مرتب سازی بر اساس: سال انتشار
(نزولی)
Results in Engineering (25901230) 27
Optimal Power Flow (OPF) plays a fundamental role in the secure and efficient management of power systems, both in system design and real-time operation. Existing OPF approaches often struggle with the problem's non-linearity, non-convexity, and mixed-variable characteristics, which hinder convergence and compromise solution diversity. This paper addresses these challenges by applying a multi-objective evolutionary algorithm based on decomposition (MOEA/D) enhanced with stable matching theory. The proposed method ensures a balanced and effective trade-off between solution accuracy and diversity in multi-objective optimization. Comparative evaluations against well-established algorithms demonstrate the superior performance of the proposed approach in approximating the Pareto front, improving computational efficiency, and maintaining solution diversity. The results highlight the effectiveness of the method in addressing OPF problems with conflicting objectives such as cost minimization, loss reduction, and voltage stability enhancement. This research provides a new perspective on applying stable matching mechanisms into evolutionary algorithms for power system optimization. © 2025 The Author(s)
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.
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.
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(22)pp. 5249-5260
During the power system restoration there is a high possibility that the load demand is greater than the normalsystem operation for thermostatic loads. This demand increment, called Cold Load Pick-up (CLPU) has been a critical concernto utilities and will slow down the restoration process. Thus, it is imperative to predict the CLPU demand to perform restorationprocess more precisely. The use of new loads such as electric vehicles (EVs) has made new problems. In this paper, first thenegative impact of EVs after an outage, on CLPU demand is investigated and then it is shown that the behavior of EVs duringrestoration service is the same as CLPU phenomenon. In doing so, the proposed approach uses Monte Carlo simulationmethod to predict EVs recharging demand. Since there will be some other new loads in the future that may have CLPUperformance, a new approach is proposed to predict the CLPU demand of any load, without the need to have its exact model.ANFIS method is used to estimate CLPU demand based on previous outage cases in the feeder. The proposed approach isimplemented in MATLAB® and simulation results confirm its ability in load prediction for restoration service. © 2020 The Institution of Engineering and Technology.
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
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
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. 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.
Iranian Journal of Science and Technology - Transactions of Electrical Engineering (23641827) 43(2)pp. 343-359
The proper placement of distributed generations, especially wind turbines, is a challenging issue in distribution networks. In this regard, this paper employs the fuzzy adaptive modified particle swarm optimization (FAMPSO) to determine the locations of wind turbines in a radial distribution network by considering power losses, operation cost reduction and voltage stability improvement as the objective functions. Considering the nature of these objective functions and load flow necessity, wind turbine placement is a nonlinear and complicated numerical problem. Therefore, the multi-objective FAMPSO and Pareto optimal methods are employed for compromising between the objective functions. Moreover, during the simulation procedure, a set of non-dominated solutions is stored in an external memory. This method is applied to a 69-bus distribution network for algorithm verification. © 2018, Shiraz University.
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
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 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(11)pp. 2530-2538
This study proposes a new adaptive and centralised under-voltage load shedding (UVLS) to prevent short-term voltage instability; it then examines the challenges related to the centralised UVLS. The proposed method uses a local measurement to estimate the amount of load shedding. It decreases the amount of load shedding by selecting the proper location of UVLS and shedding more powers within seconds after activating UVLS. Dynamic simulations are performed on the IEEE 118-bus test system, New England test system, and on Isfahan regional power grid (IRPG) as the case studies. Simulation results, when compared with the conventional multi-port network model and sensitivity-based methods, provide a considerable reduction in the active power shedding in addition to the number of the load shedding steps. Moreover, it indicates that the measurement bias errors have a considerable effect on UVLS. Finally, a method is introduced to overcome the effect of measurement errors. © 2018, The Institution of Engineering and Technology.
International Transactions on Electrical Energy Systems (20507038) 27(7)
In this paper, a new wide area neural network–based method is presented for the accurate detection of necessity and the time of controlled islanding execution in large interconnected power systems. By performing coherency analysis at different conditions, the initial coherent groups of the network are determined. To account different stability margins between areas at different conditions and network topologies, we introduced the new parallel neural network (P-NN) structure. The proposed P-NN consists of different individual recurrent neural networks between each of adjacent initial groups. The P-NN is trained with respect to selected wide area signals and generated database through comprehensive stability studies. After the online detection of possible asynchronous oscillations and the corresponding final coherency determination, the alarm signal is sent to the designed P-NN to investigate the network stability between initial groups in real time. The proposed method is applied to New England 39- and 118-bus power systems at different cases and is compared with another intelligent method. It is shown that the proposed method is able to detect islanding necessity and related islands accurately for different disturbances. The speed of the islanding detection, as an important aspect in intelligent controlled islanding, is increased by the proposed method. This will in turn help the system keep stability. In addition, the proposed method could distinguish large stable swings from unstable ones in different contingencies. Copyright © 2017 John Wiley & Sons, Ltd.
