Mohammad Abido - Academia.edu (original) (raw)

Papers by Mohammad Abido

Research paper thumbnail of A novel approach to conventional power system stabilizer design using tabu search

International Journal of Electrical Power & Energy Systems, 1999

A tabu search (TS) based power system stabilizer (PSS) is presented in this article. The proposed... more A tabu search (TS) based power system stabilizer (PSS) is presented in this article. The proposed approach uses the TS algorithm to search for the optimal settings of conventional lead-lag power system stabilizer (CPSS) parameters. Incorporation of the TS algorithm in the PSS design ...

Research paper thumbnail of Pole placement approach for robust optimum design of PSS and TCSC-based stabilizers using reinforcement learning automata

Electrical Engineering, 2010

Power system stability enhancement via robust optimum design of power system stabilizers (PSSs) a... more Power system stability enhancement via robust optimum design of power system stabilizers (PSSs) and thyristor controlled series capacitor (TCSC)-based stabilizers is thoroughly investigated in this paper. The design problem of PSS and TCSC-based stabilizers is formulated as an optimization problem where a reinforcement learning automata-based optimization algorithm is applied to search for the optimal setting of the proposed PSS and CSC parameters. A pole placement based objective function is considered to shift the dominant system eigenvalues to the left in the s-plane. For evaluation of the effectiveness and robustness of the proposed stabilizers, their performances have been examined on a weakly connected power system subjected to different disturbances, loading conditions, and system parameter variations. The nonlinear simulation results and eigenvalues analysis demonstrate the high performance of the proposed stabilizers and their ability to provide efficient damping of low frequency oscillations. In addition, it is observed that the proposed CSC has greatly improved the voltage profile of system under severe disturbances.

Research paper thumbnail of Development and implementation of a hybrid intelligent controller for interior permanent magnet synchronous motor drive

A hybrid neuro-fuzzy scheme for the online tuning of a genetic based proportional-integral (PI) c... more A hybrid neuro-fuzzy scheme for the online tuning of a genetic based proportional-integral (PI) controller for interior permanent magnet synchronous motor (IPMSM) drives is presented in this paper. The proposed controller is developed for accurate speed control of the IPMSM drive under various system disturbances. In this work, initially different operating conditions are obtained based on motor dynamics incorporating uncertainties. At each operating condition, a genetic algorithm (GA) is used to optimize the PI controller parameters in a closed loop vector control scheme. In the optimization procedure, a performance index is developed to reflect the minimum speed deviation, minimum settling time and zero steady-state error. A fuzzy basis function network (FBFN) is utilized for online tuning of the PI controller parameters to ensure optimum drive performance under different disturbances. The proposed FBFN based PI controller provides a natural framework for combining numerical and linguistic information in a uniform fashion. The proposed controller is successfully implemented in realtime using a digital signal processor board DS 1102 for a laboratory 1 hp IPMSM. The efficacy of the proposed controller is verified by simulation as well as experimental results at different dynamic operating conditions. The proposed controller is found to be robust for applications In IPMSM drive.

Research paper thumbnail of Development and implementation of a hybrid intelligent controller for interior permanent-magnet synchronous motor drives

IEEE Transactions on Industry Applications, 2004

A hybrid neuro-fuzzy scheme for online tuning of a genetic-based proportional-integral (PI) contr... more A hybrid neuro-fuzzy scheme for online tuning of a genetic-based proportional-integral (PI) controller for an interior permanent-magnet synchronous motor (IPMSM) drive is presented in this paper. The proposed controller is developed for accurate speed control of the IPMSM drive under various system disturbances. In this work, initially different operating conditions are obtained based on motor dynamics incorporating uncertainties. At each operating condition a genetic algorithm is used to optimize the PI controller parameters in a closed-loop vector control scheme. In the optimization procedure a performance index is developed to reflect the minimum speed deviation, minimum settling time and zero steady-state error. A fuzzy basis function network (FBFN) is utilized for online tuning of the PI controller parameters to ensure optimum drive performance under different disturbances. The proposed FBFN-based PI controller provides a natural framework for combining numerical and linguistic information in a uniform fashion. The proposed controller is successfully implemented in real time using a digital signal processor board DS 1102 for a laboratory 1-hp IPMSM. The effectiveness of the proposed controller is verified by simulation as well as experimental results at different dynamic operating conditions. The proposed controller is found to be robust for applications in an IPMSM drive.

