应用人工神经网络分析电力系统n-1故障安全性

SECURITY ANALYSIS OF n-1 FAULTS IN POWRE SYSTEMS USING ARTIFICIAL NEURAL NETWORK

本文提出应用人工神经网络进行电力系统n-1故障安全分析,文中介绍了神经网络模型的选取,使用加速B—P学习算法,经样本训练,能快速有效地识别系统n-1故障安全性,并给出调整对策. 本文经过系统测试,所得结果证明该方法可行、效果满意、适用于在线运行。程序在IBM PC—XT微机上实现。

In this paper we propose using artificial neural networks(ANNS) as an operator aid in the security analysis of n-1 faults in power systems. Firstly, in this paper we discuse the basic model of ANN S Selection and it′s some advantage over tyaditional, we study the samples to selected. next the method of spced-up Back-Propagation algorithm was introduced in detail and example which include 10 generators and 50 lines was calculated, after through train by typical sample,the ANN S can identify the security of n-1 faults in power systems fast and effectively, and giving out a rectifying plan.