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《Power System Technology》 2017-12
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Power Grid Fault Diagnosis Based on Immune Clonal Constrained Multi-Objective Optimization Method

WANG Shoupeng;ZHAO Dongmei;School of Electrical and Electronic Engineering,North China Electric Power University;  
Aiming at the problem that weight values in existing mathematical models for power grid fault diagnosis based on optimization technology are remarkably affected by artificial subjective factors,this paper presents a fault diagnosis approach based on immune clonal constrained multi-objective optimization method.Firstly,this paper analyses objective functions of original models,and then employs multi-objective method to transform the fault diagnosis into a multi-objective optimization problem.Pareto method is used to solve the problem,avoiding errors caused by artificial setting of weights in procedure of fault diagnosis.Secondly,considering shortcomings of existing mathematical models applying penalty function method to deal with constraints,this paper transforms the constraints into an objective function,converting constrained multi-objective optimization problem to an unconstrained one.And then an immune clonal constrained multi-objective optimization algorithm is put forward to achieve optimal solution.Procedure of the optimization algorithm for power grid fault diagnosis is formulated.Finally,fuzzy set theory is used to evaluate Pareto optimal solution.Based on fault diagnosis cases,feasibility and efficiency of the developed method is verified.
【Fund】: 国家自然科学基金项目(51377054);; 中央高校基本科研业务费专项资金资助项目(2017XS019)~~
【CateGory Index】: TM732
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