Research paper thumbnail of Hybridizing rule-based power system stabilizers with genetic algorithms

IEEE Transactions on Power Systems, 1999

Research paper thumbnail of Assessment of Genetic Algorithm selection, crossover and mutation techniques in reactive power optimization

In this paper assessment of different genetic algorithm (GA) selection, crossover and mutation te... more In this paper assessment of different genetic algorithm (GA) selection, crossover and mutation techniques in term of convergence to the optimal solution for single objective reactive power optimization problem is presented and investigated. The problem is formulated as a nonlinear optimization problem with equality and inequality constraints. Also, in this paper a simple cost appraisal for the potential annual cost saving of these GA techniques due to reactive power optimization will be conducted. Wale & Hale 6 bus system was used in this paper study.

Research paper thumbnail of Robust design of multimachine power system stabilizers using simulated annealing

IEEE Transactions on Energy Conversion, 2000

Robust design of multimachine power system stabilizers (PSSs) using simulated annealing (SA) opti... more Robust design of multimachine power system stabilizers (PSSs) using simulated annealing (SA) optimization technique is presented in this paper. The proposed approach employs SA to search for optimal parameter settings of a widely used conventional fixed-structure lead-lag PSS (CPSS). The parameters of the proposed simulated annealing based power system stabilizer (SAPSS) are optimized in order to shift the system electromechanical modes at different loading conditions and system configurations simultaneously to the left in the s-plane. Incorporation of SA as a derivative-free optimization technique in PSS design significantly reduces the computational burden. One of the main advantages of the proposed approach is its robustness to the initial parameter settings. In addition, the quality of the optimal solution does not rely on the initial guess. The performance of the proposed SAPSS under different disturbances and loading conditions is investigated for two multimachine power systems. The eigenvalue analysis and the nonlinear simulation results show the effectiveness of the proposed SAPSS's to damp out the local as well as the interarea modes and enhance greatly the system stability over a wide range of loading conditions and system configurations

Research paper thumbnail of Review of conventional power system stabilizer design methods

In the past two decades, the utilization of supplementary excitation control signals for improvin... more In the past two decades, the utilization of supplementary excitation control signals for improving the dynamic stability of power systems has received much attention. In recent years, several approaches based on modern control theory and intelligent control and optimization techniques have been applied to PSS design problem. This paper introduces a review on the techniques applied on the conventional PSS design only. The techniques could be mainly classified into linear and nonlinear. Each classification includes several design methods which make the PSS more effective and robust in damping out the low frequency oscillations.

Research paper thumbnail of Optimal power flow using particle swarm optimization

International Journal of Electrical Power & Energy Systems, 2002

This paper presents an ef®cient and reliable evolutionary-based approach to solve the optimal pow... more This paper presents an ef®cient and reliable evolutionary-based approach to solve the optimal power¯ow (OPF) problem. The proposed approach employs particle swarm optimization (PSO) algorithm for optimal settings of OPF problem control variables. Incorporation of PSO as a derivative-free optimization technique in solving OPF problem signi®cantly relieves the assumptions imposed on the optimized objective functions. The proposed approach has been examined and tested on the standard IEEE 30-bus test system with different objectives that re¯ect fuel cost minimization, voltage pro®le improvement, and voltage stability enhancement. The proposed approach results have been compared to those that reported in the literature recently. The results are promising and show the effectiveness and robustness of the proposed approach. q

Research paper thumbnail of A novel multiobjective evolutionary algorithm for environmental/economic power dispatch

