基于分层分区协同进化算法的电力系统无功优化

随着电力系统的大范围互联以及电压等级的增多,无功优化问题变得越来越复杂。无功优化问题是一个多变量、非线性、非连续性问题,在不同电压等级电网中无功又有不同的特点。针对电力系统无功优化的上述特点以及大范围互联电网控制变量较多的问题,提出了按电压等级将电力系统分层,各层之间独立优化互不影响,层内分区域并采用协同进化算法优化的方法。对于电力系统分层的方法作了探讨,提出了节点分裂的方法。在此基础上针对层内无功优化详细讨论了协同进化算法的原理、步骤以及其应用。IEEE30节点的算例表明,该方法要优于DFP,BFS等经典优化算法以及普通遗传算法。

Power System Reactive Power Optimization Based on Layering Partition Cooperative Evolutionary Algorithm

With the wide interconnection of the power system and the increasing voltage levels,the reactive power optimization problem is getting more and more complicated.it is multivariate,non-liner,non-successive,and has different peculiarities in different voltage grades.According to the problems above,this paper proposes a new method for the reactive power optimization,which divides the power system into several levels in term of the voltage grades.Each level is divided into several areas and is optimized by means of cooperative evolutionary algorithm independently.IEEE 30 buses simulation results show that compared with DFP,BFS and conventional genetic algorithm,this method has a better optimization result.