet demand. For numerical investigation, the proposed model is applied to a modified IEEE 14-bus power system and a 10-node natural gas system. Numerical results demonstrate a 9.426% reduction in investment costs and a significant 10.6% reduction in wind curtailment costs through proposed planning model. © 2024 The Author(s). IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.
Sustainable Cities and Society (22106715) 112
Floods, categorized as high-impact low-probability (HILP) events, pose significant risks to power distribution systems (PDS) and natural gas systems (NGS). Ensuring mutual support during emergencies through energy sharing, facilitated by coupling devices, highlights the necessity for optimal integration. However, managing these systems separately by different operators calls for coordinated yet decentralized operation. Hence, this paper introduces a risk-constrained bi-level model to integrate PDS and NGS. The upper level deals with siting and sizing power to gas (P2G) and gas to power (G2P) units. Meanwhile, the lower level employs decentralized load restoration using the alternating direction method of multipliers (ADMM) algorithms, with each system individually minimizing its own risk. To account for the unpredictable nature of HILP events surpassing a predefined risk threshold (α), this study defines Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) for each system as resilience criteria. Validation of the model is demonstrated using an IEEE 33-bus PDS and a 20-node NGS, and applied to a real-world large-scale PDS in Khuzestan province, Iran. Across various scenarios, higher system risks prompt an increase in the number and size of planned coupling devices, particularly to address the most severe 5% of scenarios. This optimization leads to enhanced energy sharing, resulting in a resilience improvement of nearly 35% in specific cases, along with a notable 25% reduction in both active and reactive power loss. Additionally, the sensitivity analysis explores the impact of varying risk levels and thresholds on outcomes, demonstrating how investors can utilize the proposed model across diverse risk perspectives. © 2024
IET Cyber-Physical Systems: Theory and Applications (23983396) 9(4)pp. 463-476
Zero-dynamics attack (ZDA) is a destructive stealthy cyberattack that threatens cyber-physical systems (CPS). The authors have warned about the risk of a cyberattack by introducing a new general ZDA that can be effective and robust in non-linear multiple-input multiple-output CPS. In this proposed attack policy, the adversary extracts the sensor and actuator online data on the network platform. Then, by utilising a state observer and considering specific delay times, the attacker injects a ZDA signal into the actuator channels of the cyber-physical system. As a result, the internal dynamics will diverge from the nominal working region of the controlled cyber-physical system, while the outputs remain close to the actual outputs of the attack-free system. Therefore, this cyberattack can remain stealthy, and it can also be robust against revealing signals. The efficiency of this new attack policy is demonstrated in the simulation results for a continuous stirred tank reactor regarded as a cyber-physical system. © 2024 The Author(s). IET Cyber-Physical Systems: Theory & Applications published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.
Journal Of Operation And Automation In Power Engineering (24234567) 11(2)pp. 83-93
This paper proposes a robust state feedback controller for Electric Vehicle aggregators to solve the challenging problem caused by the participation of Electric Vehicles in the load frequency control of the power system. The Lyapunov-Krasovskii functional method is used to achieve two objectives of the robust performance and stability. Then, by using teaching learning based optimization algorithm, both primary and secondary participation gains of EV aggregators in LFC are optimally determined. The Generation Rate Constraint and time delay, as nonlinear elements, are also taken into account. Simulations are carried out on two nonlinear power systems by using the power system simulation software. The results show that the designed controller gives a desirable robust performance for frequency regulation at the presence of uncertainties. © 2023, University of Mohaghegh Ardabili, Faculty of Electrical Engineering. All rights reserved.
Smart Grids and Sustainable Energy (27318087) 8(2)
Efficient utilization of existing energy resources within smart industrial grids constitutes an indispensable part of any energy management system (EMS). In this regard, virtual power plants (VPPs) play a crucial role in smart exploitation of available generated power. The present paper offers a new and exciting perspective at the EMS of Industrial VPPs (IVPPs). The grid management simultaneously makes use of demand response (DR) loads and electric vehicles (EVs) deployed at parking spaces. The EMS follows the objective of maximizing overall profit of its assemblage. At the same time, the EMS endeavors to augment the grid reliability at peak conditions and reduce load shedding of industrial centers. Naturally, there are uncertainties in such parameters as electricity market prices, EVs, and renewable energy production sources. Thus, a random-based energy management problem approach is adopted. To validate, the proposed method is experimented on the second zone of the modified IEEE-RTS standard network. The simulations reveal that the EVs’ presence in dedicated parking spaces can bring about a dramatic increase in the storage capacity of the IVPPs. This causes a reduction in the use of network’s overall power capacity. In fact, a prominent feature of the EMS is constant use of DR programs and selecting best one for each IVPP at different time hours. On the whole, the adopted procedure gives rise to a general reduction in network’s operational costs, considerable de-peaking as well as enhanced performance of EVs at parking spaces. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.
International Journal of Energy Research (1099114X) 2023
Nowadays, consumption of different energy carriers is increasing due to the division of community activities in various sectors such as residential, commercial, and industrial. The energy hub concept is used to meet the demands of different energy carriers in these sections. In this paper, a new method for energy management of a microgrid is presented in an intelligent network based on three types of commercial, residential, and industrial energy hubs. In the energy hubs, a wide range of components, including renewable and nonrenewable generation units, converters, storage devices, intelligent parking lots consisting of electric vehicles, P2G units, and cogeneration units, are used to supply electrical, heating, cooling, and natural gas energies. Some parameters like renewable generations, energy demands, and arriving and departure time of electric vehicles are considered to be uncertain, and a relevant method is applied to provide a near-realistic profile for them. In addition, a demand response paradigm has also been proposed for three types of electrical, heating, and cooling demands at the hub output side. Therefore, in this method, a mixed integer linear programming model is proposed based on benefit and reduction of emission caused by the activity of gas-burning units for short-term planning and obtaining an optimal solution for generation and sending loads in a distribution network containing energy hubs. To evaluate the performance of the proposed modeling and structure, the presented approach is applied on a modified 33-bus IEEE test network. According to the results of the energy management model, it is possible to significantly increase benefits and also obtain a smoother consumption pattern in consumption with financial incentives. © 2023 Majid Abbasi Gharai et al.
Reliability Engineering and System Safety (18790836) 230
Integrity data (DI) attacks are considered malicious cyber threats to the economic performance of power markets in current power systems. A cyber attacker could mislead the system operator by implementing a DI attack, through the deviation of measured information, and causes non-optimal power distribution and erroneous participation in the electricity market (EM). This paper proposes a placement scheme of phasor measurement units (PMUs) to defend against these attacks, so that network observability is guaranteed; the possibility of detecting DI attacks by the operator is increased; and the effect of electricity price fluctuations caused by these attacks is prevented. For this purpose, we introduce two possible indices to determine the degree of attack detectability and the magnitude of system congestion variation. Accordingly, the two-objective placement model of PMUs is upgraded, in which the minimum number of PMUs and their placement must be specified to improve the proposed indices so as to minimize the possibility of financial misconduct taking place in the real time market. Using IEEE standard systems, the effectiveness of this PMU placement-based defense scheme has been confirmed. © 2022 Elsevier Ltd
IEEE Transactions on Power Delivery (19374208) 38(6)pp. 4157-4165
With the growing use of sensitive loads and distributed generations (DGs), power quality is of great importance in distribution networks (DNs). Voltage sag is a significant power quality disturbance. Hence, monitoring of the voltages and currents of the network is necessary to identify the voltage sag occurrence and its location. However, installing measuring units at every busbar in very expensive. In this article, an optimal method for locating the voltage sag monitors (VSMs) in DNs is proposed, considering the DGs. The proposed method is based on the DN zoning algorithm that utilizes the matrix of voltage sag transfer coefficients. The optimal number of zones is determined based on the proposed threshold value or the financial limits. Then, in each zone, the electrical center busbar is determined by solving an optimization problem. The electrical center busbar in each zone is chosen as the optimal location of the VSMs. The location, size, type, and control strategy of DGs, and the network structure affect the optimal location of the VSMs. The proposed method is implemented in different simulation scenarios at the IEEE 33 bus test system and the simulation results show the efficiency of the proposed algorithm. © 1986-2012 IEEE.
In recent years, the power grid has evolved from a traditional network to an advanced smart grid, and with the widespread implementation of cyber technologies, the power network has become highly vulnerable to destructive cyber-attacks. A key tool used extensively today to enhance information security and prevent cyber-attacks on the network is Phasor Measurement Units (PMUs). A new method for combating cyber-attacks has been proposed in this article, which focuses on identifying the best locations for PMUs to reduce the likelihood of cyber-attacks on the network. To identify key network points and enhance cybersecurity at these points, a new attack criterion has been proposed. Additionally, network observability has been considered using the Tabu Search Algorithm (TS) in the proposed method. Since the DC system model has less computational volume and faster computation speed, the DC system model has been considered in the proposed method. Simulations performed on IEEE 14, 30, and 57 bus networks demonstrate the ability of the proposed method to deal with cyber-attacks. © 2023 IEEE.
International Journal of Electrical Power and Energy Systems (01420615) 139
Penetration of inverter-based distributed energy (DG) resources into power grid has notably risen in recent years. Hence, new grid code standards require DGs to remain connected to the main grid even during faults and inject a certain amount of reactive power. However, in weak grids and during severe voltage faults, converters may fail to maintain their synchronization with the main grid. A main cause for this synchronization instability is the improper operation of synchronization unit which is phase locked loop (PLL). In literature, imitating the transient stability analysis of synchronous generators, swing equation and Equal Area Criterion (EAC) are applied to study the synchronization of grid-connected converters. In this paper, a new method based on EAC and swing equation is proposed to keep the damping coefficient in the swing equation positive, and consequently increase the maximum buffer area in EAC. Hence, the synchronization stability of voltage source converters (VSCs) connected to weak grids is enhanced. When the fault is detected, the proposed technique simply adds a certain gain of frequency deviation to the PLL and does not need any additional information of grid changes. The simulation results in MATLAB verify the viability of the proposed controller. © 2022 Elsevier Ltd
Panah, P.G. ,
Cui, X. ,
Bornapour, S.M. ,
Hoshmand, R. ,
Guerrero, J.M. International Journal of Hydrogen Energy (03603199) 47(25)pp. 12443-12455
Green hydrogen is produced through different methods in the lab but only a few technologies are commercialized. Cost reduction is widely expected to compete with the existing carbon-emitting alternatives. This paper compares alkaline, proton exchange membrane, and solid oxide electrolysis cells as the dominant technologies. Economic analyses with scale-up effects show meaningful differences between PEM and alkaline electrolyzers as relatively settled methods and solid oxide as an immature technology. Monte Carlo simulations on grid-connected electrolysis using the Danish electricity market confirm that both PEM and alkaline electrolyzers can already produce hydrogen with less than 3 €/Kg if taxes and levies are removed. The price may even drop below 2 €/Kg after the mass adoption of all three technologies. Furthermore, if electricity is delivered at half prices, the levelized cost of hydrogen falls around 1 €/Kg. The capabilities for cost reduction after scaling-up are 33%, 34%, and 50% in alkaline, PEM, and solid oxide electrolyzers respectively while they could get intensified with subsidization to 56%, 59%, and 70%. The results indicate that solid oxide electrolyzers can be as economical as alkaline and PEM ones. However, grey hydrogen seems to remain unbeatable without subsidized electricity and/or carbon tax adjustments. © 2022 Hydrogen Energy Publications LLC
International Journal of Electrical Power and Energy Systems (01420615) 138
False data injection (FDI) attacks can significantly impact on economic performance of electricity markets in modern power systems. These attacks can be stealthily accomplished by cyber-attackers for the purpose of profitability through financial arbitrage in electricity markets. In this paper, a new strategy of FDI attack based on Monte Carlo is proposed for an attacker participating in an electricity market, who has overmuch imperfect level of the network information. This piece of information, including both the connection /disconnection situation and admittance values of the transmission lines is denominated as topology and parametric uncertainties, respectively. Herein, a probable model is offered for analyzing the uncertainties by the Monte Carlo simulation (MCS). Afterwards, considering the probable errors of uncertainties, the attack strategy is designed in such a manner that the attacker obtains the most profit based on the contribution of each transmission line. The numerical results on two PJM 5-bus and IEEE 30-bus test networks could obviously demonstrate the success of such limited attackers in current electricity markets. © 2022 Elsevier Ltd
Sustainable Cities and Society (22106715) 78
Extreme dust storms (EDSs) are rare natural disasters, occurring with a higher rate of incidence and severity in recent years in coastal areas with humid climate. EDSs can hamper the operation of power distribution systems (PDSs) and other related urban infrastructures, and damage PDS insulation equipment. In this paper, a bi-level stochastic mixed-integer linear programming model is proposed for PDS resilience enhancement against EDSs. In the proposed model, the investment cost and total expected operating costs under the EDS conditions are minimized while considering uncertainties and PDS financial and operational constraints. The proposed actions for PDS resilience enhancement include pre-and post-EDS actions. Pre-EDS actions include simultaneous hardening of lines and substations, optimal placement of sectionalizing switches, and installation of emergency generators (EGs) in critical points. Post-EDS actions include damaged lines and substations repair, optimal network reconfiguration, power dispatch of EGs and optimal load shedding. The planning results at different budget levels show that coordinating pre-and post-event actions can reduce investment costs besides reducing operational costs. Implementation of the proposed model on the IEEE 33-bus test system and a large-scale PDS in Khuzestan province, a coastal province in southwestern Iran, confirms the efficiency of the proposed method for PDS resilience enhancement planning. © 2021
Electric Power Systems Research (03787796) 205
The economic operations of real time (RT) electricity markets are vulnerable to false data injection (FDI) attacks, designed by cyber-attackers. Strategically, the RT locational marginal prices (LMPs) are stealthily altered by manipulating some of measurement data and it provides conditions for profitable financial misconduct in the electricity market. This paper proposes a new Monte Carlo-based FDI attack strategy for a cyber-attacker, who has very limited knowledge about the topology and parametric information of targeted network, which called an attacker with model topology-parametric uncertainties (TPUs). The main feature of the proposed attack is that despite the model errors, the attacker can guarantee the stealthy and profitable attack in advance, since the attack is designed based on an optimization problem of worst-case robust against uncertainties. Two 5-bus PJM and 30 IEEE bus systems are used to demonstrate the success of such cyber-attacks in real-time electricity markets. © 2021 Elsevier B.V.
IEEE Transactions on Instrumentation and Measurement (00189456) 71
Power quality disturbances can cause damages to the electrical network's customers. Therefore, nowadays, power quality is considered an essential issue in distribution networks. In this regard, voltage sag is of a lot of significance among power quality disturbances. The first step in the reduction of damages caused by voltage sag is to determine the location of the disturbance source. Furthermore, recent attention to distributed generation (DG) particularly in distribution networks led to the inefficiency of the previous voltage sag source location (VSSL) approaches. In this article, a new method based on voltage and current measurement data is proposed, in which cosine similarity (CS) is used to locate a voltage sag source. In the proposed method, the CS sign between two data sets is used to identify the relative location of the voltage sag source. Simulation results are presented for different scenarios in the IEEE 33 bus test network. In doing so, various issues including VSSL, voltage sag original type (symmetric/asymmetric short-circuits or motor starting), the fault resistance, the x/r ratio of the grid lines, DG size, DG location, measurements error, and current transformer saturation are studied in simulations. The simulation results confirm the performance of the proposed method for the voltage sag source locating. Moreover, the comparison with some previous methods shows that the proposed method gives a better response in determination of location of the voltage sags. © 1963-2012 IEEE.
Panah, P.G. ,
Hoshmand, R. ,
Gholipour shahraki, M. ,
Macana, C.A. ,
Guerrero, J.M. ,
Vasquez, J.C. Sustainable Energy Technologies and Assessments (22131388) 48
Islanded microgrids with high shares of RES are more exposed to frequency disturbances. The largest generator is typically in charge of frequency regulation. This study tries to upgrade this monopoly to a competitive market. A novel framework is proposed to invite prosumers of any kind/size to participate in a local ancillary service market. A multi-criteria decision-maker is developed to select the proper service from the pool of bids. Flexibility Flags and Prosumer Deviation Index are introduced to quantify the behaviors of individuals and the stability of autonomous microgrids. Furthermore, an innovative reward/punishment framework is suggested for the billing of subscribers. In this method, the extra cost of the activated reserved power is solely compensated by disturbance makers rather than the conventional way of blindly charging all subscribers for frequency regulation. An urban microgrid including electric vehicles, micro combined heat/power generator, thermostatic loads, and kinetic energy storage is considered for the performance assessment. The results indicate that electric vehicles and flexible loads are privileged. Also, the bill of the planned loads for the regulation service falls from 46–48% down to 3–6% under the proposed framework while the cost of frequency regulation drops by 59% when the unnecessary reserved power is modified. © 2021 Elsevier Ltd
Sustainable Energy Technologies and Assessments (22131388) 45
Due to a growing trend in electricity consumption and limitations in expanding the capacity of power plants, the issue of privatizing and restructuring the electricity industry has come to the fore. In this regard, with the emergence of competitive markets, drawing upon responsive programs and electric vehicles in planning smart networks has become an intense topic of research. This paper presents a new method for programming industrial virtual power plants (IVPP) considering synchronous presence of demand response programs and electric vehicles. The proposed algorithm aims at maximizing the proceeds from industrial networks through demand response planning and managing the energy consumption of electrical vehicles. The algorithm is implemented in Zone 2 of the modified version of the IEEE Reliability Test System. The simulation results show that the presence of electric vehicles in the parked position will increase the storage capacity of the IVPPs, whereupon the consumption load on IVPPs is reduced. Using demand response programs in this regard and selecting the best program for each IVPP at different times of the day cuts back on both network operating costs and high consumption peaks, whereby an improvement in the efficiency of electric vehicles parking schemes is obtained. © 2021 Elsevier Ltd
IEEE Transactions on Instrumentation and Measurement (00189456) 70
Increasing power quality disturbances is one of the significant concerns of power systems that have attracted attention in recent years. One of the most important power quality disturbances is flicker. Flicker not only leads to flickering lighting systems but also damages network equipments, especially those with a high degree of sensitivity. As power systems are restructured, it is possible to take some measures against polluting subscribers. In this article, a new short-circuit-based method is proposed for determining the flicker transfer coefficient. Moreover, four new indices are introduced to assess the effect of flicker sources on target buses' voltage. In the proposed indices, the flicker sensitivity coefficient and the amount of load supplied by each target bus are considered. Using these indices, one can take an accurate impression of the effect of one or more flicker sources on the target buses' voltage. Finally, using the proposed indices, a new flicker propagation pricing method is presented, which can be used to penalize the flicker sources based on their flicker contribution in the target buses. To demonstrate the effectiveness of the proposed method in determining the contribution of flicker sources, the simulations are conducted on IEEE 14-bus test system. The simulation results show that by doing so, while taking into account the introduced indices, it is possible to identify and evaluate the contribution of different flicker sources. Moreover, experimental measurements are conducted on Isfahan region power system as a part of Iran transmission network. Finally, as a result, by applying proper penalty fees to subscribers, it is possible to reduce the flicker level of the network. © 1963-2012 IEEE.