International Transactions on Electrical Energy Systems (20507038) 27(4)
This study presents a new undervoltage load shedding (UVLS) method to reduce the amount of power curtailment in emergency conditions. At first, the effect of temperature is considered in an existing multiport network model. Then, a new centralized method called 2-factor UVLS is proposed. The proposed method considers the load reactive power and the multiport network model to determine the effective location of the UVLS. So as to take the actual conditions into account, the main challenges related to the centralized applications are evaluated and then a solution is introduced to overcome these challenges. The proposed 2-factor method and the multiport network model are implemented in the IEEE 57-bus test system, IEEE 118-bus test system, and a real 341-bus power system. Moreover, a comparison is made between 2-factor and sensitivity-based methods. The results show that the proposed 2-factor UVLS method needs less active power shedding than the multiport network model and sensitivity-based method. Copyright © 2016 John Wiley & Sons, 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.
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
Renewable and Sustainable Energy Reviews (13640321) 63pp. 1-12
Voltage stability assessment is a major issue in monitoring the power system stability. Different voltage stability indices (VSIs) have been proposed in the literature for voltage stability assessment. These indices can be used for distributed generation (DG) placement and sizing, detecting the weak lines and buses and triggering the countermeasures against voltage instability. This paper reviews the VSIs from different aspects such as concepts, assumptions, critical values and equations. The review results provide a comprehensive background to find out the future works in this field and select the best VSI for different applications like DG placement and sizing and voltage stability assessment. © 2016 Elsevier Ltd.
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.
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) 83pp. 124-133
This paper presents an optimal design for simultaneously locating unified power flow controller (UPFC) and power system stabilizer (PSS). The parameters of their controllers are also tuned coordinately to enhance the power system stability. A mixed integer nonlinear problem is obtained for the design procedure due to the characteristics of selected objective functions. A new population-based meta-heuristic algorithm, called water cycle algorithm (WCA) is used to solve this problem. The best Pareto optimal set is also attained by defining this problem as a multi-objective function. The simulations results on IEEE 39-bus power system confirm the efficiency and the superior performance of the proposed method when compared with other algorithms. © 2016 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
IET Generation, Transmission and Distribution (17518687) 10(10)pp. 2336-2350
This study presents a new design of a wide area damping controller for the convertible static compensator (CSC) to limit some major blackouts due to asynchronous oscillations. The adaptive neuro-fuzzy inference system (ANFIS) approach is adopted in the dual heuristic programming method to have an optimal response at different disturbances. The proposed ANFIS parameters are optimised by using the multi-swarm particle swarm optimisation method. The CSC dynamic performance in both of unified power flow controller and interline power flow controller configurations is investigated to increase the damping of inter-area oscillations and to prevent the uncontrolled network islanding. The Iranian power grid and New England power system are selected to install CSC and to apply the designed damping controller. It is shown that the considerable number of wide area blackouts could be avoided by CSC application equipped with the proposed damping controller. In other scenarios, which the controlled islanding is an unavoidable task, the boundaries of islands are determined adaptively considering the changes of generators coherency and the loadings of lines. Simulation results verify that the load shedding amounts are decreased and the stability margins of islands are increased. The uncontrolled islanding condition is also delayed significantly. © The Institution of Engineering and Technology 2016.
International Journal of Electrical Power and Energy Systems (01420615) 82pp. 599-607
This paper presents a new optimization algorithm, named intersect mutation differential evolution (IMDE) to optimally locate and to determine the size of DGs and capacitors in distribution networks simultaneously. The objective function is taken to minimize the power loss and loss expenses providing that the bus voltage and line current remain in their limits. Simulation results on IEEE 33-bus and 69-bus standard distribution systems show the efficiency and the superior performance of the proposed method when it is compared with other algorithms. © 2016 Elsevier Ltd. All rights reserved.
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.
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.