Electric Power Systems Research, 2003

In this paper, a novel multiobjective evolutionary algorithm for optimal reactive power (VAR) dis... more In this paper, a novel multiobjective evolutionary algorithm for optimal reactive power (VAR) dispatch problem is presented. The optimal VAR dispatch problem is formulated as a nonlinear constrained multiobjective optimization problem where the real power loss and the bus voltage deviations are to be minimized simultaneously. A new Strength Pareto Evolutionary Algorithm (SPEA) based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and noncommensurable objectives. A hierarchical clustering algorithm is imposed to provide the decision maker with a representative and manageable Pareto-optimal set. The results demonstrate the capabilities of the proposed approach to generate true and well-distributed Paretooptimal nondominated solutions in one single run. The results also show the superiority of the proposed approach and confirm its potential to solve the multiobjective VAR dispatch problem.

Research paper thumbnail of Application of Novel Reinforcement Learning Automata Approach in Power System Regulation

Journal of Circuits, Systems, and Computers, 2009

In this paper, a novel efficient optimization method based on reinforcement learning automata (RL... more In this paper, a novel efficient optimization method based on reinforcement learning automata (RLA) for optimum parameters setting of conventional proportional-integralderivative (PID) controller for AVR system of power synchronous generator is proposed. The proposed method is Combinatorial Discrete and Continuous Action Reinforcement Learning Automata (CDCARLA) which is able to explore and learn to improve control performance without the knowledge of the analytical system model. This paper demonstrates the full details of the CDCARLA technique and compares its performance with Particle Swarm Optimization (PSO) as an efficient evolutionary optimization method. The proposed method has been applied to PID controller design. The simulation results show the superior efficiency and robustness of the proposed method.

Research paper thumbnail of Optimization of UPFCs using hierarchical multi-objective optimization algorithms

Analog Integrated Circuits and Signal Processing

Optimal location, number, and settings of unified power flow controllers (UPFC) using various mul... more Optimal location, number, and settings of unified power flow controllers (UPFC) using various multi-objective optimization algorithms is presented in this paper. The UPFC parameters, locations and number are computed to maximize the voltage stability margin and minimize the real power losses at the same time. For this, developed hierarchical optimization versions of three recent multi-objective algorithms are proposed namely: non-dominated genetic algorithms (NSGA-II), non-dominated sorting particle swarm optimization (NSPSO) and Strength Pareto Evolutionary Algorithm 2 (SPEA2). The fuzzy logic is proposed to extract the best compromise solution from the Pareto set. The proposed algorithms are applied to IEEE 30-bus power system. The line flow and load bus voltage limits are taken into account. The obtained results show that the installation of the UPFC in the power system minimizes the power losses, enhances the static voltage stability, and improves the voltage profiles. Furthermore, the proposed methods are able to solve a hard discrete–continuous constrained multi-objective optimization problem. In addition, they do not show any limitation on the number of objective functions under consideration.

Research paper thumbnail of Assessment study of shunt FACTS-based controllers effectiveness on power system stability enhancement

Research paper thumbnail of ROBUST COORDINATED DESIGN OF PSS & STATCOM CONTROLLERS FOR DAMPING POWER SYSTEM OSCILLATION

The main objective of this paper is to investigate the enhancement of damping the power system os... more The main objective of this paper is to investigate the enhancement of damping the power system oscillation via coordinated design of the Power System Stabilizer (PSS) and STATic COMpensator (STATCOM) controllers. The design problem of PSS and STATCOM controllers are formulated as an optimization problem. Using the developed linearized model of a power system equipped with STATCOM-based stabilizer & PSS, the particle swarm optimization (PSO) algorithm is employed to search for optimal controllers parameters. In addition, the paper presents a singular value decomposition (SVD) based approach to asses and measures the controllability of the poorly damped electromechanical modes by different controllers' inputs. The proposed controllers are evaluated on a single machine infinite bus power system with STATCOM installed. The nonlinear time domain simulation and eigenvalue analysis results show the effectiveness of the coordinated design in damping the power system oscillation.

