Hierarchical Control Strategy for Reactive Power and Voltage of Wind Farm Cluster Based on Adjacent Experiential Particle Swarm Optimization

被引：0
作者：
Yang J. [1 ]
Hao J. [2 ]
Bo Z. [3 ]
机构：
[1] College of Information Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning Province
[2] Shenyang Power Supply Company, State Grid Liaoning Provincial Power Grid Corp, Shenyang, 110811, Liaoning Province
[3] XJ Group Corporation, Xuchang, 461000, Henan Province
来源：
Dianwang Jishu/Power System Technology | 2017年 / 41卷 / 06期
关键词：
Adjacent experiential particle swarm optimization algorithm; DFIG; Reactive power and voltage control; Wind farms cluster;
D O I：
10.13335/j.1000-3673.pst.2016.2237
中图分类号：
学科分类号：
摘要：
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. © 2017, Power System Technology Press. All right reserved.
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页码：1823 / 1829
页数：6
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