IET Generation, Transmission and Distribution (17518687) 9(16)pp. 2686-2696
This study presents a new intelligent controlled islanding scheme based on wide area measurement systems data to avoid the wide area blackout. Three offline, online and real-time parts are applied to solve three problems including where and when to implement islanding and what to do after separation. New security-based criteria are used to determine the initial stable coherent groups. The boundaries of islands are obtained adaptively considering different operating points by using the weighted time varying graph structure of the network. To reach more stable islands, reactive power is considered by using a self-tuned online fuzzy factor in graph weights. The number of necessary islands with their locations is determined in online part by monitoring the dominant inter-area oscillations between the initial groups (IGs). Then, the network is split into islands with the objective of minimum power flow disruption. To detect the unavoidable islanding cases correctly, a new parallel adaptive neuro-fuzzy inference system (ANFIS) structure is designed. In a parallel structure, for each of two adjacent IGs a distinct ANFIS is also applied to consider variable stability margins between groups. Simulation results confirm that the blackout can be avoided in a large power grid by using the proposed method. © 2015. The Institution of Engineering and Technology.
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.
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.
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.
SIMULATION (00375497) 89(9)pp. 1041-1055
This paper presents a new optimization method for designing the parameters of a power system stabilizer (PSS) using a smart bacteria foraging algorithm (SBFA). The proposed technique, which is a modification of the bacteria foraging method (BFA), can direct bacteria by performing a tumble with a smart unit of length, decreasing the cost function better than the conventional BFA method. This algorithm not only considers social intelligence, but also emphasizes the individual intelligence of bacteria for finding a better nutritional path. A new cost function in the proposed SBFA has been used for specifying the direction of movement after a tumble. This approach led to a higher convergence speed and also better performance than the BFA. The effectiveness of the proposed method has been tested on a multi-machine power system while considering a frequency error-based objective function to enhance damping of the electromechanical oscillation modes. Simulation results for the proposed method are compared with conventional PSS, BFA- and fuzzy-based PSS methods. The results show the superior performance of the proposed SBFA-based PSS in comparison with other techniques for damping power system oscillations. © 2013, The Society for Modeling and Simulation International. 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.
International Journal of Electrical Power and Energy Systems (01420615) 49(1)pp. 269-279
FACTs devices are being used in transmission networks for increasing the power transfer limit and stability improvement. They also help damp out both local and inter-area low frequency oscillations. However, uncoordinated design of these devices with excitation systems may deteriorate the power system performance. Moreover, power system is a large, complex and nonlinear system, and the controllers that are designed based on linear control theories may have a detrimental effect on the system performance, especially when there are large disturbances occurring in the system. The design method of a nonlinear control technique, named zero dynamics is given in this paper to design the controllers of STATCOM and excitation systems coordinately for multi-machine power systems. This technique is able to provide the stability of both external and internal dynamic performances of the system. Simulations results clearly verify that the proposed method improves the power system stability. © 2013 Elsevier Ltd. All rights reserved.
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.
Electric Power Systems Research (03787796) 101pp. 36-48
Synchronous generators are generally equipped with power system stabilizers (PSS) to damp out low frequency oscillations. Among different types of PSSs it has been recently shown that the new advanced stabilizer, called multi-band PSS (MB-PSS), has a better performance to cope with all global, inter area and local modes. All different types of PSSs are mainly designed based on one operating point of the system using a linear model. However, power system is inherently nonlinear and its operating conditions frequently change and the PSS performance may deteriorate. This paper develops a new design for MB-PSS in which the parameters are tuned by using a new Meta-heuristic optimization algorithm based on the combination of culture algorithm, particle swarm optimization (PSO) and co-evolutionary algorithms. In this new culture-PSO-co evolutionary (CPCE) algorithm, the characteristics of all three mentioned algorithms are combined and a new strong optimization technique is obtained. The proposed MB-PSS is tested on a multi-machine power system and results are compared with PSO-based MB-PSS (PSO-MB-PSS) and conventional MB-PSS (C-MB-PSS). Simulation results confirm the effectiveness of the proposed optimization tuning method for improving the power system dynamic stability. © 2013 Elsevier B.V. All rights reserved.
International Journal of Electrical Power and Energy Systems (01420615) 44(1)pp. 571-580
Conventional power system stabilizer (CPSS) has been widely used as a supplementary controller to damp out the low frequency oscillations. The tuning of CPSS parameters for nonlinear power systems in a robust way in order that the overall system stability can be improved is a major drawback of CPSS. Several meta-heuristic optimization techniques have been tried out to overcome this shortcoming. This paper presents a new technique named cultural algorithms (CAs) to tune the PSS parameters. This technique is robust and computationally efficient as compared with other meta-heuristic algorithms. Simulations are carried out on two typical multi-machine electric power systems. The results clearly verify that the proposed method improves the dynamic stability of the system, especially when the operating point changes. © 2012 Elsevier Ltd. All rights reserved.
