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An analytic model and genetic algorithm based methos for fault diagnosis in power systems Part 1:The model and method

Wen Fushuan Han Zhenxiang Tian Lei Shi Juewei (Dept of Electrical Engineering,Zhejiang University Hangzhou 310027) Zhang Huaiyu (Central Dispatching Institute,Zhejiang Provincial Power Company 310007)  
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.
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