Optimal planning of flood‐resilient electric vehicle charging stations

Abstract

This study is the first attempt to integrate flood resilience into the electric vehicle (EV) charging station planning process. Instead of fully avoiding flood-prone areas, an optimized placement considering the magnitude of flood inundations can minimize the impact of flood hazards and simultaneously maximize the socio-economic benefit of EV charging station networks. In this study, an integrated framework of the non-dominated sorting genetic algorithm-III (NSGA-III) and the technique for order of preference by similarity to ideal solution (TOPSIS) is proposed to optimize the charging station locations by maximizing the charging convenience, minimizing the impact of flood hazards, and minimizing the impact of existing charging stations. The NSGA-III is applied to solve the multi-objective location optimization of charging stations.TOPSIS is subsequently used to determine the best solution from the feasible candidates generated by the NSGA-III. A case study conducted in the Waikiki area demonstrates that the proposed optimization framework can effectively deal with the trade-off between the impact of flood hazards and the charging service of a charging station network. This study provides new insights into best practices for dealing with multiple conflicting objectives in EV charging station planning under climate change.

Strategies and sustainability in fast charging station deployment for electric vehicles

“…To address these issues, numerous studies have been conducted to analyze and mitigate their impacts using appropriate algorithms. Twenty-Four related studies 97 – 119 will be discussed in the following subsections to define the main characteristics of recent approaches and research gaps in FCS planning.…”

“…Several publications aim to enhance the voltage profile and quality of the distribution grid by optimizing the sizing and location of charging stations, DGs, and other renewable sources. The objective is to minimize voltage fluctuations, improve thermal stability, and enhance the overall voltage profile 97 , 98 , 100 – 102 , 111 – 113 , 119 .…”

Electrical energy systems resilience: A comprehensive review on definitions, challenges, enhancements and future proceedings

“…The location and sizing of components in electrical energy systems are also determined by various approaches such as data-driven models [116,120,123]. The influence of EVs and parking lots is analysed in [122,124] and eventually, References [118,119,121] present modification strategies or transmission line expansion to enhance resiliency versus extreme events.…”

On the role of time‐of‐use electricity price in charge scheduling for electric bus fleets

“…Meanwhile, battery degradation can lead to reduced capacity, necessitating recharging during daily operations. Thus, when determining a BEB fleet's service schedules, the BEBs’ charging activities must be jointly considered to ensure that they can fulfill their assigned service runs without exhausting the batteries, commonly known as charge scheduling (X. Liu et al., 2023; Q. Zhang et al., 2023). Compared to the conventional bus scheduling problem for diesel buses, jointly optimizing the charge scheduling renders the BEB scheduling problem much more complicated (Ji et al., 2022; Zhao et al., 2021).…”