神经网络法电力系统状态估计  

Power System State Estimation Using the ArtificialNeural Network Method

作　　者：李光熹[1] 熊曼丽[1] 

机构地区：[1]武汉水利电力大学电力工程系

出　　处：《武汉水利电力大学学报》1995年第1期58-60,共3页Engineering Journal of Wuhan University

摘　　要：提出了一种神经网络（Ｈｏｐｆｉｅｌｄ连续ＡＮＮ）法求解电力系统状态估计问题的新方法．根据加权最小二乘原理导出的状态估计模型可计及各种伪量测量．采用ＡＮＮ神经计算，可实现并行分布处理．经数值实例计算，结果表明，该方法是有效的，而且精度高、数值稳定性好．A new method of artificial neural network (Hopfield Continuous ANN ) is presented for solving problems of power system state estimation. According to the theory ofweighted least square, the state estimation model derived by the authors can take variousfictitious measurements into account. The parallel disposal of distribution can be realized byANN. The numerical calculations prove that this method is effective and has the advantagesof higher accuracy and satisfactory numerical stability.

关 键 词：电力系统 神经网络法 状态估计 

分 类 号：TM769[电气工程—电力系统及自动化] TM734