Distributed Integrated Synthetic Adaptive Multi-Objective Reactive Power Optimization
Reactive power is the core problem of voltage stability and economical operation in power systems. Aiming at the problem that multi-objective normalization reactive power optimization function is dependent on weight, an integrated synthesis of adaptive multi-objective particle swarm optimization (IS...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Symmetry |
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| Online Access: | https://www.mdpi.com/2073-8994/14/6/1275 |
| _version_ | 1797481890935996416 |
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| author | Jiayin Song Chao Lu Qiang Ma Hongwei Zhou Qi Yue Qinglin Zhu Yue Zhao Yiming Fan Qiqi Huang |
| author_facet | Jiayin Song Chao Lu Qiang Ma Hongwei Zhou Qi Yue Qinglin Zhu Yue Zhao Yiming Fan Qiqi Huang |
| author_sort | Jiayin Song |
| collection | DOAJ |
| description | Reactive power is the core problem of voltage stability and economical operation in power systems. Aiming at the problem that multi-objective normalization reactive power optimization function is dependent on weight, an integrated synthesis of adaptive multi-objective particle swarm optimization (ISAMOPSO) is proposed to achieve weight adaptive. Through seven test functions and three algorithm comparison experiments, it is proved that the ISAMOPSO algorithm has stronger global search capability and better convergence. Considering the optimal access position and capacity of distributed generation (DG), the ISAMOPSO algorithm is used for three-objective reactive power optimization. Finally, the results indicate that the ISAMOPSO algorithm can not only provide a variety of optimization schemes to meet different needs, but also realize dynamic reactive power optimization, which further proves that the algorithm can provide effective technical support for solving reactive power optimization problems in practical engineering. |
| first_indexed | 2024-03-09T22:21:02Z |
| format | Article |
| id | doaj.art-492df652e56c4fb89bbe1ede520272de |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-03-09T22:21:02Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-492df652e56c4fb89bbe1ede520272de2023-11-23T19:13:45ZengMDPI AGSymmetry2073-89942022-06-01146127510.3390/sym14061275Distributed Integrated Synthetic Adaptive Multi-Objective Reactive Power OptimizationJiayin Song0Chao Lu1Qiang Ma2Hongwei Zhou3Qi Yue4Qinglin Zhu5Yue Zhao6Yiming Fan7Qiqi Huang8Department of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, ChinaDepartment of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, ChinaDepartment of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, ChinaDepartment of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, ChinaDepartment of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, ChinaState Grid HLJ Electric Power T&T Engineering Co., Ltd., Harbin 150040, ChinaDepartment of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, ChinaDepartment of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, ChinaDepartment of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, ChinaReactive power is the core problem of voltage stability and economical operation in power systems. Aiming at the problem that multi-objective normalization reactive power optimization function is dependent on weight, an integrated synthesis of adaptive multi-objective particle swarm optimization (ISAMOPSO) is proposed to achieve weight adaptive. Through seven test functions and three algorithm comparison experiments, it is proved that the ISAMOPSO algorithm has stronger global search capability and better convergence. Considering the optimal access position and capacity of distributed generation (DG), the ISAMOPSO algorithm is used for three-objective reactive power optimization. Finally, the results indicate that the ISAMOPSO algorithm can not only provide a variety of optimization schemes to meet different needs, but also realize dynamic reactive power optimization, which further proves that the algorithm can provide effective technical support for solving reactive power optimization problems in practical engineering.https://www.mdpi.com/2073-8994/14/6/1275synthetic adaptivemulti-objective optimizationdistributed generationreactive power optimization |
| spellingShingle | Jiayin Song Chao Lu Qiang Ma Hongwei Zhou Qi Yue Qinglin Zhu Yue Zhao Yiming Fan Qiqi Huang Distributed Integrated Synthetic Adaptive Multi-Objective Reactive Power Optimization Symmetry synthetic adaptive multi-objective optimization distributed generation reactive power optimization |
| title | Distributed Integrated Synthetic Adaptive Multi-Objective Reactive Power Optimization |
| title_full | Distributed Integrated Synthetic Adaptive Multi-Objective Reactive Power Optimization |
| title_fullStr | Distributed Integrated Synthetic Adaptive Multi-Objective Reactive Power Optimization |
| title_full_unstemmed | Distributed Integrated Synthetic Adaptive Multi-Objective Reactive Power Optimization |
| title_short | Distributed Integrated Synthetic Adaptive Multi-Objective Reactive Power Optimization |
| title_sort | distributed integrated synthetic adaptive multi objective reactive power optimization |
| topic | synthetic adaptive multi-objective optimization distributed generation reactive power optimization |
| url | https://www.mdpi.com/2073-8994/14/6/1275 |
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