Abstract
Aiming at the problem of site selection for electric vehicle charging station, a comprehensive optimization objective function considering construction cost and running cost was established. Based on the operating costs such as land cost, construction cost and power loss, and the traffic convenience of users, the objective function comprehensively and scientifically reflects the essence of electric vehicle charging station location. The location of electric vehicle charging station is a multiobjective, multi-constrained and nonlinear optimization problem. On the basis of determining the objective function, the dynamic adaptive adaptive inertia weight coefficient and improved particle swarm optimization with random particle individual are proposed. The algorithm solves this problem and reasonably avoids the disadvantage that the particle swarm algorithm is easy to fall into the local optimal solution. Using this algorithm and the optimized model, the electric vehicle charging station in a certain area is planned. The comparison analysis shows that the method is feasible and effective.
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