Fault-section estimation in power systems based on improved optimization model and binary particle swarm optimization

This paper proposes an improved model which takes the failure of protetive relays (PRs) or circuit breakers (CBs) into account, and classifies different information per its importance. A weighted contribution factor is introduced in objective function, which aims to solve two problems: the influence of PRs and CBs failure, and information important factor. Binary Particle Swarm Optimization (BPSO) is employed to solve the fault-section estimation (FSE) optimization problems. In order to measure the efficiency of BPSO and make comparisons, a Genetic Algorithm (GA) is also employed. The software codes have been developed to implement the algorithms. Numerical studies reveal that BPSO is superior to GA for the convergence speed and estimation results. The proposed method based on the new model and BPSO is rational and practical and the diagnosis results are more accurate.

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