Ruifeng Zhao
ABSTRACT
Good self-healing ability is a sign of smart power grid construction and also an important research direction of distribution network planning. The optimal switch configuration based on distribution automation can effectively improve the self-healing ability of distribution network. In order to demonstrate the superiority of the improved binary particle swarm optimization algorithm, the standard binary particle swarm optimization algorithm is applied to solve the optimization problem. The improved binary particle swarm optimization algorithm used in this paper effectively improves the disadvantage of the standard particle swarm optimization algorithm, which is easy to fall into local optimum, and has good convergence. In the process of solving the model, the convergence of PSO algorithm is greatly improved by nonlinear adjustment of inertia coefficient and learning factor. In the 100 operations, the standard binary particle swarm optimization algorithm failed to converge 18 times, and the average number of iterations reached convergence was 116 times. However, the number of unconvergence of the improved binary particle swarm optimization algorithm is only 0, and the average number of iterations reaching convergence is 35.
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Index Terms
- Research on Self-healing Optimization of Distribution Network Switch based on Binary Particle Swarm Optimization
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