This page has only limited features, please log in for full access.
Abbas Ketabi (Member, IEEE) received B.Sc. and M.Sc. degrees in electrical engineering from the Department of Electrical Engineering at the Sharif University of Technology, Tehran, Iran, in 1994 and 1996, respectively, and a Ph.D. degree in electrical engineering jointly from the Sharif University of Technology and the Institut National Polytechnique de Grenoble (Grenoble Institute of Technology), Grenoble, France, in 2001. Since then, he has been with the Faculty of Electrical Engineering at the University of Kashan, Iran, where he is currently an Associate Professor. He has published more than 80 technical articles and books. He is a Manager and an Editor of the Energy: Engineering and Management journal. His research interests include power system restoration, smart grids, renewable energy, optimization shape of electric machines, and evolutionary computation. He was a recipient of the University of Kashan Award for Distinguished Teaching and Research.
In this article, a novel multi-port modular multilevel inverter topology is presented for grid-connected photovoltaic systems, which feature a smaller capacitor size compared with its counterparts. In the proposed MMC topology, each submodule is an individual input port being fed by an independent PV array through a boost converter. This allows modularity of the proposed topology, easing its maintenance and facilitating its expansion for PV integration. Individual maximum power point tracking controllers are used to operate the boost converters in each submodule to extract maximum energy from their PV arrays under different radiation conditions. A model-predictive control scheme is designed for regulating the proposed multi-port MMC topology to inject the harvested solar power to the grid. This controller enables minimized circulating currents in the MMC arms and balanced capacitor voltages in the MMC submodules, while total harmonic distortion (THD) of injected current to the grid is kept within the limits. The proposed multi-port MMC topology with model-predictive control is validated under different radiation conditions for a grid-connected PV system to indicate that the proposed topology has a desirable performance under different radiation conditions.
Sheila Safaee; Abbas Ketabi; Mohammad Farshadnia; Mohammad Shahidehpour. A multi‐port MMC topology with reduced capacitor size for use in grid‐connected PV systems. Energy Science & Engineering 2021, 1 .
AMA StyleSheila Safaee, Abbas Ketabi, Mohammad Farshadnia, Mohammad Shahidehpour. A multi‐port MMC topology with reduced capacitor size for use in grid‐connected PV systems. Energy Science & Engineering. 2021; ():1.
Chicago/Turabian StyleSheila Safaee; Abbas Ketabi; Mohammad Farshadnia; Mohammad Shahidehpour. 2021. "A multi‐port MMC topology with reduced capacitor size for use in grid‐connected PV systems." Energy Science & Engineering , no. : 1.
Smart microgrids (SMGs), as cyber–physical systems, are essential parts of smart grids. The SMGs’ cyber networks facilitate efficient system operation. However, cyber failures and interferences might adversely affect the SMGs. The available studies about SMGs have paid less attention to SMGs’ cyber–physical features compared to other subjects. Although a few current research works have studied the cyber impacts on SMGs’ reliability, there is a research gap about reliability evaluation simultaneously concerning all cyber failures and interferences under various cyber network topologies and renewable distributions scenarios. This article aims to fill such a gap by developing a new Monte Carlo simulation-based reliability assessment method considering cyber elements’ failures, data/information transmission errors, and routing errors under various cyber network topologies. Considering the microgrid control center (MGCC) faults in comparion to other failures and interferences is one of the major contributions of this study. The reliability evaluation of SMGs under various cyber network topologies, particularly based on an MGCC’s redundancy, highlights this research’s advantages. Moreover, studying the interactions of uncertainties for cyber systems and distributed generations (DGs) under various DG scenarios is another contribution. The proposed method is applied to a test system using actual historical data. The comparative test results illustrate the advantages of the proposed method.
Mehrdad Aslani; Hamed Hashemi-Dezaki; Abbas Ketabi. Reliability Evaluation of Smart Microgrids Considering Cyber Failures and Disturbances under Various Cyber Network Topologies and Distributed Generation’s Scenarios. Sustainability 2021, 13, 5695 .
AMA StyleMehrdad Aslani, Hamed Hashemi-Dezaki, Abbas Ketabi. Reliability Evaluation of Smart Microgrids Considering Cyber Failures and Disturbances under Various Cyber Network Topologies and Distributed Generation’s Scenarios. Sustainability. 2021; 13 (10):5695.
Chicago/Turabian StyleMehrdad Aslani; Hamed Hashemi-Dezaki; Abbas Ketabi. 2021. "Reliability Evaluation of Smart Microgrids Considering Cyber Failures and Disturbances under Various Cyber Network Topologies and Distributed Generation’s Scenarios." Sustainability 13, no. 10: 5695.
