Application of improved PSO algorithm in power grid fault diagnosis

This paper proposes a method to improve the weight of Particle swarm optimization (PSO) by using similarity, so as to realize the fast and accurate diagnosis of power grid fault. First, a mathematical model of power grid fault diagnosis is established by analyzing the circuit breaker, equipment protection and action information in the power grid. Next, the model is transformed into a 0-1 integer programming problem. Last, the traditional PSO algorithm is improved, so that the inertia weight in the algorithm can be adjusted dynamically according to the concept of similarity. Simulation results show that the improved PSO greatly increases the convergence speed and efficiency of power grid fault diagnosis.