Research paper thumbnail of An artificial neural network for online tuning of genetic algorithm-based PI controller for interior permanent magnet synchronous motor drive

Canadian Journal of Electrical and Computer Engineering-revue Canadienne De Genie Electrique Et Informatique, 2006

An artificial neural network for online tuning of a genetic algorithm-based proportional-integral... more An artificial neural network for online tuning of a genetic algorithm-based proportional-integral (PI) controller for an interior permanent magnet synchronous motor (IPMSM) drive is presented in this paper. The proposed controller is designed to achieve accurate speed control of the IPMSM drive under system disturbances. Initially, different operating conditions are obtained, based on motor dynamics incorporating various uncertainties. For each operating condition a generic algorithm is used to optimize the PI controller parameters in a closed-loop vector control scheme. In the optimization procedure a performance index is developed to reflect the minimum speed deviation, minimum settling time, and zero steady-state error. A radial basis function network is utilized for online tuning of the PI controller parameters to ensure optimum drive performance under different disturbances. The proposed controller is successfully implemented in real time using a digital signal processor board (DS-1102) for a laboratory 1 hp IPMSM. The efficacy of the proposed controller is verified by simulation as well as experimental results under different dynamic operating conditions. The proposed approach is found to be quite robust for application in the controller for IPMSM drives.

Research paper thumbnail of Simultaneous stabilization of multimachine power systems via genetic algorithms

IEEE Transactions on Power Systems, 1999

This paper presents the simultaneous tuning of power system stabilizers in a multi-machine power ... more This paper presents the simultaneous tuning of power system stabilizers in a multi-machine power system. The problem of selecting the parameters of power system stabilizers in converted into an optimization problem that is solved by genetic algorithm using eigen value based objective function. The dynamic performance of the system has been investigated under small perturbation and large disturbance. The performance of genetic algorithm based PSS has been compared with the conventional power system stabilizer. The non-linear simulation results on 4 machine, 11 bus system verifies the effectiveness of the proposed genetic algorithm based power system stabilizers.

Research paper thumbnail of Optimal multiobjective design of robust power system stabilizers using genetic algorithms

IEEE Transactions on Power Systems, 2003

... Presently, the conventional lead-lag power system stabilizer is widely used by power system u... more ... Presently, the conventional lead-lag power system stabilizer is widely used by power system utilities. ... [9] C. Chen and Y. Hsu, “Coordinated synthesis of multimachine power system stabilizer using an efficient decentralized modal control algo-rithm,” IEEE Trans. Power Syst., vol. ...

Research paper thumbnail of Robust tuning of power system stabilizers in multimachine power systems

IEEE Transactions on Power Systems, 2000

This paper demonstrates the robust tuning of power systems stabilizers for power systems, operati... more This paper demonstrates the robust tuning of power systems stabilizers for power systems, operating at different loading conditions. A classical lead-lag power system stabilizer is used to demonstrate the technique. The problem of selecting the stabilizer parameters is converted to a simple optimization problem with an eigenvalue-based objective function, which is solved by a tabu search algorithm. The objective function allows the selection of the stabilizer parameters to optimally place the closed-loop eigenvalues in the left-hand side of a vertical line in the complex -plane. The effectiveness of the stabilizers tuned using the suggested technique, in enhancing the stability of power systems, is confirmed through eigenvalue analysis and simulation results.

Research paper thumbnail of On-line identification of synchronous machines using radial basis function neural networks

IEEE Transactions on Power Systems, 1997

Research paper thumbnail of Real-time performance evaluation of a genetic algorithm based fuzzy logic controller for IPM motor drives

Journal of Electroanalytical Chemistry, 2003

This paper presents a novel speed control scheme using a genetic-based fuzzy logic controller (GF... more This paper presents a novel speed control scheme using a genetic-based fuzzy logic controller (GFLC) for an interior permanent-magnet synchronous motor (IPMSM) drive. The proposed GFLC is developed to have less computational burden, which makes it suitable for real-time implementation. The parameters for the GFLC are tuned by genetic algorithm (GA). The complete drive incorporating the GFLC is successfully implemented in real-time using a digital signal processor board DS 1102 for a laboratory 1-hp interior permanent magnet motor.