Increasing the usage of distributed generations (DGs) leads the microgrids (MGs) to develop. Considering the existence of alternating current (ac) loads and sources and concerning increasing direct current (dc) loads and sources, hybrid ac/dc MGs have been used to have the advantages of both ac and dc MGs and reduce the drawbacks of them. By integrating the DG units in hybrid ac/dc MGs. Hence, a proper control method is required in such MGs to achieve precise voltage regulation and power-sharing, desired power quality, high efficiency, and high reliability. This article focused on nonlinear exponential control and distributed secondary control schemes to properly control the MG and form an integrated nonlinear hierarchical control and management for hybrid ac/dc MGs. Finally, to evaluate the proposed nonlinear control strategy's performance, offline digital time-domain simulation studies are carried out on a test MG system in MATLAB/Simulink environment. The results are also compared with previously reported methods. The simulation results and the comparisons showed that the proposed methods could properly share the power among subgrids and DGs in both ac and dc subgrids. In contrast, the proposed control scheme can prove its effectiveness and superiority over conventional controllers.
Mojtaba Biglarahmadi; Abbas Ketabi; Hamid Reza Baghaee; Josep M. Guerrero. Integrated Nonlinear Hierarchical Control and Management of Hybrid AC/DC Microgrids. IEEE Systems Journal 2021, PP, 1 -12.
AMA StyleMojtaba Biglarahmadi, Abbas Ketabi, Hamid Reza Baghaee, Josep M. Guerrero. Integrated Nonlinear Hierarchical Control and Management of Hybrid AC/DC Microgrids. IEEE Systems Journal. 2021; PP (99):1-12.
Chicago/Turabian StyleMojtaba Biglarahmadi; Abbas Ketabi; Hamid Reza Baghaee; Josep M. Guerrero. 2021. "Integrated Nonlinear Hierarchical Control and Management of Hybrid AC/DC Microgrids." IEEE Systems Journal PP, no. 99: 1-12.
Microgrids active characteristics such as grid-connected or islanded operation mode, the distributed generators with an intermittent nature, and bidirectional power flow in active distribution lines lead to malfunction of traditional protection schemes. In this article, an impedance-based fault detection scheme is proposed as the main protection of microgrids by applying the proposed equivalent circuits for doubly-fed lines. In this scheme, relay location data and positive sequence voltage absolute value of the other end of the line are used. It can detect even high impedance faults in grid-connected and islanded modes. It is robust against load and generation uncertainties and network reconfigurations. Low sampling rate and minimum data exchange are among the advantages of the proposed scheme. Moreover, a backup protection scheme based on the conductance variations is suggested. No requirement for the communication link is a distinguished advantage of the proposed backup protection scheme. The proposed schemes have been simulated using PSCAD and MATLAB software and the results confirmed their validity.
Seyyed Mohammad Nobakhti; Abbas Ketabi; Miadreza Shafie-Khah. A New Impedance-Based Main and Backup Protection Scheme for Active Distribution Lines in AC Microgrids. Energies 2021, 14, 274 .
AMA StyleSeyyed Mohammad Nobakhti, Abbas Ketabi, Miadreza Shafie-Khah. A New Impedance-Based Main and Backup Protection Scheme for Active Distribution Lines in AC Microgrids. Energies. 2021; 14 (2):274.
Chicago/Turabian StyleSeyyed Mohammad Nobakhti; Abbas Ketabi; Miadreza Shafie-Khah. 2021. "A New Impedance-Based Main and Backup Protection Scheme for Active Distribution Lines in AC Microgrids." Energies 14, no. 2: 274.
The optimization of energy systems, including various kinds of energies, based on the concepts of energy hub (EH) has received a great deal of attention. Different methods have been introduced for optimization of EH’s operation, which considered the uncertainties of distributed renewable energy sources (DRESs). However, a knowledge gap exists in developing a stochastic optimization method, which comprehensively considers the uncertainties of DRESs and different configurations of EH due to outage of sub-systems. In existing methods, it has been assumed that the EH’s sub-systems are ideal and they are in-service every time. Therefore, most of the introduced methods have been developed based on the base configuration of EH, while all sub-systems are available. This paper tries to fill such a knowledge gap by proposing a new stochastic optimization method considering different configurations of EH due to N-1 contingency as well as DRESs’ uncertainties. The comparison of test results with other available deterministic and probabilistic methods that did not concern the different EH’s configurations illustrates the advantages of the proposed method. Test results show that more than 9 % inaccuracy might occur due to non-consideration of different EH’s configurations.
