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Publication Date: 2026
Energy Conversion and Management (0196-8904) 348
This paper proposes a comprehensive framework for cyber-resilient optimal energy management system (EMS) in smart grids. A complete 24-hour closed-loop operational cycle is modeled and simulated. It begins with data measurement via a real-time updated nonlinear Digital Twin, followed by transmission through SCADA/RTUs, detection of cyberattacks, accurate reconstruction of corrupted data, and finally EMS. The outputs of EMS are then sent back to the Digital Twin, which is dynamically updated to reflect the actual network conditions and generate accurate synthetic measurements for the next hour. This entire process is embedded within a 24-hour rolling optimization scheme. The EMS includes a power flow model integrated with various distributed energy resources (DERs), such as renewables, diesel generator, battery, electric vehicle, and controllable loads. It also incorporates and ensures all technical, security, and dynamic constraints of the grid and DERs. Unlike previous studies that focus only on isolated aspects such as attack detection, data estimation, or day-ahead energy management, this work implements the entire process in a unified and dynamic framework. The model functions effectively in networks where PMUs are unavailable, as is the case in most real-world distribution grids, because it is designed solely based on RTU and SCADA data. Detection and reconstruction of coordinated attacks rely on physics-based recalculation methods, utilizing grid topology and data from neighboring buses to improve accuracy. The proposed model is validated on the IEEE 33-bus test system, successfully detecting various attack scenarios targeting different parameters, locations, and times. It reconstructs the correct values with high precision and optimizes the network operation accordingly. This 24-hour rolling simulation demonstrates the practicality and robustness of the approach in enabling secure, cost-effective, and resilient energy management in modern smart grids. © 2025 Elsevier Ltd.
Publication Date: 2026
Energy Conversion and Management: X (25901745) 30
This paper proposes a real-time energy management optimization model for active distribution networks. In this model, the active distribution network connected to distributed energy resources exchanges data iteratively with a centralized energy management and control system at each time interval. Network-level parameters, including bus voltages and active and reactive power injections, are measured and sent to the central control system, where data are analyzed for variation, validation, noise detection, and cyberattack identification. Based on this analysis, the system performs rolling optimization for upcoming time-intervals and sends updated operational schedules back to the network, ensuring that generation units and controllable loads operate according to the newest optimal plan. As a result, the optimization of grid performance is carried out at every time interval, and the grid along with local generation–consumption resources are scheduled to operate according to the latest changes in grid parameters such as prices and power loads. Such adaptive scheduling guarantees both optimal and robust performance across all upcoming time periods. During data exchange, measurements may be corrupted by noise or falsified by stealthy false data injection (FDI) attacks with amplitudes close to measurement noise (low-magnitude FDI), making them difficult to detect. To address this challenge, several indices are proposed, including the Bus Current Imbalance Index (BCII), the Residual Current Magnitude Index (RCMI), and the Residual Current Angle Index (RCAI), which can effectively distinguish between noisy and falsified data while identifying the location, start time, and duration of cyberattacks. The results indicate that under varying input parameters such as electricity price, solar irradiance, and network load, the rolling optimization updates schedules and provides an optimal plan for upcoming hours. For example, at hour 6, the diesel generator schedule is adjusted for hours 6–24, and at hour 15, a new schedule is set for hours 15–24. Similarly, the battery plan is updated throughout the day; discharging initially scheduled at hours 17 and 19 is shifted to hours 18 and 19. These operational adjustments impacts operational cost. At hour 6 the total cost rises by 153.34%, whereas at hour 20 the total cost drops by 30.26%. The results also show that the model effectively detects small-magnitude FDI attacks under noise, with amplitudes equal to or 1–3 times the noise. Sensitivity analysis confirms that the proposed index consistently detects attacks under noise levels ranging from 1% to 5%. © 2026 The Author(s)
Publication Date: 2025
Energy (0360-5442) 318
In recent years, reinforcing the electric power system against natural disasters has emerged as a critical challenge and concern. Natural disasters, events, and cyber-attacks pose significant challenges to distribution networks, leading to widespread outages and blackouts. One effective approach to addressing such challenges is to implement a microgrid formation strategy in conjunction with mobile or stationary distributed energy resources. This paper addresses a significant research gap by analyzing load restoration during outages as a part of network resilience strategy, through two simultaneous approaches: (i) microgrid formation and graph theory, and (ii) mobile charging station with battery swapping technology. The proposed microgrid formation utilizes tie-line breaker switches (BS) and a mobile battery-swapping van (MBSV) in a coordinated manner to enhance resilience of system. The IEEE 33-bus network serves as a case study, incorporating both active and reactive powers into the nonlinear power flow equations. Mixed integer linear programming (MILP) is employed, effectively linearizing nonlinear equations for efficient computation. The results show that within 24 h, the objective function value (total power of restored loads) is approximately 687,421 kW, and load restoration is achieved at a rate of 76 %. According to the comparative study, the network without formation suffers from voltage collapse while the proposed plan properly deals with voltage fluctuations and fixes the voltage magnitude within bounds. Additionally, the present research shows load restoration rates that are 5.8 % higher compared to the formed network without a battery swapping station, and 2.3 % higher compared to the formed network with a fixed battery swapping station. During the outages, the MBSV is dispatched to the affected area to maximize the total power of restored loads, primarily due to the high priority of loads in this region. Simulations of network performance under long-term failure is conducted with limited and unlimited fuel. In both cases, batteries discharge after 8 h. With limited fuel, the network performance drops to 55 %, while with unlimited fuel, it drops to 40 %. © 2025 Elsevier Ltd
Publication Date: 2025
Results in Engineering (25901230) 28
In a typical microgrid, multiple control strategies run simultaneously. Therefore, it is essential to protect the system against faults, islanding, large-scale grid outages, natural disasters, and cyberattacks. In this paper, a general multi-purpose framework is presented to increase the resilience of AC microgrids against cyberattacks and physical faults. The proposed method is designed based on the second derivative analysis of vital signals such as frequency, voltage, and power, which provides the ability to distinguish between real faults and cyber attacks, and stabilizes the voltage and frequency within the permissible range using an adaptive soft switch controller in islanded mode through a battery and capacitor. Additionally, the Fault Ride-Through (FRT) capability is enhanced through the immediate injection of reactive power to mitigate the impact of a severe fault. Here, the microgrid consists of two separated and parallel subsets that are connected to the main grid through a transmission line, and each subset is supported by its battery. Simulation results in MATLAB/Simulink confirm that the proposed method effectively identifies attacks and real faults, and this controller offers a robust and practical solution for real-time cyber-physical threat mitigation and reliable microgrid operation. © 2025 The Authors.
Publication Date: 2025
Energy Conversion and Management: X (25901745) 27
Microgrids enable the integration of renewable energy sources; however, managing electricity from intermittent wind and solar power remains a significant challenge. This study investigates two storage strategies for managing surplus renewable electricity in an IEEE 84-Bus microgrid with wind turbines and photovoltaic units. The first option involves producing hydrogen via electrolyzers, which is stored for later electricity generation through fuel cells. The second option involves converting surplus electricity into heat using heat pumps, which is then stored in thermal energy storage systems to efficiently meet the microgrid's thermal load requirements. A scenario-based day-ahead scheduling model is proposed to optimize the microgrid's electrical and thermal load management while considering uncertainties in market prices, wind speeds, and solar irradiance. The resulting large-scale optimization challenge is effectively tackled using the self-adaptive charge system search algorithm. The results indicate that, for the optimal utilization of excess renewable electricity, heat generation via heat pumps is more cost-effective than hydrogen production, primarily due to the inefficiencies in hydrogen conversion and the ability of heat pumps to produce several units of heat for each unit of electricity consumed. Moreover, heat pumps prove to be more economical than natural gas combustion in boilers for meeting the thermal demands across a wide range of gas prices. These findings highlight the economic benefits of integrating heat pumps and thermal energy storage systems into renewable energy microgrids. © 2025 The Author(s)
Publication Date: 2025
Physica Scripta (00318949) 100(5)
This study presents the design and analysis of an optimized Surface Plasmon Resonance (SPR) sensor for enhancing the detection sensitivity of crude oil samples. Conventional SPR sensors, which commonly use gold or silver layers, are limited in stability and sensitivity when measuring complex substances like crude oil at near-infrared wavelengths. In this work, we develop a sodium-based SPR sensor coated with Transition Metal Dichalcogenides (TMDCs), and an oxide layer for real-time crude oil sensing. The sensor’s performance is optimized through theoretical simulation using the Transfer Matrix Method (TMM) and Finite Element Method (FEM) with Kretschmann configuration at the near-infrared wavelength (1550 nm). The performance parameters of SPR sensors, including sensitivity, detection accuracy, and signal-to-noise ratio, were measured, indicating significant improvements over traditional SPR configurations. The maximum sensitivity achieved is 169.382 deg RIU−1 with FoM of 162.867 1/RIU. Results demonstrate that the proposed sensor provides high sensitivity and reliability for detecting and analyzing real-time crude oil refractive index changes, marking a potential breakthrough in petrochemical analysis. © 2025 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.
Publication Date: 2024
Journal of Cleaner Production (0959-6526) 471
The rising occurrences of natural disasters, terrorist actions, and cyber-attacks that result in extensive, long-lasting, and expensive disruptions have necessitated a shift in focus towards the resilience of electrical grids for network operators. However, the task of designing a resilient network remains complex and costly. One potential solution to bolster resilience is the deployment of battery energy storage devices on the consumer side, known as distributed energy systems (DES). Despite its effectiveness, the high construction costs and lengthy payback period associated with investing in energy storage devices have led consumers to exhibit reluctance in adopting them. Cloud energy storage (CES) is an innovative and cost-effective solution to address those challenges. In the CES platform, investors install storage facilities in the network which can be rented by consumers to fulfill their needs and they become holders of the virtual batteries. By adopting this approach, consumers are relieved from the burden of maintenance, repair, and installation. While a single CES facility offers reduced costs and increased comfort for consumers, it compromises the resilience of the grid when compared to the Distributed Energy Storage (DES) mechanism. In order to bridge this gap, this paper proposes a dual CES model which serves as an intermediate solution between DES and single CES. The dual CES model strikes a balance between the resilience of the grid and cost-effectiveness. It provides a higher level of resilience compared to a single CES and a lower level compared to DES. Additionally, the costs associated with the dual CES model fall between that of a single CES and DES. This model not only increases the profit margin for investors but also enhances the overall comfort and well-being of consumers compared to the single CES. To validate the proposed model, a Mixed Integer Linear Programming (MILP) problem is formulated and simulated on the IEEE 33 bus network. Three cases are considered: DES, single CES, and dual CES. The results indicate that the dual CES reduces consumers' costs by 28 %, losses by 27 %, unsupplied load costs by 45 %, and return on investment by 33 %. Moreover, it increases the stability margin time by 2 intervals and improves robustness by 47 %. © 2024 Elsevier Ltd
Publication Date: 2024
Journal of Energy Storage (2352152X) 83
In this paper, a centralized management mechanism is presented for cloud energy storage (CES), which is a new competitor to distributed energy storage (DES). In the CES, a central energy storage is installed by an investor and the consumers can rent portions of the CES capacity according to their needs. The investor's revenue includes the received rent from the consumers. In the proposed model, the investor of CES ensures that the annual cost of the consumers is less than the DES approach. The consumers are therefore encouraged to participate in the CES mechanism. IEEE 33-bus distribution network is assumed as a case study, and it is simulated under three cases: the network without storage, the network with DES approach, and the network with CES approach. The simulation results verify that the CES improves the well-being of the consumers compared to the DES approach. In the CES, the annual cost of the consumers decreases by 6 % and 4.48 % compared to cases 1 and 2, respectively. The return on investment is less than 3 years, with a projected lifespan of 10 years. The CES decreases the purchased power from the upstream network by 1.4 % compared to the DES. It is demonstrated that the renting cost of the CES services is between 49 % and 56 % of the investment cost in the DES approach. In addition, a conceptual comparison is made between CES and centralized energy storage (CENES) systems. Simulation results show that while investment cost is reduced by 6.1 % in the CENES approach, revenue and profit decrease by 35 % and 38 % respectively. The return on investment for CENES is approximately 44 months, whereas for CES, it is approximately 28 months. © 2024 Elsevier Ltd
Publication Date: 2024
IEEE Transactions on Industrial Informatics (1551-3203) 20(1)pp. 649-658
District energy systems (DESs) and integrated electricity-gas systems (IEGSs) are closely related. The performance of these systems in critical situations, such as faults and equipment outages, has not been adequately investigated. The operation of DESs may also be significantly affected by installing central generating systems for gas or electricity sectors. These central generating units may deal with outages and faults. In the literature, there is not a comprehensive model that considers renewables in IEGS, uncertainties of generating systems, a mutual connection between electricity and gas sub-grids, the ability to exchange power with the upstream grid, a centralized storage device for the electrical sector, and centralized power supply for the gas sector. All these points are considered and modeled in the proposed model. This article presents several multipurpose control strategies for DES that are designed and implemented on an IEGS. Electricity and thermal loads are used to model the DES energy needs. In the electricity subsystem, by using several local renewable energy sources (RESs) and a central battery, not only the electric loads are supplied, but also the DES can be connected to the upstream grid and trade the scheduled power in accordance with the electricity market contract in all normal and critical conditions. On the other hand, the gas subsystem is powered by a central fuel cell. Gas and electricity subsystems in the DES region are designed to assist each other during outages and events to increase resilience. All RESs, central batteries, and fuel cells are equipped with individual controllers to achieve the above-mentioned objectives. A centralized control framework is used to manage all these controllers under a variety of operating conditions. Numerical simulations in MATLAB software verify the model's ability to control DES and IEGS properly. © 2005-2012 IEEE.
Publication Date: 2024
IET Smart Grid (25152947) 7(5)pp. 531-553
A comprehensive model is developed for coordinated control of voltage-frequency-inertia and identifying multiple cyberattacks simultaneously in two microgrids (MGs). The MGs are integrated with solar units, Wind turbine (WT), hybrid supercapacitor-battery, and fuelcell. The MGs are modelled and controlled for operation under both an island and connected states. In the proposed method, a data centre is designed in which all the electrical and control signals related to the solar, wind, hybrid supercapacitor-battery, and Fuel cell (FC) are collected, evaluated, and matched. The data centre comprises the following blocks: voltage-frequency control, inertia control of WT, and identification of false data injection (FDI) cyberattacks on frequency, power, power/frequency, and voltage. The technique used in this article to identify FDI attacks is based on the real-time method coupled with logical comparisons conducted in the time domain. This methodology provides prompt and precise detection, allowing for timely preventive measures and strategic responses. After FDI attacks occur, the implemented control system effectively manages and regulates the voltage and frequency at the desired levels, efficiently differentiating between ordinary functioning, faulty states, and potential cyber-attacks. The unhealthy MG can transfer its load to the healthy MG for safety reasons. The healthy MG is then connected to the external grid and the synchronisation conditions are checked by the proposed control system. The results of the non-linear simulation performed in MATLAB-Simulink software confirm that the proposed model successfully operates and controls all resources (i.e. solar/wind/battery/FC), regulates the voltage/frequency under various loading conditions, and identifies FDI cyberattacks. © 2024 The Authors. IET Smart Grid published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.
Hemmati, R. ,
Hemmati, R. ,
Hemmati, R. ,
Mehrjerdi, H. ,
Mahdavi, S. ,
Dehghanian, P. ,
Hatamirad, A. Publication Date: 2024
Conference Record - Industrial and Commercial Power Systems Technical Conference (21584907)
In the recent years, the electric power system reinforcement against natural disasters has become one of the key challengers and concerns. The natural disasters, events and cyber-attacks are the most important challenges facing distribution networks causing widespread outages and blackouts. One of the useful techniques to cope with such problems is to utilize the microgrid formation strategy. This paper applies microgrid formation for load restoration and preventing voltage collapse. The given model enhances the system resilience following events. The proposed microgrid formation is developed by utilizing the tie-line breaker switches (BS). The IEEE 33-bus network is considered as case study and both the active-reactive powers are included in the power flow equation. The mixed integer linear planning (MILP) is used and the nonlinear equations are efficiently linearized. The results are presented under three cases including (i) without formation, (ii) formation without tie-lines, and (iii) formation with tie-lines. The numerical results demonstrate that the supplied loads in cases 1 to 3 are 57%, 64% and 71%, respectively. Therefore, the load restoration under cases 2 and 3 is increased by 7% and 14%, respectively. As well, the results illustrate that the proposed model not only improves the voltage profile but also reduces the generated power by DGs resulting in less environmental pollutions and costs. © 2024 IEEE.
Publication Date: 2024
Journal of Chemical Physics (10897690) 161(9)
We investigate the numerical accuracy of the extended Koopmans’s theorem (EKT) in reproducing the full configuration interaction (FCI) and complete active-space configuration interaction (CAS-CI) ionization energies (IEs) of atomic and molecular systems calculated as the difference between the energies of N and (N − 1) electron states. In particular, we study the convergence of the EKT IEs to their exact values as the basis set and the active space sizes vary. We find that the first FCI EKT IEs approach their exact counterparts as the basis set size increases. However, increasing the basis set or the active space sizes does not always lead to more accurate CAS-CI EKT IEs. Our investigation supports the observation of Davidson et al. [J. Chem. Phys. 155, 051102 (2021)] that the FCI EKT IEs can be systematically improved with arbitrary numerical accuracy by supplementing the basis set with diffuse functions of appropriate symmetry, which allow the detached electron to travel far away from the reference system. By changing the exponent and the center of the diffuse functions, our results delineate a complex pattern for the CAS-CI EKT IE of LiH, which can be important for the spectroscopic studies of small molecules. © 2024 Author(s).
Publication Date: 2024
Csee Journal Of Power And Energy Systems (20960042) 10(2)pp. 786-796
In this paper, a DC microgrid (DCMG) integrated with a set of nano-grids (NG) is studied. DCMG exchanges predetermined active and reactive power with the upstream network. DCMG and NGs are coordinately controlled and managed in such a way the exchanged P-Q power with external grid are kept on scheduled level following all events and operating conditions. The proposed control system, in addition to the ability of mutual support between DCMG and NGs, makes NGs support each other in critical situations. On the other hand, in all operating conditions, DCMG not only feeds three-phase loads with time-varying active and reactive power on the grid side but also injects constant active power into the grid. During events, NGs support each other, NGs support DCMG, and DCMG supports NGs. Such control strategies are realized by the proposed control method to increase resilience of the system. For these purposes, all resources and loads in DCMG and NGs are equipped with individual controllers. Then, a central control unit analyzes, monitors, and regularizes performance of individual controllers in DCMG and NGs. Nonlinear simulations show the proposed model can effectively control DCMG and NGs under normal and critical conditions. © 2015 CSEE.