IET Generation, Transmission and Distribution (17518687) 15(17)pp. 2446-2459
Improving network power quality through harmonic reduction requires recognition of Harmonic Sources (HSs) to drive them to compensate their harmonics. This paper proposes a new method for equitable distribution of the Harmonic Compensation Cost of the network among the HSs based on the Harmonic Contribution Matrix. Each element of the Harmonic Contribution Matrix is the harmonic contribution of a specific source to the harmonic voltage of a specific bus. The output of the proposed method is a penalty curve for each HS over time. The amount of the fine estimated for each individual HS per hour is a function of not only the contribution of that HS to the harmonic voltage of different buses, but also the contribution of the Harmonic Compensation Cost from the perspective of each bus, nominal voltage of each bus, and the sensitivity of each bus to the harmonic voltage. The proposed algorithm is evaluated on the IEEE 14-bus network and Esfahan regional electrical power network in Iran. The simulation results demonstrate the capability of the proposed method to allocate the hourly penalty curve to the HSs. © 2021 The Authors. IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology
IET Generation, Transmission and Distribution (17518687) 15(7)pp. 1136-1143
With the increasing penetration of inverter based distributed generation, recent grid codes do not permit the disconnection of converters as soon as fault happens. Considering the fact that electrical grids are not purely inductive, the grid connected converters face instability issues by fault occurrence. Converters applying Phase Lock Loop (PLL) are not able to synchronize with the weak grid during deep low voltage faults. This paper proposes a novel control strategy based on virtual impedance to maintain the synchronization of grid connected converters during heavy decrease of the grid voltage. Utilizing a virtual impedance and the measured current at the point of common coupling, the inverter can be virtually synchronized to a point which has a stronger connection. The virtual impedance can be a rough estimation of the line impedance or resistance from point of common coupling to the fault point. Furthermore, to avoid the need for impedance estimation, a simple technique is also proposed. Simulation results with MATLAB confirms the competence of the proposed method in improving the synchronization stability of the grid connected converters. © 2020 The Authors. IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology
IET Renewable Power Generation (17521416) 15(1)pp. 58-72
Today, with growing expansion of renewable energy resources, electricity production is accompanied by uncertainties. The usage and optimal management of energy storage is one of the effective ways to compensate for these uncertainties. Compressed air energy storage (CAES) is one of the two bulk electricity storage methods for power systems, burning natural gas (NG) to extract the stored energy. Therefore, the NG price uncertainty and gas availability along with carbon emission resulting from burning NG can affect optimal bidding result of this unit. Hence, this study addresses the optimal bidding problem of CAES and wind units, considering the aforementioned issues, while taking into account uncertainties of day-ahead (DA) and balancing market prices, wind speeds, and NG prices and availability. Furthermore, the dynamics of natural gas flow in the pipeline is modelled. The stochastic programming (SP) method is proposed for solving this problem while taking risk into consideration. The scheduling has been presented for participation of generating company in DA and carbon emission markets. Simulation results indicate the capability of the proposed method in optimal bidding of CAES units while taking gas-burning related constraints into consideration. © 2020 The Authors. IET Renewable Power Generation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology
Journal of Energy Storage (2352152X) 41
Today, implementation of an efficient and economical energy management system (EMS) in industrial smart grids- given the rising trend in electrical load consumption and restrictions in ramping up the power plants' capacities- cannot be underestimated. Optimal planning avails itself of the exploitation manner of existing energy resources alongside appropriate employment of demand response (DR) programs and available electric vehicles (EV) in parking lots of immense industrial centers as storage sites in energy management systems in industrial smart grids have been seriously considered. This article introduces a new perspective in the simultaneous use of demand response loads and available electric vehicles in parking lots toward energy management of industrial virtual power plants (IVPPs) aiming at augmenting the system's profits as well as increasing the grid reliability under peak load conditions and cutting down on industrial centers load shedding. The objective function of the problem is formulated within the framework of short-term production planning for distributed energy resources (DER) and conventional ones in conjunction with DR programs and EV in such a way that the IVPPs' profits are maximized. In order to validate the performance of the proposed method, we have applied and tried on the second zone of IEEE-RTS standard grid. The outcomes accrued from various simulations point to the fact that the presence of EV within the boundaries of EV's parking lots prompts considerable increase in IVPPs' storage amount and consequent decline in exploiting full power grid capacity. Utilizing DR programs for responding load and selecting best scheduling schemes for each IVPP during various times of a day-night cycles will bring about a reduction in operation costs, de-peaking as well as an enhanced performance of EV's parking installations. © 2021 Elsevier Ltd
Sustainable Cities and Society (22106715) 59
Power markets are undergoing structural alterations in accordance with emerging technologies. Traditional market rules and participants' behaviour are currently dominated by conventional power plants and synchronous generators. Renewable energy sources have gradually found their market share in the generation party specifically in developed countries. Apart from new energy resources, Demand Response Programs (DRP) have garnered attention due to substantial capabilities and potentials. This paper particularly sheds light on two flexible loads of Plugin Electric Vehicles (PEV) and cooling/heating responsive loads. PEV parking lots can be modelled as stochastic battery storages partially available for power exchange over short intervals. Besides, cooling/heating systems are naturally shiftable loads in short time horizons without deteriorating the resident's convenience. This study provides a comparative view of short-term power regulating markets in terms of bidding constraints and payment mechanisms. Consequently, a typical park & ride is considered as a reconfigurable urban microgrid to participate in short term regulating markets under different constraints. The results confirm that the internal coordination between the sub-units of microgrid brings more flexibility to enhance the total profitability. In addition, it is shown that the bidding constraints, as well as time slots, can be influential particularly in intermittent situations. © 2020 Elsevier Ltd
Journal Of Operation And Automation In Power Engineering (24234567) 8(2)pp. 152-163
After extreme events such as floods, thunderstorms, blizzards and hurricanes there will be devastating effects in the distribution networks which may cause a partial or complete blackout. Then, the major concern for the system operators is to restore the maximum critical loads as soon as possible by available generation units. In order to solve this problem, this paper provides a restoration strategy by using Distributed Generations (DGs). In this strategy, first, the shortest paths between DGs and critical loads are identified. Then, the best paths are determined by using a decision-making method, named PROMOTHEE-II to achieve the goals. The uncertainties for the output power of DGs are also considered in different scenarios. The IEEE 123-node distribution network is used to show the performance of the suggested method. The simulation results clearly show the efficiency of the proposed strategy for critical loads restoration in distribution networks. © 2020 University of Mohagheg hArdabili. All rights reserved.
IET Generation, Transmission and Distribution (17518687) 14(15)pp. 2901-2914
Nowadays, the determination of the contribution of individual customers to the harmonic pollution of an electric power network is very essential for power quality improvement. In this study, four new indices are introduced to investigate the effect of harmonic contribution (HC) of the pollutant customers for an arbitrary time period without any access to a network model. These indices are defined according to data measured at the connection point of the suspicious loads and targeted buses under study. In this regard, a continuous HC matrix is developed where its entries are determined by using a new multi-point and continuous HC calculation method without having to measure the phase angle, which makes this method practical and cost-effective. The method and indices are applied to a standard power network-based calculation example. In addition, experimental measurements, which are gathered based on the Isfahan city and Iran electric power transmission systems, are carefully analysed. The results demonstrated the capability of the proposed algorithm to evaluate the effects of harmonic sources in power networks. © 2019 The Institution of Engineering and Technology.
International Journal of Electrical Power and Energy Systems (01420615) 116
This paper proposes a two-layer hierarchical control structure to realize compensation of voltage unbalances optimally in different buses of islanded microgrids. The primary layer controls the microgrid voltage and frequency. The secondary layer is used to realize the unbalance compensation of the sensitive load bus (SLB). Improvement of the voltage unbalance factor (VUF) at the SLB may lead to an increase in VUF at local buses and/or DG terminals. A complementary part is designed and added to the secondary control in order to tune the compensation portion of each DG source while limitations of VUF at DG terminals and local buses are considered too. This method realizes multi-power-quality-level control through a simple yet effective solution. Simulation results are given to demonstrate the advantages of the proposed control scheme. © 2019 Elsevier Ltd
IET Electrical Systems in Transportation (20429738) 10(2)pp. 213-223
Using different types of generation systems in ships, which are known as all-electric ships, can play a key role in increasing economic benefits in the long term. On the other hand, electrical energy storage systems (EESSs) provide flexibility for supporting the electrical load of ships in the presence of renewable energy sources and the other generation units. Since power demands of a ship are not limited to an electrical load, combined heat and power (CHP) units can be considered as backup units for heat-only units in addition to their economic and environmental advantages. In this study, new optimal power management is presented to handle a generation scheduling problem of a cruise ship for 12 h time intervals. In this regard, this method is based on the Lagrangian relaxation approach, a subset of ε-constraint approaches, and the use of marginal cost to determine the performance of EESS in each time interval by taking all the constraints into account. The capability of the proposed algorithm is analysed by simulation results of a cruise ship, including conventional, CHP, EESS and heat-only units, in order to achieve minimum operation cost with a short runtime. © The Institution of Engineering and Technology 2019
International Transactions on Electrical Energy Systems (20507038) 30(4)
The observability of power systems during the parallel restoration of subsystems is one of the most important issues for system operators to accomplish the restoration task as quick as possible. Thus, this article proposes a coordinated optimal plan to solve the observability and sectionalizing problems by determining the locations of phasor measurement units (PMUs) and subsystems. Also, the impact of renewable energy resources on power system sectionalizing and the reliability value of power generation are taken into account in the proposed model. The objective functions that are considered in the optimization problem are the cost of wide-area measurement system (WAMS), the worst observability index among all subsystems and the lowest value of quality among all subsystems based on the reliability of subsystems. Since there are three contradictory objective functions, a multi-objective problem (MOP) is proposed as a mixed-integer nonlinear problem (MINLP). The Pareto curve of the proposed MOP is extracted by using a particle swarm optimization (PSO) algorithm. Two standard power grids are considered to validate the suggested technique. The outcomes of simulations confirm that the observability value of all sections is enhanced during the parallel restoration of the system. Also, the results show that the quality of subsystems in the presence of renewable energy resources is enhanced. © 2019 John Wiley & Sons Ltd
International Journal of Emerging Electric Power Systems (1553779X) 21(2)
Nowadays, the sustainable energy management of industrial environments is of great importance because of their heavy loads and behaviors. In this paper, the Virtual Power Plant (VPP) idea is commented as a collected generation to be an appropriate approach for these networks handling. Here, Technical Industrial VPP (TIVPP) is characterized as a dispatching unit contains demands and generations situated in an industrial network. A complete structure is proposed here for possible conditions for different VPPs cooperation in the power market. This structure carries out a day-ahead and intra-day generation planning by choosing the best Demand Response (DR) programs considering wind power and market prices as the uncertain parameters. A risk management study is likewise taken into account in the proposed stages for contingency conditions. So, some component changes, like, regular demand changes and single-line outage are prepared in the framework to authorize the suggested concept in the contingency situation. To determine the adequacy and productivity of the proposed strategy, the IEEE-RTS modified framework is examined to test the technique and to evaluate some reassuring perspectives too. By the proposed methodology, the delectability of DR projects is uncovered in industrial networks and the improvement level of load shedding and the lower cost will be achieved. © 2020 Walter de Gruyter GmbH, Berlin/Boston.
Journal of Energy Engineering (19437897) 146(1)
This paper proposes the idea of independent models of a microgrid (MG) based on operation modes. In grid-connected operation, optimal power flow is proposed to minimize the power generation cost. A new decision variable was introduced to represent a MG as an equivalent unit from the viewpoint of the upstream network. In island operation, contingency condition was considered and reliability improvement of the MG through load restoration is proposed. A new performance index is proposed to model MGs as small self-adequate islands in contingency. The main distinction between this research and the literature is the consideration of the uncertainty of the components of the MG. Monte Carlo simulation (MCS) was used as a framework to consider the uncertainty of components, including load consumption, renewable power generation, and fault duration. The proposed probabilistic models can be used to assess the generation adequacy and to indicate vulnerable loads in grid-connected and island operation modes, respectively. The proposed method was applied to the IEEE 69-bus test system and the results were discussed. © 2019 American Society of Civil Engineers.
Journal of Energy Storage (2352152X) 29
Today in developed megacities, municipal waste incinerators are a practical solution although they require a relatively high initial investment. On the other hand, E-Transport is growing in metropolitans along with the Renewable Energy Sources (RES). This study proposes an Urban Micro Grid (UMG) consisting of a Waste-to-Energy Combined Heat and Power generation unit (WtE-CHP) and series of Plugin Electric Vehicles (PEV). The main purpose is to provide ancillary services through the incorporation of PEVs as fast-responsive storages. The parking lots may aggregate to form PEV clusters and make bilateral contracts with WtE-CHP to be able to participate in the regulating power markets. A Crow Search Algorithm (CSA) is developed for the UMG operation. In addition, a data analysis section is provided focusing on the behavior of urban drives to extract the realistic probabilities for PEVs available during the daytime. Moreover, the power market of Denmark east (DK2) is considered for the case study of Copenhagen. The results confirm that in case the UMG succeeds in selling the products in the regulating up market, the economic value per MW is remarkably enhanced and the total profit is escalated. © 2020 Elsevier Ltd
Renewable and Sustainable Energy Reviews (13640321) 108pp. 355-368
Using different types of renewable energy sources considering their uncertainties causes numerous challenges for minimizing the operation cost and maximizing the reliability of system. Hence, stochastic programming is an essential tool to consider the system uncertainties. This paper presents a day-ahead energy management system to decrease the operation cost and increase the reliability of a Microgrid considering a number of challenges for supporting electrical and thermal loads. In the proposed method, micro-CHP units, renewable energy sources, auxiliary boiler and energy storage system are all responsible for supplying the electrical and thermal loads. The problem is formulated as a multi-objective optimization problem. Moreover, the influence of considering the electrical energy storage system as a non-ideal battery with charge/discharge efficiency less than 1 is investigated. Also, demand response programs are provided based on load shifting contracts to consumers. A scenario-based approach is used to cover the uncertainties of renewable energy sources, market price and electrical load. Besides, this paper considers both islanding and grid-connected modes of Microgrid and investigates the influence of demand side management on operation cost and reliability in both modes. The capability of the proposed algorithm is analyzed by simulation results of a 3-feeder Microgrid. © 2019 Elsevier Ltd
ISA Transactions (00190578) 89pp. 186-197
Passive filters are used as one of the effective solutions to mitigate harmonics and improve power quality in electrical networks. In this paper, a new fuzzy approach is proposed for the allocation of detuned passive filters based on a Nonhomogeneous Cuckoo Search Algorithm (NoCuSa). In this method, a resonance index is inserted in the problem formulation to avoid being in a resonance condition after the allocation of passive filters. In this regard, the candidate locations for the installation of passive filters are first selected based on a sensitivity analysis. Then, the values and tuning orders of the passive filters are optimized by using the proposed algorithm for single- and multi-load levels while applying fixed and switched passive filters. In the simulations, different scenarios for optimal allocation of passive filters are investigated and compared with optimal allocation of capacitors. Finally, the fuzzy problem model is implemented on an IEEE 69-bus network by NoCuSa and compared with different optimization algorithms. The results demonstrate an improvement in the final annual net benefit by applying NoCuSa in comparison with other algorithms. In addition, another comparison made between the proposed method and those implemented on IEEE 69-bus system shows the efficiency of the proposed method. © 2018 ISA
Renewable Energy (09601481) 130pp. 1049-1066
Nowadays, renewable energy resources are increasingly used to supply electrical loads in micro grids, which these units should be scheduled coordinately. In this paper a stochastic model for coordinated scheduling of renewable and thermal units is proposed. Understudied units consists of fuel cell units with proton exchange membrane which generate heat and power simultaneously (PEMFC-CHP), wind and photovoltaic units. Moreover, the strategy of storing hydrogen is also considered for PEMFC-CHP units. Uncertainties of wind speed, solar radiation and market prices are considered using scenario based method. In the proposed stochastic programming problem, the strategy of storing hydrogen is considered by a mixed integer nonlinear programming (MINP) problem. The uncertainties of parameters convert the MINP problem to a stochastic MINP one. Moreover, optimal coordinated scheduling of renewable energy resources and thermal units in micro-grids improve the value of the objective function. To solve this problem, Modified Teaching-Learning-Based Optimization (MTLBO) algorithm is used and its performance is evaluated on a modified 33 bus distribution network. Simulation results represent that by using MTLBO method, the revenue increases more than 5 percentages in comparison with other optimization methods. In addition, considering CHP increases total profit of the system more than 15%. © 2018 Elsevier Ltd
Iranian Journal of Science and Technology - Transactions of Electrical Engineering (23641827) 43pp. 15-37
Optimal scheduling of power plants is an important problem in power system operations. This problem is a complex programming approach based on the dimension of power systems, number, and types of power generation units. In recent years, the penetration of renewable energy sources (RES) as clean, cheap, and green resources of energy has been increased in power systems. Therefore, the classic power generation scheduling problem is converted to a large-scale mixed-integer non-linear and stochastic optimization problem. In this regard, a review of various optimal scheduling problems in restructured power systems, their solution methods, advantages, and disadvantages is introduced in the presence of RES in this paper. © 2018, Shiraz University.
IET Generation, Transmission and Distribution (17518687) 13(20)pp. 4630-4641
After occurring extreme events distribution systems might be disconnected from the main grid, and there will be a complete blackout in the distribution network. In such situations, the only way to re-energise loads is to use available microgrids (MGs). Since power outputs of MGs are limited, the major concern for system operators is to energise the maximum critical loads (CLs) during the time needed for fault isolation and maintenance. To solve this problem, this study provides a systematic restoration process by using MGs. First, after the fault clearance the shortest paths between MGs and CLs are identified by Dijkstra's algorithm. Then, the best paths are determined by using a new modified analytic hierarchical process (AHP) algorithm and fuzzy logic to achieve four goals: Increasing restored energy, reducing path preparing time, decreasing number of switching operations and reducing unavailability of path. In the modified AHP, the parameters are so tuned that the engineers' personal preferences are eliminated for selecting the best restoration paths. Also, the uncertainty of available energy of MGs is considered. The IEEE 123-node distribution network with MGs and CLs is used for simulations. Results clearly show the benefits of using this method for CL restoration. © The Institution of Engineering and Technology 2019.
IET Generation, Transmission and Distribution (17518687) 13(1)pp. 73-80
Today, with the restructuring of the power systems, it is possible to implement a program, such as the demand response for the harmonic issues, and use customers to reduce the harmonic level of the network. In this study, a new method is presented based on harmonic pricing to control the harmonic level of the network. Given the fact that the power system is usually infected by the background harmonics, the basis for pricing is the harmonic contribution determination in order to impose a fine fair on the customers. Usually, the determination of the harmonic contribution at each harmonic order is done separately; therefore, a new index is presented, to sum up, the dominant orders in determining the harmonic contribution. This can provide an appropriate impression of the harmonic emission level at the point of common coupling. Simulation results on the standard IEEE 14-bus network show that customers are encouraged to control their harmonic level with a fair harmonic pricing, otherwise, the independent system operator can install harmonic filters at appropriate buses, using the fines received from the customers. © The Institution of Engineering and Technology 2018.
IET Smart Grid (25152947) 2(1)pp. 115-122
This study proposes a two-layer hierarchical control to actualize optimal total harmonic distortion (THD) compensation in different buses of parallel-connected inverters in islanded microgrids which had not been studied so far. The proposed secondary layer is used to realize THD compensation of sensitive load bus (SLB) and make distributed generators (DGs) distribute the compensating efforts between them according to their rated capacity. It is noteworthy that improving THD at the SLB can lead to an increase in THD at local buses and/or DG terminals. Although the THD limitations of these buses are not as strict as the THD limitation of SLB, it is necessary to control them within their allowed range. This important problem is not well studied in the literature. A novel complementary part is designed and added to the secondary control to tune the compensation portion of each DG while the THD limitations in DG terminals and local buses are considered. The proposed method actualizes a multi-level voltage quality control in multi-bus islanded microgrids with parallel DGs through a simple yet effective solution. Furthermore, considering the DGs peak current limitation is added to the controller and a method for calculating this peak value is proposed. © 2019 Institution of Engineering and Technology. All Rights Reserved.