Jamal Faraji; Hamed Hashemi-Dezaki; Abbas Ketabi. Stochastic operation and scheduling of energy hub considering renewable energy sources’ uncertainty and N-1 contingency. Sustainable Cities and Society 2020, 65, 102578 .
AMA StyleJamal Faraji, Hamed Hashemi-Dezaki, Abbas Ketabi. Stochastic operation and scheduling of energy hub considering renewable energy sources’ uncertainty and N-1 contingency. Sustainable Cities and Society. 2020; 65 ():102578.
Chicago/Turabian StyleJamal Faraji; Hamed Hashemi-Dezaki; Abbas Ketabi. 2020. "Stochastic operation and scheduling of energy hub considering renewable energy sources’ uncertainty and N-1 contingency." Sustainable Cities and Society 65, no. : 102578.
Although much efforts have been devoted to the optimal design of the energy systems, there is a research gap about the multi-year load growth-based optimal planning of microgrids. This paper tries to fill such a research gap by developing a novel method for the optimal design of the grid-connected microgrids based on the long-term load demand forecasting. The multilayer perceptron artificial neural network is used for time-series load prediction. The impacts of the annual load growth are analyzed under various cases based on the consideration and determination methods of yearly load growth. The proposed method is applied to an actual microgrid in Tehran, Iran, using HOMER (Hybrid Optimization of Multiple Energy Resources) software. The load modeling’s capabilities of HOMER software, as a well-known software for the optimal design of energy systems, are used, which have received less attention. Since most existing research works in Iran focused on the off-grid operating mode, the study of an actual microgrid under grid-connected operating mode is one of the most contributions of this paper. The comparison of the obtained results and other available methods illustrate the impacts of the adequately precise estimation of annual load growth in the design of energy systems.
Jamal Faraji; Hamed Hashemi-Dezaki; Abbas Ketabi. Multi-year load growth-based optimal planning of grid-connected microgrid considering long-term load demand forecasting: A case study of Tehran, Iran. Sustainable Energy Technologies and Assessments 2020, 42, 100827 .
AMA StyleJamal Faraji, Hamed Hashemi-Dezaki, Abbas Ketabi. Multi-year load growth-based optimal planning of grid-connected microgrid considering long-term load demand forecasting: A case study of Tehran, Iran. Sustainable Energy Technologies and Assessments. 2020; 42 ():100827.
Chicago/Turabian StyleJamal Faraji; Hamed Hashemi-Dezaki; Abbas Ketabi. 2020. "Multi-year load growth-based optimal planning of grid-connected microgrid considering long-term load demand forecasting: A case study of Tehran, Iran." Sustainable Energy Technologies and Assessments 42, no. : 100827.
Prosumer microgrids (PMGs) are considered as active users in smart grids. These units are able to generate and sell electricity to aggregators or neighbor consumers in the prosumer market. Although the optimal scheduling and operation of PMGs have received a great deal of attention in recent studies, the challenges of PMG’s uncertainties such as stochastic behavior of load data and weather conditions (solar irradiance, ambient temperature, and wind speed) and corresponding solutions have not been thoroughly investigated. In this paper, a new energy management systems (EMS) based on weather and load forecasting is proposed for PMG’s optimal scheduling and operation. Developing a novel hybrid machine learning-based method using adaptive neuro-fuzzy inference system (ANFIS), multilayer perceptron (MLP) artificial neural network (ANN), and radial basis function (RBF) ANN to precisely predict the load and weather data is one of the most important contributions of this article. The performance of the forecasting process is improved by using a hybrid machine learning-based forecasting method instead of conventional ones. The demand response (DR) program based on the forecasted data and considering the degradation cost of the battery storage system (BSS) are other contributions. The comparison of obtained test results with those of other existing approaches illustrates that more appropriate PMG’s operation cost is achievable by applying the proposed DR-based EMS using a new hybrid machine learning forecasting method.
Jamal Faraji; Abbas Ketabi; Hamed Hashemi-Dezaki; Miadreza Shafie-Khah; Joao P. S. Catalao. Optimal Day-Ahead Self-Scheduling and Operation of Prosumer Microgrids Using Hybrid Machine Learning-Based Weather and Load Forecasting. IEEE Access 2020, 8, 157284 -157305.