Publication Date: 2024
Energy (0360-5442) 295
In light of the recent developments in the green hydrogen industry, it is essential to investigate its compatibility and integration with existing electrical grids. This task becomes more challenging when considering its implementation in off-grid sites that solely rely on renewable energy. In cases where off-grid sites should provide electricity and hydrogen to a variety of consumers, it is compulsory to have electrical and hydrogen storage devices with long-term storage capabilities. Consequently, a precise programming technique is necessary to manage the storage and consumption of hydrogen and electricity. To investigate such a model, this paper presents a connected electricity-hydrogen grid in which all the required energy is supplied by solar and hydroelectric units. This off-grid system supplies the necessary energy for industrial and residential loads, electric vehicle charging stations, fuelcell car refueling stations, and natural gas pipelines. The power-to-hydrogen (P2H) and hydrogen-to-power (H2P) systems are used to facilitate energy flow between the electrical and hydrogen sectors. A daily-seasonal hydrogen storage is integrated as well. The proposed method contributes by integrating and improving the modeling, management, optimization, and operation of the daily-seasonal hydrogen storage and electrical storage. Its primary objective is to supply electricity and hydrogen to various consumers using solely renewable energy, even in the face of renewable energy fluctuations and outages. The model is mathematically expressed as a mixed integer linear optimization, implemented in GAMS software, and solved by the CPLEX solver. It aims at maximizing profit from selling electricity and hydrogen to the users. Results demonstrate that P2H and H2P units have a complementary operation with the solar system. When there is abundant solar energy, the P2H converts excess clean energy to green hydrogen and H2P operates when solar energy is not available. Seasonal storage also stores hydrogen from spring to autumn and discharges it in winter because of higher hydrogen prices in this season. Such an operation increases the annual profit by about 9%. When the hydroelectricity unit faces an outage in hours 8 to 13, the fuelcell uses the stored hydrogen and comes into operation to compensate hydropower outage. The net present value of profit amounts to $275,179 per year. The total hydrogen required is approximately 49,870 kg per year, with a total electricity requirement of 1190 MWh per year. The levelized revenue from hydrogen is achieved at around $4 per kilogram, while the levelized revenue from electricity is about $0.058 per kilowatt-hour. It is concluded that the integration of seasonal storage effectively reduces costs, boosts profits, and efficiently manages renewable energy fluctuations across different seasons. © 2024 Elsevier Ltd
Publication Date: 2023
Innovations in Education and Teaching International (14703297) 60(5)pp. 688-702
The purpose of this study is to investigate the impact of major developments in Iran’s higher education system and their implications for doctoral education. In all, four major developments __ massification, privatisation, internationalisation, and the coronavirus pandemic __ are investigated, and their impact is analysed. The results indicated that, despite continuing turbulence, doctoral education in Iran has continued much as before because the system has limited flexibility in facing new national and international requirements. In view of the latter, it is argued that there is a need for policymakers to consider revising the nature and goals of doctoral education. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
Publication Date: 2023
Energy (0360-5442) 277
This paper addresses a novel multi-stage dynamic distribution network expansion planning (DNEP) taking into account the electric vehicle (EV) charging station based on the battery swapping model. The battery swapping station (BSS) is transferred seasonally and integrated to different buses in various seasons in order to defer the investment on the new lines. The BSS is as well integrated with rooftop solar panels. The uncertainties of loads and renewable energies are taken into account and handled by stochastic programming. The charging scheduling is optimized for all the batteries inside the BSS. A comparative study is presented for 3 cases including expansion planning without BSS, planning with a fixed location of BSS, and the proposed method (i.e., planning with seasonally transferred BSS). The numerical simulations demonstrate that the proposed model transfers the BSS every six months, where, it is installed on bus 25 in seasons 1 and 2, and on bus 17 in seasons 3 and 4. The congested lines such as lines 2 to 19, 16 to 17, and 6 to 7 are expanded by installing new lines in years 2, 4, and 5, respectively. The BSS sends power to the external grid in on-peak loading times such as hours 12 to 15 and 18 to 21. The proposed model reduces the planning cost by 5% compared to the expansion planning with a fixed location for BSS. © 2023 Elsevier Ltd
Publication Date: 2023
pp. 1-375
Energy Management in Homes and Residential Microgrids: Short-Term Scheduling and Long-Term Planning provides an in-depth exploration of Home Energy Management Systems (HEMS), with a focus on practical applications for both short- and long-term models. Through this guide, readers will learn how to create efficient systems that facilitate the integration of renewable energy into the grid and simultaneously manage end-users' energy consumption. The short-term operation of Home Energy Management Systems is analyzed through various lenses, including renewable energy integration, energy storage integration, uncertainty in parameters, off-grid operation, outages and events, resilience, electric vehicle integration, and battery swapping strategy. The modelling of these topics is explained with step-by-step instructions, and the parameters and implications are thoroughly discussed. Additionally, the book offers insight into the long-term expansion planning for residential microgrids, providing a detailed examination of dynamic modeling, control, and stability of these small-scale energy systems. Throughout the book, simple and advanced examples are provided, and each example comes with numerical data, detailed formulation, modelling, and simulation. © 2024 Elsevier Inc. All rights reserved.
Hemmati, R. ,
Hemmati, R. ,
Summers, T.J. ,
Hemmati, R. ,
Miller, J.E. ,
Agbaglo, D.A. ,
Cheng, Q. ,
Deyonker, N.J. Publication Date: 2023
Journal of Chemical Physics (10897690) 158(6)
Designing realistic quantum mechanical (QM) models of enzymes is dependent on reliably discerning and modeling residues, solvents, and cofactors important in crafting the active site microenvironment. Interatomic van der Waals contacts have previously demonstrated usefulness toward designing QM-models, but their measured values (and subsequent residue importance rankings) are expected to be influenceable by subtle changes in protein structure. Using chorismate mutase as a case study, this work examines the differences in ligand-residue interatomic contacts between an x-ray crystal structure and structures from a molecular dynamics simulation. Select structures are further analyzed using symmetry adapted perturbation theory to compute ab initio ligand-residue interaction energies. The findings of this study show that ligand-residue interatomic contacts measured for an x-ray crystal structure are not predictive of active site contacts from a sampling of molecular dynamics frames. In addition, the variability in interatomic contacts among structures is not correlated with variability in interaction energies. However, the results spotlight using interaction energies to characterize and rank residue importance in future computational enzymology workflows. © 2023 Author(s).
Publication Date: 2023
Sustainable Cities and Society (2210-6707) 98
In this paper, DC fast charging (DCFC) stations are integrated into the distribution network (DN). The designed DCFC stations are equipped with several charging devices (CDs) at different rated powers, which can charge electric vehicles (EVs) at various power levels through charging points (CPs). A central control system (CCS) is designed for each DCFC, which is applied for managing its local controllers. The CDs also use distributed energy storage (DES) alongside the DC chargers in order to increase the speed of the charging process and utilize the stored energy for improving the DN operation. The DN central controller scheme is as well designed to control the CCS of DCFCs and make positive effects on the upstream distribution grid. The CCS of DN, in addition to managing the CCS of DCFCs, is responsible for controlling the charge level of DCFCs according to four control strategies in each station including improving voltage fluctuations on the DN side, injecting reactive power from DCFCs to DN during a fault on the DN side, increasing DN resiliency by supplying critical loads in the time of upstream network outage, and supplying loads with time-varying active-reactive powers. The nonlinear simulations using MATLAB-SIMULINK demonstrate that the proposed strategies can effectively improve the performance of DN in addition to accurate control of the charging process in the EVs. © 2023 Elsevier Ltd
Publication Date: 2023
Electric Power Systems Research (03787796) 215
This paper presents a multi-objective control scheme on the interconnected wind farms which are formed by different wind turbines including doubly fed induction generators (DFIG) and squirrel cage induction generators (SCIG). The proposed control system aims to control voltage, frequency, and mechanical power in the wind farms under wind/load alterations, faults, and outages. The voltage stability and fault ride through capability are improved. The proposed model also deals with unbalanced loading and faulty conditions. All the aforementioned points are realized under both off-grid and grid-tied conditions. For voltage stability improvement, each wind farm is integrated with one static VAR compensator (SVC) and the grid-side is integrated with one static synchronous compensator (STATCOM). In the grid-tied, the resilience following events is improved by proper control of STATCOM. In the off-grid, the installed SVC at each site is responsible for increasing resilience. The proposed control systems are modeled and implemented on a typical test grid, and numerical simulations are carried out in MATLAB/SIMULINK software. It is demonstrated that the proposed multi-objective control scheme efficiently controls all individual wind farms, achieves a coordinated management between different wind farms, deals with stability/unbalanced operating condition/faults, increases resilience and improves fault ride through capability. © 2022 Elsevier B.V.
Publication Date: 2022
International Journal of Energy Research (1099114X) 46(9)pp. 11925-11942
This paper presents a new concept for district energy (DE) systems using central battery storage and decentralized hybrid renewable systems. The proposed DE consists of five buildings integrated with centralized 300 (V), 6.5 (A.h) batteries, locally distributed generations such as 8.5 (kW) wind turbines and 10 (kW) solar cells rated at 110 (V) and three-phase loads. The central battery can be connected to each home for exchanging power. To increase the resilience, the proposed control system connects home 1 to the external 380 (V) and 50 (Hz) network when the battery is operating above the limited power (ie, 50 [kW] for this case study). The connection to the external grid is done by assessing and confirming a set of necessary conditions. The proposed integrated control system for DE is designed to achieve the following objectives: maximum power extraction from local wind/solar units by maximum power point tracking, optimal charge-discharge process for central battery, connecting DE to the upstream network under outages and supplying the loads under all operating conditions. These goals are investigated by implementing six different scenarios of performance. In scenario 1, wind and solar units produce 6.6 (kW) and 24 (kW), respectively. Therefore, to feed the total load of 42.5 (kW), the central battery produces 15 (kW). In scenario 2, the total load in the first step is 35 (kW) and it is 95 (kW) in the second step. The power of solar and wind units in both loading steps is constant. The battery power increases from 6.5 (kW) absorption in the first step to 22 (kW) injections in the second step. In scenario 3, the solar units are switched off and in scenario 4, both solar and wind units are switched off. In such conditions, the battery responds to supply loads of homes. Increasing the energy resilience of DE during grid outages is modeled in scenario 5; where the battery power increases from 21 to 51.7 (kW) to deal with such outages. The nonlinear simulations in MATLAB/SIMULINK software show that the developed control strategy is able to control local renewable energies as well as the central battery while increasing the resilience and harvesting maximum power from decentralized wind/solar units. © 2022 John Wiley & Sons Ltd.
Publication Date: 2022
Energy (0360-5442) 252
This paper presents a control scheme including resources and load management in the residential DC microgrid. The DC microgrid is supported by fuel-cell, solar-cell and battery. The DC, AC single-phase and AC three-phase loads with 50 Hz frequency are integrated. The DC microgrid is connected to the external 60 Hz AC three-phase network. An efficient multi-bus topology is proposed for the microgrid and it is formed by various AC/DC buses to supply the loads and managing the resources. The main bus of system is a 470 V DC bus and it is connected to the external 440 V/60 Hz AC grid. The main DC bus supplies three LV, MV and HV DC buses with 100, 220, and 110–380 V, respectively. The HV DC bus produces a variable output DC voltage between 110 and 380 V in order to regulate the load power (i.e., motor speed). The MV DC bus is connected to 220 V/50 Hz AC single-phase loads. The connections between DC microgrid with AC loads and AC external gird are made by single-phase or three-phase inverters. The interface inverters between DC bus and AC loads are operated to control power, torque, speed, frequency and voltage of loads. The unbalanced AC loads are appropriately balanced by proper control of interface inverters. The resources and inverters are efficiently controlled to enable operation of residential building under both off-grid or grid-tied conditions. The coordination of fuel-cell, solar-cell and battery can supply a fixed 8 kW power to external grid and supply the internal loads under all outages and off-grid conditions. The simulations demonstrate that the proposed control realizes all the objectives including AC/DC load management, unbalanced load amendment, frequency adaptation, and off-grid operation. © 2022 Elsevier Ltd
Hemmati, R. ,
Hemmati, R. ,
Hemmati, R. ,
Nosratabadi, S.M. ,
Mehrjerdi, H. ,
Bornapour, S.M. Publication Date: 2022
Energy Sources, Part A: Recovery, Utilization and Environmental Effects (15567230) 44(1)pp. 632-649
This paper utilizes the thermal and wind energies in power to gas (P2G) process. The purpose of the proposed P2G system is to reduce the operating costs and environmental pollutions. The wind energy is used to produce Hydrogen (H2) via water electrolyzer. The Carbon dioxide (CO2) of thermal energies is also captured by Carbon Capture and Storage (CCS). The achieved H2 and CO2 are combined to make Methane (CH4) through Methanation reaction. The unit commitment denotes the optimal operation schedule of thermal generating units at each hour. The proposed model also determines the optimal size of wind energy. In the case of any event or outage, the wind energy recovery is studied by application of hybrid battery-capacitor storage system. The achieved CH4 from wind energy is sold to make profit. The wind speed volatility is included in the model and handled by stochastic programming. The proposed P2G achieves several purposes including optimal wind turbine sizing, uncertainty management, CO2 decrease and operating cost reduction. It is demonstrated that the Carbon tax can reduce the CO2 pollutions up to 8%. The high-cost and high-polluting generating systems like oil fired steam turbines are only used at on-peak hours like 17–21. These units produce about 6% of total energy but releases 11% of total CO2. The optimal capacity of wind generating system is obtained equal to 107 MW and the profit of process is estimated about 2.383 million $ in year. © 2022 Taylor & Francis Group, LLC.
Publication Date: 2022
International Journal of Energy Research (1099114X) 46(6)pp. 8061-8075
This paper presents a novel control scheme on AC/DC ring bus islanded microgrid under unbalanced and non-linear loads. The DC bus is integrated with the fuel cell, one wind turbine, and two batteries. The DC bus can be divided into two sub-sections, where the first zone is supported by the fuel cell and battery 1, and the second zone is installed with the wind turbine and battery 2. The AC bus is also able to be sectionalized into two sub-sections where the diesel generator and the unbalanced load are located on the first section and the non-linear load with one wind turbine are placed on the other section. The DC bus is connected to the AC bus through two parallel three-phase lines each one configured by three single-phase inverters. The proposed control scheme in the ringed and separated modes presents several contributions including balancing the unbalanced loads, compensating the harmonics of non-linear loads, improving the voltage stability and sag/swells, enabling partial operation under outages, and enhancing resilience. In the ring mode, wind turbine 1 and diesel generator inject balanced and linear P-Q powers to the system as 39 kW/6 kVAr and 7 kW/9 kVAr, respectively. In the separated mode, the P-Q powers of wind turbine 1 are 36 kW/9 kVAr and they are 15 kW/9 kVAr for diesel generators. In both modes, the unbalanced and non-linear powers are supplied by the DC bus. The results verify that the developed control strategy efficiently deals with harmonic components, unbalanced currents and voltage issues. © 2022 John Wiley & Sons Ltd.
Publication Date: 2022
Journal of Energy Storage (2352152X) 50
This paper designs a unified management framework in zero-energy building (ZEB) integrated with renewable resources, energy storage, AC/DC loads, and critical/non-critical loads. The developed model controls solar-cell and fuel-cell operation, battery charging-discharging, load energy, and voltage of buses. The faults, outages and cyber-attacks are detected, separated and dealt with. The AC loads with different voltage levels and frequencies are integrated and successfully supplied. The loads are considered as critical and non-critical and the system is forced to supply the critical loads under any circumstances. The fault detection units on both AC and DC buses are designed to control the AC and DC voltages under steady-state and fault conditions. The outage detection unit is also designed to compensate lack of disconnected resources. The cyber-attack detection unit is implemented to detect the attacks on solar-cell power, fuel-cell power, AC voltage and DC voltage. With the operation of control system, the DC bus voltage is stabilized on 100 V and under outage conditions, the solar-cell is supported by fuel-cell and the battery is operated as backup for fuel-cell. The fault conditions in AC and DC buses are improved by battery performance. Furthermore, a variety of individual and concurrent cyber-attacks are detected. The simulations validate that the proposed method conveniently realizes all the objectives, including feeding DC/AC loads, managing battery/ resources and identifying/dealing with outages/faults/attacks. © 2022 Elsevier Ltd
Publication Date: 2022
Energy Equipment And Systems (23831111) 10(1)pp. 1-11
This paper presents a new algorithm for validation (identification and correction) of measurement and parameter errors (branch parameters as well as unified power flow controller (UPFC) parameters), simultaneously. The algorithm is composed of three steps. First, in the step 1, state estimation (SE) is solved by the modified weighted least square (MWLS) and then, the normalized measurement residual and Lagrange multiplier vectors are computed. The errors in measurement and parameter are identified in the step 2. Finally, in the step 3, erroneous measurement and parameter values are corrected. The correction algorithm is based on a proposed approach without the using of augmented state vector (ASV). The IEEE-14 bus system and 230 kV East Azerbaijan network of Iran modified by incorporating UPFC are used as test systems. Simulation results demonstrate the effectiveness of the proposed method. Also, results indicate that the proposed method can validate the erroneous values with lower error percentage. © 2022, University of Tehran. All rights reserved.
