Switched Reluctance Motor (SRM) has become popular in various applications because of its high to... more Switched Reluctance Motor (SRM) has become popular in various applications because of its high torque to inertia ratio, high efficiency, variable speed operation capabilities. The SRM primary drawback is torque ripples in the developed torque leading to notable noise and vibrations. Large torque ripples in SRM are due to the switching currents into its stator coils and its nonlinear magnetic nature during operation. By controlling and monitoring the torque of the SRM a significant decrease in torque ripples and even motor efficiency improvement can be carried out. In this study, two stochastic-based optimal PI controllers are used for speed control of an 8/6 SRM Model using MATLAB/Simulink tool with three types of torque sharing functions for torque ripple reduction and achieving overall performance improvement.
EPS (Electric power system) of the satellite is a critical aspect for the success of the satellit... more EPS (Electric power system) of the satellite is a critical aspect for the success of the satellite mission, likewise the optimum usage of the available power resources for the satellite EPS is the main key of success for the system design process. Furthermore, implementing the modular concept in the design of the satellite EPS improves the reliability and quality of the design and makes the platform adaptable for various missions and payloads. Optimizing the usage of solar array output power during beginning of life and exiting from shadow periods while there are excess of power from the solar arrays stabilizes the bus voltage within the required designed margins and consequently protects all satellite loads connected to the main bus. A hybrid modular configuration is proposed including linear and non-linear regulation for implementing the sequential switching shunt regulation of the solar array output power, the proposed configuration employs the fuzzy logic concept to issue the switching pattern for the solar array sections subjected to the error signal in the feedback loop of the bus voltage. Moreover, a simulation is performed for the three domain control concept of the EPS demonstrating how the bus voltage levels decide the operating domain of the EPS.
Optimum usage of the available resources for the spacecraft electric power system is the main key... more Optimum usage of the available resources for the spacecraft electric power system is the main key for success for the satellite EPS design process. Furthermore, implementing modular design of the satellite EPS improves the operation of the satellite because it (i) enables the EPS to work on different power levels, (ii) enhances the EPS integration with various payloads, and (iii) decreases design modifications required to operate the EPS on missions regardless of the height and duration of these missions. A new method for controlling the output power of the satellite solar arrays is proposed in this paper. The proposed method depends on a hybrid modular configuration where the output power of the solar arrays is controlled by linear and non-linear regulations. Moreover, the proposed hybrid configuration is implemented on a microcontroller to show the feasibility of the real-time operation. The proposed method shows its superiority over other methods previously published in literature.
Abstract—This article investigates the operation of a microgrid system through a novel control sc... more Abstract—This article investigates the operation of a microgrid system through a novel control scheme. The proposed microgrid system employs various autonomous generation systems, including photovoltaic, wind, a diesel engine, a fuel cell, an aqua electrolyzer, and a battery. A simulation model for this microgrid system was developed using MATLAB/SIMULINK (The MathWorks, Natick, Massachusetts, USA). A proportion-integral-derivative control scheme is employed, and the parameters of proportion-integral-derivative controllers for various controllable sources are tuned with a firefly algorithm. This is done using a new proposed weighted goal attainment method for achieving improved and fault-tolerant operation. The proposed control scheme shows better performance over the classical proportion-integral-derivative and bacterial foraging– proportion-integral- derivative controller in both transient and steady-state conditions. The firefly algorithm–proportion-integral-derivative controller also shows stronger robustness properties against system perturbations, disturbances, and faults than that with other controller structures. The robustness is a highly desirable property in such a scenario since many components of the microgrid may be switched on/off or may run at lower/higher power output at different time instants.