AMA StyleJamal Faraji, Abbas Ketabi, Hamed Hashemi-Dezaki, Miadreza Shafie-Khah, Joao P. S. Catalao. Optimal Day-Ahead Self-Scheduling and Operation of Prosumer Microgrids Using Hybrid Machine Learning-Based Weather and Load Forecasting. IEEE Access. 2020; 8 (99):157284-157305.
Chicago/Turabian StyleJamal Faraji; Abbas Ketabi; Hamed Hashemi-Dezaki; Miadreza Shafie-Khah; Joao P. S. Catalao. 2020. "Optimal Day-Ahead Self-Scheduling and Operation of Prosumer Microgrids Using Hybrid Machine Learning-Based Weather and Load Forecasting." IEEE Access 8, no. 99: 157284-157305.
Uncertainties of renewable energy sources (RESs) such as wind turbine (WT) and photovoltaic (PV) units are one of the considerable challenges of prosumer microgrids (PMGs) for the optimal day‐ahead operation. In this study, a new probabilistic scenario‐based method of optimal scheduling and operation of PMGs is developed. In this regard, different scenarios are generated using Monte Carlo Simulations (MCS). Furthermore, k‐means, k‐medoids, and differential evolution algorithms (DEA) are deployed to cluster the scenarios in the proposed method. A realistic commercial PMG in Iran is selected to apply the introduced method. The validity of the developed probabilistic optimization method for PMG operation is examined by comparing the results under various scenario reduction algorithms and MCS ones. The comparison of the obtained results and those of other existing deterministic methods highlights the advantages of the presented method. Furthermore, the sensitivity analyses are carried out to investigate the robustness of the developed method against the increase in the system uncertainty level. According to the test results, it is concluded that the k‐medoids algorithm has the best performance in comparison with the k‐means and the DEA‐based clustering under various conditions.
Jamal Faraji; Hamed Hashemi‐Dezaki; Abbas Ketabi. Optimal probabilistic scenario‐based operation and scheduling of prosumer microgrids considering uncertainties of renewable energy sources. Energy Science & Engineering 2020, 8, 3942 -3960.
AMA StyleJamal Faraji, Hamed Hashemi‐Dezaki, Abbas Ketabi. Optimal probabilistic scenario‐based operation and scheduling of prosumer microgrids considering uncertainties of renewable energy sources. Energy Science & Engineering. 2020; 8 (11):3942-3960.
Chicago/Turabian StyleJamal Faraji; Hamed Hashemi‐Dezaki; Abbas Ketabi. 2020. "Optimal probabilistic scenario‐based operation and scheduling of prosumer microgrids considering uncertainties of renewable energy sources." Energy Science & Engineering 8, no. 11: 3942-3960.
The deployment of the energy storage systems by prosumers is steadily growing due to uncertainties of renewable energy resources. There is a knowledge gap about the techno-economic analysis of the loss of life (LOL) cost of the battery storage systems (BSSs) in the optimal day-ahead scheduling of the residential and commercial prosumers. This paper tries to fill such a research gap by proposing a novel optimization method for the day-ahead scheduling of prosumers, which considers the BSS LOL costs. The comparison of the proposed prosumers’ optimal scheduling method and other existing methods illustrates the techno-economic advantages of the introduced method. Different kinds of BSS technologies, i.e. Li-ion and Lead-acid, are studied in this paper. The proposed method is examined under different weather conditions and corresponding output power of renewable distributed generations. The sensitivity analysis is carried out to investigate how the changes in the BSS LOL cost affect the prosumers’ optimal costs and the operational decisions. The sensitivity analysis results infer that the effectiveness of the proposed method is highlighted when the BSS LOL costs are increased.
Jamal Faraji; Abbas Ketabi; Hamed Hashemi-Dezaki. Optimization of the scheduling and operation of prosumers considering the loss of life costs of battery storage systems. Journal of Energy Storage 2020, 31, 101655 .
AMA StyleJamal Faraji, Abbas Ketabi, Hamed Hashemi-Dezaki. Optimization of the scheduling and operation of prosumers considering the loss of life costs of battery storage systems. Journal of Energy Storage. 2020; 31 ():101655.
Chicago/Turabian StyleJamal Faraji; Abbas Ketabi; Hamed Hashemi-Dezaki. 2020. "Optimization of the scheduling and operation of prosumers considering the loss of life costs of battery storage systems." Journal of Energy Storage 31, no. : 101655.