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.
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.
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.
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.
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.
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.
International Journal of Electrical Power and Energy Systems (01420615) 41(1)pp. 112-119
A new robust power system stabilizer (PSS) design using Quantitative Feedback Theory (QFT) for damping electromechanical modes of oscillations and enhancing power system stability is proposed in this paper. The design procedure is carried out on a multi-input-multi-output (MIMO), non-minimum phase and unstable plant. A multi-machine electric power system with system parametric uncertainties is considered as a case study. To show the effectiveness of the QFT technique, the proposed method is compared with a conventional PSS (CPSS) whose parameters are tuned using the classical lead-lag compensation and genetic algorithms. Several nonlinear time-domain simulation tests indicate that the suggested control scheme is robust to the changes in the system parameters and also to successfully reject the disturbances. The results also show that the performance of the QFT method given in this paper is more desirable than CPSS and genetic algorithm (GA). © 2012 Elsevier Ltd. All rights reserved.
Canadian Conference on Electrical and Computer Engineering (08407789) pp. 687-690
Although it has been proved that Facts devices can increase the damping of the power system, uncoordinated design of theses devices with power system stabilizers (PSSs) may degrade the system performance. This paper presents a new hybrid algorithm, named BF-NM, to design the parameters of PSS and STATCOM coordinately. In order to have the best optimization procedure two methods of Bacteria Foraging (BF) and Nelder-Mead (NM) methods are employed. Simulations are carried on a single-machine-infmite-bus system. Comparing the results of the proposed method with other intelligent methods, PSO and BFA shows that a better performance is achieved when using the new technique. © 2011 IEEE.
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.
Canadian Conference on Electrical and Computer Engineering (08407789) pp. 713-716
This paper presents a new method to design a Power System Stabilizer (PSS) using Smart Bacteria Foraging Algorithm (SBFA). The proposed algorithm can conduct bacteria at a smart direction to decrease the cost function better than conventional Bacteria Foraging (BFA) method. This algorithm not only considers social intelligence, but also emphasizes the individual intelligence of bacteria for finding a better nutrition path. This approach leads to have a higher convergence speed and also a better performance than BFA. Simulation results in Two-area four-machine power system show that SBFA improves the dynamic performance of the power system. © 2011 IEEE.
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.
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.
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 equipment. This paper presents a fast and optimal adaptive load shedding method, for isolated power system using Artificial Neural Networks (ANN). The proposed method is able to determine the necessary load shedding in all steps simultaneously and is much faster than conventional methods. This method has been tested on the New-England power system. The simulation results show that the proposed algorithm is fast, robust and optimal values of load shedding in different loading scenarios are obtained in comparison with conventional method. ©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.
This paper presents a new technique for tuning the parameters of a PID controller for load frequency control (LFC) using sequential quadratic programming (SQP) method. In this method the frequency deviation of the system is directly utilized to tune the controller parameters. Simulations are carried out with considering the effect of generation rate constraints (GRC) and the governor limiters. 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.
This paper presents construction of Lyapunov functions for power systems in the presence of SVC based on solving the Linear Matrix Inequality (LMI) derived from the Lyapunov stability theorem considering the AVR control system and SVC in two control strategies. The proposed Lyapunov function is constructed as a quadratic form of state variables and an integral term which satisfies the sector condition. Two-machine one-load system in the presence of SVC is considered. The critical clearing time (CCT) of power system with common mode and transient mode of SVC can be calculated by Lyapunov function. To verify the proposed Lyapunov function, the transient stability assessment is shown for comparison. ©2010 IEEE.
European Transactions on Electrical Power (15463109) 19(2)pp. 323-338
The paper presents a unified approach for the design of the decentralized PID load frequency controller, based on the Quantitative Feedback Theory (QFT). This method not only handles the parametric uncertainty in power systems, but also covers a wide range of load changes. The proposed controller design is simple and effective. The digital simulation results on a multimachine power system example with different operating conditions show that the performance of the controller is robust and effectively improves the dynamical stability of power system. © 2008 John Wiley & Sons, Ltd.
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.
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.