This paper introduces modelling and simulation of Doubly-Fed Induction Generator (DFIG) of Wind E... more This paper introduces modelling and simulation of Doubly-Fed Induction Generator (DFIG) of Wind Energy Conversion System (WECS). Two Pulse Width Modulation (PWM) converters have been connected back to back from the rotor terminals to the utility grid via a dc-link. Vector control system typically controlled by a set of PI controllers, which have an important effect on the performance of system dynamics. This paper presents an optimally tuned PI controllers design of a DFIG wind energy system connected to grid using Particle Swarm Optimization (PSO), and Grey Wolf Optimizer (GWO). PSO and GWO used to optimize PI controller parameters of both Grid side converter (GSC), and Rotor side converter (RSC) to improve the dynamic operation of the DFIG wind energy system under a variable speed condition.
An intelligent control of Doubly Fed Induction Generator (DFIG) system using Proportional-Integra... more An intelligent control of Doubly Fed Induction Generator (DFIG) system using Proportional-Integral (PI)controller tuned by optimization techniques is proposed in this paper.System identification technique was presented in this work to estimate the transfer function of the reactive power loop and speed loop of the proposed system.An implemented laboratory prototype consists of 0.37kW, 220 V, 50Hz Brushless DC Motor (BLDC) and its drive circuit controlled by voltage source inverter for various wind speed.A 0.27 kW wound rotor induction machine, working as the DFIG, coupled with turbine machine by a coupler and driven through a back-to-back converter. This system can be applied as a stand-alone power supply system or as the emergency power system when the electricity grid fails. The rotor side converter is controlled using the field-oriented control to control the reactive power at different rotor speeds.Grey Wolf Optimizer (GWO) proposed in this study to tune the (PI) controller. Moreover, Particle Swarm Optimization (PSO) is also used to tune the PI controller for comparison. For studying the performance of each algorithm, different case studies are performed, such as step changes in the rotating speed andelectrical load. Experimentalresults showed that the proposed techniqueis adequate and sufficient to be used with off-grid stand-alone DFIG systems. It alsoshowed the improved performance of GWO over the PSOin tuning the PI controller.
This paper aimed at exploring the use of the proposed hybrid Fuzzy-Particle Swarm Optimization-Si... more This paper aimed at exploring the use of the proposed hybrid Fuzzy-Particle Swarm Optimization-Simplex (F-PSO-S) algorithm to optimize the structural design of PM couplings subject to several key design constraints. The new proposed hybrid optimization algorithm is constructed based on combining three well-known techniques: fuzzy logic (FL), particle swarm optimization (PSO), and simplex method (SM). FL is used to aggregate different scaling and/or conflicting objectives in one objective function using fuzzy combination operators. On the other hand, the PSO has obvious capabilities in global search whereas the SM has exceptional advantages in local search. As a hybrid algorithm, the F-PSO-S has the outstanding feature of combining the ability of global searching and local canvassing for different scales and/or conflicting objective functions. The proposed algorithm has been applied to permanent magnet (PM) drive couplings. A standard coupling design is used as a good initial point for the conventional SM and to define the performance constraints for the proposed optimization technique. New coupling designs are developed and optimized to show the superior capabilities of the F-PSO-S algorithm as a global optimization technique. The sensitivity analysis is also performed to identify the effects of different design parameters on the coupling performance.
9th International Conference on Electrical Engineering ICEENG 2014, May 27, 2014
This paper presents modeling, analysis and control of a grid connected Doubly Fed Induction Gener... more This paper presents modeling, analysis and control of a grid connected Doubly Fed Induction Generator (DFIG) wind turbine, during steady-state and transient operations. A mathematical model for different parts of the wind energy conversion system using DFIG has been examined using MATLAB/SIMULINK. A control structure using standard Proportional Integral (PI) controller and a voltage-oriented control strategy based on a rotating reference frame has been used. The machine model considers operating conditions below and above synchronous speed. The Maximum Power Point Tracking (MPPT) method has been presented also to improve efficiency and energy extraction in wind turbine systems. Characteristic power curve method has been used as one of the popular MPPT methods. In this paper, simulation results of the DFIG model have been presented. Then, DFIG model has been connected to the grid model and examined using PI controller under different conditions. The Internal Model Control (IMC) method has been used for tuning the PI controller. The proposed PI controller shows stable operation at different conditions.