Many efforts have been made to increase the utilization of renewable energy resources (RESs) in Iran. This paper aimed to evaluate the techno‐economic performance of an introduced hybrid microgrid (HMG) in eight climate zones of Iran. Therefore, ten cities are selected from the eight climate conditions of Iran. An electricity pricing strategy is also implemented according to the electricity tariffs defined by the Ministry of Energy (MOE) of Iran. The proposed electricity pricing strategy is applied to the HOMER software for investigating the optimal system configuration, RES electricity generation, and the economics of each understudy city. Optimization results indicate that Urmia (in moderate and rainy climate zone) has the least net present cost (NPC) (−5839$) and levelized cost of energy (COE) (−0.0122 $/kWh), whereas Golestan (in semimoderate and rainy climate zone) has the highest NPC (4520 $) and COE (0.012 $/kWh). It is shown that the combination of photovoltaic (PV)/wind turbine (WT)/converter in the grid‐connected operation mode is the most economical configuration. Moreover, the cities with higher potentials of wind speed and solar irradiance have lower NPC and COE. It is concluded that the utilization of the battery energy storage (BES) is technically and economically infeasible for all eight climate zones, even if the stored electricity is sold to the grid. Two sensitivity analyses are conducted to the electricity feed‐in‐tariff (FiT) and solar module price, respectively. The first sensitivity analysis indicates that by increasing FiT, more contribution of RESs is seen, which leads to lower COE and NPC. Furthermore, the two cities of Urmia and Yazd have the highest NPC and COE reductions. The second sensitivity analysis studies the module price impacts on the NPC and COE of each understudy city. It is revealed that the PV module price has a considerable effect on NPC and COE. However, this effect is more significant in some cities such as Bam, where a linear relationship is seen between the module price and economic results (NPC and COE).
Seyyed Ali Sadat; Jamal Faraji; Masoud Babaei; Abbas Ketabi. Techno‐economic comparative study of hybrid microgrids in eight climate zones of Iran. Energy Science & Engineering 2020, 8, 3004 -3026.
AMA StyleSeyyed Ali Sadat, Jamal Faraji, Masoud Babaei, Abbas Ketabi. Techno‐economic comparative study of hybrid microgrids in eight climate zones of Iran. Energy Science & Engineering. 2020; 8 (9):3004-3026.
Chicago/Turabian StyleSeyyed Ali Sadat; Jamal Faraji; Masoud Babaei; Abbas Ketabi. 2020. "Techno‐economic comparative study of hybrid microgrids in eight climate zones of Iran." Energy Science & Engineering 8, no. 9: 3004-3026.
This study suggests an adaptive and optimal control method to achieve the maximum power point tracking (MPPT) in the photovoltaic (PV) systems. For the maximum power transmission under varying the environmental conditions and partially shaded conditions, MPPT technologies are utilized in PV systems. For the improvement of functioning MPPT, a new four‐level control structure which decreases difficulty in the control process and efficiently deals with the uncertainties in the PV systems is introduced. The first one is a novel mechanism to estimate the reference voltage at a global maximum power point (GMPP), and an optimal and intelligent GMPP tracker (GMPPT) is employed as the last one. An extended state‐dependent Riccati equation (ESDRE) approach and fuzzy sliding mode control (FMSC) are selected as a GMPPT. The FMSC generates the duty cycle for the boost converter, and the ESDRE removes the underdamped and oscillatory response of PV systems. To verify the proposed method, several irradiation profiles that create several peaks (five peaks) in the P‐V curve are used. The simulation results show that the proposed method causes PV systems to track the GMPP immediately so that no oscillation around the GMPP is observed. Therefore, maximum efficiency can be derived from the PV system.
Mostafa Rahideh; Abbas Ketabi; Abolfazl Halvaei Niasar. State‐dependent Riccati equation–based MRAC and fuzzy sliding mode control for maximum power point tracking in partially shaded conditions in PV systems. International Transactions on Electrical Energy Systems 2019, 30, 1 .
AMA StyleMostafa Rahideh, Abbas Ketabi, Abolfazl Halvaei Niasar. State‐dependent Riccati equation–based MRAC and fuzzy sliding mode control for maximum power point tracking in partially shaded conditions in PV systems. International Transactions on Electrical Energy Systems. 2019; 30 (2):1.
Chicago/Turabian StyleMostafa Rahideh; Abbas Ketabi; Abolfazl Halvaei Niasar. 2019. "State‐dependent Riccati equation–based MRAC and fuzzy sliding mode control for maximum power point tracking in partially shaded conditions in PV systems." International Transactions on Electrical Energy Systems 30, no. 2: 1.