IET Generation, Transmission and Distribution (17518687) 13(1)pp. 55-63
These main goals of the restoration in distribution networks are to reenergise loads in the area where the power outage occurs. In this study, a new multi-stage restoration process by the aid of the decision-making tree algorithm is proposed to maximise the restored loads and also to minimise switching operations in the distribution networks with distributed generations (DGs). This method includes three stages of initial restoration, reconfiguration and optimal load shedding. In order to reduce the search space, the network switches are categorised into different sets which avoid moving to any inappropriate result space. The simulations are carried out on the 69-bus distribution system and the results show the high capability and accuracy of the proposed method in the restoration of distribution networks. © The Institution of Engineering and Technology 2018.
The use of storage systems has recently been increased to cope with the uncertainties related to renewable energy sources and also to increase the flexibility required for applying energy management system. Energy management system is considered as a key factor to enhance the effective performance of Microgrids regarding energy demand boosting. Since any parking lot with electric vehicles can participate in distribution systems as a storage unit, this paper employs a new technique for parking management system to develop competition between electric vehicles owners inside the parking lot. Parking lot is responsible to support energy management system to decrease the operation cost and to increase the reliability in grid-connected and islanding modes of Microgrid. The new method considers the stochastic behaviors of electric vehicles, including their arrivals and departures with their bids. The strategy of energy management system is based on determining the output power of generation units and the operation mode of the parking lot. This system also provides the demand response programs to consumers for load shifting. A multi-objective optimization problem is used to optimize both the operation cost and the reliability of the Microgrid. The capability of the proposed algorithm is verified by simulation results. © 2019 Elsevier Ltd
Energy (18736785) 171pp. 535-546
One effective way to compensate for uncertainties is the use and management of energy storage. Therefore, a new method based on stochastic programming (SP) is proposed here, for optimal bidding of a generating company (GenCo) owning a compressed air energy storage (CAES) along with wind and thermal units to maximize profits. This scheduling has been presented for the GenCo's participation in day-ahead energy and spinning reserve (SR) markets and CVaR is also considered as a risk-controlling index. Firstly, the obtained results are validated by comparing with those of two previous studies. Then, the complete results of the proposed method are presented on a real power system, which indicate the capability of SP in scheduling CAES units. Furthermore, it is observed that CAES units can gain greater profits in joint energy and reserve markets due to their high ramp rates. In addition, the value of stochastic solution (VSS) is used to quantify the advantage of the stochastic method over a deterministic one, which illustrates the advantage of SP-based optimal bidding method especially for CAES and wind units and also for risk-averse GenCos. Overall, it is concluded that the stochastic method is efficient for optimal-bidding of GenCos owning CAES and wind units. © 2019 Elsevier Ltd
IET Generation, Transmission and Distribution (17518687) 13(8)pp. 1391-1400
In the market, the aggregators offer various proposals for an electrical customer, who selects one among all of them. The proposals may include different numbers of levels of uncontracting capacity rates, demand and energy prices, measuring intervals and billing periods. To schedule the best contract between user and electricity supply provider for upcoming months, two new approaches are presented here to solve the multi-optional multi-level demand-contracting problem. First, the feasible region is curtailed to the certain edged points and then, the optimal proposal and contracting demand (CD) are obtained by either direct or indirect proposed method. Moreover, a robustness analysis on the solution due to having errors in the forecasted maximum demands and changing the generations of the connected energy resource (ER) or installing a new one is presented. Some useful stability indices are also proposed. Likewise, updating the optimal solution due to having such errors is presented. Various numerical tests are taken place to analyse the influence of each parameter of the problem on the optimum and compare the proposed techniques. The results highlight the efficient capability of the proposed methods in fast obtaining the optima and stability investigation on the solution. © The Institution of Engineering and Technology 2019.
Electric Power Components and Systems (15325016) 46(16-17)pp. 1769-1781
This paper proposes a novel algorithm for power angle control (PAC) which aims to simplify the control algorithm and obtain a fast dynamic response. It also extends the capability of PAC to compensate voltage unbalance with or without phase angle jump in a simple way. Using this control strategy, unified power quality conditioner (UPQC) can improve power quality problems such as sag, swell, and unbalances of source voltage, load reactive power and harmonics in distribution systems. The series converter in UPQC is responsible for compensation for voltage-related problems. In PAC method, the series converter also participates in load reactive power compensation which is the superiority of this control strategy. The proposed method uses triangular rules of vector addition/subtraction to determine phase and magnitude of voltage that should be injected by series converter. It reduces the required calculations and hence raises the velocity of compensation. For achieving a better dynamic response, a sliding mode control is used to control DC link voltage instead of conventional PI control. This makes the control algorithm faster and more robust. Simulation results obtained through MATLAB/SIMULINK verify the effectiveness of the proposed method. © 2019, © 2019 Taylor & Francis Group, LLC.
International Journal of Electrical Power and Energy Systems (01420615) 102pp. 23-37
One of the most important processes during load restoration is to use a suitable sectionalizing scheme to enhance the stability, especially when two islands are synchronized. In this regard, this paper provides a new scheme for the coordination of sectionalizing and load restoration to enhance the power system performance before and during the synchronization of islands. In doing so, there will be contradictory objective functions including maximizing the quality of sectionalizing process, minimizing the maximum standing phase angle (SPA) between islands, and minimizing the sum of energy not supplied (ENS) with unavailable energy capability (UEC) between all N-1 contingencies. Therefore, a multi-objective problem is defined as a mixed integer non-linear problem (MINLP). Also, a reliability-based index is defined to determine the quality of each island. Then, the θ-based water cycle algorithm (θ-WCA) is used to obtain the best Pareto optimal set. Two IEEE 39-bus and 118-bus power systems are used for validating the proposed method. The simulation results imply that the system can benefit from this scheme not only to have the good quality of sectionalizing, but also to enhance the power system performance during load restoration and the synchronization of islands. © 2018 Elsevier Ltd
International Transactions on Electrical Energy Systems (20507038) 28(11)
Installing new energy sources as redundant black-start (BS) units is an efficient way to enhance the speed of power system restoration, especially when there is a high risk that the available power plants considered as BS units fail to operate. In this regard, this paper provides a new optimal design for the placement of the gas turbine as the redundant energy source considering N-1 contingency analysis to improve the BS capability during restoration conditions. In doing so, there will be 2 contradictory objective functions of minimizing the maximum unavailable energy capacity and maximizing the minimum cranking path reliability. Therefore, a multiobjective problem, as a mixed integer nonlinear programming, is defined. The Pareto optimal solutions of the multiobjective problem are obtained by using a population-based meta-heuristic technique, called crow search algorithm. Two power systems are used for the validation of the proposed method. The simulation results show that the system can benefit from this method not only to increase the capability of BS generation but also to enhance the reliability of generators start-up. During the restoration process, the optimal start-up sequences of nonblack-start units and the most reliable transmission paths are also provided. Copyright © 2018 John Wiley & Sons, Ltd.
IEEE Transactions on Power Systems (08858950) 33(1)pp. 463-472
Low voltage (LV) state estimation in distribution networks mainly relies on pseudo measurements because the real-time monitoring is impossible for all customers. This paper presents a new method to determine the pseudo load profiles (PLPs) of customers with small consumptions connected to the LV distribution networks. This method is comprised of two stages. First, a new frequency-based clustering algorithm is proposed to extract the essential load patterns of limited number of customers who are equipped by smart meters and are called as sample customers. The superior performance of the proposed clustering algorithm is also shown in comparison with three of the most widely used clustering methods: k-means, self-organizing maps and hierarchical algorithms. In the second stage, a new approach is proposed to estimate the daily energy consumptions two weeks ahead for other customers who are not equipped by smart meters by using their previous billing cycle energy consumptions and the load data of sample customers. The PLP of a customer is obtained by multiplying the estimated daily energy consumption by the corresponding normalized load pattern. Studies have been conducted on the data of a real distribution system to verify the proposed method and to show its application for the PLP estimation of distribution networks. © 2017 IEEE.
International Transactions on Electrical Energy Systems (20507038) 28(2)
In the operation of a deregulated power system, congestion and power loss are the two major factors causing price fluctuation in different parts of the network. In this paper, a new method is proposed for calculating and investing the congestion surplus. In this method, congestion surplus, which is calculated on the basis of flow-gate marginal prices, is used as an economic signal to control the network. In this regard, different strategies such as the definition of sensitive buses and priority list of the congested lines are proposed from the perspective of flow-gate marginal price concept. In order to verify the novel reformation, distributed generation planning is presented as an illustrative example. In this approach, proper investment is applied to increase the social welfare under new formulation in the presence of distributed generation resources. The proposed algorithm is implemented on IEEE 30-bus and IEEE 57-bus networks. The results emphasize the accuracy and efficiency of the proposed algorithm for calculating the congestion surplus and increasing social welfare with the least amount of investment. Copyright © 2017 John Wiley & Sons, Ltd.
International Journal of Electrical Power and Energy Systems (01420615) 97pp. 363-371
Distribution network decision makers need accurate and reliable information about load characteristics to plan, estimate and control the system properly. Load information is generally extracted from the collected load data of selected sample customers and, therefore, a proper sample customer selection is the pillar of any load research study. In this regard, this paper presents a new stratified sampling technique which includes three stages of sample size determination and customer stratification, sample size assignment to determined strata (subgroups), and sample customer selection. The sample size assignment to determined strata is done by considering the compatibility between load research objectives and sampling design and preparing the way to use the data and information provided by previous load research studies. Furthermore, sample customers are selected by considering the energy consumption (kWh) range of customers, their activity classification, and their locations in distribution feeders. The numerical results from a real data of an electric power distribution system in Esfahan-Iran verify the efficiency of the proposed technique when compared to the conventional method. © 2017 Elsevier Ltd
IET Generation, Transmission and Distribution (17518687) 12(12)pp. 3097-3105
This study presents a new analytical solution to solve the contracting capacity (CC) optimisation problem that several sets of the demand and energy rates are available in the market. The proposed method (PM) obtains the best option for the prices and the best CC. It is mathematically proved that the best CC is the maximum demand for a specific month of interest. Further, despite most existing methods such as linear programming, PM is able to obtain all optima. Some significant properties of and the influence of the input parameters on the optimal solution are discussed. Moreover, the errors on the forecasted maximum demand and the forecasted prices are separately analysed. Finally, the PM is performed on the data of various scenarios of a large real electrical user to highlight the effectiveness of this method. © The Institution of Engineering and Technology 2018.
Journal of Cleaner Production (09596526) 172pp. 1748-1764
The Virtual Power Plants containing Distributed Energy Resources are classified into two main categories of Commercial Virtual Power Plant and Technical Virtual Power Plant as a suitable way to manage industrial environments. Here, Industrial Technical Virtual Power Plant is defined as a scheduling unit containing loads and generations located in an industrial grid. A comprehensive framework is proposed here for normal and contingency conditions for various Virtual Power Plants participating in a short-term market. This framework performs a day-ahead and intra-day generation scheduling by selecting the best Demand Response programs. In this framework, the wind generations and the day-ahead and intra-day electricity market prices are considered as the stochastic parameters. A risk-management aspect is noticed in the proposed stages for contingency conditions. Then, some element changes such as seasonal load change and single-line outage are trained in the system to accredit the proposed solution in the contingency condition. Hereof, an appropriate technique is defined to represent the proposed model and solution. To specify the effectiveness and efficiency of the proposed methodology, the modified Isfahan Regional Electric Power Company network in Iran is experimented to test the method and to assess some encouraging aspects as well. By the proposed approach, attractiveness of Demand Response programs is revealed in industrial grids and the lower cost will be imposed. Also the improvement percentage of load shedding can be gained by performing the proposed scheduling that is so important for industrial processes. © 2017 Elsevier Ltd
Oboudi, M.H. ,
Hoshmand, R. ,
Faramarzi, F. ,
Boushehri, M.J.A. IET Renewable Power Generation (17521416) 12(2)pp. 219-226
Intentional islanding operation (IIO) is a feasible solution to improve the reliability of active distribution network (ADN) by supplying critical loads through the local DG when a fault occurs. Aiming at this goal, a new two-stage methodology is proposed to supply critical loads based on cost-effective improvement. In the first stage, the interruption cost is proposed as the load priority and the ON/OFF status of switches are considered as the binary decision variables. Therefore, IIO is considered as a mixed integer linear programming (MILP) problem to minimise the interruption cost. At the second stage, the power flow calculation is performed on the initial islands for the real-time operation. The proposed method can be utilised for both long- and short-term studies. In the long-term study, the inherent uncertainty of ADN is considered in MILP by using a Monte-Carlo simulation. This concept is used for clustering ADN into self-sufficient microgrids. Moreover, by taking a snapshot of the ADN status and performing operational feasibility, the proposed method can be considered as a real-time power regulation method. The proposed methodology is implemented on the IEEE 33-bus distribution network, and the results are discussed in detail. © The Institution of Engineering and Technology 2017
IEEE Journal of Photovoltaics (21563381) 8(3)pp. 825-833
With the increasing deployment of photovoltaic (PV) sources in the power grid and their contribution to power generation, it is imperative to obtain accurate models for the reliability and stability of these plants. In this paper, a novel method is proposed for reliability assessment for the different structures involved in the implementation of PV plants, in which the failure rate of system components is calculated using the FIDES Guide standard, taking into account environmental conditions such as radiation curves, temperature, and humidity. Failure rates of the insulated gate bipolar transistor and converter capacitor were found to be greater than other components. After precise calculation of failure and repair rates, the probability of functioning in three states of full generation, partial failure, and down was obtained through Monte Carlo simulations. Considering the effect of the system's structure on its stability, the reliability of the system can be increased by adding inverter paths to its structure. Several such structures are proposed, and the most economical design is identified by analyzing load duration curves to obtain the energy loss in each configuration. The proposed algorithm was implemented in Isfahan University's 20 kW PV power plant. Simulations demonstrate the efficiency of the proposed algorithm in design and evaluation of economic system structures. © 2011-2012 IEEE.
Zare, M. ,
Azizipanah-abarghooee, R. ,
Hoshmand, R. ,
Malekpour, M. IET Generation, Transmission and Distribution (17518687) 12(6)pp. 1271-1284
Reconfiguration and smart control of remote-controlled sectionalising switches in distribution networks are considered as the major solutions for loss mitigation, interruption time reduction and reliability improvement after events. That is because these automation tools bring about changes in the topology of the network, isolate the faulted regions, operate distributed generators for local load satisfaction and restore the un-faulted regions as rapidly as possible. Thus, a new solution methodology for solving the simultaneous optimal wind turbines (WTs)/switches placement as well as network reconfiguration is developed to enhance the distribution network's efficiency and reliability. Power losses, voltage deviation index, switch cost and reliability cost based on expected customer interruption cost are considered as the objective functions. The approach profits from a new multi-objective algorithm based on modified artificial bee colony for providing the best compromise solution. The presented framework is shown to provide superior results when applied to the IEEE 69-node test feeder. Finally, different scenarios based on feeder reconfiguration, switch placement and WT placement problems are constructed and presented in Section 5. © The Institution of Engineering and Technology 2017.
Applied Soft Computing (15684946) 62pp. 1044-1055
Phase unbalancing is a problem in distribution networks that causes feeder service tripping and reduces the network quality. Re-phasing is the strategy used for phase balancing. Moreover, the power loss reduction is a significant problem in distribution networks. A common solution for power loss reduction is reconfiguration. Besides, optimal DG placement can reduce power loss and improve voltage profile. In this paper, a new method is proposed for simultaneous optimization of re-phasing, reconfiguration, and DG placement in distribution networks to reduce phase unbalancing and power loss and improve voltage profile. As there are four dissimilar objective functions, the objectives are made fuzzy and integrated as the fuzzy multi-objective function. Finally, the optimization is done by using Bacterial Foraging with Spiral Dynamic (BF-SD) algorithm. To demonstrate the performance of the proposed method, it is applied to IEEE 123-node test feeder. © 2017 Elsevier B.V.
IET Generation, Transmission and Distribution (17518687) 12(9)pp. 2173-2180
Keeping voltage quality in isolated microgrids while feeding non-linear and/or unbalanced loads is one of the major challenges in the control of these networks. This study proposes a new hierarchical control for enhancing voltage quality in sensitive load bus (SLB) of isolated microgrids considering non-SLBs (NSLBs (DG buses and local buses)) with voltage quality limitations. At the primary level of this hierarchical control, a droop controller is responsible for controlling voltage and frequency of microgrids. The duty of the secondary control level is that in the case of the reduction of voltage quality indices at SLB, it enhances them to their determined levels by sending proper control signals to the primary level to determine each DGs compensation effort. It is worth noting that improving the voltage quality indices at SLB can lead to a drop in NSLBs voltage quality indices. Although NSLBs do not have the strict voltage quality limitation of SLB, but keeping the voltage quality of these buses in their allowed limitation is necessary. The third level of the proposed hierarchical control is designed to guarantee the voltage quality indices limitation at NSLBs. Simulation results are given to demonstrate the effectiveness of the proposed control scheme. © The Institution of Engineering and Technology 2018.
Journal of Solar Energy Engineering (15288986) 139(5)
This paper proposes a new method based on a Markov model to calculate the reliability of grid-connected photovoltaic (PV) systems. This system is a grid-connected PV system consisting of PV modules, a multiphase DC-DC converter, an inverter, an inverter controller, and an maximum power point tracking (MPPT) controller at University of Isfahan. This system is considered repairable. Also, different levels of operation are considered for the system equipment. Reliability of the PV modules, the multiphase DC-DC converter, and the inverter has been calculated by the Markov model. Finally, the reliability of the entire PV system is calculated by the Markov model. The proposed algorithm is applied to the PV system positioned at University of Isfahan. Simulation results show the applicability of this method for calculating the reliability of grid-connected PV systems. Copyright © 2017 by ASME.
Renewable and Sustainable Energy Reviews (13640321) 67pp. 341-363
Due to different viewpoints, procedures, limitations, and objectives, the scheduling problem of distributed energy resources (DERs) is a very important issue in power systems. This problem can be solved by considering different frameworks. Microgrids and Virtual Power Plants (VPPs) are two famous and suitable concepts by which this problem is solved within their frameworks. Each of these two solutions has its own special significance and may be employed for different purposes. Therefore, it is necessary to assess and review papers and literature in this field. In this paper, the scheduling problem of DERs is studied from various aspects such as modeling techniques, solving methods, reliability, emission, uncertainty, stability, demand response (DR), and multi-objective standpoint in the microgrid and VPP frameworks. This review enables researchers with different points of view to look for possible applications in the area of microgrid and VPP scheduling. © 2016 Elsevier Ltd
Swarm and Evolutionary Computation (22106502) 35pp. 14-25
Intentional islanding is a suitable approach to increase the system reliability in situations where the electrical connection between the microgrid and the upstream network is lost. In this paper, an innovated two-stage method for the intentional islanding process in microgrids is proposed. The important and practical issues such as the load controllability; load priorities; voltage and the line capacity constraints; reduction of problem solution space and ability to make larger islands are taken into account. In the first stage, the problem is relaxed by considering the problem as an optimization problem known as Tree Knapsack Problem (TKP) solved by Particle Swarm Optimization (PSO). In the second stage, the power flow is calculated and the constraints are verified, then adjusting measures will be taken. The proposed method is conducted on the IEEE 69-bus test system with 6 DGs and the results are compared with other methods. Moreover, for real time verification, the obtained results are simulated by DIgSILENT/Power Factory software package. The simulation results suggest that the proposed algorithm is a valid method for the intentional islanding process. © 2017 Elsevier B.V.
