The Experts below are selected from a list of 47559 Experts worldwide ranked by ideXlab platform
Xuexia Zhang - One of the best experts on this subject based on the ideXlab platform.
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Optimal Multi-objective Reactive Power Dispatch Considering Static Voltage Stability Based on Dynamic Multi-group Self-Adaptive Differential Evolution Algorithm
2012 Second International Conference on Intelligent System Design and Engineering Application, 2012Co-Authors: Xuexia Zhang, Weirong Chen, Ponnuthurai Nagaratnam SuganthanAbstract:Optimizing multi-objective reactive power dispatch in power systems is an effective way of improving voltage quality, decreasing active power losses and increasing voltage stability margin. This is a non-linear, constrained, non-convex, mixed discrete-continuous variable problem. Recently, computational intelligence-based methods such as genetic algorithms (Gas), Differential evolution (DE) algorithms, particle swarm optimization (PSO) algorithms and immune algorithms (IAs) have been applied to solve this problem. This paper employs dynamic multi-group self-adaptive Differential evolution (DMSDE) algorithm to solve multi-objective reactive power optimization problem. In DMSDE, the population is divided into multiple groups which exchange information dynamically. Further, in the mutation phase, the best vector among the three randomly vectors is used as the base vector while the difference vector is determined by the remaining two vectors. Moreover, two parameters, F and CR, are self-adapted. The presented method is tested on IEEE 30-bus, IEEE 57-bus and IEEE 118-bus power systems. The numerical results, when compared with other algorithms, show that DMSDE is an efficient tool to solve dispatch reactive power flow problem.
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Reactive power dispatch considering voltage stability with seeker optimization algorithm
Electric Power Systems Research, 2009Co-Authors: Chaohua Dai, Weirong Chen, Yunfang Zhu, Xuexia ZhangAbstract:Optimal reactive power dispatch (ORPD) has a growing impact on secure and economical operation of power systems. This issue is well known as a non-linear, multi-modal and multi-objective optimization problem where global optimization techniques are required in order to avoid local minima. In the last decades, computation intelligence-based techniques such as genetic algorithms (Gas), Differential evolution (DE) algorithms and particle swarm optimization (PSO) algorithms, etc., have often been used for this aim. In this work, a seeker optimization algorithm (SOA) based method is proposed for ORPD considering static voltage stability and voltage deviation. The SOA is based on the concept of simulating the act of human searching where search direction is based on the empirical gradient by evaluating the response to the position changes and step length is based on uncertainty reasoning by using a simple Fuzzy rule. The algorithm's performance is studied with comparisons of two versions of Gas, three versions of DE algorithms and four versions of PSO algorithms on the IEEE 57 and 118-bus power systems. The simulation results show that the proposed approach performed better than the other listed algorithms and can be efficiently used for the ORPD problem.
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Seeker Optimization Algorithm for Optimal Reactive Power Dispatch
IEEE Transactions on Power Systems, 2009Co-Authors: Chaohua Dai, Weirong Chen, Yunfang Zhu, Xuexia ZhangAbstract:Optimal reactive power dispatch problem in power systems has thrown a growing influence on secure and economical operation of power systems. However, this issue is well known as a nonlinear, multimodal and mixed-variable problem. In the last decades, computation intelligence-based techniques, such as genetic algorithms (Gas), Differential evolution (DE) algorithms and particle swarm optimization (PSO) algorithms, etc., have often been used for this aim. In this work, a seeker optimization algorithm (SOA)-based reactive power dispatch method is proposed. The SOA is based on the concept of simulating the act of human searching, where the search direction is based on the empirical gradient by evaluating the response to the position changes and the step length is based on uncertainty reasoning by using a simple Fuzzy rule. In this study, the algorithm's performance is evaluated on benchmark function optimization. Then, the SOA is applied to optimal reactive power dispatch on standard IEEE 57- and 118-bus power systems, and compared with conventional nonlinear programming method, two versions of Gas, three versions of DE algorithms and four versions of PSO algorithms. The simulation results show that the proposed approach is superior to the other listed algorithms and can be efficiently used for optimal reactive power dispatch.
Shinji Kambara - One of the best experts on this subject based on the ideXlab platform.
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Hydrogen production system combined with a catalytic reactor and a plasma membrane reactor from ammonia
International Journal of Hydrogen Energy, 2019Co-Authors: Yukio Hayakawa, Tomonori Miura, Kota Shizuya, Shintaro Wakazono, Kenya Tokunaga, Shinji KambaraAbstract:Abstract Ammonia is a 1promising raw material for hydrogen production because it may solve several problems related to hydrogen transport and storage. Hydrogen can be effectively produced from ammonia via catalytic thermal decomposition; however, the resulting residual ammonia negatively influences the fuel cells. Therefore, a high-purity hydrogen production system comprising a catalytic decomposition reactor and a plasma membrane reactor (PMR) has been developed in this work. Most of the ammonia is converted to hydrogen and nitrogen by the catalytic reactor. After the product Gas containing unreacted ammonia is introduced to the PMR, unreacted ammonia is decomposed and hydrogen is separated in the PMR. Based on these processes, hydrogen with a purity of 99.99% is obtained at the output of the PMR. Optimal operation conditions maximizing the hydrogen production flow rate were investigated. The gap length of the PMR and the Gas Differential pressure and applied voltage of the plasma influence the flow rate. A pure hydrogen flow rate of ∼120 L/h was achieved using the current operating conditions. The maximum energy efficiency of the developed hydrogen production system is 28.5%.
