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Robust Expansion Planning of Electric Vehicle Charging System and Distribution Networks

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Large integration of electric vehicles(EVs)brings uncertainties and challenges for distribution networks.Reliability and allocation of charging systems(charging stations and piles)need strong support from the distribution network,whose expan-sion planning would be also greatly impacted by the incremental load from the charging system.To address this issue,a collabora-tive planning scheme of the EV charging system and distribution networks that combines economic and reliability benefits is proposed,which is formulated as a two-stage distributionally robust optimization model considering source-load uncertainties.First,a candidate EVCS planning scheme is obtained using queuing theory.Then,system reliability is quantified by adopting the average energy not supplied index and correlated integrated into the two-stage mixed-integer linear programming model.Finally,it is solved to perform distributionally robust expansion planning by the column and constraint generation algorithm.Effectiveness and scalability of the proposed planning method are illustrated by numerical case studies.Results indicate the planning scheme that considers economic and reliability benefit can perform better than traditional optimization methods.

Distribution network planningdistributionally robust optimizationelectric vehiclereliability benefit

Yue Xiang、Ping Xue、Yanliang Wang、Lixiong Xu、Wang Ma、Miadreza Shafie-khah、Junlong Li、Junyong Liu

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College of Electrical Engineering,Sichuan University,Chengdu 610065,China

State Grid Sichuan Technical Training Center,Sichuan Electric Vocational and Technical College,and also the College of Electrical Engineering,Sichuan University,Chengdu 610065,China

School of Technology and Innovations,Univer-sity of Vaasa,Vaasa 8130,Finland

Department of Electronic and Electrical Engineering,University of Bath,Bath BA2 7AY,UK

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2024

10.17775/CSEEJPES.2021.08540

中国电机工程学会电力与能源系统学报(英文版)
中国电机工程学会

中国电机工程学会电力与能源系统学报(英文版)

CSTPCDEI
ISSN：2096-0042
年,卷(期)：2024.10(6)