Publication Date: 2022
International Journal of Electrical Power and Energy Systems (01420615) 135
This paper presents a novel control scheme in doubly-fed induction generators (DFIG) wind turbine for operation under time-varying unbalanced loads. The proposed control scheme is implemented on a DFIG connected to the external grid. Additional equipment such as battery, thyristor-controlled reactor (TCR) and thyristor-switched capacitor (TSC) are integrated to the DFIG. These devices are integrated to DC link, grid side and rotor side converters. The developed control scheme aims to achieve several purposes simultaneously including voltage compensation, damping fluctuations, regulating frequency, increasing resilience, and balancing the unbalanced time-varying loads. Each purpose is realized by designing a separated control loop on DFIG, battery and TCR-TSC. All the designated control loops are operated coordinately. The non-linear time-domain modelling and simulations are carried out in MATLAB software and demonstrate that the proposed multi-purpose control plan can optimally utilize set of DFIG/battery/TCR/TSC and achieve all the objectives efficiently. © 2021 Elsevier Ltd
Hemmati, R. ,
Hemmati, R. ,
Mehrjerdi, H. ,
Hemmati, R. ,
Mahdavi, S. ,
Shafie-khah, M. ,
Catalao, J.P.S. Publication Date: 2022
IEEE Transactions on Industrial Informatics (1551-3203) 18(7)pp. 4674-4687
The microgrid operation is addressed in this article based on a multicarrier energy hub. Natural gas, electricity, heating, cooling, hydrogen, carbon dioxide, and renewable energies are considered as the energy carriers. The designed microgrid optimizes and utilizes a wide range of resources at the same time including renewables, electrical storage, hybrid storage, heating-cooling storage, electric vehicles (EVs) charging station, power to gas unit, combined cooling-heating-power, and carbon capture-storage. The purpose is to reduce the environmental pollutions and operating costs. The resilience and flexibility of the energy hub is also improved. Vehicle to grid and fully-partial charge models are incorporated for EVs to improve the system resilience and supplying the critical loads following events. Different events are modeled to evaluate the system resilience. The model is expressed as a stochastic mixed integer linear programming problem. Both active and reactive powers are modeled. The microgrid is simulated under four different cases. The results show that the multitype energy storages reduce the annual cost of energy while the integrated charging station can decrease the load shedding. © 2005-2012 IEEE.
Publication Date: 2022
IET Generation, Transmission and Distribution (17518687) 16(7)pp. 1334-1348
This paper presents a control mechanism on high voltage direct current (HVDC) transmission line for frequency/voltage regulation, fault ride through (FRT) capability, and cyber-attack/fault detection. The network under study consists of two areas with different frequencies that are connected through one 300 km HVDC line. The proposed control system regulates the frequency in both areas by managing power through HVDC line. The converters on both sides of HVDC line are controlled to handle faults on the DC and AC sections as well as improving fault ride through capability. The control strategies are implemented and operated depending on fault/cyber-attack type and behaviour. In this respect, the control mechanism may change the firing angle of converters, switch their operating mode from rectifier to converter and vice-versa or even block the converters. The proposed paradigm successfully distinguishes between the cyber-attacks and faults. The simulations in MATLAB software validate that the proposed mechanism realizes all the objectives and the cyber-attacks are completely identified and separated from the faults. © 2021 The Authors. IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology
Publication Date: 2022
IEEE Systems Journal (19379234) 16(2)pp. 2639-2647
In this article, a comprehensive control scheme is designed on multimicrogrid system. The system is formed by several submicrogrids. In each submicrogrid, the dc and ac buses are linked via three single-phase converters. The hybrid wind/solar system based on Maximum power point tracking (MPPT) is utilized in the submicrogrids. The proposed control system balances the unbalanced loads, compensates the harmonics of nonlinear loads and supplies time-varying loads. The submicrogrids are designed to operate under both the islanded and grid-tied modes. In the islanded condition, the proposed model enables the submicrogrids to support each other for resilience improvement. Such model increases the load restoration following faults on both the dc and ac buses. The proposed model is tested on a typical multimicrogrid including five submicrogrids. The simulations are performed in MATLAB software. The results demonstrate that the developed scheme achieves all the purposes at the same time. © 2007-2012 IEEE.
Publication Date: 2022
IET Renewable Power Generation (17521416) 16(3)pp. 565-580
A resilient control system in the island microgrid including AC and DC buses is designed here. The DC bus is supported by fuel cell, solar cell and battery and the AC bus is equipped with diesel generator and wind turbine. The AC bus is sectionalized into three sub-buses that enables to continue operation when one section is not functioning. The connection between DC and AC buses is made by two parallel three-phase lines each line made by three single-phase inverters. The objectives are to eliminate the harmonics, the unbalanced load management, dealing with outage of resources and short circuits, providing backup strategies and supplying critical loads under all events. The simulations are performed by MATLAB/Simulink. It is demonstrated that the resilient control technique can achieve all the defined purposes at the same time. The harmonics are eliminated, the unbalanced load issues are dealt with and the microgrid has sufficient resilience against outages and faults. © 2021 The Authors. IET Renewable Power Generation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology
Hemmati, R. ,
Hemmati, R. ,
Panah, P.G. ,
Bornapour, S.M. ,
Hemmati, R. ,
Guerrero, J.M. Publication Date: 2021
Renewable and Sustainable Energy Reviews (1364-0321) 144
Today, the zero-emission transport system is a public will in megacities. A promising alternative among the countermeasures is to employ Battery Electric Buses (BEB) and Fuel-Cell Buses (FCB) at reasonable prices. This paper addresses Multi-product Charging Stations (MCS) in the selected bus terminals for refilling hydrogen and electricity. The core of MCS is constituted of a pair of Electrolyzer/Fuel Cell working back to back by Proton Exchange Membrane (PEM) technology. The innate flexibility in the operation of such a configuration enables for providing regulating services when the market price is soaring. The multi-criteria programming for the hourly schedule in different weather conditions is investigated using the Crow Search Algorithm. The objective is to enhance the daily profit of charging stations through the optimized multi-products/services selection. Uncertainty in wind speed, market price, and electric vehicles is considered in scenarios. The weightings are decided through the Analytic Hierarchy Process (AHP) and Criteria Importance through Inter-criteria Correlation (CRITIC) methods. The superiority of MC-CSA Stochastic Programming is showcased by simulations on a modified 33-bus IEEE distribution system using DK2 (east Denmark) data under subsidized and liberal markets. Regarding the daily profit outcomes, CRITIC was advantageous on windy days when the market prices vary with wind speed whilst AHP was preferred in low wind hours. The most lucrative operations are achievable when the products are fully accepted by regulating markets, BEBs, and FCBs on windy days. The results indicate that the additional remuneration on green hydrogen leaves a deeper impact rather than subsidies on electricity prices for EVs. © 2021
Publication Date: 2021
Journal of Energy Storage (2352152X) 36
A stochastic price-based planning model is proposed for a multi-energy microgrid (MEM) in this article. The MEM can supply the electricity, heating and cooling loads. The presented model can control the flexible demands and also can provide continuous control in the presence of smart and comprehensive programming of electricity, heating, ice, compressed air, and hydrogen energy storages. In the proposed procedure, all the energy carriers’ price is considered to be uncertain and the market prices are applied in the proposed modeling by some scenarios with appropriate probabilities. The features of the MEM parts like losses and amortization costs of electricity, heat and cool energy storages, also the operating area of the combined heat and power (CHP) units can fully be planned. The principle of convexity is considered related to the CHP unit operation area. The proposed formulation is applied on two days in the summer and winter seasons for a variety of studies including the storage effect, energy sales to network, charge and discharge of plug-in hybrid electric vehicles (PHEVs), and flexible devices planning. The outcomes represent that utilizing the proposed stochastic MEM plan and available demand planning with the proposed storage programming results in significant advantages for the power network and the consumer. One of the important outcomes is 6.6% and 50.9% cost saving for winter and summer days respectively, when the power is offered to the power distribution system. It is worth mentioning that the proposed plan can make the curve of demand optimally utilization from the demand response program and energy storage plan. © 2021 Elsevier Ltd
Hemmati, R. ,
Hemmati, R. ,
Nosratabadi, S.M. ,
Hemmati, R. ,
Bornapour, S.M. ,
Abdollahpour, M. Publication Date: 2021
Sustainable Energy Technologies and Assessments (2213-1388) 43
The energy supply concerns are increased with the increment of demand, environmental emission, and global warming. As an alternative to fossil fuels, the development of renewable energy technologies is one of the most important strategies. Thus, governments around the world have adopted policies to expand the share of clean energy with a view to the greenhouse gas (GHG) emissions reduction and many other policies. In this study, the economic evaluation and energy/exergy analysis of using renewable energy resources (wind, solar, and fuel cell) has been performed under three scenarios in Sirjan city, Iran. The studied scenarios are distinguished from each other due to the capacity to be installed, renewable energy sources type, and different work policies. Related to the photovoltaic (PV) and wind energy, different types of PV panels and wind turbines are studied, and the most favorable one is selected. Also, the best way is considered to install PV panels and fuel cells in this location based on different policies. According to this, it can be said that the economic aspects of the investigation are clarified and studied in renewable energy under the policies and scenarios for investors in this field. © 2020 Elsevier Ltd
Publication Date: 2021
International Journal of Energy Research (1099114X) 45(14)pp. 20384-20399
This paper presents a linear model for optimal operation of distributed generations (DGs) including renewable and nonrenewable DGs in the electrical grids. The accurate model of active-reactive losses is formed by two quadratic terms that are linearized by piecewise linear approximation of the quadratic curves. The DGs' technical/economic formulations are also presented based on the linear model. The proposed linear models are combined to implement linear optimal power flow (OPF) in the electrical grid integrated with hybrid diesel/wind/solar/battery. The model is associated with uncertainties and expressed as stochastic mixed integer linear programming. Both the active and reactive powers of the grid and resources are incorporated. The model optimizes the following design variables: sitting and sizing of energy storage systems and DGs, depth of discharge, energy of battery, operation pattern of battery, operation pattern of non-renewables units, and investment/operational costs. The proposed model is tested on 69-bus distribution grid. The simulation results show that the depth of discharge is optimized on 30% to 95%. Active and reactive losses achieved by the proposed model are 72% and 47% more accurate compared to the other existing models. The voltage profile is improved by about 8%. The network losses are reduced by 24%. The peak shaving is performed at hours 18 to 24. © 2021 John Wiley & Sons Ltd.
Hemmati, R. ,
Hemmati, R. ,
Hemmati, R. ,
Mehrjerdi, H. ,
Shafie-khah, M. ,
Siano, P. ,
Catalao, J.P.S. Publication Date: 2021
IEEE Transactions on Sustainable Energy (1949-3029) 12(1)pp. 705-714
An efficient unit commitment planning must consider frequency regulation capacity in the model. Such models are more complicated under a high penetration level of renewable energy because of renewable ramping and uncertainty. This paper addresses these issues in the unit commitment. The proposed model for unit commitment considers uncertainty and ramping of wind power, frequency regulation capacity, spinning reserve, demand response, and pumped-storage hydroelectricity. Two reserve capacities including primary frequency regulation and spinning reserve are designed to handle the intermittency and ramping of renewable energies. In order to optimize the costs, the pumped-storage hydroelectricity and demand response program are also included to deal with ramping and uncertainty. The numerical results specify that the arrangement of frequency regulation capacity, pumped-storage system and demand response can effectively tackle both the ramping and uncertainty. The system includes 10-generator with total power equal to 1070 MW and one wind generator with 300 MW power. The initial wind integration level is about 28%. It is verified that decreasing the frequency regulation capacity by 10% reduces wind integration level by 94%. The demand response and pumped-storage increase wind integration level by 10% and 16%; while both together increase wind integration by 25% compared to the initial level. The wind integration level without large wind ramping can be increased up to 200%. © 2010-2012 IEEE.
Publication Date: 2021
Power Systems (18604676) pp. 151-175
Nowadays, the resilience enhancement is one of the most important concerns in electric power networks. The division of the main microgrid into several sub-microgrids, i.e., microgrid formation (MF), is a resilient strategy for distribution systems against natural disasters and cyber-physical attacks. Such effective solution not only increases the resilience and load restoration but also reduces the costs. The extensive penetration of renewable resources in microgrids increases the issues about safe operation under faults. This chapter presents a resilient microgrid formation in the presence of solar, wind, and diesel Distributed generation (DG) for load restoration maximization. In order to carry out the microgrid formation, several candidate breakers and tie-line switches are considered, and their optimal on-off conditions are determined. Both the active and reactive powers are included in the model. The model is expressed as mixed-integer linear programming (MILP) and is simulated under three various cases including case 1, without formation strategy; case 2, formation strategy with line breaker switch; and case 3, formation strategy with both line and tie breaker switches. The numerical results are carried out based on IEEE 33-bus and 69-bus standard distribution networks. The results emphasize on the effectiveness of the developed formation strategy with both the breaker and tie line switches for load restoration and resilience enhancement. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Hemmati, R. ,
Hemmati, R. ,
Aljabery, A.A.M. ,
Mehrjerdi, H. ,
Mahdavi, S. ,
Hemmati, R. Publication Date: 2021
International Journal of Hydrogen Energy (03603199) 46(46)pp. 23795-23814
In this paper, the multi carrier energy (MCE) systems are reviewed from different point of views including mathematical models, integrated components and technologies, uncertainty management, planning objectives, environmental pollution, resilience, and robustness. The basic of MCE systems is formed by combination of cooling, heating and power (CCHP). The natural gas and electricity are the main inputs to MCE systems and the cooling, heating, and electricity are the common outputs. The regular energy converters in the MCE systems are combined heat and power (CHP), gas boiler, absorption-electrical chillers, power to gas (P2G) and fuel-cell. The generic energy storages are electrical, heating, cooling, hydrogen, carbon dioxide (CO2) and hydro systems. © 2021 Hydrogen Energy Publications LLC
Publication Date: 2021
International Journal of Energy Research (1099114X) 45(5)pp. 6985-7017
This article proposes a planning model for a multi-energy microgrid (MEM) that supplies the electricity, heating, and cooling loads. This controls flexible demands and provides continuous control in the presence of smart and comprehensive programming of electricity, heat, ice, compressed air, and hydrogen energy storage. The features of the MEM are considering the losses and amortization costs of electricity, heating and cooling energy storage, and the operating area of the combined heat and power (CHP) units in the planning procedure. Besides, the principle of convexity in the CHP unit operation area is attended. The proposed formulation is applicable in days of summer and winter seasons for a variety of planning studies. The outcomes represent that utilizing the proposed MEM planning results in significant advantages for the power network and the consumer. The cost savings are respectively obtained equal to 33% and 34% in the winter and summer seasons. The cost savings can be considered besides the investiture cost of MEM elements to specifying the MEM profits made during the designing step. Another valuable result is the cost-saving of PHEV smart charge about 1.38 times of PHEV smart discharge for summer and about 1.05 for winter. It also makes the curve of demand optimal utilization from the demand response program and energy storage plan. © 2020 John Wiley & Sons Ltd
Publication Date: 2021
Energy (0360-5442) 237
The purpose of this paper is to demonstrate the impacts of mobile battery and diesel DG in integrated electrical-heating networks for promoting the resilience, self-adequacy, load restoration, power quality as well as reducing the load shedding and operational cost. The case study is IEEE 33-bus electrical system with both the electrical and heating demands. Several buses of the grid are integrated with combined heat and power (CHP). The battery is moved between the buses hourly and the diesel DG is moved seasonally. The transfer time between origin and destination buses is considered in the given model. The electric network feeds three regions (i.e., three different loading patterns) including residential, industrial and agricultural areas where the major activity of the industrial loads is at night due to low energy price and the major activity of the agricultural loads is in the spring and summer. The outage of electricity and natural gas (NG) are two faults that are imposed on the network in order to evaluate the resilience and load restoration. The demand response program (DRP) is included in the model. Both the active and reactive powers are considered for battery, diesel DG and CHP. Several cases are simulated, studied and compared like fixed, mobile and mixed fixed-mobile locations for energy resources. The simulation results show that the proposed model reduces the total annual cost by 16.5% while the other costs such as purchased energy, NG and losses are reduced by 16.5%, 22.9% and 21.5%, respectively. The self-adequacy of network is increased by 2.5 h and the electrical-heating load restorations are increased by 36% and 38%, respectively. © 2021 Elsevier Ltd
Publication Date: 2021
Sustainable Cities and Society (2210-6707) 71
This paper presents a flexible model for microgrid formation in the integrated electricity-gas system by optimal sizing, siting and operation of combined heat and power (CHPs) in order to improve the system operation/resilience and reduce the operational/energy cost. The resilience is defined in terms of critical load restoration following events. The upstream grid blackout, CHP outage and power line outage are modeled as the events. All the power lines (32 lines of the grid) may be subject to outage. The events are applied on the system as single event as well as consecutive events. The system is designed to be able to handle all these events. Under the events, the grid is sectionalized into several microgrids. The created microgrids are allowed to change their structure under different single and multiple disruptions. The partial and full overlap between the microgrids is modeled and studied. The results demonstrate that the end-buses of the grid are the best locations for CHPs in order to achieve the defined objectives all together. The CHPs reduce the overall cost by 11.6 % and supply all critical loads under single and multiple events. © 2021 Elsevier Ltd
Publication Date: 2021
Electric Power Systems Research (03787796) 194
This paper presents an advanced control strategy for balancing the time-varying and unbalanced loads by using the fuel cell and battery under the grid-tied and off-grid operations. In the grid-tied operation, the fuel cell and the battery are coordinately controlled to balance the three-phase unbalanced active and reactive powers of the loads. In this case, the received three-phase active-reactive powers from the grid become completely balanced by the given strategy. In the off-grid, the diesel generator supplies the active-reactive powers of load and the unbalances are handled by coordinated operation of fuel cell and battery. As well, the voltage of off-grid system is improved by injecting adequate reactive power to the system through the fuel cell, battery and diesel generator. The dynamic stability of the system is evaluated under non-linear disturbances like grid outage and single-phase fault. The time-varying unbalanced active-reactive powers are balanced under both off-grid and grid-tied states by implementing the proposed model. The purpose of the proposed control system is to balance the unbalanced load from point of view of the upstream grid at all time periods. In order to realize such function in the model, the load is modeled by two terms including the balanced and unbalanced parts. The unbalanced share is supplied by the inverters (DC bus) and the balanced term of load is supplied by the grid. The designed system is resilient under the events like grid outage and short circuits. As well, the system properly regulates and controls the load variations and unbalances. © 2021
Hemmati, R. ,
Hemmati, R. ,
Mehrjerdi, H. ,
Hemmati, R. ,
Shafie-khah, M. ,
Catalao, J.P.S. Publication Date: 2021
IEEE Transactions on Industrial Informatics (1551-3203) 17(8)pp. 5474-5484
This article proposes a unified solution to address the energy issues in net-zero energy building (ZEB), as a new contribution to earlier studies. The multicarrier energy system, including hydro-wind-solar-hydrogen-methane-carbon dioxide-thermal energies is integrated and modeled in ZEB. The electrical sector is supplied by hydro-wind-solar, combined heat and power (CHP), and pumped hydro storage (PHS). The thermal sector is supplied by CHP, thermal boiler, and electric heating. The hydrogen storage system and Methanation process operate as the interface energy carriers between the electrical and thermal sectors. The carbon dioxide (CO2) of the ZEB is captured and fed into the Methanation process. The purpose is minimizing the released CO2 to the atmosphere while all the electrical-thermal load demands are successfully supplied considering events and disruptions. The model improves simultaneously the energy resilience and minimizes the environmental pollutions. The results demonstrate that the developed model reduces the CO2 pollution by about 33 451 kg per year. The model is a resilient energy system that can handle all failures of components. The model can efficiently handle 26% increment in the electrical loads and 110% increment in the thermal loads. © 2005-2012 IEEE.