Chaohua Dai - One of the best experts on this subject based on the ideXlab platform.
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Reactive power dispatch considering voltage stability with seeker optimization algorithm
Electric Power Systems Research, 2009Co-Authors: Chaohua Dai, Weirong Chen, Yunfang Zhu, Xuexia ZhangAbstract:Optimal reactive power dispatch (ORPD) has a growing impact on secure and economical operation of power systems. This issue is well known as a non-linear, multi-modal and multi-objective optimization problem where global optimization techniques are required in order to avoid local minima. In the last decades, computation intelligence-based techniques such as genetic algorithms (Gas), Differential evolution (DE) algorithms and particle swarm optimization (PSO) algorithms, etc., have often been used for this aim. In this work, a seeker optimization algorithm (SOA) based method is proposed for ORPD considering static voltage stability and voltage deviation. The SOA is based on the concept of simulating the act of human searching where search direction is based on the empirical gradient by evaluating the response to the position changes and step length is based on uncertainty reasoning by using a simple Fuzzy rule. The algorithm's performance is studied with comparisons of two versions of Gas, three versions of DE algorithms and four versions of PSO algorithms on the IEEE 57 and 118-bus power systems. The simulation results show that the proposed approach performed better than the other listed algorithms and can be efficiently used for the ORPD problem.
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Seeker Optimization Algorithm for Optimal Reactive Power Dispatch
IEEE Transactions on Power Systems, 2009Co-Authors: Chaohua Dai, Weirong Chen, Yunfang Zhu, Xuexia ZhangAbstract:Optimal reactive power dispatch problem in power systems has thrown a growing influence on secure and economical operation of power systems. However, this issue is well known as a nonlinear, multimodal and mixed-variable problem. In the last decades, computation intelligence-based techniques, such as genetic algorithms (Gas), Differential evolution (DE) algorithms and particle swarm optimization (PSO) algorithms, etc., have often been used for this aim. In this work, a seeker optimization algorithm (SOA)-based reactive power dispatch method is proposed. The SOA is based on the concept of simulating the act of human searching, where the search direction is based on the empirical gradient by evaluating the response to the position changes and the step length is based on uncertainty reasoning by using a simple Fuzzy rule. In this study, the algorithm's performance is evaluated on benchmark function optimization. Then, the SOA is applied to optimal reactive power dispatch on standard IEEE 57- and 118-bus power systems, and compared with conventional nonlinear programming method, two versions of Gas, three versions of DE algorithms and four versions of PSO algorithms. The simulation results show that the proposed approach is superior to the other listed algorithms and can be efficiently used for optimal reactive power dispatch.
Weirong Chen - One of the best experts on this subject based on the ideXlab platform.
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Optimal Multi-objective Reactive Power Dispatch Considering Static Voltage Stability Based on Dynamic Multi-group Self-Adaptive Differential Evolution Algorithm
2012 Second International Conference on Intelligent System Design and Engineering Application, 2012Co-Authors: Xuexia Zhang, Weirong Chen, Ponnuthurai Nagaratnam SuganthanAbstract:Optimizing multi-objective reactive power dispatch in power systems is an effective way of improving voltage quality, decreasing active power losses and increasing voltage stability margin. This is a non-linear, constrained, non-convex, mixed discrete-continuous variable problem. Recently, computational intelligence-based methods such as genetic algorithms (Gas), Differential evolution (DE) algorithms, particle swarm optimization (PSO) algorithms and immune algorithms (IAs) have been applied to solve this problem. This paper employs dynamic multi-group self-adaptive Differential evolution (DMSDE) algorithm to solve multi-objective reactive power optimization problem. In DMSDE, the population is divided into multiple groups which exchange information dynamically. Further, in the mutation phase, the best vector among the three randomly vectors is used as the base vector while the difference vector is determined by the remaining two vectors. Moreover, two parameters, F and CR, are self-adapted. The presented method is tested on IEEE 30-bus, IEEE 57-bus and IEEE 118-bus power systems. The numerical results, when compared with other algorithms, show that DMSDE is an efficient tool to solve dispatch reactive power flow problem.