Research paper thumbnail of A novel approach to conventional power system stabilizer design using tabu search

International Journal of Electrical Power & Energy Systems, 1999

A tabu search (TS) based power system stabilizer (PSS) is presented in this article. The proposed... more A tabu search (TS) based power system stabilizer (PSS) is presented in this article. The proposed approach uses the TS algorithm to search for the optimal settings of conventional lead-lag power system stabilizer (CPSS) parameters. Incorporation of the TS algorithm in the PSS design ...

Research paper thumbnail of Pole placement approach for robust optimum design of PSS and TCSC-based stabilizers using reinforcement learning automata

Electrical Engineering, 2010

Power system stability enhancement via robust optimum design of power system stabilizers (PSSs) a... more Power system stability enhancement via robust optimum design of power system stabilizers (PSSs) and thyristor controlled series capacitor (TCSC)-based stabilizers is thoroughly investigated in this paper. The design problem of PSS and TCSC-based stabilizers is formulated as an optimization problem where a reinforcement learning automata-based optimization algorithm is applied to search for the optimal setting of the proposed PSS and CSC parameters. A pole placement based objective function is considered to shift the dominant system eigenvalues to the left in the s-plane. For evaluation of the effectiveness and robustness of the proposed stabilizers, their performances have been examined on a weakly connected power system subjected to different disturbances, loading conditions, and system parameter variations. The nonlinear simulation results and eigenvalues analysis demonstrate the high performance of the proposed stabilizers and their ability to provide efficient damping of low frequency oscillations. In addition, it is observed that the proposed CSC has greatly improved the voltage profile of system under severe disturbances.

Research paper thumbnail of Development and implementation of a hybrid intelligent controller for interior permanent magnet synchronous motor drive

A hybrid neuro-fuzzy scheme for the online tuning of a genetic based proportional-integral (PI) c... more A hybrid neuro-fuzzy scheme for the online tuning of a genetic based proportional-integral (PI) controller for interior permanent magnet synchronous motor (IPMSM) drives is presented in this paper. The proposed controller is developed for accurate speed control of the IPMSM drive under various system disturbances. In this work, initially different operating conditions are obtained based on motor dynamics incorporating uncertainties. At each operating condition, a genetic algorithm (GA) is used to optimize the PI controller parameters in a closed loop vector control scheme. In the optimization procedure, a performance index is developed to reflect the minimum speed deviation, minimum settling time and zero steady-state error. A fuzzy basis function network (FBFN) is utilized for online tuning of the PI controller parameters to ensure optimum drive performance under different disturbances. The proposed FBFN based PI controller provides a natural framework for combining numerical and linguistic information in a uniform fashion. The proposed controller is successfully implemented in realtime using a digital signal processor board DS 1102 for a laboratory 1 hp IPMSM. The efficacy of the proposed controller is verified by simulation as well as experimental results at different dynamic operating conditions. The proposed controller is found to be robust for applications In IPMSM drive.

Research paper thumbnail of Development and implementation of a hybrid intelligent controller for interior permanent-magnet synchronous motor drives

IEEE Transactions on Industry Applications, 2004

A hybrid neuro-fuzzy scheme for online tuning of a genetic-based proportional-integral (PI) contr... more A hybrid neuro-fuzzy scheme for online tuning of a genetic-based proportional-integral (PI) controller for an interior permanent-magnet synchronous motor (IPMSM) drive is presented in this paper. The proposed controller is developed for accurate speed control of the IPMSM drive under various system disturbances. In this work, initially different operating conditions are obtained based on motor dynamics incorporating uncertainties. At each operating condition a genetic algorithm is used to optimize the PI controller parameters in a closed-loop vector control scheme. In the optimization procedure a performance index is developed to reflect the minimum speed deviation, minimum settling time and zero steady-state error. A fuzzy basis function network (FBFN) is utilized for online tuning of the PI controller parameters to ensure optimum drive performance under different disturbances. The proposed FBFN-based PI controller provides a natural framework for combining numerical and linguistic information in a uniform fashion. The proposed controller is successfully implemented in real time using a digital signal processor board DS 1102 for a laboratory 1-hp IPMSM. The effectiveness of the proposed controller is verified by simulation as well as experimental results at different dynamic operating conditions. The proposed controller is found to be robust for applications in an IPMSM drive.

