Frequency fluctuation is a major concern for the transmission system operators (TSO) or power gri... more Frequency fluctuation is a major concern for the transmission system operators (TSO) or power grid companies from the beginning of power system operation because it has some adverse effects on modern computer controlled industrial system, i.e., lamp flicker, inaccuracy of timing devices, etc. Because of huge penetration of wind power into the power grid, the frequency fluctuation is becoming a severe problem nowadays where randomly varying wind power causes the fluctuation of grid frequency of power system. Therefore, in this paper, the minimization of frequency fluctuation of power system including wind farm is proposed using energy capacitor system (ECS). A scaled down multi-machine power system model from Hokkaido prefecture, Japan, is considered for the analysis. A novel adaptive neural network (ANN) controller is considered for controlling the DC-bus connected ECS. The control objective is to smooth the line power of wind farm, taking into consideration the frequency deviation. The effects of wind power penetration levels as well as load variations are also analyzed. The proposed control method is verified by simulation analysis which is performed by PSCAD/EMTDC using real wind speed data. It is found that the adaptive neural network controlled ECS is an effective means to diminish the frequency fluctuation of multi-machine power system with connected wind farm. Index Terms-Energy capacitor system (ECS), electric double layer capacitor (EDLC), adaptive neural network (ANN), load frequency control (LFC), variable speed wind turbine (VSWT), permanent magnet synchronous generator (PMSG).
Permanent Magnet Synchronous Motors (PMSMs) have been replacing conventional DC motors in numerou... more Permanent Magnet Synchronous Motors (PMSMs) have been replacing conventional DC motors in numerous automotive applications. One of which is Electrically Power Assisted Steering Systems (EPAS). PMSMs offer better performance and a longer lifetime while slightly increasing the system's cost and complexity. In a vector-controlled PMSM drive system, the rotor position sensor's resolution plays a vital role in the overall system performance. The better the resolution, the higher the cost. Although numerous sensor-less control algorithms currently exist, machine startup and operation with dynamically changing set-points and loads still impose a challenge for such an approach. For this reason, inexpensive Hall-Effect sensors have been recently used along with a proper position estimation algorithm to provide high-resolution rotor position. In this paper, an implementation of a vector-controlled drive system is applied to an EPAS using only low-resolution Hall-Effect sensors. Additionally, an improved rotor position estimation algorithm based on speed integration is developed to decrease estimation errors and torque ripples in the case of direction reversal. This is to cater to the dynamically changing commands encountered during the normal power assist operation. Comparisons of the proposed rotor position estimation system with the conventional technique are introduced. A complete representation of the proposed system is built using MATLAB/Simulink. An experimental setup is developed and built around a Motor-Driven Power Steering (MDPS) unit which is a column-assist type EPAS system made by Hyundai Mobis. The simulation and experimental results are presented to verify and evaluate the effectiveness of the proposed algorithm.
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Tremendous penetration of photovoltaic (PV) systems into the electric grids develops many challen... more Tremendous penetration of photovoltaic (PV) systems into the electric grids develops many challenges in the modern power systems. In the simulation analyses of PV systems, accurate modelling of PV modules plays a crucial role in enhancing the characteristics of such systems. Modelling of such PVs is represented by a non-linear I-V behavior, involving various unknown parameters because of the inadequate data offered in the datasheet of PV cells. This paper proposes a novel implementation of the equilibrium optimizer algorithm (EOA) to identify the nine-parameters of a three-diode (TD) model of a PV module. Soundness of the EOA-TD model is extensively confirmed by the simulation results that are carried out in different environmental conditions. The optimal parameters obtained using the proposed approach are compared with those realized using other optimization techniques-based TD models. To achieve a practical study, the simulation and experimental outcomes are checked for various commercial PV panels and the error among these results records a value less than 0.5%. Moreover, the optimal parameters attained using the EOA are competitive and very close to that realized using other approaches, where the offered EOA has exhibited a minimum fitness value of 1.14e-14 and 7.154 e-13 for Kyocera and Solarex marketable PV cells, respectively. The effectiveness of the proposed TD PV model is adequately assessed by evaluating its absolute current error (ACE) with the ACE in different PV models. The EOA technology is considered to be an accurate means of achieving the proper modelling of any commercial PV module.
