Optimization of electric vehicle charging station layout considering the improvement of distribution network resilience under extreme disasters

IF 9.4 1区 工程技术 Q1 ENERGY & FUELS Energy Pub Date : 2025-03-27 DOI:10.1016/j.energy.2025.135831
Haozhou Mei , Qiong Wu , Hongbo Ren , Jinli Zhang , Qifen Li
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引用次数: 0

Abstract

The challenge posed by extreme natural disasters to the resilience of power distribution networks is growing increasingly severe. Electric vehicles, as distributed and mobile energy storage devices, have the potential to enhance the resilience of distribution networks through vehicle to grid technology. In this study, resilience is integrated into the evaluation metrics for charging station layout planning, and a methodology for the layout of electric vehicle charging stations is proposed, balancing both economy and resilience. After constructing a typical extreme disaster scenario model using typhoons as an example, a resilience deployment model for charging stations is developed, which comprehensively considers the resilience of the distribution network and traffic flow. The objective function is designed to minimize the annual total social cost, which includes factors such as construction and operation costs, user usage costs, charging loss costs, and resilience configuration costs. A joint solution algorithm, combining the Voronoi diagram and particle swarm optimization algorithm, is proposed to solve the model. According to the simulation results of an illustrative example, the resilience optimization scenario performs well in terms of load loss penalty. This indicates that, in extreme disaster situations, this planning approach can effectively mitigate losses caused by power outages and improve the reliability and stability of the power system.
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优化电动汽车充电站布局,考虑提高极端灾害下配电网的抗灾能力
极端自然灾害对配电网恢复能力的挑战日益严峻。电动汽车作为分布式和移动储能设备,有可能通过车辆到电网技术增强配电网的弹性。本研究将弹性纳入充电站布局规划的评价指标,提出了一种兼顾经济性和弹性的电动汽车充电站布局方法。在以台风为例构建典型极端灾害情景模型的基础上,综合考虑配电网和交通流的弹性,建立充电站弹性部署模型。目标函数的目的是最小化年度社会总成本,其中包括建设和运营成本、用户使用成本、充电损失成本和弹性配置成本等因素。提出了一种结合Voronoi图和粒子群优化算法的联合求解算法。实例仿真结果表明,弹性优化方案在负荷损失惩罚方面表现良好。这表明,在极端灾害情况下,该规划方法可以有效减轻停电造成的损失,提高电力系统的可靠性和稳定性。
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来源期刊
Energy
Energy 工程技术-能源与燃料
CiteScore
15.30
自引率
14.40%
发文量
0
审稿时长
14.2 weeks
期刊介绍: Energy is a multidisciplinary, international journal that publishes research and analysis in the field of energy engineering. Our aim is to become a leading peer-reviewed platform and a trusted source of information for energy-related topics. The journal covers a range of areas including mechanical engineering, thermal sciences, and energy analysis. We are particularly interested in research on energy modelling, prediction, integrated energy systems, planning, and management. Additionally, we welcome papers on energy conservation, efficiency, biomass and bioenergy, renewable energy, electricity supply and demand, energy storage, buildings, and economic and policy issues. These topics should align with our broader multidisciplinary focus.
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