Research paper thumbnail of Hybridizing rule-based power system stabilizers with genetic algorithms

IEEE Transactions on Power Systems, 1999

Research paper thumbnail of Assessment of Genetic Algorithm selection, crossover and mutation techniques in reactive power optimization

In this paper assessment of different genetic algorithm (GA) selection, crossover and mutation te... more In this paper assessment of different genetic algorithm (GA) selection, crossover and mutation techniques in term of convergence to the optimal solution for single objective reactive power optimization problem is presented and investigated. The problem is formulated as a nonlinear optimization problem with equality and inequality constraints. Also, in this paper a simple cost appraisal for the potential annual cost saving of these GA techniques due to reactive power optimization will be conducted. Wale & Hale 6 bus system was used in this paper study.

Research paper thumbnail of Robust design of multimachine power system stabilizers using simulated annealing

IEEE Transactions on Energy Conversion, 2000

Robust design of multimachine power system stabilizers (PSSs) using simulated annealing (SA) opti... more Robust design of multimachine power system stabilizers (PSSs) using simulated annealing (SA) optimization technique is presented in this paper. The proposed approach employs SA to search for optimal parameter settings of a widely used conventional fixed-structure lead-lag PSS (CPSS). The parameters of the proposed simulated annealing based power system stabilizer (SAPSS) are optimized in order to shift the system electromechanical modes at different loading conditions and system configurations simultaneously to the left in the s-plane. Incorporation of SA as a derivative-free optimization technique in PSS design significantly reduces the computational burden. One of the main advantages of the proposed approach is its robustness to the initial parameter settings. In addition, the quality of the optimal solution does not rely on the initial guess. The performance of the proposed SAPSS under different disturbances and loading conditions is investigated for two multimachine power systems. The eigenvalue analysis and the nonlinear simulation results show the effectiveness of the proposed SAPSS's to damp out the local as well as the interarea modes and enhance greatly the system stability over a wide range of loading conditions and system configurations

Research paper thumbnail of Review of conventional power system stabilizer design methods

In the past two decades, the utilization of supplementary excitation control signals for improvin... more In the past two decades, the utilization of supplementary excitation control signals for improving the dynamic stability of power systems has received much attention. In recent years, several approaches based on modern control theory and intelligent control and optimization techniques have been applied to PSS design problem. This paper introduces a review on the techniques applied on the conventional PSS design only. The techniques could be mainly classified into linear and nonlinear. Each classification includes several design methods which make the PSS more effective and robust in damping out the low frequency oscillations.

Research paper thumbnail of Optimal power flow using particle swarm optimization

International Journal of Electrical Power & Energy Systems, 2002

This paper presents an ef®cient and reliable evolutionary-based approach to solve the optimal pow... more This paper presents an ef®cient and reliable evolutionary-based approach to solve the optimal power¯ow (OPF) problem. The proposed approach employs particle swarm optimization (PSO) algorithm for optimal settings of OPF problem control variables. Incorporation of PSO as a derivative-free optimization technique in solving OPF problem signi®cantly relieves the assumptions imposed on the optimized objective functions. The proposed approach has been examined and tested on the standard IEEE 30-bus test system with different objectives that re¯ect fuel cost minimization, voltage pro®le improvement, and voltage stability enhancement. The proposed approach results have been compared to those that reported in the literature recently. The results are promising and show the effectiveness and robustness of the proposed approach. q

Research paper thumbnail of A novel multiobjective evolutionary algorithm for environmental/economic power dispatch