Electric Power Components and Systems. 02/2015; 43(3). DOI: 10.1080/15325008.2014.981320, Feb 2015
The proportional-integral-derivative controllers were the most popular controllers of this centur... more The proportional-integral-derivative controllers were the most popular controllers of this century because of their remarkable effectiveness, and simplicity of implementation. However, proportional-integral-derivative controllers are usually poorly tuned in practice. This article presents a hybrid particle swarm optimization and bacterial foraging techniques for determining the optimal parameters of a proportional-integral-derivative controller for speed control of a Permanent magnet brushless DC motor. The first part of
the article deals with the system modeling and its verification where a model of modest accuracy cannot be expected to give a fair comparison of different controllers. The remaining parts of the article present the application of different optimization techniques to tune the proportional-integral-derivative controller as applied to the motor model. The particle swarm optimization, bacterial foraging, and bacterial foraging-particle swarm optimization algorithms are implemented in MATLAB while the GA Toolbox is used. The performance of the tuned controllers is simulated and experimentally verified to evaluate the main characteristics of each one. It is found that the proposed hybrid bacterial foraging-particle swarm optimization technique is more efficient in improving the step response characteristics and achieving the desired performance indices.
Electric Power Systems Research 116 (2014) 29–35, Nov 2014
The aim of this paper is to explore the use of the proposed hybrid Particle Swarm Optimization-Si... more The aim of this paper is to explore the use of the proposed hybrid Particle Swarm Optimization-SimplexMethod (PSO-SM) algorithm to optimize the design of PM couplings subject to several key design con-straints. The proposed hybrid optimization algorithm is constructed based on combining two well-knownoptimization techniques: Particle Swarm Optimization (PSO) and Simplex Method (SM). The PSO hasobvious capabilities in global search while the SM has exceptional advantages in local search. As a hybridalgorithm, the PSO-SM has the outstanding feature of combining the ability of global searching and localcanvassing. On the other hand, Permanent Magnet (PM) drive couplings are used in power transmissionin a wide range of industrial applications. A standard coupling design is used as a good starting pointfor the conventional Simplex Method and to define the performance constraints for the proposed hybridoptimization algorithm. New coupling designs are developed and optimized to demonstrate the superiorcapabilities of PSO-SM algorithm as a global optimization technique.
Switched Reluctance Motor (SRM) has become popular in various applications because of its high to... more Switched Reluctance Motor (SRM) has become popular in various applications because of its high torque to inertia ratio, high efficiency, variable speed operation capabilities. The SRM primary drawback is torque ripples in the developed torque leading to notable noise and vibrations. Large torque ripples in SRM are due to the switching currents into its stator coils and its nonlinear magnetic nature during operation. By controlling and monitoring the torque of the SRM a significant decrease in torque ripples and even motor efficiency improvement can be carried out. In this study, two stochastic-based optimal PI controllers are used for speed control of an 8/6 SRM Model using MATLAB/Simulink tool with three types of torque sharing functions for torque ripple reduction and achieving overall performance improvement.
EPS (Electric power system) of the satellite is a critical aspect for the success of the satellit... more EPS (Electric power system) of the satellite is a critical aspect for the success of the satellite mission, likewise the optimum usage of the available power resources for the satellite EPS is the main key of success for the system design process. Furthermore, implementing the modular concept in the design of the satellite EPS improves the reliability and quality of the design and makes the platform adaptable for various missions and payloads. Optimizing the usage of solar array output power during beginning of life and exiting from shadow periods while there are excess of power from the solar arrays stabilizes the bus voltage within the required designed margins and consequently protects all satellite loads connected to the main bus. A hybrid modular configuration is proposed including linear and non-linear regulation for implementing the sequential switching shunt regulation of the solar array output power, the proposed configuration employs the fuzzy logic concept to issue the switching pattern for the solar array sections subjected to the error signal in the feedback loop of the bus voltage. Moreover, a simulation is performed for the three domain control concept of the EPS demonstrating how the bus voltage levels decide the operating domain of the EPS.