During recent years power systems are operated near the nominal capacity of system equipment with low stability margin. Operation of power systems in this condition is extremely risky and power systems lose their stability with any intense failure of system equipment. In bulk power system, it is more critical and may cause a partial or overall blackout. The capability of black start to bring back system to a normal condition in the case of partial or overall shut down is very important in each power system. When a shutdown occurs, power plants with black start capability supply cranking power for non-black start power plants, pick up critical loads and energize required transmission lines. These actions should be done in minimum time interval to maximize system provided energy during the restoration process. Most important decision making during restoration process is the determination of start-up sequence of generation units. During the restoration process, units with black start capability (BS units) start at the beginning of the process to provide cranking power for non-black start units (NBS units). Hence the determination of NBS units is decision variable in the restoration problem. In this paper, this problem has been described as a bi-level optimization problem which in upper level determines the optimal start-up sequence of NBS units by using a Teaching-Learning Based Optimization algorithm and in lower level determines the optimal transmission path with minimum number of switching and maximum reliability between any two necessary buses using the searching path graph-based algorithm. The proposed approach has been implemented successfully on IEEE 24-bus RTS and IEEE 118-bus test systems.
Abbas Ketabi; Amin Karimizadeh; Mohammad Shahidehpour. Optimal generation units start-up sequence during restoration of power system considering network reliability using bi-level optimization. International Journal of Electrical Power & Energy Systems 2018, 104, 772 -783.
AMA StyleAbbas Ketabi, Amin Karimizadeh, Mohammad Shahidehpour. Optimal generation units start-up sequence during restoration of power system considering network reliability using bi-level optimization. International Journal of Electrical Power & Energy Systems. 2018; 104 ():772-783.
Chicago/Turabian StyleAbbas Ketabi; Amin Karimizadeh; Mohammad Shahidehpour. 2018. "Optimal generation units start-up sequence during restoration of power system considering network reliability using bi-level optimization." International Journal of Electrical Power & Energy Systems 104, no. : 772-783.
In this paper an intelligent-based approach is introduced to evaluate harmonic overvoltages during three-phase transformer energization. In a power system that appears in an early stage of a black start of a power system, an overvoltage could be caused by core saturation on the energization of a three-phase transformer with residual flux. Such an overvoltage might damage some equipment and delay power system restoration. A new approach based on worst case determination is proposed to reduce time-domain simulations. Also, an artificial neural network (ANN) has been used to estimate the temporary overvoltages (TOVs) due to three-phase transformer energization. Three learning algorithms, delta-bar-delta (DBD), extended delta-bar-delta (EDBD), and directed random search (DRS), were used to train the ANNs. ANN Training is performed based on equivalent circuit parameters of the network; thus trained ANN is applicable to every studied system. The developed ANN is trained with the worst case of the switching condition and remanent flux, and tested for typical cases. The simulated results for a partial of 39-bus New England test system, show that the proposed technique can estimate the peak values and durations of switching overvoltages with good accuracy and EDBD algorithm presents best performance.
Iman Sadeghkhani; Abbas Ketabi; Rene Feuillet. Study of Transformer Switching Overvoltages during Power System Restoration Using Delta-Bar-Delta and Directed Random Search Algorithms. ENERGYO 2018, 1 .
AMA StyleIman Sadeghkhani, Abbas Ketabi, Rene Feuillet. Study of Transformer Switching Overvoltages during Power System Restoration Using Delta-Bar-Delta and Directed Random Search Algorithms. ENERGYO. 2018; ():1.
Chicago/Turabian StyleIman Sadeghkhani; Abbas Ketabi; Rene Feuillet. 2018. "Study of Transformer Switching Overvoltages during Power System Restoration Using Delta-Bar-Delta and Directed Random Search Algorithms." ENERGYO , no. : 1.
Overvoltages caused by switching operation of power system equipments might damage some equipment and delay power system restoration. This paper presents a comparison between transmission line (TL) models for overvoltages study and investigates which TL model is most proper for every case study. Both simulation time and accuracy factors of TL models are considered for selecting best TL model. Various cases of switching of transformer, shunt reactor, capacitor bank, and transmission line are investigated and simulation results for a partial of 39-bus New England test system, show that the proposed TL model evaluation increase accuracy and reduce simulation time (accelerate power system restoration) properly.
Iman Sadeghkhani; Abbas Ketabi; Rene Feuillet. Investigation of Transmission Line Models for Switching Overvoltages Studies. ENERGYO 2018, 1 .
AMA StyleIman Sadeghkhani, Abbas Ketabi, Rene Feuillet. Investigation of Transmission Line Models for Switching Overvoltages Studies. ENERGYO. 2018; ():1.
