Optimal configuration method for electric automobile charging pile

Abstract

The invention discloses an optimal configuration method for an electric automobile charging pile. The method comprises the following steps: predicting the charging power demand of a planning area by a Monte Carlo simulation method on the basis of analysis of various electric automobile behavior characteristics; building a bi-level planning model of charging station investment profit and user perception effect under the consideration of constraint conditions such as a power grid, a charging station and an investor budget; and introducing a KKT (Karush-Kuhn-Tucker) condition to realize equivalent conversion of a double-layer model and a single-layer model, and solving by adopting a variable neighborhood search-particle swarm mixed algorithm with a convergence polymerization degree. Through adoption of the method, the problem of premature convergence of particles is avoided effectively; population diversity is increased; the optimization capacity of the particles and the convergence speed of the algorithm are improved and increased remarkably; the calculation speed and the calculation accuracy of optimal configuration of the charging station are increased; and important references are provided for investors to plan and build the charging station under an enterprise-dominant pattern.

Description

technical field [0001] The invention relates to the technical field of optimal configuration of electric vehicle charging stations, in particular to a method for optimal configuration of electric vehicle charging stations. Background technique [0002] In recent years, countries around the world have reached a consensus on strengthening the development and utilization of renewable energy under the dual pressure of energy crisis and environmental pollution. At present, as a green vehicle that can make full use of renewable energy to achieve energy conservation and environmental protection, electric vehicles have been rapidly developed and widely used in developed countries such as Europe, America, and Japan. Investors of enterprises under the enterprise-led model (such as Tesla, BYD, BAIC and other large automobile manufacturers) pay more attention to the investment income and comprehensive market competitiveness of electric vehicle charging stations. One of the key concerns...

AI Technical Summary

Problems solved by technology

The particle swarm optimization algorithm adopted is an intelligent optimization algorithm based on social group behavior, which has fast search ability, but it often falls into local optimum due to the loss of population diversity and premature convergence in the later stage of evolution.

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