Scholarlink

This article presents an approach applying an evolutionary algorithm for the problem of locating the charging infrastructure for electric vehicles, a very relevant problem in the context of smart cities. An automatic method employing a multi-objective evolutionary algorithm, specifically NSGA-II, is developed with the objective of maximizing energy demand fulfillment while minimizing the associated costs. Furthermore, the approach is restricted to guaranteeing effective coverage of the designated area. A real case study is addressed using existing gas station locations and different service demand scenarios. The results demonstrate the effectiveness of the proposed approach to optimize the location of chargers according to the established criteria and highlight the potential of evolutionary optimisation techniques to solve complex urban planning problems.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

An Evolutionary Approach for Determining Electric Vehicle Charging Infrastructure Location: A Case Study in Montevideo

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Rodrigo Gordienko,
  • Joaquín Scaletti,
  • Sergio Nesmachnow,
  • Jamal Toutouh

摘要

This article presents an approach applying an evolutionary algorithm for the problem of locating the charging infrastructure for electric vehicles, a very relevant problem in the context of smart cities. An automatic method employing a multi-objective evolutionary algorithm, specifically NSGA-II, is developed with the objective of maximizing energy demand fulfillment while minimizing the associated costs. Furthermore, the approach is restricted to guaranteeing effective coverage of the designated area. A real case study is addressed using existing gas station locations and different service demand scenarios. The results demonstrate the effectiveness of the proposed approach to optimize the location of chargers according to the established criteria and highlight the potential of evolutionary optimisation techniques to solve complex urban planning problems.