Optimum usage of the available resources for the spacecraft electric power system is the main key... more Optimum usage of the available resources for the spacecraft electric power system is the main key for success for the satellite EPS design process. Furthermore, implementing modular design of the satellite EPS improves the operation of the satellite because it (i) enables the EPS to work on different power levels, (ii) enhances the EPS integration with various payloads, and (iii) decreases design modifications required to operate the EPS on missions regardless of the height and duration of these missions. A new method for controlling the output power of the satellite solar arrays is proposed in this paper. The proposed method depends on a hybrid modular configuration where the output power of the solar arrays is controlled by linear and non-linear regulations. Moreover, the proposed hybrid configuration is implemented on a microcontroller to show the feasibility of the real-time operation. The proposed method shows its superiority over other methods previously published in literature.
Abstract—This article investigates the operation of a microgrid system through a novel control sc... more Abstract—This article investigates the operation of a microgrid system through a novel control scheme. The proposed microgrid system employs various autonomous generation systems, including photovoltaic, wind, a diesel engine, a fuel cell, an aqua electrolyzer, and a battery. A simulation model for this microgrid system was developed using MATLAB/SIMULINK (The MathWorks, Natick, Massachusetts, USA). A proportion-integral-derivative control scheme is employed, and the parameters of proportion-integral-derivative controllers for various controllable sources are tuned with a firefly algorithm. This is done using a new proposed weighted goal attainment method for achieving improved and fault-tolerant operation. The proposed control scheme shows better performance over the classical proportion-integral-derivative and bacterial foraging– proportion-integral- derivative controller in both transient and steady-state conditions. The firefly algorithm–proportion-integral-derivative controller also shows stronger robustness properties against system perturbations, disturbances, and faults than that with other controller structures. The robustness is a highly desirable property in such a scenario since many components of the microgrid may be switched on/off or may run at lower/higher power output at different time instants.
This paper introduces modelling and simulation of Doubly-Fed Induction Generator (DFIG) of Wind E... more This paper introduces modelling and simulation of Doubly-Fed Induction Generator (DFIG) of Wind Energy Conversion System (WECS). Two Pulse Width Modulation (PWM) converters have been connected back to back from the rotor terminals to the utility grid via a dc-link. Vector control system typically controlled by a set of PI controllers, which have an important effect on the performance of system dynamics. This paper presents an optimally tuned PI controllers design of a DFIG wind energy system connected to grid using Particle Swarm Optimization (PSO), and Grey Wolf Optimizer (GWO). PSO and GWO used to optimize PI controller parameters of both Grid side converter (GSC), and Rotor side converter (RSC) to improve the dynamic operation of the DFIG wind energy system under a variable speed condition.
An intelligent control of Doubly Fed Induction Generator (DFIG) system using Proportional-Integra... more An intelligent control of Doubly Fed Induction Generator (DFIG) system using Proportional-Integral (PI)controller tuned by optimization techniques is proposed in this paper.System identification technique was presented in this work to estimate the transfer function of the reactive power loop and speed loop of the proposed system.An implemented laboratory prototype consists of 0.37kW, 220 V, 50Hz Brushless DC Motor (BLDC) and its drive circuit controlled by voltage source inverter for various wind speed.A 0.27 kW wound rotor induction machine, working as the DFIG, coupled with turbine machine by a coupler and driven through a back-to-back converter. This system can be applied as a stand-alone power supply system or as the emergency power system when the electricity grid fails. The rotor side converter is controlled using the field-oriented control to control the reactive power at different rotor speeds.Grey Wolf Optimizer (GWO) proposed in this study to tune the (PI) controller. Moreover, Particle Swarm Optimization (PSO) is also used to tune the PI controller for comparison. For studying the performance of each algorithm, different case studies are performed, such as step changes in the rotating speed andelectrical load. Experimentalresults showed that the proposed techniqueis adequate and sufficient to be used with off-grid stand-alone DFIG systems. It alsoshowed the improved performance of GWO over the PSOin tuning the PI controller.