Turkish Journal Of Electrical Engineering And Computer Sciences (13000632) 25(1)pp. 172-183
The distribution static compensator (DSTATCOM) is used for various purposes such as load balancing, harmonic rejection, and power factor correction (PFC) in power distribution networks. In unbalanced and polluted power systems, the classic definition of power factor cannot be used for PFC due to the existence of harmonics and negative sequence components in voltage and current waveforms. In this paper, PFC is performed using the IEEE power factor definition for harmonic and unbalanced environments. Moreover, the application of a proportional-resonant (PR) controller is proposed as an effective controller in the stationary frame for DSTATCOM performance improvement. The PR controller is used in the abc-frame for load balancing and is then compared theoretically and by simulation with the conventional PI controller, which has the main drawback of steady-state error when used in the stationary frame. To improve the DSTATCOM structure, an LCL harmonic filter is used as it is advantageous over the L/LC filter in terms of the size of the filter. The proposed DSTATCOM compensates for the disturbances in the source current imposed by nonlinear, unbalanced, and low power factor loads. Simulation results show the capability of the DSTATCOM including the proposed PR controller in improving the power quality of distribution systems. © 2017 TÜBITAK.
Renewable and Sustainable Energy Reviews (13640321) 80pp. 1043-1060
Increased penetration of distributed generation (DG) into the power systems has created fundamental challenges from the viewpoints of control and reliable operation of systems. Microgrids (an aggregation of DG units, loads, and storage elements) with proper control strategies can be a good solution for removing or facilitating these challenges. The introduction of inverter-based microgrid in a distribution network has facilitated the utilization of renewable energy resources, distributed generations, and storage resources; furthermore, it has improved power quality and reduced losses, thus improving the efficiency and the reliability of the system. As most DG units are connected via a power electronic interface to the grid, special control strategies have been developed for inverter interfaces of DG units in islanded microgrids. This paper presents an overview of advanced control methods for microgrids, especially the islanded and inverter-based. Moreover, various control methods are compared and categorized in terms of their respective features. It also summarizes microgrid control objectives with their most problematic solutions as well as their potential advantages and/or disadvantages. Finally, some suggestions are put forward for the future research. © 2017 Elsevier Ltd
UPB Scientific Bulletin, Series C: Electrical Engineering and Computer Science (22863540) 79(3)pp. 93-112
Security analysis is one of the most important functions employed by power system operators to prevent undesired cascading contingencies leading to a blackout, in an ultimate phase. To improve the security analysis of an internal power network, the accurate modeling of the external network is important in an interconnected power system. In this paper, a new methodology is proposed to identify the line outage in an external power system by using the minimum PMU measurements shared by the external system. This method is organized in several steps. First, the branches of an external power system that their outages have the considerable effect on the flow of tie-lines are identified. These branches are called critical lines. Then, based on a sensitivity analysis technique, the most sensitive measurements are identified with respect to the outage of critical lines. After that, an algorithm is proposed to prioritize these measurements to determine the minimum number of the required measurements. All of these steps are done with the help of a new artificial neural network-based approach. The proposed method is tested on a real power network which is a part of Iranian power system. Simulation results show the effectiveness of the proposed method.
Journal of Renewable and Sustainable Energy (19417012) 9(3)
This paper investigates the impacts of renewable energy resources and energy storage systems (ESS) on flow-gate marginal pricing (FMP) and locational marginal pricing (LMP) in a deregulated environment. Renewable energy resources including wind turbines and photovoltaic solar cells are modeled and discussed. Also, ESS are defined and mathematically modeled. Then, the mathematical formulation of LMP and FMP and their relationship are discussed. An IEEE six bus test system is considered as a case study. Several simulations are carried out to investigate the impacts of renewable energy resources and ESS on LPM and FMP. Furthermore, a comprehensive sensitivity analysis is conducted. It is demonstrated that renewable energy resources and their related uncertainty have a great impact on both LMP and FMP. Also, charging and discharging states of ESS significantly change LMP and FMP. It is also demonstrated that the reactive power of loads and line capacities are highly important in the FMP analysis. © 2017 Author(s).
Simulation Modelling Practice and Theory (1569190X) 75pp. 77-95
Distributed Generation (DG) resources in industrial microgrids affect the reliability parameters in the networks. Therefore, the aim of the paper is to assess the reliability of industrial microgrids using a proposed composite index in the presence of DG and Demand Response (DR) resources. The reliability evaluation is performed on the basis of sequential Monte-Carlo method with regard to the available time load. Here, the widely used renewable generations such as wind and photovoltaic ones are used. Since the output of this type of DGs depends on random variables such as wind speed and solar radiation, a number of scenarios have been considered to determine the output amount per hour. The newly presented composite index shows the changes of conventional reliability indices (SAIFI, SAIDI, and EENS) per kW of DG installed. Due to the increase of industrial loads, a 10-year study is scheduled for both islanding and grid-connected performance conditions. In the islanding condition, the DR concept is also used. The proposed method is applied to IEEE-RBTS BUS2 standard network and real-world Mahmoud-Abad industrial zone network located in Isfahan, Iran in the presence of DG resources to show its effectiveness. The results are evaluated and compared in different conditions for elucidation. © 2017 Elsevier B.V.
IET Generation, Transmission and Distribution (17518687) 11(13)pp. 3210-3221
Optimal capacitor placement in distribution systems has been studied for many reasons such as the improvement of voltage profile, mitigation of total harmonic distortion, and reduction of power losses. In this study, a new approach is presented for capacitor placement in the presence of harmonic distortion along with a proposed resonance index (RI). In this approach, a sensitivity analysis is first applied to find candidate buses. After that, the size and location of capacitors are optimised by a proposed fitness function. The fitness function includes a fuzzy membership function of annual net benefit, maximum THD of voltage, maximum voltage deviation, and a resonance constraint. This procedure supports different load levels employing fixed and switched capacitors. Also, a new RI is presented to prevent resonance conditions. Finally, the approach is tested on an IEEE 18-bus and an IEEE 69-bus system using the multi-swarm particle swarm optimisation algorithm. The simulation results show the efficiency of the method in comparison with the other methods. © The Institution of Engineering and Technology.
Applied Energy (18729118) 202pp. 308-322
Nowadays, renewable energy sources and combined heat and power units are extremely used in micro grids, so it is necessary to schedule these units to improve the performance of the system. In this regard, a stochastic model is proposed in this paper to schedule proton exchange membrane fuel cell-combined heat and power, wind turbines, and photovoltaic units coordinately in a micro grid while considering hydrogen storage. Hydrogen storage strategy is considered for the operation of proton exchange membrane fuel cell-combined heat and power units. To consider stochastic generation of renewable energy source units in this paper, a scenario-based method is used. In this method, the uncertainties of electrical market price, the wind speed, and solar irradiance are considered. This stochastic scheduling problem is a mixed integer- nonlinear programming which considers the proposed objective function and variables of coordinated scheduling of PEMFC-CHP, wind turbines and photovoltaic units. It also considers hydrogen storage strategy and converts it to a mixed integer nonlinear problem. In this study a modified firefly algorithm is used to solve the problem. This method is examined on modified 33-bus distributed network as a MG for its performance. © 2017 Elsevier Ltd
Energy Conversion and Management (01968904) 150pp. 725-741
Nowadays the operation of renewable energy sources and combined heat and power (CHP) units is increased in micro grids; therefore, to reach optimal performance, optimal scheduling of these units is required. In this regard, in this paper a micro grid consisting of proton exchange membrane fuel cell-combined heat and power (PEMFC-CHP), wind turbines (WT) and photovoltaic (PV) units, is modeled to determine the optimal scheduling state of these units by considering uncertain behavior of renewable energy resources. For this purpose, a scenario-based method is used for modeling the uncertainties of electrical market price, the wind speed, and solar irradiance. It should be noted that the hydrogen storage strategy is also applied in this study for PEMFC-CHP units. Market profit, total emission production, and average energy not supplied (AENS) are the objective functions considered in this paper simultaneously. Consideration of the above-mentioned objective functions converts the proposed problem to a mixed integer nonlinear programming. To solve this problem, a multi-objective firefly algorithm is used. The uncertainties of parameters convert the mixed integer nonlinear programming problem to a stochastic mixed integer nonlinear programming problem. Moreover, optimal coordinated scheduling of renewable energy resources and thermal units in micro-grids improve the value of the objective functions. Simulation results obtained from a modified 33-bus distributed network as a micro grid illustrates the effectiveness of the proposed method. © 2017 Elsevier Ltd
Journal of Electrical Engineering and Technology (19750102) 12(4)pp. 1357-1368
The lack of controllability over the wind causes fluctuations in the output power of the wind generators (WGs) located at the wind farms. Distribution Static Compensator (DSTATCOM) equipped with Battery Energy Storage System (BESS) can significantly smooth these fluctuations by injecting or absorbing appropriate amount of active power, thus, controlling the power flow of WGs. But because of the component aging and thermal drift, its harmonic filter parameters vary, resulting in performance degradation. In this paper, Quantitative Feedback Theory (QFT) is used as a robust control scheme in order to deactivate the effects of filter parameters variations on the wind power generation power smoothing performance. The proposed robust control strategy of the DSTATCOM is successfully applied to a microgrid, including WGs. The simulation results obviously show that the proposed control technique can effectively smooth the fluctuations in the wind turbines' (WT) output power caused by wind speed variations; taking into account the filter parameters variations (structural parameter uncertainties). © The Korean Institute of Electrical Engineers.
IEEE Access (21693536) 5pp. 14490-14501
The quantitative feedback theory is adopted as a robust control scheme for the distribution-static-compensator (DSTATCOM) in order to deactivate the effects of variations in its harmonic filter parameters on the fault ride through the capability of wind turbines (WTs). These variations may be due to factors like component aging and thermal drift. The DSTATCOM is applied in parallel with the wind generation (WG) together with a bridge-type-fault-current-limiter in series, to improve FRT capability of the WT. This proposed robust control strategy of the DSTATCOM is applied to a microgrid, including WG. The performance of this proposed scheme is simulated in PSCAD/EMTDC environment and the results indicate its efficiency. © 2013 IEEE.
Mohammadi, M.B. ,
Hoshmand, R. ,
Haghighatdar fesharaki f., F.H. IEEE Transactions on Smart Grid (19493053) 7(1)pp. 84-93
In recent years, power utilities have been designing and implementing wide area measurement system (WAMS) to provide more intelligent monitoring, control, and protection for the power grid. In this paper, a new method is presented for the optimization of the cost of different parts of the WAMS. In this method, the cost of optimal placement of phasor measurement units (PMUs) and a phasor data concentrator (PDC), as well as their associated communication infrastructure (CI) are simultaneously considered and minimized. For this purpose, the binary imperialistic competition algorithm is used for the optimal placement of PMUs. Dijkstra's single-source shortest-path algorithm is used to obtain the minimum CI cost. It is also used for optimal placement of PDC. Because of the good adaptability of the proposed methodology to understudy problem, the proposed method is implemented in different conditions of the power network such as N - 1 contingency condition (e.g., a single-line outage or a single-PMU outage), and some important and practical considerations are provided. Practical considerations are the availability of preinstalled PMUs in some buses and the availability of the communication links in some parts of the power network. The effectiveness of the proposed method is verified on different IEEE standard test systems. © 2015 IEEE.
Turkish Journal Of Electrical Engineering And Computer Sciences (13000632) 24(4)pp. 3178-3197
Among several methods used for calculating the root mean square (RMS) of electrical signals, Fourier and wavelet transforms are the most common approaches. The latter also has the advantage of being able to analyze both stationary and nonstationary signals. However, in the wavelet-based methods, the presence of both odd and even harmonics in the input signal causes the harmonic components not to be in the center of the extracted frequency bands and this will reduce the accuracy of the RMS calculation. In order to remove this drawback, this paper proposes a new method based on wavelet and Hilbert transforms, in which the frequency of all harmonic components is increased by half of the main frequency by using a preprocessing technique. In simulation results, the RMS value of a real signal of the steel electric arc furnace of the Esfahan Mobarakeh Steel Company is calculated by using the suggested method. The results clearly show that the accuracy of the proposed approach is better than that of conventional and grouping methods. © 2016 Tübitak.
Electric Power Components and Systems (15325016) 44(7)pp. 726-736
Following the penetration of microgrids in distribution systems, frequency deviations in contingency conditions are becoming increasingly important. Therefore, effective load shedding is necessary to regulate the frequency. This article develops a new load-shedding method for microgrids considering wind speed changes. The proposed method uses a combination of frequency and voltage data for determining load-shedding amounts in each contingency condition. For this purpose, the total required load shedding is determined first by using transient stability analysis in different contingency scenarios in microgrids. This will establish a database for an adaptive neuro-fuzzy inference system network to determine the total required load shedding. Then a fuzzy system is used to determine the load shedding in each step dynamically based on the severity of contingencies. The proposed method capability is compared with the conventional load-shedding method. Simulation results show the effectiveness of the proposed method for microgrid control in contingency conditions. © 2016, Copyright © Taylor & Francis Group, LLC.
Nosratabadi, S.M. ,
Hoshmand, R. ,
Gholipour, E. ,
Parastegari, M. International Transactions on Electrical Energy Systems (20507038) 26(5)pp. 1103-1120
Summary Virtual power plant (VPP) is combining different types of generations and interruptible loads to be able to contribute to the market as a power plant with a significant output. In other words, different power generations are combined in a complementary manner to form a defined generation and a demand profile. Because the most important elements of these operators are distributed generation (DG) units and demand response loads (DRLs), the determination of optimal location, capacity, type, as well as the installation time of DGs, DRLs participation size, and place in the distribution system are the most important challenges of operators. In this paper, the formulation of optimal placement of DG resources and DRLs is presented and solved simultaneously in a distribution system to determine the optimal VPP. For this purpose, the concepts of commercial virtual power plant and technical virtual power plant are introduced first, and then the optimal VPP, which can send its energy bids as a short-term and long-term power scheduling to the power market, is determined. Here, commercial virtual power plant and technical virtual power plant will act jointly as commercial-technical virtual power plant to extract the results of the proposed optimization procedure. In this paper, the binary particle swarm optimization algorithm is used to solve the optimization problem in the distribution system. The proposed method is applied to the IEEE 33-bus distribution test network, and the results confirm the effectiveness of the proposed method. © Copyright 2015 John Wiley & Sons, Ltd.
Renewable Energy (09601481) 85pp. 620-630
This paper deals with a coordinated generation expansion planning (GEP)-transmission expansion planning (TEP) in competitive electricity market. In the proposed method, GEP and TEP are performed at the same time, with consideration of wind farm uncertainty. The uncertainty is modeled by normal probability distribution function (PDF) and Monte-Carlo simulation (MCS) is used to include the uncertainty into the problem. The planning is managed for two master and slave levels. At slave level, all generation company (GENCO) and transmission company (TRANSCO) maximize their profit and then at master level, the system constraints are checked by independent system operator (ISO). In other words, the proposed planning aims at maximizing the expected profit of all GENCOs and TRANSCOs, while considering security and reliability constraints such as reserve margin and loss of load expectation (LOLE). The proposed problem is a constrained, nonlinear, mixed-integer optimization programming and solved by using particle swarm optimization (PSO) method. Simulation results verify the effectiveness and validity of the proposed planning for maximizing GENCOs and TRANSCOs profit in the presence of wind farm uncertainty under electricity market. © 2015 Elsevier Ltd.
International Journal of Electrical Power and Energy Systems (01420615) 78pp. 745-754
Intentional islanding is a feasible solution to improve the reliability of the smart distribution system with distributed generations (DGs) when the electrical connections between the smart distribution system and upstream network are lost. In this paper, a heuristic method is proposed for the intentional islanding of microgrids. In this method, some practical and important factors such as reduction of problem solution space; load controllability; load priority; bus voltage; line capacity constraints; and the ability to construct larger islands by the combination of islands are taken into account. The proposed method is a two-stage method. In the first stage, the intentional islanding problem is relaxed and in the second stage, the feasibility of the solution is verified. In the first stage, the intentional islanding problem is assumed as a series of tree knapsack problems (TKPs) and solved by the modified shuffled frog leap algorithm (SFLA). In the second stage, the power flow calculation is carried out to check the feasibility of the islands and essential modifications are provided. The proposed method is applied to IEEE 69-bus test system with 6 DGs. The results are compared with other methods and the effects of different methods on the system reliability indices are discussed. These comparisons indicate that the proposed method is feasible and valid. © 2015 Elsevier Ltd. All rights reserved.
Energy (18736785) 117pp. 176-189
In this paper, a stochastic model is proposed for coordinated scheduling of combined heat and power units in micro grid considering wind turbine and photovoltaic units. Uncertainties of electrical market price; the speed of wind and solar radiation are considered using a scenario-based method. In the method, scenarios are generated using roulette wheel mechanism based on probability distribution functions of input random variables. Using this method, the probabilistic specifics of the problem are distributed and the problem is converted to a deterministic one. The type of the objective function, coordinated scheduling of combined heat and power, wind turbine, and photovoltaic units change this problem to a mixed integer nonlinear one. Therefore to solve this problem modified particle swarm optimization algorithm is employed. The mentioned uncertainties lead to an increase in profit. Moreover, the optimal coordinated scheduling of renewable energy resources and thermal units in micro grids increase the total profit. In order to evaluate the performance of the proposed method, its performance is executed on modified 33 bus distributed system as a micro grid. © 2016 Elsevier Ltd
Electric Power Components and Systems (15325016) 44(15)pp. 1721-1734
This article proposes a new control approach for an interline unified power quality conditioner and a multi-converter unified power quality conditioner to optimize the utilization of the inverters of these structures. In this method, the series active power filter is controlled by the application of a power angle control concept to compensate an unbalanced voltage (asymmetrical voltage sag/swell with or without phase angle jumps) and also partial-load reactive power for power factor correction. Since voltage variation (sag/swell, unbalance, etc.) is a short-duration power quality problem in distribution systems, under normal operating conditions, series inverters are not utilized effectively in conventional methods. By using the proposed method, optimal utilization of series inverters of both structures and also a reduction in the shunt inverter rating of a multi-converter unified power quality conditioner will be achieved. Also, the shunt active power filter is controlled to compensate the unbalanced current, harmonics, and neutral current of a three-phase four-wire system and to take part in power factor correction. The proposed approach is validated through MATLAB/SIMULINK-based (The MathWorks, Natick, Massachusetts, USA) simulation and the results are discussed. © 2016, Copyright © Taylor & Francis Group, LLC.