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
The precise electrical modeling of photovoltaic (PV) module is crucial due to the large-scale per... more The precise electrical modeling of photovoltaic (PV) module is crucial due to the large-scale permeation of PV power plants into electric power networks. Therefore, a triple-diode photovoltaic (TDPV) model is presented to address all PV losses. However, the TDPV is mathematically modelled by a nonlinear I-V behavior, including nine-parameters that cannot be directly determined from the PVs datasheet due to the lack data offered by the PV manufacturers. This article presents a new application of the marine predators algorithm (MPA) to properly extract the electrical parameters of the TDPV model of a PV panel. The validity of the MPA-based TDPV model is widely appraised by the numerical analyses, which are carried out under various temperatures and solar irradiations. The optimal nine-parameters achieved using the MPA are compared with that realized by different optimization approaches-based PV model. For a realistic study, the numerical results and the measured data are compared for the marketable Kyocera KC200GT and Solarex MSX-60 PV panels. The efficacy of the MPA-based TDPV model is properly executed by checking its current error with that obtained from various models. With the MPA technology, a highly accurate model of any marketable PV module can be attained, which represents a new contribution to the sector of PV power systems. INDEX TERMS Marine predators algorithm, photovoltaic modeling, photovoltaic power systems, solar energy, triple-diode model.
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
This paper proposes a novel approach for testing dynamics and control aspects of a large scale ph... more This paper proposes a novel approach for testing dynamics and control aspects of a large scale photovoltaic (PV) system in real time along with resolving design hindrances of controller parameters using Real Time Digital Simulator (RTDS). In general, the harmonic profile of a fast controller has wide distribution due to the large bandwidth of the controller. The major contribution of this paper is that the proposed control strategy gives an improved voltage harmonic profile and distribute it more around the switching frequency along with fast transient response; filter design, thus, becomes easier. The implementation of a control strategy with high bandwidth in small time steps of Real Time Digital Simulator (RTDS) is not straight forward. This paper shows a good methodology for the practitioners to implement such control scheme in RTDS. As a part of the industrial process, the controller parameters are optimized using particle swarm optimization (PSO) technique to improve the low voltage ride through (LVRT) performance under network disturbance. The response surface methodology (RSM) is well adapted to build analytical models for recovery time (Rt), maximum percentage overshoot (MPOS), settling time (Ts), and steady state error (Ess) of the voltage profile immediate after inverter under disturbance. A systematic approach of controller parameter optimization is detailed. The transient performance of the PSO based optimization method applied to the proposed sliding mode controlled PV inverter is compared with the results from genetic algorithm (GA) based optimization technique. The reported real time implementation challenges and controller optimization procedure are applicable to other control applications in the field of renewable and distributed generation systems. Index Terms-Current control scheme, DC-AC power converter, DC-DC power converter, parameter optimization, low voltage ride through, power system transients, photovoltaic system, sliding mode controller.
Electric Power Components and Systems, Jun 13, 2015
This paper presents a novel application of the particle swarm optimization (PSO) technique to opt... more This paper presents a novel application of the particle swarm optimization (PSO) technique to optimally design all the proportional-integral (PI) controllers required to control both the real and reactive powers of the superconducting magnetic energy storage (SMES) unit for enhancing the low voltage ride through (LVRT) capability of a grid-connected wind farm. The control strategy of the SMES system is based on a sinusoidal pulse width modulation (PWM) voltage source converter (VSC) and PI-controlled DC-DC converter. The control of VSC depends on the cascaded PI control scheme. All the PI controllers in the SMES system are optimally designed by the PSO technique. The statistical response surface methodology (RSM) is used to build the mathematical model of the voltage responses at the point of common coupling (PCC) in terms of PI controllers' parameters. The effectiveness of the PI-controlled SMES optimized by the proposed PSO technique is then compared to that optimized by genetic algorithms (GA) technique taking into consideration symmetrical and unsymmetrical fault conditions. Two-mass drive train model is used for the wind turbine generator system because of its large influence on the fault analyses. The paper demonstrates the systemic design approach in determining the controller parameters of SMES unit and validates its effectiveness in augmenting the LVRT of grid-connected wind farm.
