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  • 标题:Multi-objective Reactive Power Optimization Based on Improved Particle Swarm Algorithm
  • 本地全文:下载
  • 作者:Xue Cui ; Jian Gao ; Yunbin Feng
  • 期刊名称:IOP Conference Series: Earth and Environmental Science
  • 印刷版ISSN:1755-1307
  • 电子版ISSN:1755-1315
  • 出版年度:2018
  • 卷号:108
  • 期号:5
  • 页码:052081
  • DOI:10.1088/1755-1315/108/5/052081
  • 语种:English
  • 出版社:IOP Publishing
  • 摘要:In this paper, an optimization model with the minimum active power loss and minimum voltage deviation of node and maximum static voltage stability margin as the optimization objective is proposed for the reactive power optimization problems. By defining the index value of reactive power compensation, the optimal reactive power compensation node was selected. The particle swarm optimization algorithm was improved, and the selection pool of global optimal and the global optimal of probability (p-gbest) were introduced. A set of Pareto optimal solution sets is obtained by this algorithm. And by calculating the fuzzy membership value of the pareto optimal solution sets, individuals with the smallest fuzzy membership value were selected as the final optimization results. The above improved algorithm is used to optimize the reactive power of IEEE14 standard node system. Through the comparison and analysis of the results, it has been proven that the optimization effect of this algorithm was very good.
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