A Fault Diagnosis Method of Power Systems Based on Improved Objective Function and Genetic Algorithm-Tabu Search

Abstract

Based on the improved optimization objective function of fault diagnosis, a genetic algorithm-Tabu search (GATS) method is introduced for the purpose of fault diagnosis of power systems. The genetic algorithm has good global search ability, while the Tabu search algorithm has good local search ability. Integrating the advantages of these two algorithms, a new hybrid algorithm, called GATS, can be obtained. Using the function of Shcaffer, the advantages of GATS are proven in this paper. The results of case studies show that GATS is superior to conventional methods in terms of the sensitivity of original solution and the dependency of original parameters. The satisfactory results can be obtained when the GATS method is applied in the event of abnormal operations of protective relays and circuit breakers or the multiple-fault scenarios.