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
The appropriate planning of electric power systems has a significant effect on the economic situa... more The appropriate planning of electric power systems has a significant effect on the economic situation of countries. For the protection and reliability of the power system, the optimal reactive power dispatch (ORPD) problem is an essential issue. The ORPD is a non-linear, non-convex, and continuous or non-continuous optimization problem. Therefore, introducing a reliable optimizer is a challenging task to solve this optimization problem. This study proposes a robust and flexible optimization algorithm with the minimum adjustable parameters named Improved Marine Predators Algorithm and Particle Swarm Optimization (IMPAPSO) algorithm, for dealing with the non-linearity of ORPD. The IMPAPSO is evaluated using various test cases, including IEEE 30 bus, IEEE 57 bus, and IEEE 118 bus systems. An effectiveness of the proposed optimization algorithm was verified through a rigorous comparative study with other optimization methods. There was a noticeable enhancement in the electric power networks behavior when using the IMPAPSO method. Moreover, the IMPAPSO high convergence speed was an observed feature in a comparison with its peers.
Iet Generation Transmission & Distribution, Dec 1, 2015
This paper presents a novel adaptive control scheme for variable-speed wind turbine (VSWT) driven... more This paper presents a novel adaptive control scheme for variable-speed wind turbine (VSWT) driven permanent magnet synchronous generator (PMSG) to ensure its operation under different operating conditions. The adaptive control scheme is based on the affine projection algorithm (APA) which provides a faster convergence and less computational complexity than the least-mean-square algorithm. The proposed adaptive controller is used to control both the generatorside converter and the grid-side inverter without giving additional tuning efforts. Each vector control scheme for the converter/inverter has four APA-based adaptive proportional-integral (PI) controllers. Detailed modeling and the control strategies of the system under study are demonstrated. Real wind speed data extracted from Hokkaido island, Japan is used in this study. The dynamic characteristics of a grid-connected VSWT-PMSG are investigated in details to ensure the proposed controller operation under different operating conditions. The effectiveness of the proposed adaptive controller is compared with that obtained using optimized PI controllers by Taguchi method. The validity of the adaptive vector control scheme is verified by the simulation results which are performed using PSCAD/EMTDC environment.
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
In wind energy conversion system, variable speed operation is becoming popular nowadays, where co... more In wind energy conversion system, variable speed operation is becoming popular nowadays, where conventional synchronous generators, permanent magnet synchronous generators, and doubly fed induction generators are commercially used as wind generators. Along with the existing and classical solutions of the aforementioned machines used in wind power applications, the switched reluctance generator (SRG) can also be considered as a wind generator due to its inherent characteristics such as simple construction, robustness, low manufacturing cost, etc. This paper presents a novel speed control of switched reluctance generator (SRG) by using adaptive neural network (ANN) controller. The SRG is driven by variable speed wind turbine and it is connected to the grid through an asymmetric half bridge converter, DC-link, and DC-AC inverter system. Speed control is very important for variable speed operation of SRG to ensure maximum power delivery to the grid for any particular wind speed. Detailed modeling and control strategies of SRG as well as other individual components including wind turbine, converter, and inverter systems are presented. The effectiveness of the proposed system is verified with simulation results using the real wind speed data measured at Hokkaido Island, Japan. The dynamic simulation study is carried out using PSCAD/EMTDC.