Electric Power Systems Research, 2003

In this paper, a novel multiobjective evolutionary algorithm for optimal reactive power (VAR) dis... more In this paper, a novel multiobjective evolutionary algorithm for optimal reactive power (VAR) dispatch problem is presented. The optimal VAR dispatch problem is formulated as a nonlinear constrained multiobjective optimization problem where the real power loss and the bus voltage deviations are to be minimized simultaneously. A new Strength Pareto Evolutionary Algorithm (SPEA) based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and noncommensurable objectives. A hierarchical clustering algorithm is imposed to provide the decision maker with a representative and manageable Pareto-optimal set. The results demonstrate the capabilities of the proposed approach to generate true and well-distributed Paretooptimal nondominated solutions in one single run. The results also show the superiority of the proposed approach and confirm its potential to solve the multiobjective VAR dispatch problem.

Research paper thumbnail of Application of Novel Reinforcement Learning Automata Approach in Power System Regulation

Journal of Circuits, Systems, and Computers, 2009

In this paper, a novel efficient optimization method based on reinforcement learning automata (RL... more In this paper, a novel efficient optimization method based on reinforcement learning automata (RLA) for optimum parameters setting of conventional proportional-integralderivative (PID) controller for AVR system of power synchronous generator is proposed. The proposed method is Combinatorial Discrete and Continuous Action Reinforcement Learning Automata (CDCARLA) which is able to explore and learn to improve control performance without the knowledge of the analytical system model. This paper demonstrates the full details of the CDCARLA technique and compares its performance with Particle Swarm Optimization (PSO) as an efficient evolutionary optimization method. The proposed method has been applied to PID controller design. The simulation results show the superior efficiency and robustness of the proposed method.

Research paper thumbnail of Optimization of UPFCs using hierarchical multi-objective optimization algorithms

Analog Integrated Circuits and Signal Processing

Optimal location, number, and settings of unified power flow controllers (UPFC) using various mul... more Optimal location, number, and settings of unified power flow controllers (UPFC) using various multi-objective optimization algorithms is presented in this paper. The UPFC parameters, locations and number are computed to maximize the voltage stability margin and minimize the real power losses at the same time. For this, developed hierarchical optimization versions of three recent multi-objective algorithms are proposed namely: non-dominated genetic algorithms (NSGA-II), non-dominated sorting particle swarm optimization (NSPSO) and Strength Pareto Evolutionary Algorithm 2 (SPEA2). The fuzzy logic is proposed to extract the best compromise solution from the Pareto set. The proposed algorithms are applied to IEEE 30-bus power system. The line flow and load bus voltage limits are taken into account. The obtained results show that the installation of the UPFC in the power system minimizes the power losses, enhances the static voltage stability, and improves the voltage profiles. Furthermore, the proposed methods are able to solve a hard discrete–continuous constrained multi-objective optimization problem. In addition, they do not show any limitation on the number of objective functions under consideration.

Research paper thumbnail of Assessment study of shunt FACTS-based controllers effectiveness on power system stability enhancement

Research paper thumbnail of ROBUST COORDINATED DESIGN OF PSS & STATCOM CONTROLLERS FOR DAMPING POWER SYSTEM OSCILLATION

The main objective of this paper is to investigate the enhancement of damping the power system os... more The main objective of this paper is to investigate the enhancement of damping the power system oscillation via coordinated design of the Power System Stabilizer (PSS) and STATic COMpensator (STATCOM) controllers. The design problem of PSS and STATCOM controllers are formulated as an optimization problem. Using the developed linearized model of a power system equipped with STATCOM-based stabilizer & PSS, the particle swarm optimization (PSO) algorithm is employed to search for optimal controllers parameters. In addition, the paper presents a singular value decomposition (SVD) based approach to asses and measures the controllability of the poorly damped electromechanical modes by different controllers' inputs. The proposed controllers are evaluated on a single machine infinite bus power system with STATCOM installed. The nonlinear time domain simulation and eigenvalue analysis results show the effectiveness of the coordinated design in damping the power system oscillation.

