基于改进粒子群算法的配电网无功优化

Reactive power optimization of distribution network based on improved particle swarm optimization algorithm

无功优化是保证系统可靠运行的重要措施,针对配电网无功优化的特点,提出一种基于局部电压稳定指标分区与改进粒子群算法相结合的配电网无功优化方法。首先计算系统负荷节点的局部电压稳定指标,根据电压稳定指标大小将负荷节点进行排序,选取排序在后的一部分负荷节点作为候选补偿点集合,结合电气距离将其分区;然后借助改进粒子群算法获得系统最佳补偿点位置与无功补偿量;最后在MATLAB中用IEEE33节点系统进行仿真验证,仿真结果表明,由局部电压稳定指标与电气距离相结合的方法可以缩小寻优范围,得到的候选补偿区合理有效,改进粒子群算法初始化粒子多样性更好,具有更快的收敛速度。

Reactive power optimization is an important measure to ensure the reliable operation of the system.According to the characteristics of reactive power optimization of distribution network,a reactive power optimization method based on localized voltage stability index partition and improved particle swarm optimization algorithm is proposed in this paper.Firstly,the local voltage stability index of the system load node is calculated,and the load nodes are sorted according to the voltage stability index.A part of the load nodes are sorted as the candidate compensation points,and the objects are partitioned by electrical distance.Then,optimal compensation point position and reactive power compensation amount are obtained through the improved particle swarm algorithm system.Finally,in MATLAB with IEEE33 node system simulation verification,the simulation results show that the method of combining the local voltage stability index with the electrical distance can narrow the optimization range,and obtain the candidate compensation area reasonably and effectively.The improved particle swarm algorithm is to initialize particle diversity better,with faster convergence speed.