IEEE Transactions on Sustainable Energy, Apr 1, 2012
This paper presents an optimum design procedure for the controller used in the frequency converte... more This paper presents an optimum design procedure for the controller used in the frequency converter of a variable speed wind turbine (VSWT) driven permanent magnet synchronous generator (PMSG) by using genetic algorithms (GAs) and response surface methodology (RSM). The cascaded control is frequently used in the control of the frequency converter using the proportional plus integral (PI) controllers. The setting of the parameters of the PI controller used in a large system is cumbersome, especially in an electrical power system, which is difficult to be expressed by a mathematical model or transfer function. This study attempts to optimally design the parameters of the PI controllers used in the frequency converter of a variable speed wind energy conversion system (WECS). The effectiveness of the designed parameters using GAs-RSM is then compared with that obtained using a generalized reduced gradient (GRG) algorithm considering both symmetrical and unsymmetrical faults. The permanent fault condition due to unsuccessful reclosing of circuit breakers is considered as well. It represents another salient feature of this study. It is found that fault-ride-through of VSWT-PMSG can be improved considerably using the parameters of its frequency converter obtained from GAs-RSM.
This paper develops a novel methodology for optimal control of islanded microgrids (MGs) based on... more This paper develops a novel methodology for optimal control of islanded microgrids (MGs) based on the coot bird metaheuristic optimizer (CBMO). To this end, the optimum gains for the PI controller are found using the CBMO under a multi-objective optimization framework. The Response Surface Methodology (RSM) is incorporated into the developed procedure to achieve a compromise solution among the different objectives. To prove the effectiveness of the new proposal, a benchmark MG is tested under various scenarios, 1) isolate the system from the grid (autonomous mode), 2) islanded system exposure to load changes, and 3) islanded system exposure to a 3 phase fault. Extensive simulations are performed to validate the new method taking conventional data from PSCAD/EMTDC software. The validity of the suggested optimizer is proved by comparing its results with that achieved using the LMSRE-based adaptive control, sunflower optimization algorithm (SFO), Ziegler-Nichols method and the particle swarm optimization (PSO) techniques. The article shows the superiority of the suggested CBMO over the LMSRE-based adaptive control, SFO, Ziegler-Nichols and the PSO techniques in the transient responses of the system. INDEX TERMS Distributed generators, sunflower optimization algorithm, microgrid, renewable energy, coot bird metaheuristic optimizer.
International Transactions on Electrical Energy Systems, 2020
This paper presents a comprehensive analytical study of conventional proportional-integral-deriva... more This paper presents a comprehensive analytical study of conventional proportional-integral-derivative (PID) controller and fuzzy logic controller in a hybrid micro-grid system (HMGS) for frequency stabilization. Conventional PID and fuzzy logic controllers are tuned by the competition over resources (COR) algorithm. The performance of proposed COR based fuzzy tilt-integral-derivative with filter (FTIDF) method is demonstrated on an interconnected HMGS. HMGS completes with variety of energy storage systems and different renewable generation sources. The system analysis is performed under number of scenarios. The scenarios include load fluctuations, variations in wind speed, and sun irradiance. The supremacy of FTIDF controller is established by comparing the results with CRO tuned conventional PID with filter (PIDF), fuzzy PIDF and fuzzy TIDF controllers. The effectiveness of the proposed system is investigated using simulation studies, which are performed using MATLAB/ SIMULINK software. K E Y W O R D S competition over resources (COR), energy storage system (ESS), hybrid micro-grid system (HMGS), load frequency control (LFC)
Abstract This paper proposes an enhancement of the meta-heuristic whale optimization algorithm (W... more Abstract This paper proposes an enhancement of the meta-heuristic whale optimization algorithm (WOA) for maximum power point tracking (MPPT) of variable-speed wind generators. First of all, twenty-three benchmark functions tested the enhanced whale optimization algorithm (EWOA). Then the statistical results of EWOA compared with the results of other algorithms (WOA, salp swarm algorithm (SSA), enhanced SSA (ESSA), grey wolf optimizer (GWO), augmented GWO (AGWO), and particle swarm optimization (PSO). Also, the non-parametric statistical test and convergence curves proved the superiority and the speed of the EWOA. After that, the EWOA and WOA are implemented to design optimal Takagi–Sugeno fuzzy logic controllers (FLCs) to enhance the MPPT control of variable-speed wind generators. Moreover, real wind speed data has confirmed the robustness of optimal EWOA-MPPT. In conclusion, the simulation results revealed that the EWOA is a promising algorithm to be applied for solving different engineering problems.