Publication Date: 2020
Journal of Physical Chemistry A (15205215) 124(45)pp. 9436-9450
Chiral discrimination, the ability of a chiral molecule to exhibit different weak intermolecular interactions than its mirror image, is investigated for dimers of oxiranemethanol (glycidol). In this regard, high-level ab initio calculations were performed to study the chiral recognition effects in the homochiral and heterochiral dimers of glycidol. Fourteen dimer structures, seven homochiral and seven heterochiral, were studied: they all feature two intermolecular O-H···O hydrogen bonds. These structures have been determined with the second-order Møller-Plesset perturbation theory (MP2) using the aug-cc-pVTZ basis set and verified to pertain to actual local minima. The benchmark interaction energy values were computed using MP2 extrapolated from the aug-cc-pVQZ and aug-cc-pV5Z bases with a higher-level correction from a coupled-cluster calculation in the aug-cc-pVTZ basis. The global minimum structure is a homochiral one, with the two hydrogen bonds forming a part of a ring with eight heavy atoms. A similar heterochiral structure has a binding energy smaller by about 0.6 kcal/mol. The largest diastereomeric energy difference is about 1.0 kcal/mol. Further insight into the origins of chiral discrimination was provided by symmetry-adapted perturbation theory (SAPT) and a functional-group SAPT (F-SAPT) difference analysis to investigate the direct and indirect effects of two -H/-CH2OH substitutions leading from an achiral ethylene oxide dimer to the chiral glycidol dimer. Last but not least, harmonic frequency shifts relative to a noninteracting glycidol molecule were calculated and analyzed for all conformations to get insight into the origins of chiral discrimination. It is found that the largest frequency shifts are related to the effect of hydrogen bonding on the O-H stretch mode, the stability of the ring involving both hydrogen bonds, and the transition between two nonequivalent minima of the glycidol molecule. © 2020 American Chemical Society.
Publication Date: 2020
Renewable Energy (0960-1481) 146pp. 568-579
The home energy management is an efficient tool to manage energy in the buildings that organizes different technologies and mathematical techniques to minimize energy cost. Home energy management often utilizes renewable energy resources to supply load demand in the building. Current home energy management systems utilize one or several of the available hardware-software capacity resources to deal with energy consumption in the buildings. However, a comprehensive model including various hardware and software capacity resources may increase the flexibility of the model. In this regard, this paper studies an efficient paradigm for home energy management in the building connected to electric grid. The proposed model forms an energy hub including the hardware resources (i.e., vehicle-to-home, wind turbine, and diesel generator) and software tools (i.e., demand response program). All the capacity resources and grid power are optimally adjusted to minimize the daily operational cost of the building as well as improvement of resiliency and self-healing. Wind energy and load uncertainty are modeled through stochastic programming. The seasonal pattern is considered for loads, prices, and wind energy. Simulation results demonstrate that operating all capacity resources minimizes the daily operational cost. When the wind energy, demand response program, vehicle-to-home, and diesel generator are not utilized, the cost is increased by 900, 230, 84, and 322%, respectively. It is also confirmed that the building not only can operate when one of the components is not connected, but also it is able to supply the demand under off-grid operation. © 2019 Elsevier Ltd
Publication Date: 2020
Energy (0360-5442) 192
An optimal energy management is addressed in the residential building. The residential building is equipped with renewable energies including wind turbines and solar panels. The uncertainty of renewable energies is modeled by stochastic programming. The demand response program is simultaneously adopted to handle such uncertainty and reducing the energy cost. In this respect, four different loads are modeled in the building including interruptible, constant energy, constant power, and uninterruptible loads. The aforementioned loads are properly adjusted and dispatched for minimizing the energy cost as well as to deal with renewable energy intermittency. The bidirectional operation is modeled for the building and it can send energy to the grid or receive it from the upstream network. The results verify that the introduced model can efficiently harvest all possible energy of the wind-solar system, handle the uncertainty, minimize the cost, and operate as off-grid. All of these purposes are achieved by optimal dispatching and adjusting of the loads through the proposed demand response program. © 2019 Elsevier Ltd
Publication Date: 2020
pp. 249-268
This chapter presents a framework to demonstrate the impacts of energy storage systems (ESSs) on transmission expansion planning (TEP). In order to integrate the ESSs into TEP, a typical test network, i.e., IEEE 24-Bus RTS, is adopted as case study, and TEP is carried out on this network. The TEP is integrated with ESSs and the impacts of ESSs are investigated. The optimal sizing, siting, and charging-discharging regime of the ESSs are determined to achieve the best and optimal operation. The TEP including ESSs is modeled as mixed integer linear programming and solved by means of GAMS/CPLEX. The objective function is regarded as the investment cost on new lines and new ESSs. The constraints are included as security constraints of the network as well as the operational constraints of the ESSs. The planning horizon is considered as 6 years, and dynamic TEP is carried out to find the best location, capacity, time, and number of new lines. The simulation results demonstrate that the TEP without ESSs installs more lines to handle load growth, but the TEP with ESSs installs less lines and uses ESSs to supply peak demand. The ESSs properly shift energy over the day hours and shave the peak load. As a result, the congestion in the lines is relieved and the network requirement for new lines is deferred. The ESSs can efficiently defer the investment on new lines and improve the congestion in the network lines. © Springer Nature Switzerland AG 2021.
Publication Date: 2020
Renewable Energy (0960-1481) 154pp. 1180-1187
This paper brings together the benefits of hydrogen and battery storage devices in the electrical network integrated with solar energy. The introduced hybrid storage system is utilized to achieve two purposes including uncertainty leveling and energy arbitrage. The volatility of solar energy and electrical-thermal loads is developed by Normal distribution. The hydrogen storage system is designed to smooth such uncertainty and storing the electrical energy in hydrogen form. Therefore, the hydrogen storage levels the uncertainties associated with solar power and loads. The battery is utilized to shift energy from pricey hours to the inexpensive time intervals and minimizing energy cost in network. The optimization programming finds optimal setting and charging-discharging pattern for both storage technologies. The seasonal profile is considered for electrical-thermal loads and solar energy. It is verified that the given hybrid storage scheme saves the cost by 117000 $/year and the solar system decreases the cost by 28%. © 2020 Elsevier Ltd
Publication Date: 2020
Journal of Energy Storage (2352152X) 30
The load growth in the distribution grids is often handled by distribution network expansion planning. Significant part of such long-term expansion plan is required to supply on-peak load demand. The on-peak load demand may be supplied by supplementary technologies to reduce or defer network expansion. The vehicle to grid (V2G) is an efficient technology to cope with such situation. This paper presents distribution network expansion plan including electric vehicle charging station and solar panels. The V2G technology is modeled in the charging station operation. The purpose is to minimize the network expansion cost by smart V2G operation subject to solar energy uncertainty. The model is expressed in the form of optimization programming and minimize the expansion cost. The model optimizes the operation pattern of electric vehicles while considers all technical constraints. The outputs validate that the V2G operation in the charging station reduces the expansion cost by 450%. The developed model successfully shaves the peak load demand and deals with solar power fluctuations. © 2020 Elsevier Ltd
Publication Date: 2020
Studies in Higher Education (03075079) 45(1)pp. 187-208
An academic learning environment has a significant role in shaping students’ learning experience, scholarly identity construction, and socialization into academic culture. The aim of the present study was to understand the experiences of PhD students from their learning environment and the challenges and problems they may face. This case study was conducted within the framework of a qualitative approach by using grounded theory. Data were collected by semi-structured interviews with thirty-one PhD student and nine faculty members from one of the public and comprehensive universities in Iran. The study provides insights into doctoral education by shedding light on the challenges and struggles that students experience in their journey and learning environment. The results indicated that in spite of the practical necessities of life and the serious challenges in the learning environment, for PhD students, having a student identity and being a student still valuable. Thus they tried to deal with this situation with different strategies. Each of these strategies had different implications for their future trajectories and the other hand for the future of the higher system. Implications for policy, practice, and further research are discussed. © 2019, © 2019 Society for Research into Higher Education.
Hemmati, R. ,
Hemmati, R. ,
Bornapour, S.M. ,
Hemmati, R. ,
Pourbehzadi, M. ,
Dastranj, A. ,
Niknam, T. Publication Date: 2020
Energy Conversion and Management (0196-8904) 206
The ever-growing augmentation of Renewable Energy Sources (RES) and Combined Heat and Power (CHP) units in microgrids (MG) exacerbates schedule management requirements in such systems. In this paper, a modified hybrid Bird Mating Optimization Differential Evolution (BMO-DE) algorithm is developed to address the mixed integer nonlinear programming problem of MG units’ probabilistic optimal planning. The proposed MG structure is consisted of MCFC-CHP, Wind Turbines (WT) and Photovoltaics (PV). The presented stochastic model schedules MG units coordinately, while the strategy of MCFC-CHP hydrogen storage is taken into account. The proposed solution models the uncertain parameters of electricity price, wind speed and sun irradiation using the 2m + 1 Point Estimate Method (PEM). The modeling of uncertain parameters results in more accurate planning and operation of the entire system. The proposed solution is applied on a 33-bus distribution network. In this manner, the total power loss decreased to 358.5 kW and the total operation cost is 3.1349 × 104$, which shows 18% decrease compared to MINLP method and 25% decrease compared to GA-PSCAD method of the total operation cost using the BMO-DE method. The results also justified the usage of CHPs while supplying thermal loads due to increased efficiency and profit. © 2020
Publication Date: 2020
Journal of Modern Power Systems and Clean Energy (21965420) 8(5)pp. 971-980
Battery energy storage system (BESS) has already been studied to deal with uncertain parameters of the electrical systems such as loads and renewable energies. However, the BESS have not been properly studied under unbalanced operation of power grids. This paper aims to study the modelling and operation of BESS under unbalanced-uncertain conditions in the power grids. The proposed model manages the BESS to optimize energy cost, deal with load uncertainties, and settle the unbalanced loading at the same time. The three-phase unbalanced-uncertain loads are modelled and the BESSs are utilized to produce separate charging/discharging pattern on each phase to remove the unbalanced condition. The IEEE 69-bus grid is considered as case study. The load uncertainty is developed by Gaussian probability function and the stochastic programming is adopted to tackle the uncertainties. The model is formulated as mixed-integer linear programming and solved by GAMS/ CPLEX. The results demonstrate that the model is able to deal with the unbalanced-uncertain conditions at the same time. The model also minimizes the operation cost and satisfies all security constraints of power grid. © 2020, Springer. All rights reserved.
Publication Date: 2020
Sustainable Energy Technologies and Assessments (2213-1388) 37
This paper designs optimal charging facility and capacity for electric vehicle charging station. The charging facility is modeled containing fast, intermediate, and slow speed chargers. The nominal powers of these chargers are determined. The charging station is linked to the utility grid and it is supplied by wind energy and the energy storage devices. The optimal sizing and operation of storage system are optimized. The electrical grid is strengthened by line reinforcement. The uncertainty of wind power is included and dealt by stochastic programming. The model is expressed as stochastic mixed integer linear programming and solved by GAMS toolbox. The results demonstrate that the rated powers of quick, intermediate, and slow speed chargers are optimized on 116, 84, and 52 kW, respectively. The power of quick charger is 27% more than the intermediate one and the intermediate charger needs about 38% larger power facility compared to the slow speed system. The storage system is designed with rated power equal to 133 kW and it can discharge 85% of its energy during one hour. The lines are reinforced by 183% to supply the energy demand of the charging station. The energy, network reinforcement, and charging facility cover about 70%, 15%, and 12% of total cost. The network without storage system needs about 2% more reinforcement. Reduction of line reinforcement by 30% increases the battery power about 4 times. © 2019 Elsevier Ltd
Publication Date: 2020
Sustainable Energy Technologies and Assessments (2213-1388) 39
With respect to the recent developments of hydrogen storage system (HSS), it is relevant to model these storage units in the network expansion planning. Also, most of the available expansion planning tools consider constant locations and sizing for renewable resources and only study the impacts of renewables on the model. It seems that considering variable location and capacity for renewable energies and finding their optimal levels may result in more flexible model. With regard to these issues, this paper presents distribution network expansion planning incorporating wind power and hydrogen storage. The optimal site and size of wind and hydrogen systems are denoted. The stochastic optimization programming is addressed to minimize the plan budgets. The purpose is to defer the investment and operating budgets. The uncertainty modeling is developed to handle the load-wind errors. The achievements demonstrate that the model finds optimal location, sizing, operation pattern, and setting for wind turbines and HSSs while the planning cost is deferred and minimized. © 2020 Elsevier Ltd
Publication Date: 2019
COMPARATIVE SOCIOLOGY (15691322) 18(5-6)pp. 791-821
Efficiency and equality are both important goals and values in higher education, and their concurrency (balance) has been one of the main concerns of higher education scholars and policy makers over the past decades. The aim of the present study is to discover the causal mechanism and contextual factors that are likely to result in concurrency of equality and efficiency in higher education. To this end, the combination of two explanatory theories of equality and efficiency were used. The theory of equality focused on three dimensions of equal opportunities, modernization, and cultural differences. Likewise, to explain efficiency, Chalabi's three-level causal model of sustainable production of science was used. Methodologically, a multiple case study method was adopted, and the cases under study (nine countries) were selected based on purposive sampling. The findings showed that for the concurrency of equality and efficiency in higher education, a set of conditions must be present in the configurational and combinational causality. The preconditions for this concurrency is the presence of some social conditions such as productive economy, the rule of law, inter-societies competitiveness, social cohesion, democracy, universalism, egalitarianism (at macro level), meritocracy, academic autonomy, and organizational competitiveness (at the meso level) and the absence of some other conditions including fatalism (at the macro level).
Publication Date: 2019
International Journal of Learning and Intellectual Capital (14794861) 16(3)pp. 274-296
This paper represents an elaborative framework of protean and boundary-crossing careers path which revealed along discovering basic categories for a joint perspective around tensions in talent literature. With applying Glaserian approach of Grounded Theory, semi-structured interviews were conducted concerning elites' attitudes, orientations, and behaviours towards protean and boundary-crossing working activities and the infrastructures of their organisational operationalisation. Qualitative analysis unfolds an interactive family of theoretical coding around job transition as a basic social structural process (BSSP). The findings determines how physical movements act as a medium elites employ to prepare a context for their protean movements aligning with psychological ones which constitute nesting paths evolving around role transitions due to job improvements. These inferred employability movements posits as elites' proactive adaptability behaviours for securing employability by acquiring movement capital through life-designing trajectories activities. Finally, operational solutions are proposed to cultivate talent phenomena by facilitating elites' employability behaviours across the organisation. © 2019 Inderscience Enterprises Ltd.
Publication Date: 2019
International Transactions on Electrical Energy Systems (20507038) 29(4)
This paper presents coordinated generation and transmission expansion planning (G&TEP) considering environmental pollutions and reliability in the presence of wind-generating units and Flexible Alternating Current Transmission System (FACTS) devices. The proposed problem is expressed as a constrained optimization programming that aims at maximizing profit of generation and transmission owners as an objective function. The constraints of the problem include security constraints of alternating current (AC) power flow, wind unit operation, FACTS device operation, and reliability equations. Moreover, the produced power by wind turbines is modeled by probability function, and stochastic programming is adopted to cope with such uncertainty. The planning also calculates the expected energy not supplied (EENS) as a part of the objective function (ie, planning cost). The problem is expressed by means of mixed-integer nonlinear programming (MINLP) and then linearized as a mixed-integer linear programming (MILP) to confirm the optimal solution. The linear model is implemented in the Generalized Algebraic Modeling System (GAMS) software. Simulation results are carried out on a large-scale electrical network, emphasizing the capability and efficiency of the introduced planning to expand the network under uncertainty. Also, the impacts of pollution, FACTS devices, and reliability on planning are demonstrated by numerous analyses and discussions, and it is confirmed that considering such items improves planning. © 2018 John Wiley & Sons, Ltd.
Publication Date: 2019
Journal of Physical Chemistry A (15205215) 123(40)pp. 8607-8618
We elucidate the subtle energetic effects that give rise to chiral recognition in the propylene oxide dimer. Specifically, we investigate 6 homochiral (RRx) and 6 heterochiral (RSx) structures of this complex, with the RRn-RSn pair sharing the same pattern of weak O-• • H-C hydrogen bonds but subtly differing in energy due to chiral effects. The interaction energies for the 12 structures are computed at various levels of electronic structure theory and basis set up to the complete basis set limit of the coupled-cluster approach with single, double, and perturbative triple excitations (CCSD(T)). These benchmark interaction energies are compared to the results of various approximate approaches, both density functional theory-based and wavefunct, ion-based. We find that while the RRn-RSn diastereomeric energy differences exhibit a great deal of error cancellation between the individual interaction energies, most approximate methods have a hard time even reproducing the correct signs of these differences consistently. The origins of the RRn-RSn differences are elucidated by several symmetry-adapted perturbation theory (SAPT) analyses ranging from ordinary intermolecular SAPT to a functional-group SAPT (F-SAPT) decomposition of direct and indirect H-)-CH3 substitution effects leading from achiral ethylene oxide complexes to chiral propylene oxide ones. It is shown that the largest diastereomeric energy differences are correlated to the variations in the electrostatic and dispersion SAPT contributions. Finally, the effect of chiral interactions on the vibrational frequencies of a propylene oxide molecule is investigated, showing that the interaction results in largest frequency shifts, splittings, and chiral discrimination effects in the lowest, torsional vibrational mode of the noninteracting monomer. © 2019 American Chemical Society. All rights reserved.
Publication Date: 2019
Journal of Energy Storage (2352152X) 26
Electric vehicle charging station is connected to the distribution network and it is equipped with battery energy storage system, diesel generator, and solar panels. The three-level charging facility including fast, medium, and slow speed chargers is incorporated and optimally designed. The proposed model optimizes the rated power of charging facilities, power and capacity of battery energy storage system, hourly operation of diesel generator, and hourly operation of battery energy storage system. The capacity of charging station (i.e., number of parking slots) and level of network reinforcement are modeled and optimized. The uncertainties of the parameters are also involved. The results demonstrate that the proposed model successfully utilizes all available options to design electric vehicle charging station. © 2019 Elsevier Ltd
Hemmati, R. ,
Hemmati, R. ,
Hemmati, R. ,
Mehrjerdi, H. ,
Iqbal, A. ,
Rakhshani, E. Publication Date: 2019
This paper addresses both the experimental and simulation studies on the application of overcurrent protective relay. The industrial overcurrent relays often have three individual settings. In this paper, the relay operating characteristics are set on normal inverse and very inverse curves. These curves operate as backup of each other. The third setting is also set on the instantaneous definite minimum time. The designated protection scheme protects the system with the least operating time. © 2019 IEEE.