Applied Energy (18729118) 164pp. 590-606
One of the main classified microgrids in a power system is the industrial microgrid. Due to its behaviors and the heavy loads, its energy management is challengeable. Virtual Power Plant (VPP) can be an important concept in managing such problems in this kind of grids. Here, a transmission power system is considered as a Regional Electric Company (REC) and the VPPs comprising Distributed Generation (DG) units and Demand Response Loads (DRLs) are determined in this system. This paper focuses on Industrial VPP (IVPP) and its management. An IVPP can be determined as a management unit comprising generations and loads in an industrial microgrid. Since the scheduling procedure for these units is very important for their participation in a short-term electric market, a stochastic formulation is proposed for power scheduling in VPPs especially in IVPPs in this paper. By introducing the DRL programs and using the proposed modeling, the operator can select the best DRL program for each VPP in a scheduling procedure. In this regard, a suitable approach is presented to determine the proposed formulation and its solution in a Mixed Integer Non-Linear Programming (MINLP). To validate the performance of the proposed method, the IEEE Reliability Test System (IEEE-RTS) is considered to apply the method on it, while some challenging aspects are presented. © 2015 Elsevier Ltd.
Journal of Renewable and Sustainable Energy (19417012) 7(5)
Due to the growing use of photovoltaic (PV) systems in recent years, the reliability of these systems as one of the most important issues regarding durability and correct performance is important. This paper presents a comprehensive assessment of the reliability of Residential PV System (RPVS) in various conditions based on the Markov model. The systems taken into considerations consist of PV modules, a DC-DC converter, an inverter, an inverter controller, and a maximum power point tracking (MPPT) controller. These systems are considered repairable. To evaluate the effect of the three-phase boost converter and the PV modules on reliability, these systems have been considered towards this specific perspective. Furthermore, the impact of various factors on the reliability of the system components and the entire system is evaluated. Simulation results demonstrate the capacity of the proposed method to assess and comparison of the reliability of different RPVS. Also, the results indicate the impact of various factors such as temperature on it. © 2015 AIP Publishing LLC.
Electric Power Components and Systems (15325016) 43(1)pp. 69-82
Optimum under-frequency load shedding during contingency situations is one of the most important issues in power system security analysis; if carried out online fast enough, it will prevent the system from going to a complete blackout. This article presents a new fast load-shedding method in which the amounts of active and reactive power to be shed are optimized with a dynamic priority list by using a hybrid culture-particle swarm optimization-co-evolutionary algorithm and artificial neural network method. The proposed method uses a five-step load-shedding scenario and is able to determine the necessary active and reactive load-shedding amounts in all steps simultaneously on a real-time basis. An artificial neural network database is established by using offline N - K (K = 1, 2, and 3) contingency analysis of the IEEE 118-bus test system. The Levenberg-Marquardt back-propagation training algorithm is used for the artificial neural network, and the training process is optimized by using a genetic algorithm. The artificial neural network database is updated based on new contingency events that occur in the system. The simulation results show that the proposed algorithm will give optimal load shedding for different N - K contingency scenarios in comparison with other available under-frequency load-shedding methods. © 2015 Taylor & Francis Group, LLC.
Energy (18736785) 83pp. 734-748
In this paper, a stochastic model is proposed for planning the location and operation of Molten Carbonate Fuel Cell Power Plants (MCFCPPs) in distribution networks when used for Combined Heat, Power, and Hydrogen (CHPH) simultaneously. Uncertainties of electrical and thermal loads forecasting; the pressures of hydrogen, oxygen, and carbon dioxide imported to MCFCPPs; and the nominal temperature of MCFCPPs are considered using a scenario-based method. In the method, scenarios are generated using Roulette Wheel Mechanism (RWM) based on Probability Distribution Functions (PDF) of input random variables. Using this method, probabilistic specifics of the problem are distributed and the problem is converted to a deterministic one. The type of the objective functions, placement, and operation of MCFCPPs as CHPH change this problem to a mixed integer nonlinear one. So, multi-objective Modified Firefly Algorithm (MFA) and Pareto optimal method are employed for solving the multi-objective problem and for compromising between the objective functions. During the simulation process, a set of non-dominated solutions are stored in a repository. The 69-bus distribution system is used for evaluating the proper function of the proposed method. © 2015 Elsevier Ltd.
Applied Soft Computing (15684946) 28pp. 57-68
In this paper, the Thyristor-Controlled Series-Compensated (TCSC) devices are located for congestion management in the power system by considering the non-smooth fuel cost function and penalty cost of emission. For this purpose, it is considered that the objective function of the proposed optimal power flow (OPF) problem is minimizing fuel and emission penalty cost of generators. A hybrid method that is the combination of the bacterial foraging (BF) algorithm with Nelder-Mead (NM) method (BF-NM) is employed to solve the OPF problems. The optimal location of the TCSC devices are then determined for congestion management. The size of the TCSC is obtained by using of the BF-NM algorithm to minimize the cost of generation, cost of emission, and cost of TCSC. The simulation results on IEEE 30-bus, modified IEEE 30-bus and IEEE 118-bus test system confirm the efficiency of the proposed method for finding the optimal location of the TCSC with non-smooth non-convex cost function and emission for congestion management in the power system. In addition, the results clearly show that a better solution can be achieved by using the proposed OPF problem in comparison with other intelligence methods. © 2014 Elsevier B.V. All rights reserved.
International Journal of Electrical Power and Energy Systems (01420615) 73pp. 665-673
Abstract Distribution network expansion planning (DNEP) is one of the most important tools to deal with the demand growth in a system. DNEP is usually carried out through reinforcement or installation of new components. In this paper, a new and combined methodology is used to consider several practical aspects in DNEP such as uncertainty, distributed generation (DG), load growth, electricity market and multi stage dynamic expansion are included in the planning. So that DNEP is addressed in the presence of distributed generation (DG), considering load and price uncertainties under electricity market environment. The proposed planning aims at minimizing investment and operational costs simultaneously. Since DNEP in coordination with DG planning leads to reduce planning cost; therefore, the coordinated DNEP and DG planning are presented in this paper. The proposed planning is implemented by the particle swarm optimization (PSO) technique. Besides, the uncertainties are modeled as the probability distribution function (PDF) and Monte-Carlo simulation (MCS) is used to insert the uncertainties into the programming. The proposed planning is carried out based on the 9-bus as well as Kianpars-Ahvaz test systems (Kianpars-Ahvaz is a practical network in Ahvaz province, Iran). The simulation results demonstrate the ability and effectiveness of the proposed planning to deal with uncertainties under electricity market environment. © 2015 Elsevier Ltd.
Transactions of the Institute of Measurement and Control (14770369) 37(9)pp. 1095-1108
In this paper, a new method is proposed for fundamental power calculation based on a wavelet transform with preprocessing by the Hilbert transform. The proposed method increases the frequencies of all harmonics by half of the main frequencies and locates both odd and even harmonics in the centres of the extracted frequency bands. Unlike the conventional method, there is no frequency interference and the fundamental power calculation is enhanced. In order to examine the proposed method, the steel electric arc furnace (EAF) of the Mobarakeh Steel Company, Esfahan, Iran is simulated in MATLAB software at the early stage of charging. Then the fundamental active, reactive and apparent power of the EAF are calculated using simulated and real data. Results confirm the effectiveness of the proposed method. © SAGE Publications.
International Journal of Electrical Power and Energy Systems (01420615) 64pp. 275-284
Renewable resources generation scheduling is one of the newest problems of the power markets. In this paper, joint operation (JO) of wind farms (WF), pump-storage units (PSU), photo-voltaic (PV) resources, and energy storage devices (ESD) is studied in the energy and ancillary service markets. There are uncertainties in wind power generation (WPG), photovoltaic power generation (PVPG) and the market prices. To model these uncertainties, the WPG is forecasted by using ARMA model and its scenarios are generated using Weibull distribution function. Moreover, other uncertain parameters are forecasted first, and their uncertainties are modeled by using scenario generation and scenario reduction method. The proposed JO method is used to determine the optimal bidding strategy of the PSU, PV, ESD and WF of IEEE 118-bus standard system. The results for these renewable energy resources confirm that the JO of these resources increases the profit and decreases the risk of the resources in comparison with their uncoordinated operation (UO). © 2014 Elsevier Ltd. All rights reserved.
ISA Transactions (00190578) 53(2)pp. 415-422
For the participation of the steam power plants in regulating the network frequency, boilers and turbines should be co-ordinately controlled in addition to the base load productions. Lack of coordinated control over boiler-turbine may lead to instability; oscillation in producing power and boiler parameters; reduction in the reliability of the unit; and inflicting thermodynamic tension on devices. This paper proposes a boiler-turbine coordinated multivariable control system based on improved sliding mode controller (ISMC). The system controls two main boiler-turbine parameters i.e., the turbine revolution and superheated steam pressure of the boiler output. For this purpose, a comprehensive model of the system including complete and exact description of the subsystems is extracted. The parameters of this model are determined according to our case study that is the 320 MW unit of Islam-Abad power plant in Isfahan/Iran. The ISMC method is simulated on the power plant and its performance is compared with the related real PI (proportional-integral) controllers which have been used in this unit. The simulation results show the capability of the proposed controller system in controlling local network frequency and superheated steam pressure in the presence of load variations and disturbances of boiler. © 2013 ISA.
International Journal of Electrical Power and Energy Systems (01420615) 61pp. 48-55
Distribution system companies (DISCOs) try to pay less to energy markets by reducing energy loss in their networks. Reconfiguration is one of the most economic ways to reach that goal. The objective of this study is to present a new method for reducing DISCO costs in deregulated environment by loss reduction and power generation control of Distributed Generators (DGs). This problem is solved at different network load levels. Since this problem enjoys a large solution space with several constrains, it is therefore one of the complex optimization problems. A new method based on shuffled frog leaping algorithm (SFLA) is used to solve this problem. The proposed method is first applied to IEEE 33-bus test system to confirm its capability relative to other methods. Then, by applying the proposed method to IEEE 33-bus and 69-bus test systems, the activity cost of DISCO in deregulated environment is decreased. © 2014 Elsevier Ltd. All rights reserved.
Renewable and Sustainable Energy Reviews (13640321) 29pp. 1-10
In this paper, a new methodology for Transmission Expansion Planning (TEP) in deregulated electricity market is presented. The proposed TEP is associated with Reactive Power Planning (RPP), reliability assessment and also consideration of wind and load uncertainties. The proposed planning aims at investment cost minimization, social welfare maximization and satisfying reliability constraint at the same time with taking into account wind and load uncertainties. Expected Energy Not Supplied (EENS) is used as an index for reliability evaluation. At first, Monte-Carlo simulation is used to obtain the Probability Density Function (PDF) of Wind Turbine Generator (WTG) output. Then, the WTG and load uncertainties are considered in TEP formulation. Particle Swarm Optimization (PSO) method is considered to solve the proposed planning problem which is a constrained nonlinear mixed integer optimization programming. Simulation results on two standard test systems (Garver and RTS systems) verify the effectiveness of the proposed planning for consideration of wind and load uncertainties in TEP problem under electricity market environment. Also, the proposed method leads to reduction of the total investment cost, the reliability improvement and the social welfare maximization. © 2013 Elsevier Ltd.
Hoshmand, R. ,
Koochak shooshtari m., M.K. ,
Eghlidos t., ,
Aref, M.R. pp. 104-108
This paper introduces a public key scheme based on polar codes to improve the performance of McEliece cryptosystem. By exploiting the interesting properties of polar codes, we put the encryption matrix of the proposed scheme in systematic form. Moreover, the nonsingular matrix is constructed from the generator matrix of used polar code. These proceedings lead to decrease the public and private key lengths compared with the original McEliece public key cryptosystem. We analyze the proposed scheme against known attacks on the public key cryptosystems based on channel coding. Moreover, it benefits from high code rate and proper error correction capability for reliable communication. © 2014 IEEE.
Energy (18736785) 72pp. 434-442
STLF (short term electric load forecasting) plays an important role in the operation of power systems. In this paper, a new model based on combination of the WT (wavelet transform) and GM (grey model) is presented for STLF and is improved by PSO (particle swarm optimization) algorithm. In the proposed model, the weather data including mean temperature, mean relative humidity, mean wind speed, and previous days load data are considered as the model inputs. Also, the wavelet transform is used to eliminate the high frequency components of the previous days load data and improve the accuracy of prediction. To improve the accuracy of STLF, the generation coefficient of GM is enhanced using PSO algorithm. To verify its efficiency, the proposed method is used for New York's and Iran's load forecasting. Simulation results confirm favourable performance of the proposed method in comparison with the previous methods studied. © 2014 Elsevier Ltd.
IEEE Transactions on Smart Grid (19493053) 5(1)pp. 312-319
The ability of data recovery during communicational failures is one of the significant advantages of the wide area measurement system (WAMS) with hierarchical structure. For this purpose, in addition to the proper partitioning of the WAMS, the relative location of phasor measurement units (PMUs) and phasor data concentrators (PDCs) should be selected so as to maximize the reliability of the communication network. The aim of this paper is to develop an organized method for partitioning the WAMS as well as proposing a new algorithm for the simultaneous optimal placement of PMUs and PDCs. In the proposed method, first it is assumed that PMUs are installed at all of the system buses. Then, redundant PMUs will be omitted sequentially to provide the system observability with the maximum communication reliability. The IEEE 30-, and 118-bus systems are used to demonstrate the proposed algorithm. Contingencies such as PMU loss and line outage are considered in power system observability achievement. Finally, to show the applicability of proposed methods to real dimensional power systems, the IEEE 300-bus power system is also analyzed in the normal operating condition. © 2013 IEEE.
International Journal of Electrical Power and Energy Systems (01420615) 45(1)pp. 313-324
In this paper, a new two-step algorithm is proposed for short-term load forecasting (STLF). In the first step of the method, a wavelet transform (WT) and an artificial neural network (ANN) are used for the primary forecasting of the load over the next 24 h. Inputs of this step are weather features (include the daily mean temperature, maximum temperature, mean humidity, and mean wind speed) and previous day load data. In the second step, a WT, the similar-hour method and adaptive neural fuzzy inference system (ANFIS) are used to improve the results of primary load forecasting. In this study, a WT is employed to extract low-order components of the load and weather data. Furthermore, the number of weather data inputs has been reduced by investigating the weather conditions of different cities. To evaluate the performance of the proposed method, it is applied to forecast Iran's load and New South Wales of Australian's load. Simulation results in four different cases show that the proposed method increases load forecasting accuracy. © 2012 Elsevier Ltd. All rights reserved.
Applied Energy (18729118) 101pp. 489-501
This paper presents a new hybrid forecasting engine for day-ahead peak load prediction in Iran National Grid (ING). In this forecasting engine the seasonal data bases of the historical peak load demand on the similar days with their weather information given for three cities (Tehran, Tabriz and Ahvaz) have been used. Wavelet decomposition is used to capture low and high frequency components of each data base from original noisy signals. A separate ANN with an iterative training mechanism which is optimized by genetic algorithm is employed for each low and high frequency data base. A day-ahead peak demand is determined with the reconstruction of low and high frequency output components of each ANN. Simulation results show the effectiveness and the superiority of the proposed strategy when compared with other methods for daily peak load demand forecasting in ING and EUNITE test cases. © 2012 Elsevier Ltd.
Electric Power Systems Research (03787796) 100pp. 43-54
In the hierarchical structure of a wide area measurement system (WAMS), the measurements obtained by phasor measurement units (PMUs) in a local area are first submitted to the related phasor data concentrator (PDC), and then to the power system control center. In this paper, a new method for the optimal placement of PMUs as well as PDCs in local networks of a WAMS is proposed. This method minimizes the probability of failures in data transmission from PMUs to PDCs. In the proposed method, first it is assumed that PMUs are installed on all system buses. Then, the redundant PMUs will be omitted one after the other in a multi-stage procedure. The multi-stage elimination procedure is such that in each stage the arrangement of PMUs-PDC with the highest reliability will be kept. The IEEE 14-, 30-, as well as 118-bus test systems are used to demonstrate the proposed algorithm and to verify the results. In numerical simulations, the power system observability is treated in various conditions such as the base case, N - 1 condition and the case of considering the single line outage. © 2013 Elsevier B.V. All rights reserved.
International Journal of Electrical Power and Energy Systems (01420615) 49(1)pp. 199-212
In this paper, Benders Decomposition method improved by Bacterial Foraging oriented by Particle Swarm Optimization method (BDI-BFPSO) is used for solving AC constrained hydro-thermal generation scheduling problem. The objective function of the proposed generation scheduling problem is to minimize the generation cost and emission cost of the power system by considering the valve point effect and prohibited operating zones of thermal units. This problem is a large scale mixed integer nonlinear programming problem with a great number of equality and inequality constraints related to generation units, hydro system and power system. In order to solve this problem using BDI-BFPSO, the optimization problem is decomposed into a master problem and a sub-problem which they can be solved iteratively. The performance of the BDI-BFPSO method is tested and evaluated on IEEE 6-bus and 118-bus standard systems. Simulation results confirm the effectiveness of the proposed BDI-BFPSO method for solving the scheduling problem in comparison with other methods. © 2013 Elsevier Ltd. All rights reserved.
Electric Power Components and Systems (15325016) 41(15)pp. 1433-1455
This article presents a new strategy for blackout prevention in a power system using parallel flexible AC transmission system devices and a combination of corrective actions. The vulnerability index of the power system is used for on-line condition monitoring to determine the status of the system. The proposed method has a high speed for detecting the security level and vulnerable points of the system. When a disturbance occurs, the vulnerability indexes of the system are first obtained; then, by considering the effect of flexible AC transmission system devices on these indices, the proposed corrective actions are utilized to prevent the blackout and restore system stability. These actions include disabling the third zones of distance relays of vulnerable lines by using static VAR compensator, static synchronous compensator, or thyristor-controlled series compensator devices to control reactive power and applying the optimal under frequency load shedding. The adaptive particle swarm optimization algorithm is used for selecting the most economic and optimal amounts of flexible AC transmission system devices and the location of the load shedding. Simulation results on the IEEE 39-bus test system show that the blackout can be effectively prevented by using the proposed method. © 2013 Copyright Taylor and Francis Group, LLC.
IET Generation, Transmission and Distribution (17518687) 7(9)pp. 955-964
Investment on generation system and transmission network is an important issue in power systems, and investment reversibility closely depends on performing an optimal planning. In this regard, generation expansion planning (GEP) and transmission expansion planning (TEP) have been presented by researchers to manage an optimal planning on generation and transmission systems. In recent years, a large number of research works have been carried out on GEP and TEP. These problems have been investigated with different views, methods, constraints and objectives. The evaluation of researches in these fields and categorising their different aspects are necessary to manage further works. This study presents a comprehensive review of GEP and TEP problems from different aspects and views such as modelling, solving methods, reliability, distributed generation, electricity market, uncertainties, line congestion, reactive power planning, demand-side management and so on. The review results provide a comprehensive background to find out further ideas in these fields. © The Institution of Engineering and Technology 2013.
Simulation Modelling Practice and Theory (1569190X) 37pp. 56-69
Renewable power plants generation scheduling and unit commitment construct new problems of the power systems. In this paper, optimal scheduling of the joint operation (JO) and uncoordinated operation (UO) of wind farms and pump-storage plants in the energy and ancillary service markets are studied. For this purpose, a new method for modeling, simulation and evaluation of these units is presented. Since there are uncertainties in wind power generation (WPG) and the market prices, the scheduling problem is modeled by a stochastic optimization problem. Optimal bidding strategy of units is determined by solving this stochastic optimization problem. For this purpose, uncertainties are modeled by a scenario tree method. In order to evaluate the performance of the results of JO and UO of the plants, the value at risk (VaR) and the profit of the plants are compared. With JO of pump-storage plants and wind units, the profit of these plants in comparison with their UO will be increased. The results for pump-storage and wind farms of IEEE 118-bus standard system, verify that the JO of these units, improves the profit and VaR of the system. © 2013 Elsevier B.V. All rights reserved.
