Particle Swarm Optimization Algorithm And Quantum-Behaved Particle Swarm Optimization Algorithm For Power Fault Section Estimation

By utilizing the action information of circuit breakers and protective relays, power fault section estimation can deduce probable fault position, identify fault elements, circuit breakers and protective relays, assess action situation of circuit breaker and protective relays. Recognition of fault elements is most important. Power fault section estimation is the dispatcher's power incident helpers, it can play a part in shorting the processing time of the incident, preventing the incident expanding and enhancing the role of power system automation level.This paper introduces basic concepts, functional requirements, purpose and meaning of power fault section estimation, analyzes and compares the basic theory and common methods of power fault section estimation. Fault section estimation is demonstrated by a 0-1 integer programming model according to the acting theory of protective relays.This paper establishes its mathematical model, discusses the automatical formation method of the objective function and fault position automatic identification strategy as well as optimization algorithm.Paticle swarm optimization and quantum particle swarm algorithm are based on a new groups of search optimization method. They have parallel processing features, and they are easy to implement with efficient computing. This article describes the basic principles of the particle swarm algorithm and quantum-behaved paticle swarm optimization, discusses in detail the two kinds of the algorithm's processes and implementation steps, analyzes the algorithm parameters effecting on the algorithm itself. It solves the fault diagnosis's problem by applying particle swarm and quantum particle swarm optimization algorithm. The concrete steps of the algorithm and the parameters's selection are also detailed.A variety of fault conditions are simulated in this paper, results show that the proposed approach converges to better solutions. It is much faster and more steady than the earlier reported approaches. For complex fault, quantum-behaved particle swarm algorithm is more effective.