Coordinated Planning of Electric Vehicle Charging Infrastructure and Renewables in Power Grids

IF 3.3 Q3 ENERGY & FUELS IEEE Open Access Journal of Power and Energy Pub Date : 2023-01-01 DOI:10.1109/OAJPE.2023.3245993
Bo Wang;Payman Dehghanian;Dongbo Zhao
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引用次数: 2

Abstract

This paper proposes a new planning model to coordinate the expansion of electric vehicle charging infrastructure (EVCI) and renewables in power grids. Firstly, individual electric vehicle (EV) charging behaviours are modeled considering EV customers adopting smart charging services as the main charging method and those using fast charging, super fast charging and battery swapping services as a complementary charging approach. Next, EV aggregation and the associated system economic dispatch model are built. A novel model predictive control (MPC) learning approach is then proposed to iteratively learn the correlation between different types of EV charging loads and the EV interactions with renewables and other generating units in modern power grids of the future. The simulation results demonstrate that the proposed approach can be used to quantify the ratio of different types of charging loads in a region and strategically guide on the integration of EVs and renewables to achieve the clean energy transition goals. The proposed framework can also be used to decide charging capacity needs in a charging demand zone.
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电动汽车充电基础设施与电网可再生能源的协同规划
本文提出了一种新的规划模型,以协调电动汽车充电基础设施和可再生能源在电网中的扩展。首先,考虑以智能充电服务为主要充电方式,以快速充电、超快速充电和换电池服务为补充充电方式的电动汽车用户,对电动汽车的个人充电行为进行建模。其次,建立了电动汽车聚合及相关系统经济调度模型。然后提出了一种新的模型预测控制(MPC)学习方法,迭代学习未来现代电网中不同类型的电动汽车充电负荷与电动汽车与可再生能源和其他发电机组的相互作用之间的相关性。仿真结果表明,该方法可以量化区域内不同类型充电负荷的比例,为电动汽车与可再生能源的融合提供战略指导,实现清洁能源转型目标。所提出的框架也可用于确定充电需求区域的充电容量需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.80
自引率
5.30%
发文量
45
审稿时长
10 weeks
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