Frequency fluctuation is a major concern for the transmission system operators (TSO) or power gri... more Frequency fluctuation is a major concern for the transmission system operators (TSO) or power grid companies from the beginning of power system operation because it has some adverse effects on modern computer controlled industrial system, i.e., lamp flicker, inaccuracy of timing devices, etc. Because of huge penetration of wind power into the power grid, the frequency fluctuation is becoming a severe problem nowadays where randomly varying wind power causes the fluctuation of grid frequency of power system. Therefore, in this paper, the minimization of frequency fluctuation of power system including wind farm is proposed using energy capacitor system (ECS). A scaled down multi-machine power system model from Hokkaido prefecture, Japan, is considered for the analysis. A novel adaptive neural network (ANN) controller is considered for controlling the DC-bus connected ECS. The control objective is to smooth the line power of wind farm, taking into consideration the frequency deviation. The effects of wind power penetration levels as well as load variations are also analyzed. The proposed control method is verified by simulation analysis which is performed by PSCAD/EMTDC using real wind speed data. It is found that the adaptive neural network controlled ECS is an effective means to diminish the frequency fluctuation of multi-machine power system with connected wind farm. Index Terms-Energy capacitor system (ECS), electric double layer capacitor (EDLC), adaptive neural network (ANN), load frequency control (LFC), variable speed wind turbine (VSWT), permanent magnet synchronous generator (PMSG).
Permanent Magnet Synchronous Motors (PMSMs) have been replacing conventional DC motors in numerou... more Permanent Magnet Synchronous Motors (PMSMs) have been replacing conventional DC motors in numerous automotive applications. One of which is Electrically Power Assisted Steering Systems (EPAS). PMSMs offer better performance and a longer lifetime while slightly increasing the system's cost and complexity. In a vector-controlled PMSM drive system, the rotor position sensor's resolution plays a vital role in the overall system performance. The better the resolution, the higher the cost. Although numerous sensor-less control algorithms currently exist, machine startup and operation with dynamically changing set-points and loads still impose a challenge for such an approach. For this reason, inexpensive Hall-Effect sensors have been recently used along with a proper position estimation algorithm to provide high-resolution rotor position. In this paper, an implementation of a vector-controlled drive system is applied to an EPAS using only low-resolution Hall-Effect sensors. Additionally, an improved rotor position estimation algorithm based on speed integration is developed to decrease estimation errors and torque ripples in the case of direction reversal. This is to cater to the dynamically changing commands encountered during the normal power assist operation. Comparisons of the proposed rotor position estimation system with the conventional technique are introduced. A complete representation of the proposed system is built using MATLAB/Simulink. An experimental setup is developed and built around a Motor-Driven Power Steering (MDPS) unit which is a column-assist type EPAS system made by Hyundai Mobis. The simulation and experimental results are presented to verify and evaluate the effectiveness of the proposed algorithm.
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Tremendous penetration of photovoltaic (PV) systems into the electric grids develops many challen... more Tremendous penetration of photovoltaic (PV) systems into the electric grids develops many challenges in the modern power systems. In the simulation analyses of PV systems, accurate modelling of PV modules plays a crucial role in enhancing the characteristics of such systems. Modelling of such PVs is represented by a non-linear I-V behavior, involving various unknown parameters because of the inadequate data offered in the datasheet of PV cells. This paper proposes a novel implementation of the equilibrium optimizer algorithm (EOA) to identify the nine-parameters of a three-diode (TD) model of a PV module. Soundness of the EOA-TD model is extensively confirmed by the simulation results that are carried out in different environmental conditions. The optimal parameters obtained using the proposed approach are compared with those realized using other optimization techniques-based TD models. To achieve a practical study, the simulation and experimental outcomes are checked for various commercial PV panels and the error among these results records a value less than 0.5%. Moreover, the optimal parameters attained using the EOA are competitive and very close to that realized using other approaches, where the offered EOA has exhibited a minimum fitness value of 1.14e-14 and 7.154 e-13 for Kyocera and Solarex marketable PV cells, respectively. The effectiveness of the proposed TD PV model is adequately assessed by evaluating its absolute current error (ACE) with the ACE in different PV models. The EOA technology is considered to be an accurate means of achieving the proper modelling of any commercial PV module.
