基于混沌神经网络的配电网无功优化  

Reactive Power Optimization of Distribution Network Based on Chaotic Artificial Neural Network

作　　者：危雪[1] 

机构地区：[1]三峡大学电气与新能源学院,湖北宜昌443002

出　　处：《电气开关》2011年第5期55-56,59,共3页Electric Switchgear

摘　　要：利用混沌人工神经网络对配电网中无功进行优化,模拟配电网中的"痛点",即无功配置不合理的线路,反应给神经元,令神经元输出"痛感",因此根据"痛点"找到无功配置不合理的线路,重新分配无功,直到实现配电网无功优化配置。经对IEEE30节点的配电网实例的计算,验证了该方法的有效性,更适应智能电网的要求。This thesis mainly focused on the study of reactive power optimization of distribution network by using chaotic artificial neural network.It depend on chaotic artificial neural network imitating the pain point of the grid,that once there was unsuitable reactive power on the line,the nerve cell can fell pain and had a pain output.Then we can find out where there is unsuitable reactive power,and redistribute reactive power once more,till the optimization of reactive power result had been found out.At last,the calculation results show that the presented method is effective through a calculation of a real distribution network with 30 nodes in IEEE.This method is also suitable for smart grids.

关 键 词：混沌神经网络 无功优化 配电网 

分 类 号：TM712[电气工程—电力系统及自动化]