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Reactive power dispatch considering voltage stability with seeker optimization algorithm
Electric Power Systems Research, 2009Co-Authors: Chaohua Dai, Weirong Chen, Yunfang Zhu, Xuexia ZhangAbstract:Optimal reactive power dispatch (ORPD) has a growing impact on secure and economical operation of power systems. This issue is well known as a non-linear, multi-modal and multi-objective optimization problem where global optimization techniques are required in order to avoid local minima. In the last decades, computation intelligence-based techniques such as genetic algorithms (Gas), Differential evolution (DE) algorithms and particle swarm optimization (PSO) algorithms, etc., have often been used for this aim. In this work, a seeker optimization algorithm (SOA) based method is proposed for ORPD considering static voltage stability and voltage deviation. The SOA is based on the concept of simulating the act of human searching where search direction is based on the empirical gradient by evaluating the response to the position changes and step length is based on uncertainty reasoning by using a simple Fuzzy rule. The algorithm's performance is studied with comparisons of two versions of Gas, three versions of DE algorithms and four versions of PSO algorithms on the IEEE 57 and 118-bus power systems. The simulation results show that the proposed approach performed better than the other listed algorithms and can be efficiently used for the ORPD problem.
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Seeker Optimization Algorithm for Optimal Reactive Power Dispatch
IEEE Transactions on Power Systems, 2009Co-Authors: Chaohua Dai, Weirong Chen, Yunfang Zhu, Xuexia ZhangAbstract:Optimal reactive power dispatch problem in power systems has thrown a growing influence on secure and economical operation of power systems. However, this issue is well known as a nonlinear, multimodal and mixed-variable problem. In the last decades, computation intelligence-based techniques, such as genetic algorithms (Gas), Differential evolution (DE) algorithms and particle swarm optimization (PSO) algorithms, etc., have often been used for this aim. In this work, a seeker optimization algorithm (SOA)-based reactive power dispatch method is proposed. The SOA is based on the concept of simulating the act of human searching, where the search direction is based on the empirical gradient by evaluating the response to the position changes and the step length is based on uncertainty reasoning by using a simple Fuzzy rule. In this study, the algorithm's performance is evaluated on benchmark function optimization. Then, the SOA is applied to optimal reactive power dispatch on standard IEEE 57- and 118-bus power systems, and compared with conventional nonlinear programming method, two versions of Gas, three versions of DE algorithms and four versions of PSO algorithms. The simulation results show that the proposed approach is superior to the other listed algorithms and can be efficiently used for optimal reactive power dispatch.
Yunfang Zhu - One of the best experts on this subject based on the ideXlab platform.
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Reactive power dispatch considering voltage stability with seeker optimization algorithm
Electric Power Systems Research, 2009Co-Authors: Chaohua Dai, Weirong Chen, Yunfang Zhu, Xuexia ZhangAbstract:Optimal reactive power dispatch (ORPD) has a growing impact on secure and economical operation of power systems. This issue is well known as a non-linear, multi-modal and multi-objective optimization problem where global optimization techniques are required in order to avoid local minima. In the last decades, computation intelligence-based techniques such as genetic algorithms (Gas), Differential evolution (DE) algorithms and particle swarm optimization (PSO) algorithms, etc., have often been used for this aim. In this work, a seeker optimization algorithm (SOA) based method is proposed for ORPD considering static voltage stability and voltage deviation. The SOA is based on the concept of simulating the act of human searching where search direction is based on the empirical gradient by evaluating the response to the position changes and step length is based on uncertainty reasoning by using a simple Fuzzy rule. The algorithm's performance is studied with comparisons of two versions of Gas, three versions of DE algorithms and four versions of PSO algorithms on the IEEE 57 and 118-bus power systems. The simulation results show that the proposed approach performed better than the other listed algorithms and can be efficiently used for the ORPD problem.
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Seeker Optimization Algorithm for Optimal Reactive Power Dispatch
IEEE Transactions on Power Systems, 2009Co-Authors: Chaohua Dai, Weirong Chen, Yunfang Zhu, Xuexia ZhangAbstract:Optimal reactive power dispatch problem in power systems has thrown a growing influence on secure and economical operation of power systems. However, this issue is well known as a nonlinear, multimodal and mixed-variable problem. In the last decades, computation intelligence-based techniques, such as genetic algorithms (Gas), Differential evolution (DE) algorithms and particle swarm optimization (PSO) algorithms, etc., have often been used for this aim. In this work, a seeker optimization algorithm (SOA)-based reactive power dispatch method is proposed. The SOA is based on the concept of simulating the act of human searching, where the search direction is based on the empirical gradient by evaluating the response to the position changes and the step length is based on uncertainty reasoning by using a simple Fuzzy rule. In this study, the algorithm's performance is evaluated on benchmark function optimization. Then, the SOA is applied to optimal reactive power dispatch on standard IEEE 57- and 118-bus power systems, and compared with conventional nonlinear programming method, two versions of Gas, three versions of DE algorithms and four versions of PSO algorithms. The simulation results show that the proposed approach is superior to the other listed algorithms and can be efficiently used for optimal reactive power dispatch.
