Multi-objective reactive power optimization based on chaos particle swarm optimization algorithm
Reactive power optimization is closely related to voltage quality, network loss and it has great significance for the safety, reliability and economical operation of the power system. For shortage of traditional reactive power optimization, this paper establishes a multiple-objective reactive power...
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| Published in: | 2013 2nd International Symposium on Instrumentation and Measurement, Sensor Network and Automation (IMSNA) pp. 1014 - 1017 |
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| Main Authors: | , , , |
| Format: | Conference Proceeding |
| Language: | English |
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IEEE
01.12.2013
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| Abstract | Reactive power optimization is closely related to voltage quality, network loss and it has great significance for the safety, reliability and economical operation of the power system. For shortage of traditional reactive power optimization, this paper establishes a multiple-objective reactive power optimization model which consists of minimum active power loss, minimum node voltage deviation, best static voltage stability and minimum reactive cost. To optimize four targets simultaneously, this paper has proposed a multi-objective reactive power optimization method which applies the chaotic particle swarm optimization algorithm based on Pareto solutions and finds the Pareto optimal solution sets of multi-objective optimization problems, then policy makers can make a scientific decision according to the actual situation. To prove the validity of the method proposed, this paper makes a multiple-objective reactive power optimization analysis for the IEEE30-bus system. The result shows that the method presented in this paper can achieve good results of reactive power optimization for decision makers to refer to. |
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| AbstractList | Reactive power optimization is closely related to voltage quality, network loss and it has great significance for the safety, reliability and economical operation of the power system. For shortage of traditional reactive power optimization, this paper establishes a multiple-objective reactive power optimization model which consists of minimum active power loss, minimum node voltage deviation, best static voltage stability and minimum reactive cost. To optimize four targets simultaneously, this paper has proposed a multi-objective reactive power optimization method which applies the chaotic particle swarm optimization algorithm based on Pareto solutions and finds the Pareto optimal solution sets of multi-objective optimization problems, then policy makers can make a scientific decision according to the actual situation. To prove the validity of the method proposed, this paper makes a multiple-objective reactive power optimization analysis for the IEEE30-bus system. The result shows that the method presented in this paper can achieve good results of reactive power optimization for decision makers to refer to. |
| Author | Pang Xia Zhu Da-rui He Xiao Liu Chong-xin |
| Author_xml | – sequence: 1 surname: He Xiao fullname: He Xiao email: 402492178@qq.com organization: Sch. of Electr. Eng., Xi'an Jiaotong Univ., Xi'an, China – sequence: 2 surname: Pang Xia fullname: Pang Xia email: howlluy@163.com organization: Sch. of Electr. Eng., Xi'an Jiaotong Univ., Xi'an, China – sequence: 3 surname: Zhu Da-rui fullname: Zhu Da-rui email: zdarui@163.com organization: Sch. of Electr. Eng., Xi'an Jiaotong Univ., Xi'an, China – sequence: 4 surname: Liu Chong-xin fullname: Liu Chong-xin email: liucx@mail.xjtu.edu.cn organization: Sch. of Electr. Eng., Xi'an Jiaotong Univ., Xi'an, China |
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| Snippet | Reactive power optimization is closely related to voltage quality, network loss and it has great significance for the safety, reliability and economical... |
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| SubjectTerms | Chaos Chaos optimized Minimization Multi-objective optimization Pareto optimization Pareto solutions Particle swarm algorithm Particle swarm optimization Power system stability Reactive power Reactive power optimization |
| Title | Multi-objective reactive power optimization based on chaos particle swarm optimization algorithm |
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