Amelian m., S.M. ,
Hoshmand, R. ,
Ashourian m.h., ,
Mirazimi s.j., ,
Saberi h., pp. 60-65
Microgrid concept provides an appropriate context for installing distributed generation resources and providing reliability and power quality for sensitive loads. However, presence of intermittent energy resources like wind turbines and solar cells may affect the microgrid performance due to the close production and consumption levels. In this paper, model of a wind turbine equipped with a doubly fed induction generator system is presented which is capable of operating in islanded mode by decentralized power control method based on active power-frequency and reactive power-voltage droop characteristics. Using this precise modeling approach, small signal stability of the entire system is assessed and then improved based on eigenvalue analysis. Simulated annealing algorithm is used to enhance stability margin and damping ratio of critical modes. Through simulation in a sample microgrid environment, accuracy of the proposed control method and the optimization process is verified. Finally, control system parameters are optimized to ensure stable operation in different loading conditions of the islanded microgrid. © 2013 IEEE.
Energy Conversion and Management (01968904) 76pp. 517-526
This paper addresses reliability constrained generation expansion planning (GEP) in the presence of wind farm uncertainty in deregulated electricity market. The proposed GEP aims at maximizing the expected profit of all generation companies (GENCOs), while considering security and reliability constraints such as reserve margin and loss of load expectation (LOLE). Wind farm uncertainty is also considered in the planning and GENCOs denote their planning in the presence of wind farm uncertainty. The uncertainty is modeled by probability distribution function (PDF) and Monte-Carlo simulation (MCS) is used to insert uncertainty into the problem. The proposed GEP is a constrained, nonlinear, mixed-integer optimization programming and solved by using particle swarm optimization (PSO) method. In this paper, Electricity market structure is modeled as a pool market. Simulation results verify the effectiveness and validity of the proposed planning for maximizing GENCOs profit in the presence of wind farms uncertainties in electricity market. © 2013 Elsevier Ltd. All rights reserved.
Electric Power Systems Research (03787796) 97pp. 116-125
One of the most effective tools to prevent the voltage amplitude from a sudden change in distribution systems is the dynamic voltage restorer (DVR). In this paper, a novel voltage control loop using quantitative feedback theory (QFT) is proposed for the emergency control of distribution systems by means of DVR. The proposed multi-functional DVR control strategy is applied to a three-phase fault which is the main cause of the worst voltage sag. The simulation results clearly show that this control strategy would be able to effectively regulate the voltage, especially when the parameters of the system change. The ability of the proposed DVR to limit the downstream fault current has been also examined. This current limitation will restore the Point of Common Coupling (PCC) (the bus to which all feeders are attached) voltage and also protect the DVR itself. © 2012 Elsevier B.V.
This paper proposes an efficient secret key cryptosystem based on polar codes over Binary Erasure Channel. We introduce a method, for the first time to our knowledge, to hide the generator matrix of the polar codes from an attacker. In fact, our main goal is to achieve secure and reliable communication using finite-length polar codes. The proposed cryptosystem has a significant security advantage against chosen plaintext attacks in comparison with the Rao-Nam cryptosystem. Also, the key length is decreased after applying a new compression algorithm. Moreover, this scheme benefits from high code rate and proper error performance for reliable communication. © 2013 IEEE.
IET Science, Measurement and Technology (17518822) 7(2)pp. 119-127
One of the main methods for partial discharge (PD) source localisation in power transformers is acoustic emission measurements. This study describes a new method for detection and location of two simultaneous partial discharge sources in three-phase power transformer. In this method, acoustic signals are detected by sensors first and are then denoised using a wavelet transform. Finally, the two PD sources are localised using the modified binary partial swarm optimisation (MBPSO) method. To prove the efficiency of the two simultaneous PD localisations, the proposed algorithm is used to localise PD sources of the arc furnace transformer at Isfahan's Mobarakeh steel company. For this purpose, the PD localisation problem converts to an optimisation problem. To prove the efficiency of the MBPSO algorithm, its performance is compared with a genetic algorithm. The PD localisation results confirm the efficiency of the proposed method for the detection and location of PD sources. © The Institution of Engineering and Technology 2013.
Microgrid concept provides an appropriate context for installing distributed generation resources and providing reliability and power quality for sensitive loads. Most of the literature have analyzed the effects of different power control strategies of inverter-based distributed energy resources on the stability of microgrids and only a few of them have addressed various load models in their formulation and analysis. This paper proposes a well-structured formulation for state-space representation of comprehensive static and dynamic load models in an islanded microgrids environment. Impact of considering induction motor models on root loci of eigenvalues is analyzed and sensitivity calculation is performed to account for the effect of different load model parameters on system oscillatory modes. © 2013 IEEE.
Microgrid concept provides an appropriate context for installing distributed generation resources and providing reliability and power quality for sensitive loads. However, presence of intermittent energy resources like wind turbines and solar cells may affect the microgrid performance due to the close production and consumption levels. In this paper, model of a wind turbine equipped with a doubly fed induction generator system is presented which is capable of operating in islanded mode by decentralized power control method based on active power-frequency and reactive power-voltage droop characteristics. Using this precise modeling approach, small signal stability of the entire system is assessed and then improved based on eigenvalue analysis. Particle Swarm Optimization algorithm is used to enhance the stability margin as well as damping ratio of critical modes. Through simulation in a sample microgrid environment, accuracy of the proposed control method and the optimization process is verified. © 2013 IEEE.
Renewable and Sustainable Energy Reviews (13640321) 23pp. 312-319
In recent years, a large number of research works have been carried out in transmission expansion planning (TEP) field. TEP problem has been investigated with different views, methods, constraints, and objectives. Thus, it is required to evaluate and to overview the proposed works. This paper will review TEP problem from different aspects such as modeling, solving methods, reliability, distributed generation, electricity market, uncertainties, line congestion and reactive power planning. The review results provide a comprehensive background to find out the further works in this field. © 2013 Elsevier Ltd. All rights reserved.
Modelling of the three phase electric arc furnace and its voltage flicker mitigation is the purpose of this paper. The arc furnace model is implemented referring to an actual electric plant installed in Mobarakeh, Isfahan, Iran. For modelling of the electric arc furnace, at first, the arc is modeled using current-voltage characteristics of a real arc, i.e., the arc current samples as inputs and their corresponding voltages as outputs in the equivalent circuit of the furnace and its supply system. Then, the arc random characteristic has been taken into account by modulating the ac voltage by a band limited white noise. Electric arc furnace compensation with static VAr compensator, Thyristor controlled reactor combined with a fixed capacitor bank (TCR/FC), is discussed for closed loop control of the compensator. Instantaneous flicker sensation curves, before and after accomplishing compensation, are measured based on IEC standard. In closed loop control, two different approaches are considered; the former is based on voltage regulation at the point of common coupling (PCC) and the later is based on enhancement of power factor at PCC. A new method for controlling TCR/FC compensator is proposed. This method is based on applying a predictive method with closed loop control of the TCR/FC. In this method, by using the previous samples of the load reactive power, the future values of the load reactive power are predicted in order to consider the time delay in compensator control.
Transactions of the Institute of Measurement and Control (14770369) 34(4)pp. 388-400
One of the main problems in small hydro-power plants that are locally used is their frequency control system. In this paper, a suggested control system based on the fuzzy sliding mode controller is presented for controlling the network frequency. Also, the proposed control strategy is compared with a PI controller and conventional sliding mode controller. In order to regulate the membership functions of fuzzy system more accurately, the particle swarm optimization algorithm is also applied. Moreover, because of unavailability of the control system variables, an estimator is suggested for estimating and identifying the system variables. This estimator will reduce the costs of implementing the control method. The simulation results show the ability of controller system in controlling the local network frequency in the presence of load and parameter's variations. © 2011, SAGE Publications. All rights reserved.
European Transactions on Electrical Power (15463109) 22(6)pp. 812-830
The load frequency control (LFC) is very important in power system operation and control for supplying sufficient, reliable, and high-quality electric power. The conventional LFC uses an integral controller. In this paper, a new control system based on the fuzzy sliding mode controller is proposed for controlling the load frequency of nonlinear model of a hydropower plant, and this control system is compared with the proportional-integral controller and the conventional sliding mode controller. To regulate the membership functions of fuzzy system more accurately, the particle swarm optimization algorithm is also applied. Moreover, because of the unavailability of the control system variables, a nonlinear estimator is suggested for estimating and identifying the system state variables. This estimator provides the physical realization of the method and will reduce the costs of implementation. The proposed control method is performed for the LFC of hydropower plant of Karoon-3 in Shahrekord, Iran. The simulation results show the capability of the controller system in controlling local network frequency. Copyright © 2011 John Wiley & Sons, Ltd. Copyright © 2011 John Wiley & Sons, Ltd.
Electric Power Systems Research (03787796) 89pp. 1-10
The application of phasor measurement units (PMUs) in power systems is increasing because of their advantages such as the capability for online state estimation and improvements in the speed of control, and protection systems. In this paper, we propose a new method using binary integer linear programming for the optimal placement of PMUs to guarantee full observability of a power system as well as maximizing the measurement redundancy. Moreover, the problem of the optimal placement of these units in the case of a single PMU loss or single line outage is investigated. A practical limitation is also considered on the maximum number of PMU channels, in the proposed formulation. In all of the investigations, the effect of zero-injection buses in the power system was considered. The efficiency of the proposed method was demonstrated in different conditions. The method was applied to several IEEE standard test systems, i.e., the 14-, 30-, 39-, 57-, and 118-bus systems, and in two very large-scale systems, i.e., 2383- and 2746-bus systems. The simulation results verified the acceptable performance of the proposed method. © 2012 Elsevier B.V. All rights reserved.
This paper presents a novel optimization approach using hybrid algorithm, named BF-NM, to determine the optimal values for the proportional-integral (PI) controller parameters in automatic generation control (AGC) of a single-machine-infinite-bus system. A local search algorithm called Nelder-Mead is combined with BF technique to improve optimization procedure for fully exploiting the promising solution region. In the design procedure the nonlinear constraints such as Generation Rate Constraint (GRC) will be also taken into account. Comparative results of the proposed control strategy and other intelligent methods, CRAZYPSO and BF, reveal the effectiveness of this new technique in terms of reducing settling time, overshoot and oscillations. © 2012 IEEE.
Applied Mechanics and Materials (discontinued) (16627482) 229pp. 1095-1099
This paper develops a power system stabilizer (PSS) design for a wind turbine equipped with doubly fed induction generator (DFIG) which is based on vector control to improve the performance and dynamic stability of DFIG under fault conditions. The proposed PSS design is combined with genetic algorithm to obtain the higher-fitness answer as a strong optimization technique to the design of PSS parameters. A study network containing a wind farm equipped with DFIG was employed and all simulations will be carried out using MATLAB. It is shown that the employment of a proposed PSS can substantially enhance the contribution of a DFIG-based wind farm to network damping and dynamic stability. © (2012) Trans Tech Publications, Switzerland.
Journal of Electrical Engineering (1339309X) 63(4)pp. 233-241
In this paper, a new method for robust PSS design based on the power system pole placement is presented. In this stabilizer, a feedback gain matrix is used as a controller. The controller design is proposed by formulating the problem of robust stability in a Linear Matrix Inequality (LMI) form. Then, the feedback gain matrix is designed based on the desired region of the closed loop system poles. This stabilizer shifts the poles of the power system in different operational points into the desired regions in s-plane, such that the response of the power system will have proper damping ratio in all the operational points. The uncertainties of the power system parameters are also considered in this robust technique. Finally, in order to show the advantages of the proposed method in comparison with conventional PSS, some simulation results are provided for a power system case study in different operational points. © 2012.
IEEE Electrical Insulation Magazine (08837554) 28(5)pp. 32-42
Electrical, mechanical, and thermal stresses can degrade the quality of the insulation in power transformers, causing faults [1]. Several methods are used for fault diagnosis in transformers, e.g., dissolved gas analysis (DGA), measurement of breakdown voltage, and tan δ, pollution, sludge, and interfacial tension tests [2]. Of these, DGA is the most frequently used. Thermal and electrical stresses result in fracture of the insulating materials and the release of several gases. Analysis of these gases may provide information on the type of fault. Various standards have been suggested for the identification of transformer faults based on the ratio of dissolved gases in the transformer oil, e.g., International Electrotechnical Commission (IEC) standards [3]-[7], and these standards has been quoted in many papers, e.g., [8]-[15]. However, they are incomplete in the sense that, in some cases, the fault cannot be diagnosed or located accurately. Intelligent algorithms, e.g., wavelet networks [16], neuro-fuzzy networks [17], [18], fuzzy logic [8], [12], and artificial neural networks (ANN) [2], [9], [10], [19], [20] have been used to improve the reliability of the diagnosis. In these algorithms, the type of fault is diagnosed first, and the fault is then located using the ratio of the concentrations of CO 2 and CO dissolved in the transformer oil [21], [22]. The algorithms are not entirely satisfactory. The wavelet network has high efficiency but low convergence, the fuzzy logic method has a limited number of inputs and, in some cases, it is very difficult to derive the logic rules, and the ANN need reliable training patterns to improve their fault diagnosis performance. In this paper, we present a new method for simultaneous diagnosis of fault type and fault location. It uses an adaptive neuro- fuzzy inference system (ANFIS) [23]-[27], based on DGA. The ANFIS is first "trained" in accordance with IEC 599 [3], so that it acquires some fault determination ability. The CO 2/CO ratios are then considered additional input data, enabling simultaneous diagnosis of the type and location of the fault. The results obtained by applying it to six transformers are presented and compared with the corresponding results obtained using ANN and some other standards and methods. © 2006 IEEE.
This paper presents a novel hybrid algorithm, named bacterial foraging Nelder-Mead (BF-NM), to determine the optimal values for the proportional-integral (PI) controller parameters in load frequency control (LFC) of a two-area thermal power system including governor dead-band and generation rate constraint (GRC) nonlinearities. In order to have the best optimization procedure, a local search algorithm called Nelder-Mead is used along with BF technique. In this study, the performance of the proposed BF-NM algorithm is compared with the performance of other intelligent algorithms such as CRAZYPSO and BF. The comparative results reveal the effectiveness of the proposed control strategy over other existing techniques. © 2012 IEEE.
Energy Conversion and Management (01968904) 55pp. 26-35
Transmission Expansion Planning (TEP) is an important issue in power system studies. It involves decisions on location and number of new transmission lines. Before deregulation of the power system, the goal of TEP problem was investment cost minimization. But in the restructured power system, nodal prices, congestion management, congestion surplus and so on, have been considered too. In this paper, an AC model of TEP problem (AC-TEP) associated with Reactive Power Planning (RPP) is presented. The goals of the proposed planning problem are to minimize investment cost and maximize social benefit at the same time. In the proposed planning problem, in order to improve the reliability of the system the Expected Energy Not Supplied (EENS) index of the system is limited by a constraint. For this purpose, Monte Carlo simulation method is used to determine the EENS. Particle Swarm Optimization (PSO) method is used to solve the proposed planning problem which is a nonlinear mixed integer optimization problem. Simulation results on Garver and RTS systems verify the effectiveness of the proposed planning problem for reduction of the total investment cost, EENS index and also increasing social welfare of the system. © 2011 Elsevier Ltd. All rights reserved.
International Journal of Electrical Power and Energy Systems (01420615) 40(1)pp. 1-8
This paper presents a new methodology, named Sequential Quadratic Programming (SQP), to design a robust PID controller for Load Frequency Control (LFC) of nonlinear interconnected power systems. This method easily copes with the nonlinear constraints such as Generation Rate Constraint (GRC) and it can be directly used on a nonlinear model of a multi-machine power system. The proposed controller is simple, effective and can ensure that the overall system performance is desirable. The robust performance of the proposed controller is compared with that of a conventional PI controller, and also with two other different techniques named PID-MPRS and PID-PSO through the simulation of two multi-machine power system examples with a variety of disturbances. Results show that the proposed technique gives a better performance. © 2011 Elsevier Ltd. All rights reserved.
Iranian Journal of Science and Technology - Transactions of Electrical Engineering (23641827) 36(E1)pp. 67-82
A new adaptive dynamic under frequency load shedding scheme for a large industrial power system with large cogeneration units is presented. The adaptive LD- df/dt method with variable load shedding amount based on the disturbance magnitude is applied to have a minimum load shedding and a proper frequency recovery for different disturbances. To increase the speed of the load shedding scheme and to have an optimum response at different loading conditions, the artificial neural network (ANN) algorithm is developed. The Levenberg-Marquardt algorithm has been used for designed feed-forward neural network training. To prepare the training data set for the designed ANN, transient stability analysis has been performed to determine the minimum load shedding in the industrial power system at various operation scenarios. The ANN inputs are selected to be total in-house power generation, total load demand and initial frequency decay, while the minimum amount of load shedding at each step is selected for the output neurons. The proposed method is applied to the Mobarakeh steelmaking company (M.S.C) at different loading conditions. The performance of the presented ANN load shedding algorithm is demonstrated by the LD- df/dt method. Numerical results show the effectiveness of the proposed method. © Shiraz University.
Applied Energy (18729118) 89(1)pp. 443-453
In this paper, a new approach is proposed to solve the economic load dispatch (ELD) problem. Power generation, spinning reserve and emission costs are simultaneously considered in the objective function of the proposed ELD problem. In this condition, if the valve-point effects of thermal units are considered in the proposed emission, reserve and economic load dispatch (ERELD) problem, a non-smooth and non-convex cost function will be obtained. Frequency deviation, minimum frequency limits and other practical constraints are also considered in this problem. For this purpose, ramp rate limit, transmission line losses, maximum emission limit for specific power plants or total power system, prohibited operating zones and frequency constraints are considered in the optimization problem. A hybrid method that combines the bacterial foraging (BF) algorithm with the Nelder-Mead (NM) method (called BF-NM algorithm) is used to solve the problem. In this study, the performance of the proposed BF-NM algorithm is compared with the performance of other classic (non-linear programming) and intelligent algorithms such as particle swarm optimization (PSO) as well as genetic algorithm (GA), differential evolution (DE) and BF algorithms. The simulation results show the advantages of the proposed method for reducing the total cost of the system. © 2011.
IEEE Transactions on Power Systems (08858950) 27(1)pp. 47-57
Due to increasing neutral current and power losses resulting from phase unbalancing in distribution networks, the act of phase balancing has been a matter of interest in recent years. In this paper, a new method for phase arrangement of laterals and the distribution transformers is presented based on bacterial foraging (BF) oriented by particle swarm optimization (PSO) algorithm (BF-PSO). The algorithm is proposed for radial and meshed distribution networks in the presence of unbalanced loads. The objective function of this problem includes the neutral current of the supporting feeder, the rephasing cost, the voltage drop, and the line losses. Since these objectives do not have similar units and the same variation ranges, the four objectives are fuzzified and then integrated as the fuzzy multi-objective function. In order to prove the efficiency of the BF-PSO algorithm, its performance is compared with bacterial foraging, genetic and immune algorithms. To evaluate the proposed method, it is applied to feeder No. 3062 in Ahwaz, Iran. The simulation results confirm the efficiency of the method for the reduction of system costs and network phase balancing. © 2006 IEEE.