Publication Date: 2019
Journal of Renewable and Sustainable Energy (19417012) 11(2)
In this paper, mobile distributed generations (DGs) and battery energy storage systems (BESSs) are modeled and integrated into the network. The optimal locations of DGs and BESSs are determined for each season over the year, and the installed DG-energy storage system (ESS) may be transferred to new buses at each season. The methodology is simulated on a radial electrical distribution network, and the location, size, and hourly operation of DGs and ESSs are optimized. DC power flow is adopted to model the power flow in the grid. In the DC power flow, the active power losses in the lines and reactive power of the loads are not included. Since the network is radial and the modeling is lossless, it is expected that the DGs and BESSs cannot present their positive abilities efficiently. Four cases are simulated including case 1: network without BESSs and DGs; case 2: fixed operation pattern and location for BESSs and DGs under all seasons; case 3: variable operation pattern and fixed location for BESSs and DGs under all seasons; and case 4: variable operation pattern and location for BESSs and DGs under all seasons. The planning installs one 0.0470 p.u. DG and one 0.0202 p.u. BESS on the network, resulting in 0.5 Million $/year reduction in the costs. However, the results verify that changing locations of the DGs and BESSs cannot have significant impacts on the results. This point confirms that the application of DC power flow in radial distribution networks is not suitable and cannot develop all advantages of BESSs and DGs. © 2019 Author(s).
Publication Date: 2019
Journal of Cleaner Production (0959-6526) 234pp. 810-821
Thanks to the unique features, deployment of battery energy storage systems in distribution systems is ever-increased. Therefore, new models are needed to capture the real-life characteristics. Beside active power, the battery energy storage system can exchange reactive power with the grid due to the inverter-based connection. Although some previous works have considered this issue, a detailed linear model suitable for the realistic large scale distribution systems is not addressed adequately. In this context, this paper proposes a mixed integer linear programming model for optimal battery energy storage system operation in distribution networks. The proposed model considers various parts of the battery energy storage system including battery pack, inverter, and transformer in addition to linear modeling of the reactive power and apparent power flow limit. Moreover, a linear power flow model is used to calculate voltage magnitudes and power losses with high accuracy. The proposed model is applied to the IEEE 33-bus test case and the results prove the accuracy and efficiency of the proposed model. The results demonstrate that considering reactive capability of the batteries offers new benefits including voltage profile improvement, decreasing reactive power flow in the network, reducing network losses, and releasing network and substation capacity. © 2019 Elsevier Ltd
Hemmati, R. ,
Hemmati, R. ,
Hemmati, R. ,
Mehrjerdi, H. ,
Al-emadi, N.A. ,
Rakhshani, E. Publication Date: 2019
This paper utilizes the electric vehicles (EVs) connected to both the building and grid at the same time. In the building, the vehicle-to-home (V2H) operation is modeled. In the gird, the vehicle-to-grid (V2G) operation is studied. The EV s are modeled in the building connected to the electrical grid. The EV s are able to send energy to both grid and building. The building is also equipped with solar panels and electrical loads. Uncertainty of solar energy and loads are incorporated by stochastic programming. The optimization is implemented in GAMS to find the minimum daily cost. The optimal charging-discharging regime is denoted for EV s. The results illustrate that V2H - V2G operation can efficiently minimize the energy cost under solar-load volatility. © 2019 IEEE.
Publication Date: 2019
Simulation Modelling Practice and Theory (1569190X) 97
Industrial overcurrent relays such as MiCOM P123 (overcurrent and earth fault protection relay) often offer three individual options for separate settings. These settings can be separately tuned and such ability can be utilized to apply the relay as backup of itself. In this system, not only the other relays operate as backup of the current relay, but also settings of the relay operate as backup for themselves. In order to verifying such ability, this paper tunes the settings of MiCOM P123 overcurrent relay as backup of each other to make the non-standard characteristic for overcurrent relay. In the developed model, the first setting of the relay is set on normal inverse (NI) curve, the second setting on very inverse (VI) curve, and the third setting on the instantaneous definite minimum tome (DMT) type. The operating area of the relay is divided into two areas. In the first area, the VI curve operates as backup of NI and in the second area, the NI curve operates as backup of VI. The third setting also operates as backup of both the first and second settings. The system is implemented in the protection laboratory as well as it is simulated using MATLAB software. The simulation outputs are verified and confirmed by the experimental tests. The results confirm that the proposed model has two advantages. The first achievement is to reduce the tripping time by about 5%. And he second advantage is to increase the protection level when one of the settings fails to operate. © 2019 Elsevier B.V.
Publication Date: 2019
Simulation Modelling Practice and Theory (1569190X) 94pp. 1-13
This paper deals with energy storage system (ESS) in active distribution networks. The purpose is to install ESSs on the grid to minimize network losses. The problem is expressed as an optimization programming to minimize annualized cost of losses and annualized investment cost of ESSs at the same time. The constraints of the programming are given as security constraints of the network and ESS operational constraints. The network is also equipped with distributed energy resource (DER) and its uncertainty is modeled and dealt by means of stochastic programming. Different DERs including diesel, wind, and solar resources are modeled and studied. The proposed nonlinear mixed integer stochastic programming is solved by particle swarm optimization (PSO). AC power flow is adopted to consider both active and reactive powers in the model. The ESSs are modeled including both active and reactive powers. The introduced planning finds optimal location, capacity, and power for ESSs. Furthermore, the charging-discharging regime for active power of ESSs and injection-absorption pattern for reactive power of ESSs are determined. The introduced methodology is successfully simulated on a typical distribution network. The simulation results confirm that the planned strategy properly installs ESSs on the grid and minimizes network losses. The results demonstrate that the ESSs decrease network losses about 22%. Finally, considering reactive power for ESSs results in about 24% cost reduction. © 2019
Publication Date: 2019
IET Renewable Power Generation (17521416) 13(12)pp. 2232-2239
This study forms and optimises the renewable energy hub to supply load demand in the autonomous building disconnected from electrical grid (i.e. net-zero energy building). The proposed energy hub is made of hybrid wind-solar-hydro generation systems and it is also strengthened by pumped-storage hydroelectricity and hydrogen storage systems. The hydro system includes two water reservoirs in cascade connection and one pumped-storage hydroelectricity. The introduced optimisation programming designs proper capacity for cascade water reservoirs and energy storage system as well as optimises their operation. The uncertainties of parameters are included to make the stochastic programming. It is demonstrated that increasing the flow-in of reservoir 1 by 25% decreases the planning cost by ∼2.5% and decreasing the flow-in of reservoir 2 by 50% increases the planning cost by ∼16%. When the hydro system does not operate, the wind power must be increased to 10 kW in order to supply the load. When the wind and solar powers are not integrated, the hydro energy must be increased by 50%. © The Institution of Engineering and Technology 2019
Publication Date: 2019
IEEE Transactions on Industrial Electronics (0278-0046) 66(3)pp. 2174-2184
In conventional hybrid energy storage systems, two storage units complement each other. One low-capacity and fast-response unit as a power supplier, and one high-capacity and low-response unit as an energy supplier. The power supplier mitigates fast fluctuations in generation or demand by transferring energy over seconds or minutes, and the energy supplier transfers energy over hours for managing energy. According to this concept, this paper presents a new model of hybrid energy storage systems, where three energy suppliers are considered as a three-level hybrid energy storage system. Energy storage at level 1 shifts energy from off-peak (or low-cost) hours to the on-peak (or high-cost) hours during one day, the storage unit at level 2 transfers energy from off-peak (or low-cost) days to the on-peak (or high-cost) days for the period of one week, and level 3 transfers energy from off-peak seasons to the on-peak seasons through one year. The proposed planning results in a large-scale optimization programming that optimizes large numbers of design variables at the same time. In order to increase the flexibility of the planning, the initial energy of the storage units is also modeled as a design variable and optimized. The uncertainty of loads is modeled and a stochastic planning is carried out to solve the problem. The introduced three-level hybrid energy storage planning is simulated on two test systems, and the results demonstrate that the proposed planning can reduce the planning cost by about 1.8%. © 2018 IEEE.
Hemmati, R. ,
Hemmati, R. ,
Mehrjerdi, H. ,
Bornapour, S.M. ,
Hemmati, R. ,
Ghiasi, S.M.S. Publication Date: 2019
Energy (0360-5442) 168pp. 919-930
This paper presents a unified model for home energy management. The proposed model optimizes the cogeneration of wind, solar, and battery storage units. The introduced tool considers electric and hydrogen vehicles and provides optimal charging pattern for them. The water electrolyze is also modeled to produced breathable oxygen and hydrogen from water. As well, the load modeling options such as adjustable and interruptible loads are included in the planning in order to increase the flexibility and adeptness of the proposed energy management system. The uncertainties of wind and solar powers are included resulting in a stochastic programming. The proposed stochastic optimization problem is mathematically expressed as a mixed integer linear programming and solved by GAMS software. The problem minimizes cost of energy consumption in the building subject to the operational constraints of wind unit, solar panel, battery system, loads, electric-hydrogen vehicles, and electricity grid. The proposed test building is studied under two states including connected to the electrical grid and disconnected from the gird (i.e., islanding mode or NetZero energy home). The impacts of the proposed planning on the environmental pollution are also considered and simulated. The results verify that the proposed strategy can successfully utilize wind-solar-battery units to supply the load, charging the electric-hydrogen vehicles, and reduction of the pollution. As well, it is demonstrated that the operation of the home under islanding mode is completely different from the connected state. © 2018 Elsevier Ltd
Hemmati, R. ,
Hemmati, R. ,
Hemmati, R. ,
Azizi, N. ,
Shafie-khah, M. ,
Catalao, J.P.S. Publication Date: 2018
International Journal of Electrical Power and Energy Systems (01420615) 102pp. 1-10
This paper simulates an islanding network including wind turbine, battery energy storage systems (BESS), and load. The purpose is to control voltage and frequency of the load following wind speed variations by proper control of BESS. A decentralized control scheme including two control loops is designed on BESS. One control loop is implemented for voltage regulation and the other loop is designed for frequency control. Both loops are equipped with PI (Proportional–Integral) type controllers as internal controllers. Furthermore, both loops are equipped with supplementary stabilizers as external controllers. The internal controllers regulate frequency and voltage and the external stabilizers enhance stability. This paper optimally tunes all the parameters of internal controllers and external stabilizers at the same time. The problem for tuning a large number of the design variables is mathematically expressed as a mixed integer nonlinear optimization programming and solved by modified-adaptive PSO technique. The proposed methodology is simulated on a typical standalone network including wind turbine, BESS, and load. The accurate model of BESS and wind turbine is incorporated to cope with real conditions. Moreover, in order to demonstrate the real-world results, non-linear time domain simulations are carried out in MATLAB software. The results verify that the proposed control scheme can efficiently utilize BESS to control voltage, regulate frequency, and damp out oscillations under wind and load variations. © 2018 Elsevier Ltd
Publication Date: 2018
Journal of Renewable and Sustainable Energy (19417012) 10
This paper presents an advanced methodology to install energy storage systems under network uncertainties. The uncertainties are related to solar and wind powers. The proposed problem minimizes the operational cost of generating units by coordinated energy storage planning and generation rescheduling. The problem is expressed as a stochastic mixed integer linear programming and solved using GAMS software. The simulations are carried out on an IEEE 24-bus test case including one wind unit and one solar power plant. The introduced stochastic problem is compared with the deterministic one in order to demonstrate its significance and effectiveness. © 2018 Author(s).
Publication Date: 2018
Journal of Renewable and Sustainable Energy (19417012) 10(1)
This paper optimizes cogeneration of a hydro-Thermal-wind-solar system. In the proposed hybrid system, the energy storage systems are also incorporated to smooth out the fluctuations of renewable energies. The uncertainties of wind and solar powers are included, and stochastic programming is adopted to deal with the uncertainties. The hydro system comprises two cascade reservoirs. The optimal scheduling of both reservoirs is presented, and the electricity generated by each reservoir is optimized. The optimal scheduling of thermal unit is also determined. The optimal location, capacity, power, and charging-discharging pattern are determined for battery energy storage systems. The simulations are carried out using an IEEE 69-bus distribution network, and the model is implemented in GAMS software and solved as a mixed integer linear programming. The objective of the problem is to minimize energy cost in the network. The results demonstrate that the proposed stochastic model can successfully optimize cogeneration of hydro-Thermal-wind-solar system. The planning moreover optimally utilizes energy storage systems for damping the fluctuations of renewable energies and minimizing energy cost. © 2018 Author(s).