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
The precise electrical modeling of photovoltaic (PV) module is crucial due to the large-scale per... more The precise electrical modeling of photovoltaic (PV) module is crucial due to the large-scale permeation of PV power plants into electric power networks. Therefore, a triple-diode photovoltaic (TDPV) model is presented to address all PV losses. However, the TDPV is mathematically modelled by a nonlinear I-V behavior, including nine-parameters that cannot be directly determined from the PVs datasheet due to the lack data offered by the PV manufacturers. This article presents a new application of the marine predators algorithm (MPA) to properly extract the electrical parameters of the TDPV model of a PV panel. The validity of the MPA-based TDPV model is widely appraised by the numerical analyses, which are carried out under various temperatures and solar irradiations. The optimal nine-parameters achieved using the MPA are compared with that realized by different optimization approaches-based PV model. For a realistic study, the numerical results and the measured data are compared for the marketable Kyocera KC200GT and Solarex MSX-60 PV panels. The efficacy of the MPA-based TDPV model is properly executed by checking its current error with that obtained from various models. With the MPA technology, a highly accurate model of any marketable PV module can be attained, which represents a new contribution to the sector of PV power systems. INDEX TERMS Marine predators algorithm, photovoltaic modeling, photovoltaic power systems, solar energy, triple-diode model.
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
This paper proposes a novel approach for testing dynamics and control aspects of a large scale ph... more This paper proposes a novel approach for testing dynamics and control aspects of a large scale photovoltaic (PV) system in real time along with resolving design hindrances of controller parameters using Real Time Digital Simulator (RTDS). In general, the harmonic profile of a fast controller has wide distribution due to the large bandwidth of the controller. The major contribution of this paper is that the proposed control strategy gives an improved voltage harmonic profile and distribute it more around the switching frequency along with fast transient response; filter design, thus, becomes easier. The implementation of a control strategy with high bandwidth in small time steps of Real Time Digital Simulator (RTDS) is not straight forward. This paper shows a good methodology for the practitioners to implement such control scheme in RTDS. As a part of the industrial process, the controller parameters are optimized using particle swarm optimization (PSO) technique to improve the low voltage ride through (LVRT) performance under network disturbance. The response surface methodology (RSM) is well adapted to build analytical models for recovery time (Rt), maximum percentage overshoot (MPOS), settling time (Ts), and steady state error (Ess) of the voltage profile immediate after inverter under disturbance. A systematic approach of controller parameter optimization is detailed. The transient performance of the PSO based optimization method applied to the proposed sliding mode controlled PV inverter is compared with the results from genetic algorithm (GA) based optimization technique. The reported real time implementation challenges and controller optimization procedure are applicable to other control applications in the field of renewable and distributed generation systems. Index Terms-Current control scheme, DC-AC power converter, DC-DC power converter, parameter optimization, low voltage ride through, power system transients, photovoltaic system, sliding mode controller.
Electric Power Components and Systems, Jun 13, 2015
This paper presents a novel application of the particle swarm optimization (PSO) technique to opt... more This paper presents a novel application of the particle swarm optimization (PSO) technique to optimally design all the proportional-integral (PI) controllers required to control both the real and reactive powers of the superconducting magnetic energy storage (SMES) unit for enhancing the low voltage ride through (LVRT) capability of a grid-connected wind farm. The control strategy of the SMES system is based on a sinusoidal pulse width modulation (PWM) voltage source converter (VSC) and PI-controlled DC-DC converter. The control of VSC depends on the cascaded PI control scheme. All the PI controllers in the SMES system are optimally designed by the PSO technique. The statistical response surface methodology (RSM) is used to build the mathematical model of the voltage responses at the point of common coupling (PCC) in terms of PI controllers' parameters. The effectiveness of the PI-controlled SMES optimized by the proposed PSO technique is then compared to that optimized by genetic algorithms (GA) technique taking into consideration symmetrical and unsymmetrical fault conditions. Two-mass drive train model is used for the wind turbine generator system because of its large influence on the fault analyses. The paper demonstrates the systemic design approach in determining the controller parameters of SMES unit and validates its effectiveness in augmenting the LVRT of grid-connected wind farm.