Chicago/Turabian StyleIman Sadeghkhani; Abbas Ketabi; Rene Feuillet. 2018. "Investigation of Transmission Line Models for Switching Overvoltages Studies." ENERGYO , no. : 1.
This paper presents an intelligent approach to evaluate switching overvoltages during power equipment energization. Switching action is one of the most important issues in power system restoration schemes. This action may lead to overvoltages that can damage some equipment and delay power system restoration. In this work, transient overvoltages caused by power equipment energization are analyzed and estimated using artificial neural network (ANN)-based approach. Three learning algorithms, delta-bar-delta (DBD), extended delta-bar-delta (EDBD), and directed random search (DRS), were used to train the ANNs. In the cases of transformer and shunt reactor energization, ANNs are trained with the worst case scenario of switching angle and remanent flux which reduce the number of required simulations for training ANN. Also, for achieving good generalization capability for developed ANN, equivalent parameters of the network are used as ANN inputs. The simulated results for a partial of 39-bus New England test system, show that the proposed technique can estimate the peak values and duration of switching overvoltages with good accuracy and EDBD algorithm presents best performance.
Iman Sadeghkhani; Abbas Ketabi; Rene Feuillet. The Study of Switching Overvoltages under Power System Restoration Scenario Using Extended Delta-Bar-Delta Algorithm. ENERGYO 2018, 1 .
AMA StyleIman Sadeghkhani, Abbas Ketabi, Rene Feuillet. The Study of Switching Overvoltages under Power System Restoration Scenario Using Extended Delta-Bar-Delta Algorithm. ENERGYO. 2018; ():1.
Chicago/Turabian StyleIman Sadeghkhani; Abbas Ketabi; Rene Feuillet. 2018. "The Study of Switching Overvoltages under Power System Restoration Scenario Using Extended Delta-Bar-Delta Algorithm." ENERGYO , no. : 1.
Microgrids are used widely in electric power systems for enhancing the power system operation in both grid-connected and island modes. One of the main problems with microgrid operations in power systems is maintaining the microgrid voltage and frequency within permissible ranges and sharing microgrid loads among participating distribution generations (DGs) in an island mode. The droop control method will pose a degraded performance when feeder impedances of DGs are different. In this study, a new control method based on the virtual impedance and the compensating voltage is proposed and the simulation results show that this method combined with the droop control will offer a balanced power sharing among DGs with negligible voltage and frequency drops. Here both single-bus and multi-bus microgrids with distributed loads have been considered. The simulation results are based on the MATLAB Simulink which shows that the proposed method has a good load sharing performance among DGs with varying feeder impedances and droop gains.
Abbas Ketabi; Sahba Sadat Rajamand; Mohammad Shahidehpour. Power sharing in parallel inverters with different types of loads. IET Generation, Transmission & Distribution 2017, 11, 2438 -2447.
AMA StyleAbbas Ketabi, Sahba Sadat Rajamand, Mohammad Shahidehpour. Power sharing in parallel inverters with different types of loads. IET Generation, Transmission & Distribution. 2017; 11 (10):2438-2447.
Chicago/Turabian StyleAbbas Ketabi; Sahba Sadat Rajamand; Mohammad Shahidehpour. 2017. "Power sharing in parallel inverters with different types of loads." IET Generation, Transmission & Distribution 11, no. 10: 2438-2447.
One of the most important challenges in modern protective requirements is in security and accuracy in the presence of different fluctuations in the network. Therefore, techniques with faster and more accurate estimations have to be developed to measure waveform phasors under steady-state and transient conditions. This paper proposes a new least error squares algorithm based on Taylor series to improve the performances of the phasor estimators. The accuracy is improved by using the fundamental phasor estimations and their estimated derivatives of Taylor series for the next step calculation. Then the proposed algorithm is evaluated through several simulations that specified in the Standard IEEE C37.118.1-2011 for different conditions. By using the proposed algorithm, a remarkable result is achieved in the presence of decaying DC component and harmonics. In addition, to demonstrate the performances of the proposed algorithm, a comparison with the conventional algorithms has also been presented.
Sh. Sadraeifar; H. Askarian Abyaneh; A. Ketabi; S.H.H. Sadeghi. A New Dynamic Synchrophasor Estimator for Digital Relaying. IETE Journal of Research 2017, 63, 1 -12.
AMA StyleSh. Sadraeifar, H. Askarian Abyaneh, A. Ketabi, S.H.H. Sadeghi. A New Dynamic Synchrophasor Estimator for Digital Relaying. IETE Journal of Research. 2017; 63 (6):1-12.
