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Logistics park charging station optimization using improved genetic algorithms
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DOI：10.1080/15472450.2024.2418922.png)
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The one-time investment and later operation efficiency of the supporting charging station are critical for the length of the investment return cycle. In this article, to meet the charging demand of logistics parks as the precondition, through the minimum total cost (construction, operation, maintenance, and depreciation) as the objective function, the improved genetic algorithm (GA) is used to look for the optimal solution. The operations of the charging station planning of a logistics park in off-season and peak-season are simulated and analyzed. The results show that the model and calculation method proposed in this article can provide effective support for the planning decision of logistics park charging. This study can guide the improvement and management in charging station configuration.
Keyword:
charging station
costs
electric vehicle
genetic algorithm
logistics park
期刊
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3.8
论文数:
4.6K
被引数:
1.2W
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