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
The appropriate planning of electric power systems has a significant effect on the economic situa... more The appropriate planning of electric power systems has a significant effect on the economic situation of countries. For the protection and reliability of the power system, the optimal reactive power dispatch (ORPD) problem is an essential issue. The ORPD is a non-linear, non-convex, and continuous or non-continuous optimization problem. Therefore, introducing a reliable optimizer is a challenging task to solve this optimization problem. This study proposes a robust and flexible optimization algorithm with the minimum adjustable parameters named Improved Marine Predators Algorithm and Particle Swarm Optimization (IMPAPSO) algorithm, for dealing with the non-linearity of ORPD. The IMPAPSO is evaluated using various test cases, including IEEE 30 bus, IEEE 57 bus, and IEEE 118 bus systems. An effectiveness of the proposed optimization algorithm was verified through a rigorous comparative study with other optimization methods. There was a noticeable enhancement in the electric power networks behavior when using the IMPAPSO method. Moreover, the IMPAPSO high convergence speed was an observed feature in a comparison with its peers.
Iet Generation Transmission & Distribution, Dec 1, 2015
This paper presents a novel adaptive control scheme for variable-speed wind turbine (VSWT) driven... more This paper presents a novel adaptive control scheme for variable-speed wind turbine (VSWT) driven permanent magnet synchronous generator (PMSG) to ensure its operation under different operating conditions. The adaptive control scheme is based on the affine projection algorithm (APA) which provides a faster convergence and less computational complexity than the least-mean-square algorithm. The proposed adaptive controller is used to control both the generatorside converter and the grid-side inverter without giving additional tuning efforts. Each vector control scheme for the converter/inverter has four APA-based adaptive proportional-integral (PI) controllers. Detailed modeling and the control strategies of the system under study are demonstrated. Real wind speed data extracted from Hokkaido island, Japan is used in this study. The dynamic characteristics of a grid-connected VSWT-PMSG are investigated in details to ensure the proposed controller operation under different operating conditions. The effectiveness of the proposed adaptive controller is compared with that obtained using optimized PI controllers by Taguchi method. The validity of the adaptive vector control scheme is verified by the simulation results which are performed using PSCAD/EMTDC environment.
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
In wind energy conversion system, variable speed operation is becoming popular nowadays, where co... more In wind energy conversion system, variable speed operation is becoming popular nowadays, where conventional synchronous generators, permanent magnet synchronous generators, and doubly fed induction generators are commercially used as wind generators. Along with the existing and classical solutions of the aforementioned machines used in wind power applications, the switched reluctance generator (SRG) can also be considered as a wind generator due to its inherent characteristics such as simple construction, robustness, low manufacturing cost, etc. This paper presents a novel speed control of switched reluctance generator (SRG) by using adaptive neural network (ANN) controller. The SRG is driven by variable speed wind turbine and it is connected to the grid through an asymmetric half bridge converter, DC-link, and DC-AC inverter system. Speed control is very important for variable speed operation of SRG to ensure maximum power delivery to the grid for any particular wind speed. Detailed modeling and control strategies of SRG as well as other individual components including wind turbine, converter, and inverter systems are presented. The effectiveness of the proposed system is verified with simulation results using the real wind speed data measured at Hokkaido Island, Japan. The dynamic simulation study is carried out using PSCAD/EMTDC.