Chicago/Turabian StyleSh. Sadraeifar; H. Askarian Abyaneh; A. Ketabi; S.H.H. Sadeghi. 2017. "A New Dynamic Synchrophasor Estimator for Digital Relaying." IETE Journal of Research 63, no. 6: 1-12.
Underfrequency load shedding plays an important role in prevention of the power system blackout. The common load shedding methods are based on measuring the frequency first derivative; therefore, an error in measurement process can highly affect their performance. Also, for proper performance of these load shedding schemes, the exact value of some parameters of power system is needed. Any error in estimation of these parameters reduces the reliability of these load shedding schemes. In this paper, an underfrequency load shedding method based on the forecast minimum frequency of system is proposed. In this method, the samples of the power system frequency are taken after disturbance; then, particle swarm optimization algorithm is used to forecast the minimum frequency based on these samples. To verify the effectiveness of the proposed load shedding scheme, its performance has been compared with a newly suggested method
Abbas Ketabi; Masoud Hajiakbari Fini. Adaptive underfrequency load shedding using particle swarm optimization algorithm. Journal of Applied Research and Technology 2017, 15, 54 -60.
AMA StyleAbbas Ketabi, Masoud Hajiakbari Fini. Adaptive underfrequency load shedding using particle swarm optimization algorithm. Journal of Applied Research and Technology. 2017; 15 (1):54-60.
Chicago/Turabian StyleAbbas Ketabi; Masoud Hajiakbari Fini. 2017. "Adaptive underfrequency load shedding using particle swarm optimization algorithm." Journal of Applied Research and Technology 15, no. 1: 54-60.
One of the major challenges in protection of the inverter-interfaced islanded microgrids is their limited fault current level. This degrades the performance of traditional overcurrent protection schemes. This paper proposes a fault detection strategy based on monitoring the transient response of the inverter current waveform using a transient monitoring function (TMF). To enhance the ability of the proposed fault detection scheme, an auxiliary control system is employed in addition to the main control system of the inverter. The proposed scheme can also differentiate asymmetrical and symmetrical fault conditions from normal load switching events and is effective for various inverter topologies (i.e., three/four-leg), main current limiting strategies, and all reference frames of the multi-loop control system. The merits of the proposed fault detection scheme are demonstrated through several time-domain simulation case studies using the CIGRE benchmark low voltage microgrid network.
Iman Sadeghkhani; Mohamad Esmail Hamedani Golshan; Ali Mehrizi-Sani; Josep Guerrero; Abbas Ketabi. Transient Monitoring Function-Based Fault Detection for Inverter-Interfaced Microgrids. IEEE Transactions on Smart Grid 2016, 1 -1.
AMA StyleIman Sadeghkhani, Mohamad Esmail Hamedani Golshan, Ali Mehrizi-Sani, Josep Guerrero, Abbas Ketabi. Transient Monitoring Function-Based Fault Detection for Inverter-Interfaced Microgrids. IEEE Transactions on Smart Grid. 2016; (99):1-1.
Chicago/Turabian StyleIman Sadeghkhani; Mohamad Esmail Hamedani Golshan; Ali Mehrizi-Sani; Josep Guerrero; Abbas Ketabi. 2016. "Transient Monitoring Function-Based Fault Detection for Inverter-Interfaced Microgrids." IEEE Transactions on Smart Grid , no. 99: 1-1.
Abbas Ketabi; Ata Yadghar; Mohammad Javad Navardi. TORQUE AND RIPPLE IMPROVING OF A SR MOTOR USING ROBUST PARTICLE SWARM OPTIMIZATION OF DRIVE CURRENT AND DIMENSION. Progress In Electromagnetics Research M 2016, 45, 195 -207.
AMA StyleAbbas Ketabi, Ata Yadghar, Mohammad Javad Navardi. TORQUE AND RIPPLE IMPROVING OF A SR MOTOR USING ROBUST PARTICLE SWARM OPTIMIZATION OF DRIVE CURRENT AND DIMENSION. Progress In Electromagnetics Research M. 2016; 45 ():195-207.
Chicago/Turabian StyleAbbas Ketabi; Ata Yadghar; Mohammad Javad Navardi. 2016. "TORQUE AND RIPPLE IMPROVING OF A SR MOTOR USING ROBUST PARTICLE SWARM OPTIMIZATION OF DRIVE CURRENT AND DIMENSION." Progress In Electromagnetics Research M 45, no. : 195-207.