Fault section estimation in power systems using a genetic algorithm

In this paper, a new method of fault section estimation in power systems using genetic algorithms (GAs) is presented. The main contributions of this paper include the following three aspects: (a) the fault section estimation problem is formulated as a 0–1 integer programming problem; (b) an efficient method to identify the faulty subnetworks is developed by using information from circuit breakers, and thus the fault diagnosis can be fulfilled in a very short time for large-scale power systems and can be implemented online; (c) a new method based upon a genetic algorithm is used to solve the fault section estimation problem, and the simulation results show that the GA based method can find multiple optimal solutions directly and efficiently in a single run, which is very suitable for complex fault diagnosis problems, especially for situations where protective relays and/or circuit breakers malfunction, because different combinations of fault sections and protective relay and/or circuit breaker malfunctions may give the same alarms.