This paper aimed at exploring the use of the proposed hybrid Fuzzy-Particle Swarm Optimization-Si... more This paper aimed at exploring the use of the proposed hybrid Fuzzy-Particle Swarm Optimization-Simplex (F-PSO-S) algorithm to optimize the structural design of PM couplings subject to several key design constraints. The new proposed hybrid optimization algorithm is constructed based on combining three well-known techniques: fuzzy logic (FL), particle swarm optimization (PSO), and simplex method (SM). FL is used to aggregate different scaling and/or conflicting objectives in one objective function using fuzzy combination operators. On the other hand, the PSO has obvious capabilities in global search whereas the SM has exceptional advantages in local search. As a hybrid algorithm, the F-PSO-S has the outstanding feature of combining the ability of global searching and local canvassing for different scales and/or conflicting objective functions. The proposed algorithm has been applied to permanent magnet (PM) drive couplings. A standard coupling design is used as a good initial point for the conventional SM and to define the performance constraints for the proposed optimization technique. New coupling designs are developed and optimized to show the superior capabilities of the F-PSO-S algorithm as a global optimization technique. The sensitivity analysis is also performed to identify the effects of different design parameters on the coupling performance.
9th International Conference on Electrical Engineering ICEENG 2014, May 27, 2014
This paper presents modeling, analysis and control of a grid connected Doubly Fed Induction Gener... more This paper presents modeling, analysis and control of a grid connected Doubly Fed Induction Generator (DFIG) wind turbine, during steady-state and transient operations. A mathematical model for different parts of the wind energy conversion system using DFIG has been examined using MATLAB/SIMULINK. A control structure using standard Proportional Integral (PI) controller and a voltage-oriented control strategy based on a rotating reference frame has been used. The machine model considers operating conditions below and above synchronous speed. The Maximum Power Point Tracking (MPPT) method has been presented also to improve efficiency and energy extraction in wind turbine systems. Characteristic power curve method has been used as one of the popular MPPT methods. In this paper, simulation results of the DFIG model have been presented. Then, DFIG model has been connected to the grid model and examined using PI controller under different conditions. The Internal Model Control (IMC) method has been used for tuning the PI controller. The proposed PI controller shows stable operation at different conditions.
Electric Power Components and Systems. 02/2015; 43(3). DOI: 10.1080/15325008.2014.981320, Feb 2015
The proportional-integral-derivative controllers were the most popular controllers of this centur... more The proportional-integral-derivative controllers were the most popular controllers of this century because of their remarkable effectiveness, and simplicity of implementation. However, proportional-integral-derivative controllers are usually poorly tuned in practice. This article presents a hybrid particle swarm optimization and bacterial foraging techniques for determining the optimal parameters of a proportional-integral-derivative controller for speed control of a Permanent magnet brushless DC motor. The first part of
the article deals with the system modeling and its verification where a model of modest accuracy cannot be expected to give a fair comparison of different controllers. The remaining parts of the article present the application of different optimization techniques to tune the proportional-integral-derivative controller as applied to the motor model. The particle swarm optimization, bacterial foraging, and bacterial foraging-particle swarm optimization algorithms are implemented in MATLAB while the GA Toolbox is used. The performance of the tuned controllers is simulated and experimentally verified to evaluate the main characteristics of each one. It is found that the proposed hybrid bacterial foraging-particle swarm optimization technique is more efficient in improving the step response characteristics and achieving the desired performance indices.