IEEE Transactions on Sustainable Energy, Apr 1, 2012
This paper presents an optimum design procedure for the controller used in the frequency converte... more This paper presents an optimum design procedure for the controller used in the frequency converter of a variable speed wind turbine (VSWT) driven permanent magnet synchronous generator (PMSG) by using genetic algorithms (GAs) and response surface methodology (RSM). The cascaded control is frequently used in the control of the frequency converter using the proportional plus integral (PI) controllers. The setting of the parameters of the PI controller used in a large system is cumbersome, especially in an electrical power system, which is difficult to be expressed by a mathematical model or transfer function. This study attempts to optimally design the parameters of the PI controllers used in the frequency converter of a variable speed wind energy conversion system (WECS). The effectiveness of the designed parameters using GAs-RSM is then compared with that obtained using a generalized reduced gradient (GRG) algorithm considering both symmetrical and unsymmetrical faults. The permanent fault condition due to unsuccessful reclosing of circuit breakers is considered as well. It represents another salient feature of this study. It is found that fault-ride-through of VSWT-PMSG can be improved considerably using the parameters of its frequency converter obtained from GAs-RSM.
This paper develops a novel methodology for optimal control of islanded microgrids (MGs) based on... more This paper develops a novel methodology for optimal control of islanded microgrids (MGs) based on the coot bird metaheuristic optimizer (CBMO). To this end, the optimum gains for the PI controller are found using the CBMO under a multi-objective optimization framework. The Response Surface Methodology (RSM) is incorporated into the developed procedure to achieve a compromise solution among the different objectives. To prove the effectiveness of the new proposal, a benchmark MG is tested under various scenarios, 1) isolate the system from the grid (autonomous mode), 2) islanded system exposure to load changes, and 3) islanded system exposure to a 3 phase fault. Extensive simulations are performed to validate the new method taking conventional data from PSCAD/EMTDC software. The validity of the suggested optimizer is proved by comparing its results with that achieved using the LMSRE-based adaptive control, sunflower optimization algorithm (SFO), Ziegler-Nichols method and the particle swarm optimization (PSO) techniques. The article shows the superiority of the suggested CBMO over the LMSRE-based adaptive control, SFO, Ziegler-Nichols and the PSO techniques in the transient responses of the system. INDEX TERMS Distributed generators, sunflower optimization algorithm, microgrid, renewable energy, coot bird metaheuristic optimizer.
International Transactions on Electrical Energy Systems, 2020
This paper presents a comprehensive analytical study of conventional proportional-integral-deriva... more This paper presents a comprehensive analytical study of conventional proportional-integral-derivative (PID) controller and fuzzy logic controller in a hybrid micro-grid system (HMGS) for frequency stabilization. Conventional PID and fuzzy logic controllers are tuned by the competition over resources (COR) algorithm. The performance of proposed COR based fuzzy tilt-integral-derivative with filter (FTIDF) method is demonstrated on an interconnected HMGS. HMGS completes with variety of energy storage systems and different renewable generation sources. The system analysis is performed under number of scenarios. The scenarios include load fluctuations, variations in wind speed, and sun irradiance. The supremacy of FTIDF controller is established by comparing the results with CRO tuned conventional PID with filter (PIDF), fuzzy PIDF and fuzzy TIDF controllers. The effectiveness of the proposed system is investigated using simulation studies, which are performed using MATLAB/ SIMULINK software. K E Y W O R D S competition over resources (COR), energy storage system (ESS), hybrid micro-grid system (HMGS), load frequency control (LFC)
Abstract This paper proposes an enhancement of the meta-heuristic whale optimization algorithm (W... more Abstract This paper proposes an enhancement of the meta-heuristic whale optimization algorithm (WOA) for maximum power point tracking (MPPT) of variable-speed wind generators. First of all, twenty-three benchmark functions tested the enhanced whale optimization algorithm (EWOA). Then the statistical results of EWOA compared with the results of other algorithms (WOA, salp swarm algorithm (SSA), enhanced SSA (ESSA), grey wolf optimizer (GWO), augmented GWO (AGWO), and particle swarm optimization (PSO). Also, the non-parametric statistical test and convergence curves proved the superiority and the speed of the EWOA. After that, the EWOA and WOA are implemented to design optimal Takagi–Sugeno fuzzy logic controllers (FLCs) to enhance the MPPT control of variable-speed wind generators. Moreover, real wind speed data has confirmed the robustness of optimal EWOA-MPPT. In conclusion, the simulation results revealed that the EWOA is a promising algorithm to be applied for solving different engineering problems.
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Papers by Hany Hasanien