摘要
本文共分三部分。第一部分发展了电力系统故障诊断的解析模型与基于遗传算法的方法；第二部分首先提出了用计算机自动形成故障诊断的目标函数的方法，这是实现在线故障诊断所必需的。之后介绍了为浙江省电力局开发的在线故障诊断实用软件的组成与功能；第三部分介绍了将该软件应用于浙江省２２０ｋＶ以上电力系统时其ＥＭＳ信息的获取方法及模拟在线测试结果。这里是第一部分，着重介绍了所发展的同时利用保护和断路器信息的故障诊断的解析模型。其在数学上是一个无约束０－１整数规划模型，借助于充分利用断路器的跳阐信息。这种模型在一定程度上解决了保护信息不完整时的电力系统的故障诊断问题。之后，概述了利用实时网络拓扑分析方法识别故障平息后的停电（故障）区域的方法，从而可将故障诊断局限于这些小的停电区域之中，以大大节省计算时间。此外，还简要介绍了用遗传算法求解故障诊断问题的基本步骤。
This is a 3 part paper.An analytic model and genetic algorithm (GA) based method for fault diagnosis in power systems is presented in Part 1.In Part 2,a method is first proposed for automatically forming the objective function of the GA based fault diagnosis method by computers, and this is essential for on line fault diagnosis implementation.Then,a brief description about the modulars and functions of the on line fault diagnosis software developed by the authors for Zhejiang Provincial Power Company is given. The adopted EMS data acquisition method and simulated on line test results for the 220 kV and above power system of Zhejiang Provincial Power Company are described in Part 3. Here is the first part.The emphasis of this part is to present an analytic model for the fault diagnosis problem utilizing the operating information form protective relays and circuit breakers,and this can be expressed as an unconstrained 0 1 integer programming problem.Through the sufficient use of the operating information from circuit breakers,this model is able to solve the fault diagnosis problem with incomplete information from protective relays to some extent.Afterwards,an efficient method is introduced to identify the dead islands (outage areas) after the occurrence of faults by utilizing the real time network topology analysis method. In this way,the fault diagnosis problem can be confined to the dead islands only and the time consumed for each diagnosis scenario can be greatly reduced.Finally,the main steps in using GA for solving the fault diagnosis problem is briefly introduced.
出处
《电力系统及其自动化学报》
CSCD
1998年第3期1-7,共7页
Proceedings of the CSU-EPSA
基金
浙江省中青年科技人才培养专项基金
曹光彪高科技发展基金