Electric Power Systems Research 116 (2014) 29–35, Nov 2014
The aim of this paper is to explore the use of the proposed hybrid Particle Swarm Optimization-Si... more The aim of this paper is to explore the use of the proposed hybrid Particle Swarm Optimization-SimplexMethod (PSO-SM) algorithm to optimize the design of PM couplings subject to several key design con-straints. The proposed hybrid optimization algorithm is constructed based on combining two well-knownoptimization techniques: Particle Swarm Optimization (PSO) and Simplex Method (SM). The PSO hasobvious capabilities in global search while the SM has exceptional advantages in local search. As a hybridalgorithm, the PSO-SM has the outstanding feature of combining the ability of global searching and localcanvassing. On the other hand, Permanent Magnet (PM) drive couplings are used in power transmissionin a wide range of industrial applications. A standard coupling design is used as a good starting pointfor the conventional Simplex Method and to define the performance constraints for the proposed hybridoptimization algorithm. New coupling designs are developed and optimized to demonstrate the superiorcapabilities of PSO-SM algorithm as a global optimization technique.
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Papers by Amged El-Wakeel
wind, a diesel engine, a fuel cell, an aqua electrolyzer, and
a battery. A simulation model for this microgrid system was developed using MATLAB/SIMULINK (The MathWorks, Natick, Massachusetts, USA). A proportion-integral-derivative control scheme is employed, and the parameters of proportion-integral-derivative controllers for various controllable sources are tuned with a firefly algorithm. This is done using a new proposed weighted goal attainment method for achieving improved and fault-tolerant operation. The proposed control scheme shows better performance over the classical proportion-integral-derivative and bacterial foraging– proportion-integral- derivative controller in both transient and steady-state conditions.
The firefly algorithm–proportion-integral-derivative controller also shows stronger robustness properties against system perturbations, disturbances, and faults than that with other controller structures.
The robustness is a highly desirable property in such a scenario since many components of the microgrid may be switched on/off or may run at lower/higher power output at different time instants.
the article deals with the system modeling and its verification where a model of modest accuracy cannot be expected to give a fair comparison of different controllers. The remaining parts of the article present the application of different optimization techniques to tune the proportional-integral-derivative controller as applied to the motor model. The particle swarm optimization, bacterial foraging, and bacterial foraging-particle swarm optimization algorithms are implemented in MATLAB while the GA Toolbox is used. The performance of the tuned controllers is simulated and experimentally verified to evaluate the main characteristics of each one. It is found that the proposed hybrid bacterial foraging-particle swarm optimization technique is more efficient in improving the step response characteristics and achieving the desired performance indices.
wind, a diesel engine, a fuel cell, an aqua electrolyzer, and
a battery. A simulation model for this microgrid system was developed using MATLAB/SIMULINK (The MathWorks, Natick, Massachusetts, USA). A proportion-integral-derivative control scheme is employed, and the parameters of proportion-integral-derivative controllers for various controllable sources are tuned with a firefly algorithm. This is done using a new proposed weighted goal attainment method for achieving improved and fault-tolerant operation. The proposed control scheme shows better performance over the classical proportion-integral-derivative and bacterial foraging– proportion-integral- derivative controller in both transient and steady-state conditions.
The firefly algorithm–proportion-integral-derivative controller also shows stronger robustness properties against system perturbations, disturbances, and faults than that with other controller structures.
The robustness is a highly desirable property in such a scenario since many components of the microgrid may be switched on/off or may run at lower/higher power output at different time instants.
the article deals with the system modeling and its verification where a model of modest accuracy cannot be expected to give a fair comparison of different controllers. The remaining parts of the article present the application of different optimization techniques to tune the proportional-integral-derivative controller as applied to the motor model. The particle swarm optimization, bacterial foraging, and bacterial foraging-particle swarm optimization algorithms are implemented in MATLAB while the GA Toolbox is used. The performance of the tuned controllers is simulated and experimentally verified to evaluate the main characteristics of each one. It is found that the proposed hybrid bacterial foraging-particle swarm optimization technique is more efficient in improving the step response characteristics and achieving the desired performance indices.