Publication Date: 2018
Journal of Cleaner Production (0959-6526) 185pp. 680-693
Battery energy storage systems (ESS) are the proper technologies to reduce operational cost of electrical networks as well as smoothing wind uncertainty. However, some characteristics of the battery energy storage systems have not been accurately analyzed such as coordination of initial energy and depth of discharge (DOD) and determining their optimal levels. Moreover, the impacts of these parameters on the planning and operational costs have not been appropriately addressed. In order to address such shortcomings, current paper presents a unified stochastic planning on battery energy storage systems in electric power systems including wind power plants. The proposed planning considers following items as objective function and optimizes them: cost of energy in the network (i.e., generators fuel cost) and investment-operational costs and lifetime of battery energy storage systems. The design variable are also classified in three categories as (i) optimal generation scheduling (i.e., determining optimal generation pattern for all generators at each hour over the day), (ii) optimal energy storage planning (i.e., denoting capacity of batteries, nominal power of interfacing converters, and location of battery energy storage units), and (iii) optimal energy storage scheduling (i.e., determining optimal charging-discharging pattern, initial energy, depth-of-discharge, lifetime, and life-cycle for energy storage units). All of these items are carried out through stochastic modeling under wind power uncertainties. The paper presents a proper coordination between design variables such as initial energy and depth-of-discharge in order to minimize the network operational cost, maximizing lifetime of battery energy storage system, and smoothing wind uncertainty. The efficiency of the introduced methodology is demonstrated through various analyses and comparative studies. © 2018 Elsevier Ltd
Publication Date: 2018
Energy (0360-5442) 152pp. 759-769
This paper aims at utilizing energy storage systems for two purposes at the same time including smoothing the uncertainties of wind-solar units as well as reduction of network losses. In order to achieve these objectives, IEEE 24-bus test system is considered as case study. This network is integrated with wind turbine and solar system. The output powers of wind and solar units are modeled by probability distribution function. The energy storage systems are installed on the network to smooth out the uncertainty as well as loss reduction. The network is modeled by AC power flow including both active-reactive power. The problem of finding location, power, capacity, and charging-discharging pattern of energy storage systems is expressed as nonlinear mixed integer optimization stochastic programming. The uncertainties are handled by Monte-Carlo simulation and the proposed stochastic programming is solved by modified particle swarm optimization algorithm. The results demonstrate that the proposed stochastic programming can efficiently install energy storage systems on the network. The problem finds optimal siting, sizing, and hourly operation pattern for all energy storage systems, while it minimizes the losses. It is worth mentioning that number of predefined locations for energy storage systems and renewable resources are limited to simplify mathematical formulation of the planning. As well, the proposed methodology can successfully improve network operation by reliving flow in transmission lines and improving voltage on buses. A sensitivity analysis is also carried out to indicate the impacts of the parameters on the planning. All simulations including modeling, solution, and sensitivity analysis are carried out in MATLAB software. © 2018 Elsevier Ltd
Publication Date: 2018
Ain Shams Engineering Journal (20904479) 9(2)pp. 311-318
This paper addresses an optimal model reference adaptive system (MRAS) to design power system stabilizer (PSS) in multi-machine electric power systems. Weighting factors of the proposed MRAS are adjusted by particle swarm optimization (PSO) as well as its input signal is limited by a normalization technique to assure network stability. The proposed modified-optimal MRAS-PSS is evaluated against conventional PSS to demonstrate its advantages. In order to investigate the performance of the proposed MRAS-PSS under parametric uncertainties, three operating conditions are defined and simulated. Several nonlinear and time-domain simulations are carried out to validate the viability and effectiveness of the proposed MRAS-PSS under network uncertainties. © 2016 Faculty of Engineering, Ain Shams University
Publication Date: 2018
Journal of Cleaner Production (0959-6526) 203pp. 1187-1200
Microgrids mainly use conventional and renewable energy resources at the same time. Conventional energy resources produce environmental pollution and need high cost for operation. In recent years, penetration of renewable resources such as photovoltaic and wind turbine has been rapidly grown in microgrids. Reduction of power losses and pollution are the main advantages of integrating renewable resources into networks. But, the renewable energy resources comprise low inertia and stability of the network integrated with such units is low. As a result, the environmental pollution and stability of microgrid are considered as the main problems and a new modeling of microgrid energy management is proposed by this paper to tackle such drawbacks. In this regard, environmental pollution is reduced by including hydrogen gas station and carbon capture-storage system. As well, the virtual synchronous generator is used to provide sufficient inertia and improving transient stability. The uncertain parameters are incorporated in the planning and stochastic programming is applied to tackle such uncertainties. Problem is mathematically expressed as a stochastic mixed integer linear programming and solved by the augmented Epsilon-constraint method. Finally, a comprehensive sensitivity analysis is carried out to evaluate the results. Based on the simulation results, by installing carbon capture-storage system, operational cost of microgrid is reduced from 64.998 $ to 56.043 $ and 1791.75 kg of carbon dioxide is stored. The revenue equal to 24 $ in one day is achieved by H2 station without any pollution. The stability of microgrid is also significantly improved by installing virtual synchronous generator. The results demonstrate the viability and effectiveness of the proposed method to minimize environmental pollution, operation cost and frequency fluctuations in microgrid energy management. © 2018 Elsevier Ltd
Publication Date: 2018
Energy (0360-5442) 151pp. 954-965
The optimal operation strategy of active distribution networks is investigated by this paper. The energy storage system (ESS) and distributed generation (DG) are utilized in the proposed planning. The paper presents two-level planning including short term and long term planning. The long term planning installs ESSs and diesel DGs on the network and the short term one determines an hourly optimal operation strategy for ESSs and diesel DGs. Different types of DG including solar photovoltaic (PV), wind, and diesel are studied at the same time. The objective function of the planning is to minimize annual operation cost of distribution network subject to security constraints of the network. The uncertainty of solar-wind units is estimated by many scenarios and stochastic programming is carried out to solve the problem. The proposed problem is expressed as a nonlinear mixed integer programming and solved by modified PSO algorithm. In order to cope with the real conditions, reactive power of ESSs and diesel DGs are included in the problem. Depth of discharge is also considered as a design variable and optimized for ESSs. The planning optimizes a large number of design variables at the same time including size and location of ESSs and diesel DGs, daily operation of diesel DGs, daily charging-discharging pattern of ESSs, and optimal depth of discharge for ESSs. The results demonstrate that the proposed two-level planning can effectively reduce cost and losses as well as increase efficiency and performance of the network. © 2018 Elsevier Ltd
Publication Date: 2017
Energy (0360-5442) 138pp. 520-528
This paper introduces an advanced control strategy on battery energy storage systems (BESS) for bidirectional power control and stability improvement. The proposed control strategy efficiently controls the charging-discharging states of BESS as well as provides bidirectional control on both active and reactive powers. The introduced control scheme is equipped with supplementary stabilizers to damp out the oscillations and stability improvement. The problem of designing the controllers is mathematically expressed as a constrained optimization programming and solved by particle swarm optimization (PSO). The results show that the proposed control strategy can efficiently control both active and reactive powers independent of each other. As well, it is able to change the direction of both active and reactive powers from positive to negative and vice-versa. The designed stabilizers also improve stability of the network and damp out the oscillations following large-signal and small-signal disturbances. © 2017 Elsevier Ltd
Publication Date: 2017
Energy (0360-5442) 134pp. 699-708
this paper presents a two-level stochastic microgrid planning tool. The proposed tool determines the optimal location and size of different technologies through a long-term plan as well as the optimal operation strategy for technologies through a short-term plan. The proposed planning tool considers distributed generation resources, energy storage systems, and lines as candidates for the expansion. One of the key characteristics of the introduced planning is its ability to tackle load and renewable energies uncertainties through stochastic planning. Both the long-term and short-term plans are mathematically expressed as mixed integer nonlinear programming problems and solved by using a strong Meta-heuristic optimization algorithm. Simulation results demonstrate that the proposed two-level planning method reduces the planning cost compared to the conventional method (i.e., only long-term planning). As well, it is indicated that considering line as an option for the expansion reduces the planning cost and increases the flexibility of the planning. © 2017
Publication Date: 2017
Energy (0360-5442) 118pp. 827-839
Renewable energy resources are often known as cost-effective and lucrative resources and have been widely developed due to environmental-economic issues. Renewable energy utilization even in small scale (e.g., microgrid networks) has attracted significant attention. Energy management in microgrid can be carried out based on the generating side management or demand side management. In this paper, portable renewable energy resource are modeled and included in microgrid energy management as a demand response option. Utilizing such resources could supply the load when microgrid cannot serve the demand. This paper addresses energy management and scheduling in microgrid including thermal and electrical loads, renewable energy sources (solar and wind), CHP, conventional energy sources (boiler and micro turbine), energy storage systems (thermal and electrical ones), and portable renewable energy resource (PRER). Operational cost of microgrid and air pollution are considered as objective functions. Uncertainties related to the parameters are incorporated to make a stochastic programming. The proposed problem is expressed as a constrained, multi-objective, linear, and mixed-integer programing. Augmented Epsilon-constraint method is used to solve the problem. Final results and calculations are achieved using GAMS24.1.3/CPLEX12.5.1. Simulation results demonstrate the viability and effectiveness of the proposed method in microgrid energy management. © 2016 Elsevier Ltd
Hemmati, R. ,
Hemmati, R. ,
Saboori, H. ,
Hemmati, R. ,
Ghiasi, S.M.S. ,
Dehghan, S. Publication Date: 2017
Renewable and Sustainable Energy Reviews (1364-0321) 79pp. 1108-1121
In the past decade, energy storage systems (ESSs) as one of the structural units of the smart grids have experienced a rapid growth in both technical maturity and cost effectiveness. These devices propose diverse applications in the power systems especially in distribution networks. Despite offering numerous applications, the ESSs are new devices characterized by high investment costs. Besides technological advancement, optimal ESS planning and scheduling is one of the effective ways to reduce the costs and justifying high investment costs by taking their benefits out as much as possible. During the past few years, various studies have been conducted by the researcher to address the problem of optimal ESS planning in distribution networks. In this context, various models, methods, and considerations have been proposed to enhance the functionality of optimal planning process. The aim of this paper is to review the problem of optimal ESS planning including optimal bus location, power rating, and energy capacity determination in the distribution networks. In order to facilitate continuing and growing research in this field, a comprehensive literature survey and classification of the related studies followed by research gaps and future opportunities is provided. © 2017 Elsevier Ltd
Hemmati, R. ,
Hemmati, R. ,
Hemmati, R. ,
Saboori, H. ,
Dehghan, S. ,
Ghiasi, S.M.S. Publication Date: 2017
Journal of Renewable and Sustainable Energy (19417012) 9(2)
An energy storage system (ESS) is a promising tool for improving the power system's technical and economical functionalities. This device possesses diverse applications in terms of system operation and planning. One of the main applications of the ESS in the power system operation, specially a large scale unit, is defined as load leveling. To this end, in the literature, various ESS models are integrated into two main power system operation frameworks, i.e., optimal power flow (OPF) and unit commitment (UC). But the question is that in which framework the obtained benefit from the load leveling by ESS is maximum and why. In other words, should ESS units schedule before generating unit commitment (UC) or after OPF and how. In this context, this paper performs three works. First, it proposes OPF and UC frameworks integrated with large scale ESS units. Second, the proposed models are implemented with identical parameters. Third, the obtained results are considered with respect to various outcomes, especially operation cost. This study is implemented on an IEEE 24 bus RTS system. The simulation results are analyzed and compared with respect to various parameters, and relevant conclusions are drawn based on the results. © 2017 Author(s).
Publication Date: 2017
Recent Advances in Electrical and Electronic Engineering (23520965) 10(3)pp. 272-278
Background: This paper investigates the impacts of uncertainties on flow-gate marginal pricing (FMP) as an efficient tool for analyzing financial transmission rights (FTR) in deregulated electricity markets. Methods: The proposed method provides a mathematical formulation for optimal power flow (OPF) and FMP is defined through OPF. Several parameters in electric power systems are modeled as probability distribution function (PDF) and Monte-Carlo simulation (MCS) is utilized to cope with the uncertainties. In order to indicate the priority of the parameters on FMP, sensitivity analysis is carried out and the priority list is derived. Conclusion: Many analyses and assessments demonstrate that network uncertainty makes great impacts on FMP and it is inevitable to include such uncertainties in FMP calculations. Results also emphasize the major effects of FMP in electric power systems under deregulated environments. © 2017 Bentham Science Publishers.
Publication Date: 2017
Renewable and Sustainable Energy Reviews (1364-0321) 71pp. 365-372
Energy storage systems (ESSs) are generally planned based on the active power. While, reactive power is another important aspect of the ESSs that has not been adequately addressed and discussed. Moreover, ESSs are often managed individually, but coordinated planning on the ESSs and distributed generators (DGs) may result in more suitable outcomes. In order to address these issues, a coordinated ESS and DG planning is presented in this paper. In the proposed planning, the place and capacity of the ESSs and DGs are determined at the same time. The active and reactive powers are included in the planning for both the ESSs and DGs. In other words, the optimal active and reactive capacities are denoted for both the ESSs and DGs on the network. The proposed coordinated ESS and DG planning is carried out on a radial distribution network under deregulated electricity market. Objective function of the proposed planning is to maximize the profit of distribution company (DISCO) subject to the secure operation of the network. The planning is expressed as a nonlinear, mixed integer optimization problem and solved by advanced PSO as a strong Meta-heuristic optimization technique. Simulation results demonstrate the great impacts of the proposed planning on the network. The results demonstrate the priority of the proposed coordinated DG and ESS planning compared to the individual ESS planning. Additionally, it is verified that considering reactive power of the DGs and ESSs changes the results of the planning and provides more realistic and reasonable outputs. The proposed planning significantly increases DISCO profit while guarantees the safe operation of the network through satisfying several security constraints. © 2016 Elsevier Ltd
Hemmati, R. ,
Hemmati, R. ,
Ahmadi jirdehi, M. ,
Tabar, V.S. ,
Hemmati, R. ,
Siano, P. Publication Date: 2017
International Journal of Electrical Power and Energy Systems (01420615) 93pp. 316-327
This paper focus on optimal scheduling of microgrid including thermal and electrical loads, renewable energy sources (solar and wind), combined heat and power (CHP), conventional energy sources (boiler and micro turbine), energy storage systems (thermal and electrical storages), and series flexible alternating current transmission system (FACTS) devices. Dynamic Voltage Restorer (DVR) is included in the line between the main network and the microgrid in order to achieve a higher power transfer to the upstream grid. In the proposed method, wind speed, solar radiation, and loads are modelled as uncertain parameters based on a stochastic approach. The problem is modelled as a linear, mixed integer, constrained, and multi objective optimization one aiming at minimizing cost and pollution at the same time. Also, a sensitivity analysis is proposed for studying the sensitive parameters in microgrid management. The proposed multi objective and stochastic problem is solved by using the augmented Epsilon-constraint method. All results and calculations are obtained by using GAMS24.1.3/CPLEX12.5.1. Finally, in order to confirm the results of the proposed method, final results are compared to the genetic algorithm method. Simulation results demonstrate the viability and effectiveness of the proposed scheduling method for microgrid. © 2017 Elsevier Ltd
This paper addresses a net zero energy home that utilizes renewable energy resources (i.e., photovoltaic solar cells and small scale wind turbines) as well as battery energy storage systems (BESS). In the introduced system, the generated power by renewable energy resources is used to supply the energy of home, and BESS is applied for energy time-of-use arbitrage. As well, the extra amount of energy is utilized for electrolysis of water into breathable oxygen and hydrogen gas as fuel of hydrogen vehicles. The proposed problem is mathematically expressed as mixed integer nonlinear programming (MINLP) and solved using particle swarm optimization (PSO) technique. Objective function of the problem is to minimize number of charging-discharging cycles resulting in increasing life-cycle of BESS. The proposed optimization problem also finds the optimal capacity and power for BESS. Simulation results demonstrate that the proposed technique can successfully manage net zero energy home and optimally utilizes renewable energy resources, BESS, and hydrogen vehicles at the same time. © 2017 IEEE.
Publication Date: 2017
Simulation Modelling Practice and Theory (1569190X) 77pp. 212-227
A new control strategy including multiband stabilizers is designed for battery energy storage system (BESS). The introduced control scheme includes two internal control loops equipped with internal proportional-integral (PI) type controllers for active and reactive power control. These control loops are also equipped with multiband stabilizers. All controllers (i.e., internal controllers and multiband stabilizers) are simultaneously tuned by Meta-heuristic optimization techniques. Several disturbances are applied and simulated. The viability and effectiveness of the introduced method is verified through various nonlinear simulations and comparative studies. © 2017 Elsevier B.V.
Publication Date: 2017
Journal of Energy Storage (2352152X) 13pp. 24-34
In recent years, battery storage systems have been widely studied in electrical networks. However, most of the studies have focused on active power in batteries. But, batteries can also produce or absorb reactive power. As well, impact of batteries on stability of the network has not been adequately addressed. Both the mentioned issues (i.e., reactive power and stability) make great impact on the battery utility such as ability of battery in energy management and power control. In order to overcome these shortcomings, current paper realizes a new control strategy on batteries for decoupled active-reactive power control. The proposed control strategy alters active power subject to constant reactive power and vice-versa. Two control loops are designed to control active and reactive powers. The control loops are equipped with PI controllers (i.e., tracking controllers). As well, both control loops of active and reactive powers are equipped with supplementary stabilizers (i.e., regulatory controllers). All controllers are simultaneously tuned by cultural-PSO-co-evolutionary (CPCE) algorithm. Several cases are simulated to demonstrate the effectiveness of the introduced strategy. It is verified that the proposed strategy is an efficient methodology to utilize battery storage systems and arising all abilities and benefits of the batteries at the same time. © 2017 Elsevier Ltd
Publication Date: 2017
Energy and Buildings (03787788) 152pp. 290-300
This paper presents an efficient home energy management system (HEMS) by optimal utilizing battery energy storage system (BESS) and photovoltaic (PV) systems. In the proposed HEMS, charging-discharging regime, capacity, and power of BESS are considered as design variables and optimally determined. Three operating conditions are considered for the home including: (i) home can receive energy from the network during off-peak low-cost hours, (ii) home can send energy to the main grid during on-peak high-cost hours for making the profit, and (iii) home can work on net-zero energy (NZE) model or standalone mode. The BESS is utilized to store energy during off-peak low-cost hours and discharge energy during on-peak high-cost hours. The proposed planning for determining the optimal operation strategy and sizing of BESS is expressed as a stochastic mixed integer nonlinear programming (MINLP). As well, output power produced by photovoltaic (PV) system is regarded as uncertain parameter and modeled by probability distribution function (PDF). Monte-Carlo Simulation (MCS) is applied to cope with uncertainties. The proposed stochastic MINLP is solved by Meta-heuristic optimization techniques. Simulation results demonstrate that the proposed HEMS can significantly reduce annual electricity bill. As well, NZE model can also be achieved by installing BESS and PV system at the same time. © 2017 Elsevier B.V.
Publication Date: 2017
Energy (0360-5442) 133pp. 380-387
This paper presents an optimal planning and scheduling on energy storage systems (ESSs) for congestion management in electric power systems including renewable energy resources. The proposed problem finds optimal capacity and charging-discharging regime of ESSs. The storage units are optimally charged and discharged to tackle the uncertainty related to wind-solar units as well as relief congestion in the lines. Output power of solar and wind units is modeled by Gaussian probability distribution function (PDF) and Monte-Carlo simulation (MCS) is applied to tackle the uncertainty. Simulation results demonstrate that the proposed planning can manage congestion of the network efficiently while dealing with wind and solar resources uncertainties. © 2017 Elsevier Ltd
Publication Date: 2017
Journal of Cleaner Production (0959-6526) 159pp. 106-118
Home energy management system (HEMS) is an important problem that has been attracting significant attentions in the recent years. However, the conventional HEMS includes several shortcomings. The conventional HEMSs mainly utilize battery energy storage system (BESS) to deal with energy uncertainties. But they only ascertain optimal charging-discharging pattern for BESS and the power and capacity of BESS are not optimally determined. Furthermore, most of the HEMSs are modeled as a mixed integer linear programming (MILP) including linearization and relaxations. Additionally, considering all possible operating conditions for home has not been adequately addressed in the existing HEMSs. The possible operating conditions are (i) receiving energy from the main grid (i.e., purchasing energy), (ii) sending energy to the utility grid (i.e., selling energy), (iii) working on standalone mode as disconnected from the network (i.e., net-zero energy building). As a result, current paper deals with these existing challenges at the same time. This paper presents HEMS including small-scale wind turbine, BESS, load curtailment option, and fuel cell vehicle. The introduced HEMS not only determines optimal charging-discharging pattern for BESS, but also specifies optimal capacity and optimal rated power of the BESS at the same time. The proposed HEMS is expressed as a mixed integer nonlinear programming (MINLP) and solved by cultural algorithm as an effective Meta-heuristic optimization algorithm. All three operating conditions are considered for home. Output power of wind unit is modeled by Gaussian probability distribution function (PDF) and Monte-Carlo simulation (MCS) is applied to deal with uncertainties. Results emphasize on the feasibility and usefulness of the introduced HEMS. © 2017 Elsevier Ltd
Hemmati, R. ,
Hemmati, R. ,
Ahmadi jirdehi, M. ,
Hemmati, R. ,
Abbasi, V. ,
Saboori, H. Publication Date: 2016
Frontiers of Information Technology and Electronic Engineering (20959230) 17(11)pp. 1218-1227
We propose a new and efficient algorithm to detect, identify, and correct measurement errors and branch parameter errors of power systems. A dynamic state estimation algorithm is used based on the Kalman filter theory. The proposed algorithm also successfully detects and identifies sudden load changes in power systems. The method uses three normalized vectors to process errors at each sampling time: normalized measurement residual, normalized Lagrange multiplier, and normalized innovation vector. An IEEE 14-bus test system was used to verify and demonstrate the effectiveness of the proposed method. Numerical results are presented and discussed to show the accuracy of the method. © 2016, Journal of Zhejiang University Science Editorial Office and Springer-Verlag Berlin Heidelberg.
Publication Date: 2016
Renewable Energy (0960-1481) 95pp. 74-84
Renewable resources, especially wind power, are widely integrated into the power systems nowadays. Managing uncertainty of the large scale wind power is often known as one of the most challenging issues in the power system operation scheduling. Additionally, energy storage systems (ESSs) have been widely investigated in the power systems owing to their valuable applications, especially renewable energy smoothing and time shift. In this paper, a stochastic unit commitment (UC) model is proposed to assess the impact of the wind uncertainty impact on ESSs and thermal units schedule in UC problem. Wind uncertainty is modeled based on the two measures. First, the wind penetration level is changed with respect to the basic level. Second, the wind forecasting error is modeled through a normal probability distribution function with different variances. The ESSs are modeled based on several technical characteristics and optimally scheduled considering different levels of the wind penetration and forecasting accuracies. The proposed formulation is a stochastic mixed integer linear programming (SMILP) and solved using GAMS software. Simulation results demonstrate that the wind uncertainty have a considerable impact on operation cost and ESSs schedule while proposed optimum storage scheduling through the stochastic programming will reduce the daily operational cost considerably. © 2016 Elsevier Ltd.
Hemmati, R. ,
Hemmati, R. ,
Parandin, F. ,
Karkhanehchi, M.M. ,
Hemmati, R. ,
Mahtabi, N. Publication Date: 2016
Tehnicki Vjesnik (13303651) 23(3)pp. 849-851
In order to attain the optical pulses with high frequency, the pulse-width must be very short. In practical systems, passive Q-switching is mainly regarded as one of the main methods to generate the short optical pulses. In passive Q-switching method, the optical pulses are generated by using laser parameters and therefore, the external electrical or optical modulators are not required to generate the optical pulses. This issue is regarded as the advantage of the passive Q-switching method compared to the other methods. In this paper, a model for two-section passive Q-switching diode laser is proposed. In the suggested method, the changing rates of the carriers are obtained in two regions by solving the equations. As well, by applying this mechanism, the pulse generation is described. Furthermore, the pulse width is achieved and it is demonstrated that the pulse width depends on the physical parameters of the laser. © 2016, Strojarski Facultet. All rights reserved.
