电网技术2017，Vol.41Issue(6)：1823-1829,7.DOI:10.13335/j.1000-3673.pst.2016.2237
基于相邻经验粒子群算法的风电场集群无功电压分层控制策略
Hierarchical Control Strategy for Reactive Power and Voltage of Wind Farm Cluster Based on Adjacent Experiential Particle Swarm Optimization
摘要
Abstract
A hierarchical control strategy for reactive power and voltage is proposed with respect of characteristics of wind farm cluster. The strategy has two layers: calculator layer and allocation layer. Firstly, required reactive power is estimated with voltage at point of common coupling (PCC) of wind farm cluster. Secondly, number of generators participating in reactive power allocation is computed with bus voltage of wind farm branches. Then, reactive powers of generators and compensation devices are calculated with an optimization algorithm. The strategy can reduce input and improve convergence speed of the optimization algorithm. A modified particle swarm optimization algorithm, adjacent experiential particle swarm optimization (AEPSO), based on above control strategy is presented. Optimization results of adjacent branches are added to velocity formula of the algorithm to improve convergence speed. Simulation results show a better performance of the control strategy in respects of optimizing power loss and voltage deviation of wind farm cluster.关键词
双馈型风机/风电场集群/无功电压控制/相邻经验粒子群算法Key words
DFIG/wind farms cluster/reactive power and voltage control/adjacent experiential particle swarm optimization algorithm分类
信息技术与安全科学引用本文复制引用
杨珺,郝敬,薄志谦..基于相邻经验粒子群算法的风电场集群无功电压分层控制策略[J].电网技术,2017,41(6):1823-1829,7.基金项目
中央高校基本科研业务费专项资金(N160404010). Project Supported by the Fundamental Research Funds for the Central Universities (N160404010). （N160404010）