Control Engineering Practice (09670661) 16(9)pp. 1069-1080
A new systematic tuning method with a new structure to design a robust PID load frequency controller for multimachine power systems is presented. The control strategy is mainly based on a maximum peak resonance specification that is graphically supported by the Nichols chart. The proposed controller design is straightforward and effective. It also guarantees that the overall system performance is desirable. Comparative results of this new load frequency controller and a conventional PI one for a multimachine power system example show its robustness with a satisfactory response when the parameters of the system change. © 2007 Elsevier Ltd. All rights reserved.
Journal of Applied Sciences (18125654) 7(22)pp. 3381-3390
A new method to tune the controller parameters is presented in study for Automatic Generation Control (AGC) of hydro turbine power systems. The controller parameters are adjusted such that the maximum phase is located on the right-most point of the ellipse, corresponding the maximum peak resonance on the Nichols chart. For this system making the open-loop frequency response curve tangent to a specified ellipse is an efficient method for controlling the overshoot, the stability and the dynamics of the system. The robustness of the feedback PID controller has been investigated on a multimachine power system model and the results are shown to be consistent with the expected performance. The results are also compared with a conventional PI controller and shown to be superior; especially since the transient droop compensator of the speed governor is removed a much faster response is obtained. The region of acceptable performance for the LFC covers a wide range of operating and system conditions. © 2007 Asian Network for Scientific Information.
This paper presents a new systematic method to design a controller using the Quantitative Feedback Theory (QFT) for a robot identified as a non-minimum phase model. The robot manipulators are highly nonlinear with an uncertain environment. A linearised transfer function of a laboratory robot is developed using the off-line system identification. The effects of nonlinearities are accounted by describing the linearised model parameters as structured uncertainty. The QFT design procedure is carried out to design a robust controller that satisfies performance specifications for tracking. The designed fixed-gain controller is easy to implement. © ICROS.
Design of a robust PID controller for load frequency control of non-minimum phase hydro power plants using the Quantitative Feedback Theory (QFT) is addressed in this paper. Motivated by the large uncertainty in dynamic models of power system components this paper proposes a simple and systematic procedure to tune the parameters of the controller. The resulting controller in simulation results is shown to minimize the effect of disturbances and to maintain the robust performance. © 2006 IEEE.
Design of a robust PID controller for load frequency control of non-minimum phase hydro power plants using the Quantitative Feedback Theory (QFT) is addressed in this paper. Motivated by the large uncertainty in dynamic models of power system components this paper proposes a simple and systematic procedure to tune the parameters of the controller. The resulting controller in simulation results is shown to minimize the effect of disturbances and to maintain the robust performance. ©2006 IEEE.
Journal of Electromagnetic Waves and Applications (09205071) 20(8)pp. 1051-1060
A simple methodology for computation of shielding effectiveness (SE) of conducting enclosures with apertures under external illumination is proposed. The methodology is suitable for prediction of electromagnetic compatibility (EMC) of the final product in the design stage. The exterior and interior regions of the enclosure are analyzed separately by employing the boundary conditions of Bethe's small aperture coupling theory [1]. The electric and magnetic SE of the enclosures is discretized using the finite elements method (FEM). Selected numerical results for the shielding effectiveness of rectangular cavity with apertures calculated by the new methodology are provided and compared with measured published data in order to show the effectiveness and the reliability of the proposed approach.
This paper presents a new method for tuning the parameters of a PID controller for power system load frequency control. A systematic tuning method is developed. This approach leads to a robust controller design using Quantitative Feedback Theory (QFT). The results of this new load frequency controller are compared in simulation with a conventional PI one from the literature for a single-machine-infinite-bus system. ©2005 IEEE.
Electric Power Systems Research (03787796) 73(1)pp. 77-86
This paper presents a new adaptive power system stabiliser able to provide acceptable damping over a wide range of operating points. The control strategy is based on a new adaptive technique named Pole-Zero Assignment Controller (PZAC) in which a particular power system transfer function (Gd(s) = Δδ/ΔPm) is modified to a standard form based on an explicit system identification. Controller design is mainly based on continuous-time system because of using the delta operator rather than the more usual shift operator. Simulation studies performed on a multimachine model are presented. Results clearly show the benefits of the proposed adaptive controller for stability enhancement of a power system, especially where there are large changes in operating point. © 2004 Elsevier B.V. All rights reserved.
This paper presents a new PID controller for power system load-frequency control. A systematic tuning method is developed. The method is mainly based on a maximum peak-resonance specification that is graphically supported by the Nichols chart. The proposed controller is simple, effective and can ensure that the overall system performance is desirable. Comparative results of this new load-frequency controller and a conventional PI one show the improvement in system damping remarkably. © 2004 IEEE.