Publication Date: 2016
IEEE Transactions on Sustainable Energy (1949-3029) 7(4)pp. 1371-1378
Nowadays, CO2 is the primary greenhouse gas pollutant and fossil fuel-fired electrical power plants are the major producer of CO2. In this regard, it is required to equip the electrical power plants with carbon capture and storage (CCS) systems. This paper addresses a multistage generation expansion planning (GEP) including nuclear units, renewable energy units, and different fossil fuel-fired units equipped with CCS. The proposed GEP minimizes the planning costs and CO2 at the same time, while it considers CCS cost and revenue. The problem is mathematically expressed as a constrained, mixed-integer, and nonlinear optimization problem and solved using particle swarm optimization (PSO) algorithm. The problem considers all practical constraints including security constraints of the network, and the generating units constraints of operation. Simulation results demonstrate that utilizing CCS significantly impacts on the planning output. Eventually, a comprehensive sensitivity analysis is carried out based on the CCS cost and revenue. © 2010-2012 IEEE.
Hemmati, R. ,
Hemmati, R. ,
Jalilian, M. ,
Sariri, H. ,
Parandin, F. ,
Karkhanehchi, M.M. ,
Hookari, M. ,
Ahmadi jirdehi, M. ,
Hemmati, R. Publication Date: 2016
International Journal of Electrical Power and Energy Systems (01420615) 74pp. 36-41
Abstract This paper designs and implements the monitoring and control systems for tap changer of the distribution transformers by using GSM (global system for mobile) network. The proposed method comprises an embedded system which collects and processes the transformer parameters such as temperature, humidity, silicone gel color, Buchholz relay status, the status of input and output phases, the current flow in each phase and power of each phase. If the parameters exceed the permitted level, the system sends all parameters using the GSM modem through GSM network to the control center, and the center receives and processes them by the GSM modem, and then they are displayed on computer. Furthermore, some commands are sent from the center to change the tap changer position, denoting the transformer position and making report on the transformer parameters. Some advantages of this system can be denoted as extending the lifetime of the transformer, consumers, wires and facilities, no need to the operator, simplifying the troubleshooting in distribution network, balancing the loads and providing customers with proper service. © 2015 Elsevier Ltd.
Publication Date: 2016
Renewable and Sustainable Energy Reviews (1364-0321) 65pp. 11-23
The idea of Hybrid Energy Storage System (HESS) lies on the fact that heterogeneous Energy Storage System (ESS) technologies have complementary characteristics in terms of power and energy density, life cycle, response rate, and so on. In other words, high power ESS devices possess fast response rate while in the contrary, high energy ESS devices possess slow response rate. Therefore, it may be beneficial to hybridize ESS technologies in the way that synergize functional advantages of two heterogeneous existing ESS technologies As a consequence, this hybridization provides excellent characteristics not offered by a single ESS unit. This new technology has been proposed and investigated by several researchers in the literature particularly in the fields of renewable energy and electrified transport sector. In this context and according to an extensive literature survey, this paper is to review the concept of the HESS, hybridization principles and proposed topologies, power electronics interface architectures, control and energy management strategies, and application arenas. © 2016 Elsevier Ltd
Publication Date: 2016
Renewable Energy (0960-1481) 97pp. 636-645
This paper addresses a multistage electricity generation expansion planning (GEP) incorporating large-scale energy storage systems (ESSs). The proposed coordinated GEP-ESS planning aims at minimizing the planning cost and environmental pollution at the same time, while it considers large-scale ESSs. Problem is expressed as a mixed-integer nonlinear programming and solved using PSO algorithm. Problem is solved subject to practical constraints of the network. ESS capacities are installed to support peak load level and reducing planning cost and environmental pollution. A typical test system including several existing and candidate generating units is considered to evaluate the proposed methodology. ESSs with various capacities are considered as candidate ESSs. Considering a large number of generating units and ESSs capacities increases the flexibility of the planning. Simulation results demonstrate that utilizing ESSs significantly reduces GEP cost as well as decreases the environmental pollution. © 2016 Elsevier Ltd.
Publication Date: 2016
Journal of Renewable and Sustainable Energy (19417012) 8(2)
In restructured electric power systems under electricity market regulations, Distribution Companies (DISCOs) mainly aim at maximizing their profit subject to safe operation of the network. In this regard, optimal planning of Energy Storage Systems (ESSs) can be a very effective method to maximize DISCOs profit. This paper addresses an optimal methodology to signify the location and capacity of ESSs in distribution network under electricity market environment. The proposed optimal ESSs planning aims at maximizing DISCO profit subject to safe and secure operation constraints (e.g., voltage and flow limits). The maximization problem is mathematically expressed as a mixed integer non-linear programming and solved using particle swarm optimization algorithm. Simulations are carried out on a typical distribution network. Simulation results demonstrate significant impact of ESSs on the network operation, security constraint, and costs. The proposed planning not only increases the DISCO profit but also guarantees the safe operation of the network. As well, several stativity analyses are carried out to indicate the impact of parameters on the planning. © 2016 Author(s).
Publication Date: 2016
Journal of Advanced Research (2090-1232) 7(3)pp. 360-372
Energy storage systems (ESSs) have experienced a very rapid growth in recent years and are expected to be a promising tool in order to improving power system reliability and being economically efficient. The ESSs possess many potential benefits in various areas in the electric power systems. One of the main benefits of an ESS, especially a bulk unit, relies on smoothing the load pattern by decreasing on-peak and increasing off-peak loads, known as load leveling. These devices require new methods and tools in order to model and optimize their effects in the power system studies. In this respect, this paper will model bulk ESSs based on the several technical characteristics, introduce the proposed model in the thermal unit commitment (UC) problem, and analyze it with respect to the various sensitive parameters. The technical limitations of the thermal units and transmission network constraints are also considered in the model. The proposed model is a Mixed Integer Linear Programming (MILP) which can be easily solved by strong commercial solvers (for instance CPLEX) and it is appropriate to be used in the practical large scale networks. The results of implementing the proposed model on a test system reveal that proper load leveling through optimum storage scheduling leads to considerable operation cost reduction with respect to the storage system characteristics. © 2016.
Publication Date: 2016
Energy (0360-5442) 113pp. 762-775
In recent decades, wind power resources have been integrated in the power systems increasingly. Besides confirmed benefits, utilization of large share of this volatile source in power generation portfolio has been faced system operators with new challenges in terms of uncertainty management. It is proved that energy storage systems are capable to handle projected uncertainty concerns. Risk-neutral methods have been proposed in the previous literature to schedule storage units considering wind resources uncertainty. Ignoring risk of the cost distributions with non-desirable properties may result in experiencing high costs in some unfavorable scenarios with high probability. In order to control the risk of the operator decisions, this paper proposes a new risk-constrained two-stage stochastic programming model to make optimal decisions on energy storage and thermal units in a transmission constrained hybrid wind-thermal power system. Risk-aversion procedure is explicitly formulated using the conditional value-at-risk measure, because of possessing distinguished features compared to the other risk measures. The proposed model is a mixed integer linear programming considering transmission network, thermal unit dynamics, and storage devices constraints. The simulations results demonstrate that taking the risk of the problem into account will affect scheduling decisions considerably depend on the level of the risk-aversion. © 2016 Elsevier Ltd
Publication Date: 2015
Energy Conversion and Management (0196-8904) 105pp. 938-945
This paper addresses multistage distribution network expansion planning (DNEP) incorporating energy storage systems (ESSs). The ESSs are utilized to shave the peak demand and to reduce the planning cost. Annual and daily load duration curves are considered to evaluate the impacts of the ESSs on the planning. The proposed planning is carried out based on the AC power flow including active power, reactive power, and network loss. The problem is formulated as a constrained, mixed-integer, and nonlinear programming (MINLP) and solved by using particle swarm optimization (PSO) algorithm. A 11 kV and 30-bus radial distribution network is considered as case study and the typical ESSs are also regarded to install on the network. Simulation results demonstrate the effectiveness and viability of the proposed method to consider the ESSs in DNEP. The results indicate that integrating the ESSs in DNEP reduces the planning cost significantly, as well improves the technical parameters of the network such as bus voltages and line loading. © 2015 Elsevier Ltd. All rights reserved.
Publication Date: 2015
Energy (0360-5442) 93pp. 2299-2312
This paper provides an optimal approach to denote the location and size of ESSs (energy storage systems) with the intention of reliability improvement in radial electrical distribution networks. The proposed optimal ESSs planning is addressed as a minimization problem which aims at minimizing the cost of ENS (energy not supplied) as well as ESSs costs at the same time, subject to safe operation of the network; where, the safe operation is guaranteed through satisfying security constraints such as voltage and line-flows limits. The minimization problem is mathematically formulated as a mixed-integer nonlinear programming and solved by PSO (particle swarm optimization) algorithm. A comprehensive sensitivity analysis is carried out on the results such as ESSs numbers, ESSs cost and reliability parameters. Simulation results demonstrate the viability of the proposed method in the real networks. Results also indicate the positive impact of ESSs on the network reliability. The proposed ESSs planning significantly reduces the ENS of the network and can be employed to deal with low reliability issues in the real networks. © 2015 Elsevier Ltd
Hemmati, R. ,
Hemmati, R. ,
Moazzami, M. ,
Hemmati, R. ,
Haghighatdar fesharaki f., F.H. ,
Rafiee rad s., Publication Date: 2013
International Journal of Electrical Power and Energy Systems (01420615) 53pp. 987-993
In deregulated electricity market environment, the power system works with lower stability margin due to demand fluctuations. Therefore, in restructured power systems all generation companies attempt to increase reliability of their own power plants. The arrangement of the busbar layouts in power stations has a great effect on the power system reliability. This paper develops a sequential Monte Carlo simulation (SMCS) to evaluate the effect of generator breaker and bus-section on the reliability indices of one and half and two-breaker busbar layouts. Karun III power station layout in Iran national grid (ING) is considered as a real world system case study. The most commonly used reliability indices such as loss of load expectation (LOLE), expected energy not supplied (EENS) and expected load curtailment (ELC) are used to evaluate the reliability in this paper. Economic and technical evaluations of reliability indices variation in presence of generator breaker and bus-section are presented. Simulation results show that how variation of forced outage rate (FOR) of generator and generator breaker affect on the reliability indices. © 2013 Elsevier Ltd. All rights reserved.
Hemmati, R. ,
Hemmati, R. ,
Taher, S.A. ,
Hemmati, R. ,
Abdolalipour, A. ,
Akbari, S. Publication Date: 2012
International Journal of Electrical Power and Energy Systems (01420615) 43(1)pp. 173-184
The unified power flow controller (UPFC) integrates properties of both shunt and series compensations, and can effectively alter power system parameters in such a way that increases power transfer capability and enhances system stability. In practice, simple proportional-integral (PI) controllers are used to control the UPFC. However, the PI control parameters are usually tuned based on classical or trial-and-error approaches and as such, they are incapable of obtaining good dynamic performance for a wide range of operating conditions and various loads in power systems. Hence, in this article robust control approaches are proposed based on the quantitative feedback theory (QFT), H ∞ loop-shaping and μ-synthesis, to design UPFC controllers (power-flow and DC-voltage regulator). The three mentioned methods are compared with each other and a supplementary damping controller is developed to improve damping power system oscillations. Here, a single-machine infinite-bus (SMIB) power system, installed with a UPFC (with system parametric uncertainties) is considered as a case study. The system parametric uncertainties are obtained following 40% simultaneous alterations in parameters and load from their typical values. The simulation results indicate satisfactory verifications of the robust control methods in dealing with the uncertainties considered. When the above three methods and the PI controller are compared in performance in several time-domain simulation tests, the results show clear superiority of the three methods over the PI controller, with the QFT presenting the best performance amongst the three robust control. © 2012 Elsevier Ltd. All rights reserved.
Publication Date: 2012
Turkish Journal Of Electrical Engineering And Computer Sciences (13000632) 20(SUPPL.2)pp. 1240-1248
With the expansion of electric power systems, the size and complexity of the network is increased. One of the most important drawbacks of network expansion is the reduction in the damping torque of the whole system. The lack of damping torque can lead to fluctuations and instability in the power system. With regard to this problem, power system stabilizers (PSSs) have been widely utilized to improve power system stability. However, due to some drawbacks of the conventional PSSs, the need for finding a better substitution still remains. Therefore, in this paper, the application of a static synchronous compensator (STATCOM) to improve dynamic stability of a multimachine electric power system is presented and a supplementary stabilizer based on the STATCOM is incorporated. Intelligence optimization methods such as particle swarm optimization and genetic algorithms are considered for tuning the parameters of the proposed stabilizer. Several nonlinear time-domain simulation tests visibly show the ability of the STATCOM in damping power system oscillations. © TÜBITAK.
Publication Date: 2012
International Journal of Electrical Power and Energy Systems (01420615) 43(1)pp. 1137-1143
This paper presents a systematic robustness analysis of unified power flow controller (UPFC) under system parametric uncertainties. The power system uncertainties are considered as different loading conditions. In order to deal with these uncertainties, robust control methods are handled to design UPFC controllers. The well known robust methods such as quantitative feedback theory (QFT) and mu-synthesis are carried out to design UPFC controller. Two test cases as single machine and multi machine are incorporated to evaluate the proposed methods. Also, the proposed methods are compared with conventional controller. The simulation results denote the ability and effectiveness of the proposed methods for tackle with uncertainties. © 2012 Elsevier Ltd. All rights reserved.
Publication Date: 2012
International Journal of Soft Computing (discontinued) (18169503) 7(3)pp. 126-130
This study presents a new generator's PSS (Power System Stabilizer) design methodology. A multi input PSS is utilized to achieve a better performance over a wide range of operating conditions instead of a conventional single input PSS. The parameters of the proposed PSS are obtained by minimizing a time domain performance index. The proposed PSS is evaluated against the Conventional Power System Stabilizer (CPSS) at a multi area power system considering system parametric uncertainties. Simulation results show that the proposed PSS provides a better performance than the conventional PSS. © Medwell Journals, 2012.
Hemmati, R. ,
Hemmati, R. ,
Boroujeni, S.M.S. ,
Delafkar, H. ,
Behzadipour, E. ,
Boroujeni, A.S. ,
Hemmati, R. Publication Date: 2011
Australian Journal of Basic and Applied Sciences (19918178) 5(7)pp. 652-659
Power System Stabilizers (PSS) are used to generate supplementary damping control signals for the excitation system in order to damp the Low Frequency Oscillations (LFO) of the electric power system. The PSS is usually designed based on classical control approaches but this Conventional PSS (CPSS) has some problems. To overcome the drawbacks of CPSS, numerous techniques have been proposed in literatures. In this paper a PID type PSS is considered for damping electric power system oscillations. The parameters of this PID type PSS are tuned based on Simulated Annealing (SA) optimization method. The proposed PSS (SA-PSS) is evaluated against the conventional power system stabilizer (CPSS) at a single machine infinite bus power system considering system parametric uncertainties. The simulation results clearly indicate the effectiveness and validity of the proposed method.
Hemmati, R. ,
Hemmati, R. ,
Farahani, S.S.S. ,
Hemmati, R. ,
Nikzad, M. ,
Isanejad, O. Publication Date: 2011
International Journal of Physical Sciences (19921950) 6(7)pp. 1643-1652
This paper presents the application of UPFC to enhance damping of Low Frequency Oscillations at a Single-Machine Infinite-Bus (SMIB) power system installed with UPFC. Since UPFC is considered to mitigate Low Frequency Oscillations (LFO), therefore a supplementary stabilizer controller based UPFC like power system stabilizer is designed to reach the defined purpose. Artificial intelligence methods such as Fuzzy logic schemes and Genetic Algorithms (GA) optimization are considered to design UPFC supplementary stabilizer controller. To show effectiveness and also comparing these two methods, the proposed methods are applied and simulated. Several linear time-domain simulation tests visibly show the validity of proposed methods in damping of power system oscillations. Also simulation results emphasis on the better performance of Fuzzy method compare to GA method. Simulations are carried out in MATLAB software. © 2011 Academic Journals.
Publication Date: 2011
Research Journal of Applied Sciences, Engineering and Technology (discontinued) (20407459) 3(8)pp. 779-784
This study presents the application of Unified Power Flow Controller (UPFC) to improvement dynamic stability of a multi-machine electric power system installed with UPFC. Since UPFC is considered to mitigate Low Frequency Oscillations (LFO) and stability enhancement, therefore a supplementary stabilizer based on UPFC (like power system stabilizer) is designed to reach the defined purpose. Intelligence optimization methods such as Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) are considered for tuning the parameters of UPFC supplementary stabilizer. To show effectiveness of UPFC and also comparing these two optimization methods, the proposed methods are applied and simulated. Several nonlinear time-domain simulation tests visibly show the ability of UPFC in damping of power system oscillations and consequently stability enhancement. Also Simulation results emphasis on the better performance of PSO based Stabilizer in comparison with GA based Stabilizer. © Maxwell Scientific Organization, 2011.
Hemmati, R. ,
Hemmati, R. ,
Hemmati, R. ,
Boroujeni, S.M.S. ,
Delafkar, H. ,
Boroujeni, A.S. Publication Date: 2011
Indian Journal of Science and Technology (discontinued) (09746846) 4(7)pp. 796-800
The Load Frequency Control (LFC) problem is one of the most important subjects in the electric power system operation and control. In practical systems, the conventional PI type controllers are applied for LFC. In order to overcome the drawbacks of the conventional PI controllers, PI and PID Fuzzy controllers are considered for LFC problem. The parameters of the proposed Fuzzy controllers are tuned using Genetic Algorithms (GA). A multi area electric power system with a wide range of parametric uncertainties is given to illustrate proposed method. The simulation results visibly show the validity of proposed controllers in LFC problem. © Indian Society for Education and Environment (iSee).
Hemmati, R. ,
Hemmati, R. ,
Boroujeni, S.M.S. ,
Boroujeni, B.K. ,
Delafkar, H. ,
Behzadipour, E. ,
Hemmati, R. Publication Date: 2011
Indian Journal of Science and Technology (discontinued) (09746846) 4(9)pp. 1025-1030
The problem of tuning Power system stabilizers (PSSs) is commonly formulated as a nonlinear optimization problem with some constraints. In this paper a new optimization technique based on Harmony Search (HS) to solve the proposed optimization problem is presented. This is a very complex nonlinear programming problem. A constructive heuristic algorithm aimed at obtaining an excellent quality solution for this problem is presented. Results of the tests, carried out with a multi machine electric power system, show the capabilities of the method and also the viability of using the HS to solve the problem. © Indian Society for Education and Environment (iSee).
