期刊
ENERGIES
卷 15, 期 14, 页码 -出版社
MDPI
DOI: 10.3390/en15145027
关键词
charging station; electric vehicles; immune algorithm; optimization
资金
- Shandong Provincial Natural Science FoundationShandong Provincial Natural Science Foundation [ZR2020QF059, ZR2021MF131]
- Foundation of State Key Laboratory of Automotive Simulation and Control [20181119]
This paper proposes an electric vehicle charging station site-selection model based on kernel density analysis of urban population, and designs an immune algorithm to optimize the solution. The effectiveness of the model is validated through a simulation example in Jinan City, and a comparison with traditional models is conducted.
To solve the problem of layout design of charging stations in the early stage of the electric vehicle industry, the user's satisfaction and the charging convenience are considered. An electric vehicle charging station site-selection model is established based on the kernel density analysis of the urban population. The goal of this model is maximum electric vehicle user satisfaction and the highest charging convenience. Then, according to model characteristics, the immune algorithm is designed and optimized to solve the model. The optimization of the immune algorithm includes two aspects. On the one aspect, judging that the stop condition is added in the mutation link. On the other aspect, two mutation operators are designed in the optimized immune algorithm. Finally, the simulation example is determined by a three-step method in Jinan City. The results show that the electric vehicle charging station site-selection model in this paper can better meet user needs compared with traditional models. Compared with the traditional immune algorithm, the convergence speed of the optimized immune algorithm is improved, and the proposed algorithm is superior to the traditional immune algorithm in terms of stability and accuracy.
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