Electric Power Components and Systems (15325016) 31(5)pp. 513-524
This paper presents a new model for the identification of the power system transfer functions. The usual model has been to use the shift operator q, or its equivalent z transform, but this gives inaccurate results with the small sampling times that are now used in modern controllers. It is shown by a comparison that this problem can be resolved by using the delta operator δ instead. This is shown by a multimachine example using both operators. The simulation results show that the delta operator formulation reflects the dynamic behavior of the system more accurately. © 2003 Taylor & Francis.
A fixed gain power system stabiliser is inadequate to provide acceptable damping characteristics as the operating point changes. For the first time in power system an adaptive Pole Assignment stabiliser is developed to overcome this problem by fixing the poles of the transfer function Gd(s) = Δδ/ΔPm. The development of the control algorithm has been made using the delta operator rather than the shift operator as this removes numerical problems at fast sampling rates. The delta operator also gives transfer functions very similar to those of the continuous system and, therefore allows simplifications of the control design by reducing the order of the numerator of the discrete-time transfer function. Comparative results of the adaptive Pole Assignment controller and a fixed parameter stabiliser show the improvement in response obtained with the adaptive algorithm as the operating point changes.
This paper presents a new method for coordinately tuning the parameters of UPFC controller and power system stabilizer (PSS) as well as determining the PSS location to enhance the stability of power system by using a new hybrid particle swarm optimization based co-evolutionary cultural algorithm, so called culture-PSO-co evolutionary (CPCE). Nonlinear simulations are implemented on the IEEE 39-bus power system. The results imply the effectiveness of the proposed method for damping out power system oscillations. © 2016 IEEE.
A new control scheme, based on Artificial Neuro-Fuzzy Inference System (ANFIS) is used to design a robust Proportional Integral Derivative (PID) controller for Load Frequency Control (LFC). The controller algorithm is trained by the results of off-line studies obtained by using particle swarm optimization. The controller gains are optimized and updated in real-time according to load and parameters variations. Simulation results of this method on a multi-machine system in comparison with conventional fuzzy controller show the satisfactory results, especially where the parameters of the system change. © 2019 ICAI 2015 - WORLDCOMP 2015. All rights reserved.
One of the main problems in the islanded microgrids is the frequency regulation. Moreover, there are several uncertainties and disturbances in the islanded microgrids that may lead to the instability. To solve this problem, this paper proposes the design of a multi-objective Linear Matrix Inequalities (LMIs) based regulator. It considers the LMI conditions in such a way that the design criterion holds. It also considers the disturbances, including solar radiation, wind speed, and load demand variations. With extracting microgrid state space model, it builds a framework to synthesize the controller. Next, it presents the mixed robust design criteria to set up the multi-objective function. The controller design process includes two steps: state feedback and observer designs. With considering weighing functions in the design process, it determines the optimal solution of the objective function. The obtained solution is the state feedback matrix, and it forms the controller by combining the state feedback matrix with a state observer. We have applied the designed controller to the islanded microgrid, and the effect of disturbances is evaluated together with parametric uncertainties. The proposed regulator is compared with the traditional PI method. The results show that the designed regulator has robust performance as well as robust stability. © 2017 IEEE.
Esmaili, M.R. ,
Khodabakhshian, A. ,
Heydarian-forushani e., ,
Shafie-khah, M. ,
Hafezi h., ,
Faranda r., ,
Catalao, J.P.S.
Installation of new power generating units as backup black-start (BBS) sources is a vital issue to improve the acceleration of power network restoration, especially when a serious problem is occurred in main BS units (BSUs) and leads to fail in operation. Accordingly, this work address a new design for the optimal locating of the Gas-based Turbine (GT) as BBS to improve the smart grid performance during both restoration and normal conditions. To this end, there will be incompatible fitness functions to be minimized. Therefore, a multi-objective problem (MOP) including a mixed integer Non-linear programming (MINLP), is formulated. The Pareto answers of the proposed MOP as the best solutions are modified and extracted by utilizing a meta-heuristic method, called crow search algorithm (CSA). A typical test system is employed for evaluation of the given plan. The extracted outcomes reveal that the network can desirably operate from this design not only to favorably enhance the capability of BSUs, but also to improve the power system performance in normal conditions. It also provides the better start-up program of non-black-start (NBS) power sources with the optimal paths during the restoration process. © 2019 IEEE.