Hemmati, R. ,
Hemmati, R. ,
Boroujeni, S.M.S. ,
Boroujeni, B.K. ,
Delafkar, H. ,
Behzadipour, E. ,
Hemmati, R. Publication Date: 2011
Indian Journal of Science and Technology (discontinued) (09746846) 4(9)pp. 1031-1035
This paper presents the application of static synchronous compensator (STATCOM) to voltage support in a multimachine electric power system. Harmony Search (HS) Algorithm as a meta-heuristic optimization method is considered for tuning the parameters of STATCOM. In order to evaluate the performance of STATCOM in voltage support, a multi-machine electric power system installed with STATCOM is considered as case study. The system under study is IEEE 14 bus standard system testing. The results are compared with the system without STATCOM. Several nonlinear time-domain simulation tests visibly show the ability of STATCOM in voltage support. © Indian Society for Education and Environment (iSee).
Hemmati, R. ,
Hemmati, R. ,
Boroujeni, S.M.S. ,
Boroujeni, B.K. ,
Delafkar, H. ,
Behzadipour, E. ,
Hemmati, R. Publication Date: 2011
Indian Journal of Science and Technology (discontinued) (09746846) 4(9)pp. 1155-1159
Static Var Compensator (SVC) in one of the most widely used FACTS devices in industry and real world power systems. The problem of finding optimal values of SVC parameters has been studied for years. Many different methods have been carried out to design SVC controllers. But trying to find better controller is still remains. In this scope, Harmony Search (HS) Algorithms method as a meta-heuristic optimization method is considered for tuning the parameters of SVC. A multi machine electric power system is used to test viability of SVC in voltage support under disturbances. Simulation results on a multi machine power system show the ability of SVC in control of voltage as well as stability enhancement. The results are carried out by numerical simulations by using MATLAB software. © Indian Society for Education and Environment (iSee).
Hemmati, R. ,
Hemmati, R. ,
Boroujeni, S.M.S. ,
Delafkar, H. ,
Behzadipour, E. ,
Boroujeni, A.S. ,
Hemmati, R. Publication Date: 2011
Australian Journal of Basic and Applied Sciences (19918178) 5(7)pp. 644-651
In multi area electric power systems if a large load is suddenly connected (or disconnected) to the system, or if a generating unit is suddenly disconnected by the protection equipment, there will be a long-term distortion in the power balance between that delivered by the turbines and that consumed by the loads. This imbalance is initially covered from the kinetic energy of rotating rotors of turbines, generators and motors and, as a result, the frequency in the system will change. Therefore The Load Frequency Control (LFC) problem is one of the most important subjects in the electric power system operation and control. In practical systems, the conventional PI type controllers are applied for LFC. In order to overcome the drawbacks of the conventional PI controllers, numerous techniques have been proposed in literatures. In this paper a PI type controller is considered for LFC problem. The parameters of the proposed PI controller are tuned using Simulated Annealing (SA) optimization method. A multi area electric power system with a wide range of parametric uncertainties is given to illustrate proposed method. To show effectiveness of the proposed method, a PI type controller optimized by Genetic Algorithms (GA) is designed in order to comparison with the proposed PI controller. The simulation results visibly show the validity of SA-PI controller in comparison with the GA-PI controller.
Publication Date: 2011
International Journal of Physical Sciences (19921950) 6(10)pp. 2363-2371
This paper presents the application of Unified Power Flow Controller (UPFC) in order to simultaneously power flow control, voltage support and also transient stability improvement at a Single-Machine Infinite-Bus (SMIB) power system installed with UPFC. In practical systems, the conventional PI type controllers are considered to control UPFC. In order to overcome the drawbacks of the conventional PI controllers, numerous techniques have been proposed in literatures. In this paper, PID type controller is considered for UPFC control and the parameters of the proposed PID controller are obtained using Particle Swarm Optimization (PSO). To show effectiveness of PID controller, a PI type controller optimized by PSO is designed in order to compare it with the proposed PID controller. The simulation results visibly show the validity of PID controller in comparison with PI controller. ©2011 Academic Journals.
Hemmati, R. ,
Hemmati, R. ,
Boroujeni, S.M.S. ,
Hemmati, R. ,
Delafkar, H. ,
Boroujeni, A.S. Publication Date: 2011
Indian Journal of Science and Technology (discontinued) (09746846) 4(4)pp. 379-383
Power system stabilizers (PSS) are used to generate supplementary damping control signals for the excitation system in order to damp the low frequency oscillations (LFO) of the electric power system. The PSS is usually designed based on classical control approaches but this conventional PSS (CPSS) has some problems. To overcome the drawbacks of CPSS, numerous techniques have been proposed in literatures. In this paper a PID type PSS is considered for damping electric power system oscillations. The parameters of this PID type PSS are tuned based on particle swarm optimization method. The proposed PSS (PSO-PSS) is evaluated against the conventional power system stabilizer (CPSS) at a single machine infinite bus power system considering system parametric uncertainties. The simulation results clearly indicate the effectiveness and validity of the proposed method. © Indian Society for Education and Environment (iSee).
Hemmati, R. ,
Hemmati, R. ,
Hemmati, R. ,
Boroujeni, S.M.S. ,
Delafkar, H. ,
Boroujeni, A.S. Publication Date: 2011
Australian Journal of Basic and Applied Sciences (19918178) 5(3)pp. 295-302
in multi area electric power systems if a large load is suddenly connected (or disconnected) to the system, or if a generating unit is suddenly disconnected by the protection equipment, there will be a long-term distortion in the power balance between that delivered by the turbines and that consumed by the loads. This imbalance is initially covered from the kinetic energy of rotating rotors of turbines, generators and motors and, as a result, the frequency in the system will change. Therefore The Load Frequency Control (LFC) problem is one of the most important subjects in the electric power system operation and control. In practical systems, the conventional PI type controllers are applied for LFC. In order to overcome the drawbacks of the conventional PI controllers, numerous techniques have been proposed in literatures. In this paper a PID type controller is considered for LFC problem. The parameters of the proposed PID controller are tuned using Particle Swarm Optimization (PSO) method. A multi area electric power system with a wide range of parametric uncertainties is given to illustrate proposed method. To show effectiveness of the proposed method, a PID type controller optimized by Genetic Algorithms (GA) is designed in order to comparison with the proposed PID controller. The simulation results visibly show the validity of PSO-PID controller in comparison with the GA-PID controller.
Hemmati, R. ,
Hemmati, R. ,
Hemmati, R. ,
Boroujeni, S.M.S. ,
Behzadipour, E. ,
Delafkar, H. Publication Date: 2011
Australian Journal of Basic and Applied Sciences (19918178) 5(5)pp. 721-727
Power System Stabilizers (PSS) are used to generate supplementary damping control signals for the excitation system in order to damp the Low Frequency Oscillations (LFO) of the electric power system. The PSS is usually designed based on classical control approaches but this Conventional PSS (CPSS) has some problems. To overcome the drawbacks of CPSS, numerous techniques have been proposed in literatures. In this paper a PID type PSS (PID-PSS) is considered for damping electric power system oscillations. The parameters of this PID type PSS (PID-PSS) are tuned based on Hybrid Genetic Algorithm optimization method. The proposed PID-PSS is evaluated against the conventional power system stabilizer (CPSS) at a single machine infinite bus power system considering system parametric uncertainties. The simulation results clearly indicate the effectiveness and validity of the proposed method.
Publication Date: 2011
Indian Journal of Science and Technology (discontinued) (09746846) 4(4)pp. 456-461
Power system stabilizers (PSS) are used to generate supplementary damping control signals for the excitation system in order to damp the low frequency oscillations (LFO) of the electric power system. The PSS is usually designed based on classical control approaches but this conventional PSS (CPSS) has some problems. To overcome the drawbacks of CPSS, numerous techniques have been proposed in literatures. In this paper a new robust hybrid method based on the combination of pole placement and nonlinear programming methods is proposed in order to design a robust power system stabilizer. The classical robust methods usually lead to a high order controller which is expensive, difficult to implement and somehow impossible. As a solution, in this paper a PID type PSS is considered for damping electric power system oscillations. The parameters of this PID type PSS (PID-PSS) are tuned based on pole placement and nonlinear programming methods. Therefore, not only the obtained PID-PSS is low order and easy to implement but also it has robust characteristics like robust controllers. The proposed PID-PSS is evaluated against the conventional and robust power system stabilizers in a single machine infinite bus power system considering system parametric uncertainties. The simulation results clearly indicate the effectiveness and validity of the proposed method. © Indian Society for Education and Environment (iSee).
Hemmati, R. ,
Hemmati, R. ,
Shirvani boroujeni s.m., ,
Hemmati, R. ,
Delafkar, H. ,
Boroujeni, A.S. Publication Date: 2011
International Review of Electrical Engineering (25332244) 6(2)pp. 818-824
This paper presents the application of Unified Power Flow Controller (UPFC) in order to simultaneous power flow control and voltage support and also transient stability improvement at a Single-Machine Infinite-Bus (SMIB) power system installed with UPFC. PI type controllers are considered for power flow and voltage control and the parameters of these PI type controllers are tuned using Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). Also a stabilizer supplementary controller based UPFC is considered for increasing power system damping and stability enhancement. In order to UPFC performance study and also comparison of PSO and GA, the SMIB power system is simulated under different scenarios. Numerous simulations show the ability of UPFC in simultaneous power flow control and voltage support and also stability enhancement by damping of power system oscillations. Simulation results emphasis on the better performance of PSO in comparison with GA. Copyright © 2011 Praise Worthy Prize S.r.l.- All rights reserved.
Hemmati, R. ,
Hemmati, R. ,
Boroujeni, S.M.S. ,
Delafkar, H. ,
Behzadipour, E. ,
Boroujeni, A.S. ,
Hemmati, R. Publication Date: 2011
Australian Journal of Basic and Applied Sciences (19918178) 5(7)pp. 1318-1325
This paper presents the application of Static Synchronous Compensator (STATCOM) to enhance damping of Low Frequency Oscillations at a single-machine infinite-bus power system installed with a STATCOM as cast study. STATCOM is considered in order to damping of Low Frequency Oscillations. Therefore the supplementary stabilizer based STATCOM (like power system stabilizer) is designed to reach defined purpose. A Meta heuristic optimization method named Simulated Annealing (SA) is used to tuning STATCOM supplementary stabilizer controller. To show effectiveness of the proposed method, the proposed method is compared with another optimization method named Genetic Algorithms (GA). Several linear time-domain simulation tests visibly show the validity of proposed method in damping of power system oscillations. Also Simulation results emphasis on the better performance of SA in comparison with GA.
Hemmati, R. ,
Hemmati, R. ,
Hemmati, R. ,
Boroujeni, S.M.S. ,
Delafkar, H. ,
Boroujeni, A.S. Publication Date: 2011
Indian Journal of Science and Technology (discontinued) (09746846) 4(7)pp. 815-819
This paper presents the application of Unified Power Flow Controller (UPFC) to enhance damping of Low Frequency Oscillations (LFO) at a Single-Machine Infinite-Bus (SMIB) power system installed with UPFC. Since UPFC is considered to mitigate LFO, a supplementary UPFC like power system stabilizer is designed to reach the defined purpose. Simulated Annealing (SA) is used to tune UPFC supplementary stabilizer. To show effectiveness, the proposed method is compared with another optimization method named Genetic Algorithms (GA). Several linear timedomain simulation tests visibly show the validity of proposed method in damping of power system oscillations. Also simulation results emphasis on the better performance of SA in comparison with GA. © Indian Society for Education and Environment (iSee).
Hemmati, R. ,
Hemmati, R. ,
Hemmati, R. ,
Boroujeni, S.M.S. ,
Behzadipour, E. ,
Delafkar, H. Publication Date: 2011
Indian Journal of Science and Technology (discontinued) (09746846) 4(5)pp. 525-529
This paper presents the application of static synchronous compensator (STATCOM) to enhance damping of Low Frequency Oscillations at a single-machine infinite-bus power system installed with a STATCOM as cast study. STATCOM is considered in order to damping of Low Frequency Oscillations. Therefore, the supplementary stabilizer based STATCOM (like power system stabilizer) is designed to reach defined purpose. Optimization methods such as Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) are considered to design STATCOM supplementary stabilizer controller. To show effectiveness and also comparing these two methods, the proposed methods are simulated under different operating conditions. Several linear time-domain simulation tests visibly show the validity of proposed methods in damping of power system oscillations. Also simulation results emphasis on the better performance of PSO in comparison with GA method. ©Indian Society for Education and Environment (iSee).
Hemmati, R. ,
Hemmati, R. ,
Hemmati, R. ,
Boroujeni, S.M.S. ,
Behzadipour, E. ,
Delqfkar, H. Publication Date: 2011
World Applied Sciences Journal (discontinued) (18184952) 12(10)pp. 1736-1744
This paper presents the application of Unified Power Flow Controller (UPFC) to enhance damping of Low Frequency Oscillations (LFO) at a Single-Machine Infinite-Bus (SMTB) power system installed with UPFC. Since UPFC is considered to mitigate LFO, therefore a supplementary damping controller based UPFC like power system stabilizer is designed to reach the defined purpose. Artificial intelligence methods such as Particle Swarm Optimization (PSO) and Fuzzy-Genetic Algorithms (GA) are considered to design UPFC supplementary stabilizer controller. In the Fuzzy-GA technique, the upper and lower bounds of the Fuzzy membership functions are obtained using genetic algorithms optimization method and so this Fuzzy method is called scaled-Fuzzy. To show effectiveness and also comparing these two methods, the proposed methods are simulated under different operating conditions. Several linear time-domain simulation tests visibly show the validity of proposed methods in damping of power system oscillations. Also Simulation results emphasis on the better performance of PSO in comparison with Fuzzy-GA method. © IDOSI Publications, 2011.
Hemmati, R. ,
Hemmati, R. ,
Nikzad, M. ,
Hemmati, R. ,
Farahani, S.S.S. ,
Boroujeni, S.M.S. Publication Date: 2010
Australian Journal of Basic and Applied Sciences (19918178) 4(10)pp. 4910-4921
The Load Frequency Control (LFC) problem has been on of the major subjects in electric power system design/operation and is becoming much more significant today in accordance with increasing size, changing structure and complexity in interconnected power systems. Practice LFC systems use simple proportional-integral (PI) or integral (I) controllers. But the PI control parameters are usually tuned based on the classical or trial-and-error approaches and they are incapable to obtain good dynamic performance under various load conditions. For this problem, in this paper the artificial intelligence methods such as Genetic Algorithms (GA) and Fuzzy logic are proposed to tune the controllers for LFC problem in power system. A two-area power system example is considered as case study to illustrate the proposed methods. To show effectiveness of proposed methods and also comparing the performance of GA and Fuzzy controllers, several time domain simulations for various load changes scenarios are presented. Simulation results emphasis on the better performance of Fuzzy controllers than GA controllers in LFC problem. © 2010, INSInet Publication.
Publication Date: 2010
International Journal of Physical Sciences (19921950) 5(17)pp. 2564-2573
Power System Stabilizers (PSS) are used to generate supplementary damping control signals for the excitation system in order to damp the low frequency oscillations (LFO) of the electric power system. The PSS is usually designed based on classical control approaches but this Conventional Power System Stabilizers (CPSS) has some problems. To overcome the drawbacks of CPSS, numerous techniques have been proposed in literatures. Intelligent based methods such as Fuzzy logic and genetic algorithms and also robust control methods such as quantitative feedback theory (QFT) have already been used for designing PSS. In this paper the goal is to study comparison of different methods used for designing PSS. For this purpose the Conventional PSS (CPSS), fuzzy based PSS (FPSS), genetic algorithms based PSS (GA-PSS) and also QFT based PSS (QFT-PSS) are considered for comparison purposes. A single machine infinite bus power system with system parametric uncertainties is considered as a case study and the proposed methods are evaluated against one another at this test system. The simulation results clearly indicate the effectiveness and validity of the proposed methods. © 2010 Academic Journals.
Hemmati, R. ,
Hemmati, R. ,
Taher, S.A. ,
Akbari, S. ,
Abdolalipour, A. ,
Hemmati, R. Publication Date: 2010
Communications in Nonlinear Science and Numerical Simulation (10075704) 15(8)pp. 2149-2161
In this paper a new method based on structured singular value (μ-synthesis) is proposed for the robust decentralized unified power flow controller (UPFC) design. To achieve decentralization, using the Schauder fixed point theorem the synthesis and analysis of multi-input multi-output (MIMO) control system is transformed into a set of equivalent multi-input single-output (MISO) control system. To cope with power system uncertainties μ-synthesis technique is being used for designing of UPFC controllers. The proposed μ-based controller has a decentralized scheme which has the advantage of reduction in the controller complexity and suitability for practical implementation. The effectiveness of the proposed control strategy on damping low frequency oscillations is evaluated under different operating conditions and compared with the conventional controller to demonstrate its robust performance through nonlinear simulation and some performance indices. © 2009 Elsevier B.V. All rights reserved.
Hemmati, R. ,
Hemmati, R. ,
Sahrai m., ,
Maleki a., ,
Hemmati, R. ,
Mahmoudi m., Publication Date: 2010
European Physical Journal D (14346060) 56(1)pp. 105-112
We investigate the dynamical behavior of the dispersion and the absorption in a V-type three level atomic system. It is shown that in the presence of decay-induced interference the probe dispersion and absorption are phase dependent. We find that an incoherent pumping field provides an additional control parameter for switching the group velocity of a light pulse. The required switching times for switching the group velocity of a probe field from subluminal to superluminal pulse propagation is then discussed. © 2009 EDP Sciences, SIF, Springer-Verlag Berlin Heidelberg.
Hemmati, R. ,
Hemmati, R. ,
Sahrai m., ,
Hemmati, R. ,
Tajalli h., ,
Mahmoudi m., Publication Date: 2008
Journal of Modern Optics (13623044) 55(1)pp. 67-78
We study the effects of quantum interference from the spontaneous emission and the incoherent pumping field on the population trapping and the spontaneous emission spectrum. It is shown that in a four-level atomic system with both interferences, the population will be trapped in degenerate two upper levels. We find that the spontaneous emission properties of the atom can be significantly modified by the interference of incoherent pumping field.
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