基于改进遗传算法的配电网无功优化

Reactive Power Optimization Based on Improved Genetic Algorithms in Distribution System

在传统无功优化模型的基础上,引入静态电压稳定裕度指标,建立了综合考虑系统有功网损最小、无功补偿容量最小和系统静态电压稳定裕度最大的配电网无功优化模型。根据节点无功2次电阻矩的大小,确定了待补偿节点以及各节点补偿容量的上下限。在基本遗传算法的基础上,对遗传操作进行了改进,提出了1种改进遗传算法。实例计算表明,采用该方法对配电网进行无功优化不仅可以降低有功网损,还能提高系统静态电压稳定性。

The reactive power optimization has profound significance to insure the safe and economic operation of power system. Based on the traditional reactive power model, A model of reactive power optimization in distribution system is established, which takes into account power loss minimization, reactive compensation capacity minimization and system static voltage stability margin maximization. Firstly, the nodes to be compensated and its compensation capacity limits are determined according to reactive secondary resistance moment. Then an improved genetic algorithms（IGA） is presented. The results show that the IGA can reduce network losses, and improve system static voltage stability.