Journal of Power Electronics (15982092) 12(1)pp. 145-156
These days, the application of electronic power transformers (EPTs) is expanding in place of ordinary power transformers. These transformers can transmit power via three or four wire converters. Their dynamic performance is extremely important, due to their complex structure. In this paper, a new method is proposed for improving the dynamic performance of distribution electronic power transformers (DEPT) by using sliding mode control (SMC). Hence, to express the dynamic characteristics of a system, different factors such as the voltage unbalance, voltage sag, voltage harmonics and voltage flicker in the system primary side are considered. The four controlling aims of the improvement in dynamic performance include: 1) maintaining the input currents so that they are in sinusoidal form and in phase with the input voltages so they have a unity power factor, 2) keeping the dc-link voltage within the reference amount, 3) keeping the output voltages at a fixed amount and 4) keeping the output voltages in sinusoidal and symmetrical forms. Simulation results indicate the potential and capability of the proposed method in improving DEPT behavior.
Simulation (17413133) 88(2)pp. 181-196
This paper presents a new optimal adaptive dynamic load-shedding scheme for a large steelmaking industry with cogeneration units. The proposed method is based on the initial rate of a frequency change (df0/dt) and is coordinated with tie-lines frequency protection relays. An adaptive network-based fuzzy inference system (ANFIS) with a new training algorithm is developed in order to increase the speed of the load-shedding scheme and to have an optimum response at different loading conditions. To overcome the ANFIS training difficulties, a new hybrid approach composed of particle swarm optimization and gradient decent algorithms is used. The training data set for the ANFIS is prepared by a transient stability analysis to determine the minimum load shedding for various operation scenarios without causing the tripping problem of cogeneration units. By using an accurate dynamic modeling of the Mobarakeh steelmaking company in Esfahan Regional Electrical Company network, the performance of the proposed method is compared with the traditional ANFIS learning algorithms, adaptive artificial neural network load-shedding scheme and transient stability analysis. Simulation results show the effectiveness of the proposed method. © 2011, Simulation Councils Inc. All rights reserved.
Goroohi sardou i., ,
Banejad m., ,
Hoshmand, R. ,
Dastfan a., IET Generation, Transmission and Distribution (17518687) 6(6)pp. 493-502
One of the main issues in distribution sector is to achieve simultaneously high system reliability and low capital costs. Distribution automation systems (DASs) involve automatic and remote-controlled switches. The switches play a significant role in system reliability improvement. This paper proposes the modified shuffled frog leaping algorithm (SFLA) to derive the optimal placement of manual and automatic switches in DASs. A fuzzy approach is used to handle the multi objective considerations, and a fuzzy membership function is defined for each term in the objective function. The first objective is reliability improvement by minimising the customer interruption cost (CIC), and the second objective is to minimise switches purchasing and maintenance cost (SPMC). In this paper, a new method is developed to evaluate CIC and SPMC indices in a distribution network. In the proposed method, customer types, customers load patterns, monthly, daily and hourly customers loading rates are considered. In addition, network branches' failure rate, restoration time and repair time are taken into account. The performance of the proposed approach is assessed and illustrated by studying on the IEEE 123-node feeder standard test system. The simulation results verify the capability of the proposed method. © 2012 The Institution of Engineering and Technology.
International Journal of Electrical Power and Energy Systems (01420615) 42(1)pp. 220-228
The frequency and voltage stability is a basic principle in the power system operation. Different short circuits, load growth, generation shortage, and other faults which disturb the voltage and frequency stability are serious threats to the system security. The frequency and voltage instability causes dispersal of a power system into sub-systems, and leads to blackout as well as heavy damages of the system equipments. Optimum load shedding during contingency situations is one of the most important issues in power system security analysis. This paper presents a fast and optimal adaptive load shedding method, for isolated power system using Artificial Neural Networks (ANNs). By creating an appropriate data-base of contingencies for training the neural network, the proposed method is able to perform correct load shedding in various loading scenario. In this regard, the total power generation, the total loads in power system, the existing spinning reserved capacity value in the network and frequency reduction rate were selected as the ANN inputs. This method has been tested on the New-England power system. The simulation results show that the proposed algorithm is very fast, robust and optimal values of load shedding in different loading scenarios, related to conventional method. © 2012 Published by Elsevier Ltd. All rights reserved.
Turkish Journal Of Electrical Engineering And Computer Sciences (13000632) 20(5)pp. 751-768
In a daily power market, price and load forecasting are the most important signals for the market participants. In this paper, an accurate feed-forward neural network model with a genetic optimization Levenberg-Marquardt back propagation training algorithm is employed for short-term nodal congestion price forecasting in different zones of a large-scale power market. The use of genetic algorithms for neural network training optimization has a remarkable effect on the accuracy of price forecasting in a large-scale power market. The necessary data for neural network training are obtained by solving optimal power flow equations that take into account all effective constraints at any hour of the day in a single month. The structure of the neural network has 2 input signals of active and reactive powers for every load busbar in every hour of the programming model. These 2 signals are always available. In this study, an IEEE 118-bus power system is used to test the proposed method authenticity. This system is divided into 3 zones, and a neural network with genetic algorithm training optimization is employed for every zone. Performance of the proposed method is compared with ARIMA and GARCH time series for the same data. The simulation results show that the proposed algorithm is robust, efficient, and accurate. Therefore, the algorithm produces better results than the ARIMA and GARCH time series for short-term nodal congestion price forecasting. © TÜBİTAK.
International Journal of Electrical Power and Energy Systems (01420615) 41(1)pp. 76-86
Rephasing strategy is one of the main methods used for phase balancing and neutral current reduction in electrical distribution networks and the reconfiguration technique is an effective method for network loss reduction. In this paper, a new method for the simultaneous implementation of reconfiguration and phase balancing strategies is presented as a combinational strategy. In order to solve the proposed optimization problem, Nelder Mead algorithm combined with a bacterial foraging algorithm (BF-NM) is used based on a fuzzy multi-objective function. The proposed method allows for the simultaneous execution of reconfiguration and phase balancing while minimizing the interruption cost of rephasing in addition to eliminating network unbalancing and reducing neutral current and network losses. To demonstrate the efficiency of the BF-NM algorithm, its performance is compared with bacterial foraging (BF), particle swarm optimization (PSO), genetic and immune algorithms (GA and IA). The proposed method is applied to the IEEE 123-bus test network for evaluation. The simulation results confirm the efficiency of the method in reducing the system costs and network phase balancing. © 2012 Elsevier Ltd. All rights reserved.
International Journal of Robotics and Automation (19257090) 27(2)pp. 163-176
One of the important problems in the design of an underwater robot is its intelligent navigation system. This system autonomously performs the task of the robot guidance and control. The intelligent control system of the fish robot guidance comprises different control sections such as control of motion trajectory angle, yaw angle, orientation control, speed control, depth control, intelligent control of error, etc. In this paper, the control of the yaw angle of a laboratory 4-link fish-like robot guiding it in the horizontal direction is studied. This is in fact part of the navigation control system which guides the robot at a given depth. In this regard, a desired dynamic model describing the under study laboratory 4-link fish-like robot motion with three joints is derived. The model validation is examined by comparing its response and the system response to an experimentally imposed torque. Then, a fuzzy controller is proposed to achieve suitable performance of the step response such as desired steady state error, reduction of the maximum overshoot, and decreasing of the settling time. The desired erformances are achieved by applying the complete rule base, data base and suitable membership functions in the fuzzy controller. The simulation results based on the practical considerations and the conventional experimental inputs show the motion trajectory improvement using the proposed control system.
IEEE Transactions on Power Delivery (19374208) 26(2)pp. 882-890
The dynamic voltage restorer (DVR) is one of the modern devices used in distribution systems to protect consumers against sudden changes in voltage amplitude. In this paper, emergency control in distribution systems is discussed by using the proposed multifunctional DVR control strategy. Also, the multiloop controller using the Posicast and P+Resonant controllers is proposed in order to improve the transient response and eliminate the steady-state error in DVR response, respectively. The proposed algorithm is applied to some disturbances in load voltage caused by induction motors starting, and a three-phase short circuit fault. Also, the capability of the proposed DVR has been tested to limit the downstream fault current. The current limitation will restore the point of common coupling (PCC) (the bus to which all feeders under study are connected) voltage and protect the DVR itself. The innovation here is that the DVR acts as a virtual impedance with the main aim of protecting the PCC voltage during downstream fault without any problem in real power injection into the DVR. Simulation results show the capability of the DVR to control the emergency conditions of the distribution systems. © 2011 IEEE.
ISA Transactions (00190578) 50(2)pp. 150-158
The voltage & current harmonics produced by nonlinear loads in power systems cause a reduction in power quality. In order to improve the power quality, active power filters (APFs) can be used. In this paper, a new control system for designing active filters despite nonlinear loads of electric arc furnaces (EAFs) is presented. The system is composed of three main parts: computation of reference currents, regulation of DC capacitor voltage, and production of firing pulses. In the first part, the active filter control system is presented based on the combination of the synchronous detection method and instantaneous power theory. In the second part, the DC capacitor voltage regulator is applied, producing a reference current and a proper voltage regulator is developed. For the third part of the control system, we use a PI controller to provide some conditions that follow the reference current in a complete cycle, and generate firing pulses by the hysteresis method. The proposed control system not only reduces the voltage and current harmonics in power systems but can also improve the power quality indices. The above design was implemented in the EAF system of the Mobarakeh steel complex (Isfahan, Iran). The simulation results show the effectiveness of the APFs in improving the power quality indices. © 2011 ISA. Published by Elsevier Ltd. All rights reserved.
Applied Soft Computing (15684946) 11(5)pp. 4021-4028
All utility companies strive to achieve the well-balanced distribution systems in order to improve system voltage regulation by means of equal load balancing of feeders and reducing power loss. Optimal reconfiguration is one of the best solutions to reach this goal. This paper presents a new combined method for optimal reconfiguration using a multi-objective function with fuzzy variables. This method considers both objectives of load balancing and loss reduction in the feeders. Since reconfiguration is a nonlinear optimization problem, the ant colony algorithm is employed for the optimized response in search space. This method has been applied on two IEEE 33-bus and 69-bus distribution systems. Simulation results confirm the effectiveness of the proposed method in comparison with other techniques for optimal reconfiguration. © 2011 Elsevier B.V.
ISA Transactions (00190578) 50(2)pp. 142-149
Thyristor controlled reactor with fixed capacitor (TCR/FC) compensators have the capability of compensating reactive power and improving power quality phenomena. Delay in the response of such compensators degrades their performance. In this paper, a new method based on adaptive filters (AF) is proposed in order to eliminate delay and increase the response of the TCR compensator. The algorithm designed for the adaptive filters is performed based on the least mean square (LMS) algorithm. In this design, instead of fixed capacitors, band-pass LC filters are used. To evaluate the filter, a TCR/FC compensator was used for nonlinear and time varying loads of electric arc furnaces (EAFs). These loads caused occurrence of power quality phenomena in the supplying system, such as voltage fluctuation and flicker, odd and even harmonics and unbalancing in voltage and current. The above design was implemented in a realistic system model of a steel complex. The simulation results show that applying the proposed control in the TCR/FC compensator efficiently eliminated delay in the response and improved the performance of the compensator in the power system. © 2011 ISA. Published by Elsevier Ltd. All rights reserved.
Applied Soft Computing (15684946) 11(4)pp. 3634-3642
This paper presents a new method to optimize locating and the size of fixed and switching capacitor banks based on bacterial foraging (BF) oriented by particle swarm optimization (PSO) algorithm (BF-PSO). The algorithm is proposed for radial and meshed networks in the presence of unbalanced and nonlinear loads. The objective function considers the minimization of the total energy loss costs and capacitor installation cost, network total harmonic distortion (THD) index, and the deviation of the voltage fundamental component from the permitted value. Since these parameters do not have similar units and variation ranges, a membership degree is assigned to each parameter by using fuzzy sets. The IEEE 123-Bus distribution network is used to test the proposed method. The simulation results of the proposed algorithm are compared with PSO, BF and genetic algorithms to show the efficiency of this method to reduce the system costs. © 2011 Elsevier B.V.
Electrical Engineering (14320487) 93(1)pp. 43-53
The shunt capacitor devices are utilized in distribution systems to possibly reduce reactive component of power losses. Besides, the dispersed generator (DG) units can be used to supply active power of loads and reduce active component of power losses. In this paper, by applying the multi-objective problem, optimal placements of these devices are determined based on bacterial foraging (BF) oriented by particle swarm optimization (PSO) algorithm (BF-PSO). The considered objective function includes the cost reduction of power losses and installation costs of shunt capacitor devices and DG units. Also, the problem solution at different load levels and the utilization of capacitor discrete values are performed for optimization. Finally, the proposed method is compared with genetic algorithm (GA), differential evolution (DE), and PSO methods. They are investigated on the IEEE 69-bus distribution system. The simulation results indicate the advantages of the proposed method for the optimization problem. © 2010 Springer-Verlag.
Engineering Intelligent Systems (discontinued) (27539806) 19(3)pp. 123-131
Electric Arc Furnaces (EAFs) are unbalanced, nonlinear and time varying loads, which can cause many problems in the power system quality. As the use of arc furnace loads increases in industry, the importance of the power quality problems increase too. So in order to optimize the usages of electric power in EAFs, it is necessary to minimize the effects of arc furnace loads on quality in power systems as much as possible. So it is essential to present an accurate and real model for the analysis of these loads operations. Therefore, in this paper, a new model based on statistical sampling for the EAF is presented. This model has included random states of the arc extensively, and adjusts desirably with real operation of the EAF in the steel industries. On the other hand, in order to take an accurate modeling, the voltage flicker has been considered sinusoidal and randomly. Also to get an exact approach in evaluation and analysis of power system along with the EAF, the whole parameters of furnace load and the system are considered. In this regard, it can be claimed that in system analysis, by applying the proposed model, the error resulted from modeling process has largely reduced comparing with other models. Finally, the simulation is performed using PSCAD/EMTDC software. The results of the simulation show the validity of the proposed method in the entire power system. © 2011 CRL Publishing Ltd.
European Transactions on Electrical Power (15463109) 21(1)pp. 824-838
Electric arc furnaces (EAFs) produce voltage fluctuations and flicker because of the reactive power severe variations. Furthermore, these loads absorb a large amount of reactive power. The static VAr compensators (SVCs) have been widely used by the industrial customers with arc furnaces to compensate the reactive power due to the quick response of the power electronic devices. In this paper, reactive power compensation in the steel industrial plant with several EAFs by utilizing open-loop controlled thyristor controlled reactor/fixed capacitor (TCR/FC) compensator is performed. The TCR/FC compensator is usually applied in conventional steel making plants; one is in Mobarakeh/ Isfahan, Iran which is considered as the case study in this paper. Simulation results show that, although open-loop controlled TCR/FC is effective for compensating reactive power, it cannot efficiently compensate the fluctuations of the reactive power and reduce the flicker intensity. © 2010 John Wiley & Sons, Ltd.
Substation has a critical role in power network because it is a subsidiary station of an electricity generation, transmission and distribution system where voltage is transformed from high to low or the reverse with power transformers. All devices in substation are controlled, protected and monitored by substation automation system (SAS) that collects information from the power equipment (process) and performs actions on it. Communication network is a fundamental element in all automation system and network performances can have a critical impact on the control process. In the past decade, new communication standard have been designed and retrofitted into substations. IEC61850 is a new international standard for substation automation. In this paper, the authors describe some important feature of IEC 61850 as an international communication standard in substation automation system, that separate this standard from other communication standard in substation. © 2011 IEEE.
This paper presents a new robust technique for tuning the parameters of a state feedback controller for load frequency control (LFC) of interconnected power systems using sequential quadratic programming (SQP) method. In this method the frequency deviation of the system is directly utilized to tune the controller parameters. The simulation studies are carried out for two-area interconnected power system. The Comparative results of the proposed method and a conventional PI controller show its robustness with a satisfactory response when the parameters of the system change. ©2010 IEEE.
International Journal of Electrical Power and Energy Systems (01420615) 32(5)pp. 375-382
This paper presents a new robust PID controller for automatic generation control (AGC) of hydro turbine power systems. The method is mainly based on a maximum peak resonance specification that is graphically supported by the Nichols chart. The open-loop frequency response curve is tangent to a specified ellipse and this makes the method to be efficient for controlling the overshoot, the stability and the dynamics of the system. Comparative results of this new load frequency controller with a conventional PI one and also with another PID controller design tested on a multimachine power system show the improvement in system damping remarkably. The region of acceptable performance of the new PID controller covers a wide range of operating and system conditions. © 2009 Elsevier Ltd. All rights reserved.
Turkish Journal Of Electrical Engineering And Computer Sciences (13000632) 18(4)pp. 597-612
Reactive power planning (RPP) involves optimal allocation and determination of the type and size of new reactive power (VAR) supplies to satisfy voltage constraints during normal and contingency states. The RPP issue is in fact an optimization of large scale mixed integer nonlinear programming problem, so it is proper to use an evolutionary algorithm to solve the problem. In this paper, in order to solve the RPP problem for corrective action of power systems, the bacterial foraging (BF) oriented by particle swarm optimization (PSO) algorithm (BF-PSO) is proposed. In the algorithm, the VAR control has been carried out by using flexible AC transmission systems (FACTS) devices, in order to minimize the installation costs of these devices. In order to determine the saving rate in the costs, corrective control is also performed by the utilization of load shedding algorithm. The IEEE 57-Bus system is used to test the proposed method. The simulation results of the proposed algorithm are compared with PSO and genetic algorithms (GA) to show the efficiency of this method in the RPP problem. © TÜBITAK.
Electric Power Systems Research (03787796) 80(12)pp. 1552-1561
In this paper, a new approach for the detection and classification of single and combined power quality (PQ) disturbances is proposed using fuzzy logic and a particle swarm optimization (PSO) algorithm. In the proposed method, suitable features of the waveform of the PQ disturbance are first extracted. These features are extracted from parameters derived from the Fourier and wavelet transforms of the signal. Then, the proposed fuzzy system classifies the type of PQ disturbances based on these features. The PSO algorithm is used to accurately determine the membership function parameters for the fuzzy systems. To test the proposed approach, the waveforms of the PQ disturbances were assumed to be in the sampled form. The impulse, interruption, swell, sag, notch, transient, harmonic, and flicker are considered as single disturbances for the voltage signal. In addition, eight possible combinations of single disturbances are considered as the PQ combined types. The capability of the proposed approach to identify these PQ disturbances is also investigated, when white Gaussian noise, with various signal to noise ratio (SNR) values, is added to the waveforms. The simulation results show that the average rate of correct identification is about 96% for different single and combined PQ disturbances under noisy conditions. © 2010 Elsevier B.V. All rights reserved.
Journal of Electrical Engineering and Technology (19750102) 5(1)pp. 116-128
Modeling of the three phase electric arc furnace and its voltage flicker mitigation are the purposes of this paper. For modeling of the electric arc furnace, at first, the arc is modeled by using current-voltage characteristic of a real arc. Then, the arc random characteristic has been taken into account by modulating the ac voltage via a band limited white noise. The electric arc furnace compensation with static VAr compensator, Thyristor Controlled Reactor combined with a Fixed Capacitor bank (TCR/FC), is discussed for closed loop control of the compensator. Instantaneous flicker sensation curves, before and after accomplishing compensation, are measured based on IEC standard. A new method for controlling TCR/FC compensator is proposed. This method is based on applying a predictive approach with closed loop control of the TCR/FC. In this method, by using the previous samples of the load reactive power, the future values of the load reactive power are predicted in order to consider the time delay in the compensator control. Also, in closed loop control, two different approaches are considered. The former is based on voltage regulation at the point of common coupling (PCC) and the later is based on enhancement of power factor at PCC. Finally, in order to show the effectiveness of the proposed methodology, the simulation results are provided.
COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering (03321649) 29(3)pp. 667-685
Purpose - The purpose of this paper is to present a 3D finite element model of the electromagnetic fields in an AC three-phase electric arc furnace (EAF). The model includes the electrodes, arcs, and molten bath. Design/methodology/ approach - The electromagnetic field in terms of time in AC arc is also modeled, utilizing a 3D finite element method (3D FEM). The arc is supposed to be an electro-thermal unit with electrical power as input and thermal power as output. The average Joule power, calculated during the transient electromagnetic analysis of the AC arc furnace, can be used as a thermal source for the thermal analysis of the inner part of furnace. Then, by attention to different mechanisms of heat transfer in the furnace (convection and radiation from arc to bath, radiation from arc to the inner part of furnace and radiation from the bath to the sidewall and roof panel of the furnace), the temperature distribution in different parts of the furnace is calculated. The thermal model consists of the roof and sidewall panels, electrodes, bath, refractory, and arc. The thermal problem is solved in the steady state for the furnace without slag and with different depths of slag. Findings - Current density, voltage and magnetic field intensity in the arcs, molten bath and electrodes are predicted as a result of applying the three-phaseACvoltages to theEAF. The temperature distribution in different parts of the furnace is also evaluated as a result of the electromagnetic field analysis. Research limitations/implications - This paper considers an ideal condition for the AC arc. Non-linearity of the arc during the melting, which leads to power quality disturbances, is not considered. In most prior researches on the electrical arc furnace, a non-linear circuit model is usually used for calculation of power quality phenomena distributions. In this paper, the FEM is used instead of non-linear circuits, and calculated voltage and current densities in the linear arc model. The FEM results directly depend on the physical properties considered for the arc. Originality/value - Steady-state arc shapes, based on the Bowman model, are used to calculate and evaluate the geometry of the arc in a real and practical three-phase AC arc furnace. A new approach to modeling AC arcs is developed, assuming that the instantaneous geometry of the AC arc at any time is constant and is similar to the geometry of a DC arc with the root mean square value of the current waveform of the AC arc. A time-stepping 3D FEM is utilized to calculate the electromagnetic field in the AC arc as a function of time. © Emerald Group Publishing Limited.
IEEJ Transactions on Electrical and Electronic Engineering (19314973) 5(6)pp. 688-694
Nonlinear loads used in industrial systems cause harmonic pollution in power system voltages and currents. Therefore, it is necessary to estimate properly the propagation of voltage and current harmonic distortions at power system buses in order to eliminate the harmonics. On the other hand, power system harmonic analysis methods can be used to avoid direct measurement of the harmonics. In this paper, a neural network (NN) based algorithm for harmonic analysis of industrial systems (i.e., systems whose topology rarely changes during the year) is proposed. In the meantime, an asynchronous simulation of the system in time and frequency domains is used to avoid the complications of some hybrid methods. Due to the use of time domain simulation to obtain the harmonic currents injected by nonlinear devices, in addition to giving acceptable precision, the method is completely independent of the measurement system. Application of NN for modeling nonlinear loads along with the use of an appropriate fast harmonic analysis procedure in frequency domain has resulted in acceptable execution time in the presented algorithm. The results obtained by modeling and simulation of the Sn-coating unit of the Mobarakeh integrated steel making plant demonstrate the high accuracy and acceptable execution time of the proposed method. Copyright © 2010 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
Journal of Electrical Systems (11125209) 5(1)
The power system dynamic instability is occurred by loosing balance relation between electrical generation and a varying load demand that justifies the necessity of using Power System Stabilizer (PSS). Moreover, the PSS must have the capability of producing appropriate stabilizing signals with limited practical amplitude and it should be robust against a wide range of operating conditions and disturbances. For this purpose, a robust PSS design based on an auto-tuning fuzzy logic control under multi-operating conditions by using Real Coded Genetic Algorithm (RCGA) is proposed. This method includes two fuzzy controllers; internal fuzzy controller and supervisor fuzzy controller. The supervisor controller tunes the internal one by on-line applying of nonlinear scaling factors to inputs and outputs using extra signals. The RCGA-based method is used for off-line training of this supervisor controller by considering that the operating conditions for training be different from those are used for test simulations. Then, the proposed PSS is tested in three operational conditions; nominal load, heavy load, and in the case of fault occurrence in transmission line. The simulation results are provided to compare the proposed PSS with conventional fuzzy PSS and conventional PSS. It is shown that the performance and robustness of proposed PSS in different operating conditions is more acceptable. Copyright © 2009 JES.
Electrical Engineering (14320487) 91(4-5)pp. 187-195
In this paper, a new adaptive unified power flow controller (UPFC) based on the Lyapunov method and neural network structure is presented. The corresponding energy function is derived for the single machine infinitive bus system with classic generator model representation. Damping control strategy to improve transient behavior of the system is determined by considering the dynamic modeling of the UPFC. The Lyapunov-based controller is extended to interconnected power system by considering the two-machine equivalent model and the center of inertia concept. The recurrent neural network (RNN) with back propagation algorithm is also used to overcome the uncertainty issues and also to consider the more detailed power system. The designed Lyapunov-RNN-based controller is applied to the interconnected power system between the Esfahan-Yazd region transmission network in Iran power system. The performance of the proposed controller is compared with other different controllers by applying some disturbances in the system. Finally, simulation results are presented and the effectiveness of the proposed method for power system stability enhancement is discussed as well. © 2009 Springer-Verlag.
American Journal of Applied Sciences (discontinued) (15469239) 6(8)pp. 1539-1547
Problem statement: The Electric Arc Furnace (EAF) is a non-linear load and creates power quality related problem. Therefore, accurate modeling of the EAF is essential. Approach: In this study, an optimal model for EAF in time domain called exponential-hyperbolic, was proposed to describe the behavior of the EAF for all of the operating conditions and it does not need the initial conditions as they needed for the existing methods of modeling of the EAF. Then, the behavior of the proposed model of EAF on the power system was studied using the PSCAD software. In order to analyze the proposed method, several characteristics for different operating conditions were investigated. Results: In the simulation, the parameters were taken from the EAF of the Mobarakeh Steel Making Company (Isfahan-Iran). The results of the simulation accurately showed the behavior of the EAF of the company. Conclusion: The finding of this study showed that the proposed exponential-hyperbolic model was capable in modeling of EAF for different operating conditions. © 2009 Science Publications.
Canadian Conference on Electrical and Computer Engineering (08407789) pp. 926-930
Shunt capacitors are extensively used in power system for reactive power compensation. Due to the existence of harmonic sources such as arc furnaces, harmonic-producing loads the possibility of harmonic resonance significantly increases. Switching shunt high voltage capacitors may cause over- voltages and this may damage the equipment considerably. In this paper the voltage profile and power losses in the sub-transmission network under study before and after installation of two high voltage shunt capacitors are compared. The harmonic analysis is employed to determine harmonic indexes such as HD in the network buses and to compare the capacitor loading limits with IEEE standard. The effect of the capacitor size on the resonance frequency is determined by using scan frequency analysis. Results show that the resonance frequency may occur in the lower frequency range with respect to the size of shunt capacitors. By considering the exact electromagnetic transient modeling of the network equipment, over-voltages during back to back switching of capacitor banks are also compared with the equipment characteristic. ©2009 IEEE.
International Review of Electrical Engineering (25332244) 4(1)pp. 129-138
The torsional mode is one of the power system problems which may lead to dynamic instability in them. In this paper, a static synchronous series compensator (SSSC) along with a fixed capacitor is used in order to avoid torsional mode instability in a series compensated transmission system. For this purpose, a 6-step harmonic neutralized inverter is used for realization of the SSSC. Also, the IEEE first benchmark model on SSR analysis is considered as the case study. The system dynamic stability is studied through EMTDC/PSCAD simulation studies. The presence of the fixed capacitor ensures increased damping of small signal oscillations. At higher levels of fixed capacitor compensation, a damping controller is required to stabilize the torsional modes of SSR. It is shown that the combination of the SSSC and the fixed capacitor improves the damping oscillations. © 2009 Praise Worthy Prize S.r.l. - All rights reserved.
Leonardo Electronic Journal of Practices and Technologies (discontinued) (15831078) 8(15)pp. 31-50
Electric Arc Furnaces (EAFs) are unbalanced, nonlinear and time varying loads, which can cause many problems in the power system quality. As the use of arc furnace loads increases in industry, the importance of the power quality problems also increase. So in order to optimize the usages of electric power in EAFs, it is necessary to minimize the effects of arc furnace loads on power quality in power systems as much as possible. Therefore, in this paper, design and simulation of an electric plant supplying an arc furnace is considered. For this purpose, a three phase arc furnace model, which can simulate all the mentioned power quality indices, is developed based on Hyperbolic -Exponential model (V-I model). Then by considering the high changes of reactive power and voltage flicker of nonlinear furnace load, a thyristor controlled reactor compensation with fixed capacitor (TCR/FC) are designed and simulated. In this procedure, the reactive power is measured so that maximum speed and accuracy are achieved. Finally, simulation results verify the accuracy of the load modelling and show the effectiveness of the proposed TCR/FC model for reactive compensating of the EAF.
Canadian Conference on Electrical and Computer Engineering (08407789) pp. 579-582
Power System Stabilizers are used to generate supplementary control signals for the excitation system in order to damp the low-frequency power system oscillations. Although Static VAR Compensators (SVC) are basically used for voltage control of long distance bulk power transmission lines, they can be also utilized to improve the dynamic stability of the power system by using a supplementary control loop. However, uncoordinated design of SVC and PSS may cause destabilizing interaction. In order to enhance power system dynamic stability this paper presents a new method to design both PSS and SVC parameters coordinately using real code genetic algorithm. Simulation results of multi-machine system confirm the advantage of using this method. ©2009 IEEE.
UPB Scientific Bulletin, Series C: Electrical Engineering and Computer Science (22863540) 71(4)pp. 49-62
With the growth of need of electrical energy in the technological societies, the demand for receiving the high quality electrical energy is being increased. Among the different disturbances affecting the power quality, the voltage sag and temporary voltage are essential issues especially that need to be fully investigated in the automated systems. In this paper, firstly, the effects of voltage sag due to three phase short circuit, staring of induction motor and transformerenergizing are studied. Then, influence of voltage sag compensation by means of distribution synchronous compensator (D-Statcom) is investigated After that, a method, namely direct control is presented for this compensator. The method measures the active and reactive powers simultaneously to control directly the switching patterns in the D-Statcom. The proposed direct control system is capable to minimize the power interruption and voltage sag and it is independent of system parameters using direct control. The method is then simulated on an IEEE standard-test system using PSCAD/EMTC software. The results of the simulation shows the proposed method in control strategy is able to compensate voltage sag.
Journal of Electrical Engineering (1339309X) 59(4)pp. 195-202
The electric arc furnace (EAF) behaves like a non-linear load that draws the attention of many researchers. At first in this paper, the important time domain models of EAF are investigated. Then, an optimal time domain model for EAF is proposed to describe the performance of the EAF for different operating situations. In this paper, after deriving a model for EAF, its effects on the power system are studied by means of the PSCAD software. Several characteristics for different operating conditions are then investigated to analyze the proposed method. In addition, for a time-variant and non-linear load which generates voltage flicker and unbalanced voltage, the EAF are modelled. In order to study the effect of voltage flicker on the systems with EAF, random and sinusoidal voltage flickers are considered. Also, in this paper, the effects of the transformer of EAF and common inductance of the flexible cables are investigated. Finally, results of the simulation show the validity of the proposed model of EAF model in this paper. © 2008 FEI STU.
In this paper, at first, an optimized resonant capacitor is designed for a practical induction furnace with parallel resonant inverter, by using Lagrange's method. Then, rectifier and inverter snubber circuits are designed. To access a control system, a passive linear controller is also designed. Meanwhile the whole system is started and load is changing, the controller, by changing firing angle of the rectifier, provides proper DC current for inverter such that output power of inverter will be fixed at a favorite amount. Also, to protect resonant capacitor from over voltages that may happen in the system, sufficient margins for firing angle of rectifier are properly designed. © 2008 IEEE.
The static compensators are capable of improving the power quality indices in the power systems. Since the Electric Arc Furnace (EAF) acts as a non-linear time-variant load, it deteriorates the power quality. Thus, with a suitable design of the static compensators the consumed power by the electric furnace can be controlled. In this regard, firstly, a power system with an electric furnace is simulated. In the next step, in order to improve the power quality indices, a Thyristor Switched Capacitor (TSC) VAr compensator is designed optimally and then simulated. The TSC static compensator is designed so that the great variations of the furnace reactive power can be measured accurately. In addition, the designed static compensator creates a reduction in the voltage and current transients at the Thyristor terminals as well as generating the suitable pulses for them. Also, a suitable harmonic filter is proposed to improve the performance of the power system. © 2008 IEEE.
Economic load dispatch is one of the most important problems in power system operation, therefore the aim of this paper is to establish a method to reduce electricity generation costs with a new approach. This method introduces two new constraints called rate of change of frequency (ROCOF) and minimum frequency as the main constraints in economic dispatch in this paper. This approach reduces emission and fuel costs of the power plants as well as transmission line losses. Therefore, this method has also the capability to control frequency in a desirable range. Finally, the proposed method is simulated on a test system. In the simulation, the economic load flow with is solved with spinning reserve, transmission lines loses and generation constraints as well as the two new mentioned constraints, i.e. ROCOF and minimum frequency constraints. Simulation results obtained from the proposed and conventional methods, show advantages of proposed method. ©2008 IEEE.
International Review of Electrical Engineering (25332244) 3(4)pp. 682-690
Economic load dispatch is one of the most important problems in power system operation, therefore the aim of this paper is to establish a method to reduce electricity generation costs with a new approach. This method introduces two new constraints called rate of change of frequency (ROCOF) and minimum frequency as the main constraints in economic dispatch in this paper. This approach reduces emission and fuel costs of the power plants as well as transmission line losses. Therefore, this method has also the capability to control frequency in a desirable range. Finally, the proposed method is simulated on a test system. In the simulation, the economic load flow is solved with spinning reserve, transmission lines losses and generation constraints as well as the two new mentioned constraints, i.e. ROCOF and minimum frequency constraints. Simulation results obtained from the proposed and conventional methods, show advantages of the proposed method. Copyright © 2008 Praise Worthy Prize S.r.l. - All rights reserved.
One important issue in power plants is the reliability. In the power systems, the power plant outage is a critical situation and as a matter of fact, the layout and the configuration has direct effect on the outage. In this paper, the effects of synchronous generator circuit breakers (SGCB) on the one & half and two circuit breaker layouts are investigated. In the simulation of this paper, the minimal cut set and path are employed. The results of the simulation and economic evaluations demonstrate the SGCB increases the reliability indices as well as reducing the cost in the deregulated electricity markets.
Journal of Applied Sciences (discontinued) (18125654) 8(16)pp. 2788-2800
Load shedding and generation reallocation (LSGR) schemes are important and powerful tools in the present day power systems to maintain system stability. In this study, a new method has been presented on the basis of Fuzzy Particle Swarm Optimization (FPSO) algorithm in order to reduce the LSGR in the form of real optimization. By real optimization in this method, it means using the discrete variables for LSGR problem by real steps of load decreasing in every buses and reallocation steps in power plant productions. Also, by considering the system frequency as an essential variable and using the electrical load model with the essential constraints, the LSGR problem is solved. Referring to the above facts and considering the large number of variables in optimization issue, utilization of the FPSO algorithm is very useful in finding the optimal procedure for LSGR problem. Finally, in order to test the proposed method, it has been implemented on the IEEE 14-Bus system and acceptable results have been obtained. © 2008 Asian Network for Scientific Information.
Computer Systems Science and Engineering (discontinued) (02676192) 23(4)pp. 241-253
One of the most important methods in loss reduction and controlling the voltages of distribution systems is the utilization of the fixed and switched capacitors. To do this, real modeling of the system in large scale unbalanced or balanced for both radial and meshed configurations are required. In this paper, a new technique for finding the optimal values of the fixed and switched capacitors in the distribution networks based on the Real-Coded Genetic Algorithm (RCGA) is presented. In this method, the modeling of radial or loop feeders with unbalanced or balanced network loads are basically considered. Also, the modeling of the load at different levels is simulated which low voltage and medium voltage capacitors those are available in the market are used. Regarding the above factors in addition to the various parameters in optimization problem, the RCGA is used to find the best and real optimal network with the best rate for the capacitors. Finally, this methodology is tested on a region of the distribution network of the city of Ahvaz in Iran and satisfactory results are obtained. These results show that in addition to the decreasing of the network losses and improvement of the voltage profile, the benefit saving due to application of capacitors is increased. © 2008 CRL Publishing Ltd.
Journal of Applied Sciences (discontinued) (18125654) 8(8)pp. 1406-1415
In order to improve dynamic stability of the power systems, the use of Power System Stabilizer (PSS) has been recently increased. For this purpose, there are varieties of methods for determining the controller coefficients of the system stabilizers. If these coefficients are tuned in each operational point by an adaptive mechanism, the robust performance of the system is improved. In this study, a new method for determining the coefficients of a selt-tuning FM with lead-lag controller based on pole-assignment and pole-slutting techniques is presented. In the design procedure, the required identification in self-tuning regulator is performed by using active and reactive power values. Moreover, the properties of the proposed methodology are compared with self-tuning PID stabilizer whose coefficients are determined by using pole assigment technique. Then, the advantages of the proposed stabilizer in which parameter adaptation is accomplished based on the proposed self-tuning method by combining the pole-assignment and pole-shifting techniques, is expressed with respect to other stabilizers. Finally, in order to show the effectiveness of the proposed methodology, some simulation results on a power system with definite parameters and different operational points are provided and compared by using ITAE performance index which denotes the integral of time multiplied by absolute error. © 2008 Asian Network for Scientific Information.
Electric arc furnace is of the non-linear loads for which different models have been suggested in order to its functioning analysis so far and it can have great effects on its neighboring generators. The goal in this paper is to study the effects of precision modeling on the power system local generator shaft. For this purpose, three models nearer to reality are employed for furnace simulation so as to study its effect on the generator shaft and on the point of connection among the turbines. The new method employed in this research is to consider different stages of melting and the use of the most suitable furnace model for simulation in that stage. So, an attempt is made to consider - the important stages of melt - which can affect the generator and to use a model which can describe the furnace operation in the best possible way in each stage. By using the graph of torque waves exercised on the generator shaft, the existing problems are studied and analyzed. © 2008 IEEE.
Journal of Electrical Engineering (1339309X) 58(4)pp. 189-199
One of the most important methods in loss reduction and controlling the voltages of distribution systems is the utilization of the fixed and switched capacitors. To do this, real modelling of the system in actual operational conditions including unbalanced or balanced loading and for actual feeder structure, i.e, radial/meshed configuration, are required. In this paper, a new technique for finding the optimal values of the fixed and switched capacitors in the distribution networks with above properties based on the real coded genetic algorithm (RCGA) is presented. For this purpose, the modelling of the loads at different load levels are simulated with low voltage and medium voltage capacitors that are available on the market. Regarding the above factors in addition to the various parameters in the optimization problem, RCGA is used to find the best and real optimal network with the best rate for the capacitors. Finally, this methodology is tested on a region of the distribution network of the city of Ahvaz in Iran and satisfactory results are obtained. These results show that in addition to the decreasing of the network losses and improvement of the voltage profile, the benefit saving due to application of capacitors is increased. © 2007 FEI STU.
