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

作　　者：杜丽艳 李磊 姚庆华 刘宏君 

机构地区：[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

出　　处：《电测与仪表》2016年第24期33-38,共6页Electrical Measurement & Instrumentation

摘　　要：针对风电场的无功优化和电压稳定问题,结合其并网的智能变电站内的静止无功补偿器(SVC),提出了一种综合考虑SVC和双馈风电机组(DFIG)的无功电压协调控制策略。采用学习自动机求解多目标无功优化的最优权衡解,在满足风电场公共接入点的电压要求的同时,使得风电场无功源的无功裕度更大。最后,以华东某风电场进行算例分析,验证了所提无功电压协调控制策略的可行性和有效性。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 

分 类 号：TM761[电气工程—电力系统及自动化]