Reactive Power Optimization of Distribution Network on Improved Genetic Algorithm

被引：0
|
作者：
Wu, Xiaomeng [1 ,2 ]
Guo, Xinyu [1 ]
Li, Fei [1 ]
Zhang, Achao [1 ]
机构：
[1] Xian Shiyou Univ, Sch Elect Engn, Xian, Shaanxi, Peoples R China
[2] Key Lab Measurement & Control Tech Oil & Gas Well, Xian, Shaanxi, Peoples R China
来源：
PROCEEDINGS OF 2018 IEEE 3RD ADVANCED INFORMATION TECHNOLOGY, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IAEAC 2018) | 2018年
关键词：
genetic algorithm; reactive power optimization; distribution network;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
An improved genetic algorithm is presented for solving the problem of slow convergence speed and premature phenomenon using traditional genetic algorithm in this paper. Combined with the characteristics of reactive power optimization of power system, binary code, initial population, crossover, mutation and fitness function had been improved by the proposed algorithm. The property and accuracy with the IEEE14 and IEEE30 bus system are tested, the results show that the model and algorithm avoid effectively premature phenomenon and reduce the active power loss in the evolution.
引用
收藏
页码：2048 / 2052
页数：5
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