电测与仪表2016，Vol.53Issue(24)：33-38,6.
基于学习自动机的智能变电站多目标无功优化
Multi-objective reactive power optimization strategy of smart substation based on learning automata
杜丽艳 1李磊 1姚庆华 1刘宏君2
作者信息
- 1. 国网冀北电力有限公司，北京100053
- 2. 长园深瑞继保自动化有限公司，广东深圳518057
- 折叠
摘要
Abstract
To solve the reactive power optimization and voltage stability problem for wind farm , considering the static var compensator ( SVC ) in the smart substation connected with power system , a reactive power and voltage control strategy is proposed to coordinate SVC and doubly-fed induction generator ( DFIG) .The optimal trade-off solution of multi-objective reactive power optimization is obtained by learning automata .Voltage requirement of point of common coupling (PCC) for wind farm is satisfied.At the same time, the reactive power margin of reactive power source in wind farm becomes bigger .Finally, taking a wind farm in East China as example for analysis , the simulation results show that the proposed reactive power and voltage control strategy is verified feasible and effective .关键词
智能变电站/双馈风电机组/静止无功补偿器(SVG)/学习自动机/无功优化Key words
smart substation/doubly-fed induction generator/static var compensator(SVC)/learning automata/re-active power optimization分类
信息技术与安全科学引用本文复制引用
杜丽艳,李磊,姚庆华,刘宏君..基于学习自动机的智能变电站多目标无功优化[J].电测与仪表,2016,53(24):33-38,6.