Research paper thumbnail of An artificial neural network for online tuning of genetic algorithm-based PI controller for interior permanent magnet synchronous motor drive

Canadian Journal of Electrical and Computer Engineering-revue Canadienne De Genie Electrique Et Informatique, 2006

An artificial neural network for online tuning of a genetic algorithm-based proportional-integral... more An artificial neural network for online tuning of a genetic algorithm-based proportional-integral (PI) controller for an interior permanent magnet synchronous motor (IPMSM) drive is presented in this paper. The proposed controller is designed to achieve accurate speed control of the IPMSM drive under system disturbances. Initially, different operating conditions are obtained, based on motor dynamics incorporating various uncertainties. For each operating condition a generic algorithm is used to optimize the PI controller parameters in a closed-loop vector control scheme. In the optimization procedure a performance index is developed to reflect the minimum speed deviation, minimum settling time, and zero steady-state error. A radial basis function network is utilized for online tuning of the PI controller parameters to ensure optimum drive performance under different disturbances. The proposed controller is successfully implemented in real time using a digital signal processor board (DS-1102) for a laboratory 1 hp IPMSM. The efficacy of the proposed controller is verified by simulation as well as experimental results under different dynamic operating conditions. The proposed approach is found to be quite robust for application in the controller for IPMSM drives.

Research paper thumbnail of Simultaneous stabilization of multimachine power systems via genetic algorithms

IEEE Transactions on Power Systems, 1999

This paper presents the simultaneous tuning of power system stabilizers in a multi-machine power ... more This paper presents the simultaneous tuning of power system stabilizers in a multi-machine power system. The problem of selecting the parameters of power system stabilizers in converted into an optimization problem that is solved by genetic algorithm using eigen value based objective function. The dynamic performance of the system has been investigated under small perturbation and large disturbance. The performance of genetic algorithm based PSS has been compared with the conventional power system stabilizer. The non-linear simulation results on 4 machine, 11 bus system verifies the effectiveness of the proposed genetic algorithm based power system stabilizers.

Research paper thumbnail of Optimal multiobjective design of robust power system stabilizers using genetic algorithms

IEEE Transactions on Power Systems, 2003

... Presently, the conventional lead-lag power system stabilizer is widely used by power system u... more ... Presently, the conventional lead-lag power system stabilizer is widely used by power system utilities. ... [9] C. Chen and Y. Hsu, “Coordinated synthesis of multimachine power system stabilizer using an efficient decentralized modal control algo-rithm,” IEEE Trans. Power Syst., vol. ...

Research paper thumbnail of Robust tuning of power system stabilizers in multimachine power systems

IEEE Transactions on Power Systems, 2000

This paper demonstrates the robust tuning of power systems stabilizers for power systems, operati... more This paper demonstrates the robust tuning of power systems stabilizers for power systems, operating at different loading conditions. A classical lead-lag power system stabilizer is used to demonstrate the technique. The problem of selecting the stabilizer parameters is converted to a simple optimization problem with an eigenvalue-based objective function, which is solved by a tabu search algorithm. The objective function allows the selection of the stabilizer parameters to optimally place the closed-loop eigenvalues in the left-hand side of a vertical line in the complex -plane. The effectiveness of the stabilizers tuned using the suggested technique, in enhancing the stability of power systems, is confirmed through eigenvalue analysis and simulation results.

Research paper thumbnail of On-line identification of synchronous machines using radial basis function neural networks

IEEE Transactions on Power Systems, 1997

Research paper thumbnail of Real-time performance evaluation of a genetic algorithm based fuzzy logic controller for IPM motor drives

Journal of Electroanalytical Chemistry, 2003

This paper presents a novel speed control scheme using a genetic-based fuzzy logic controller (GF... more This paper presents a novel speed control scheme using a genetic-based fuzzy logic controller (GFLC) for an interior permanent-magnet synchronous motor (IPMSM) drive. The proposed GFLC is developed to have less computational burden, which makes it suitable for real-time implementation. The parameters for the GFLC are tuned by genetic algorithm (GA). The complete drive incorporating the GFLC is successfully implemented in real-time using a digital signal processor board DS 1102 for a laboratory 1-hp interior permanent magnet motor.