Optimal Planning of Distribution Systems and Charging Stations Considering PV-Grid-EV Transactions

被引:2
|
作者
Yao, Haotian [1 ]
Xiang, Yue [1 ]
Gu, Chenghong [2 ]
Liu, Junyong [1 ]
机构
[1] Sichuan Univ, Coll Elect Engn, Chengdu 610065, Peoples R China
[2] Univ Bath, Dept Elect & Elect Engn, Bath BA27AY, England
基金
中国国家自然科学基金;
关键词
Planning; Electric vehicle charging; Indexes; Distribution networks; Substations; Peer-to-peer computing; Costs; Distribution network expansion planning; EV charging station; network charges; PV-grid-EV transactions; PV prosumer; ELECTRIC-POWER; TRANSPORTATION; OPTIMIZATION; NETWORKS; STRATEGY;
D O I
10.1109/TSG.2024.3429371
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Uncertainties associated with large-scale deployment of electric vehicles (EVs) and photovoltaic (PV) pose challenges to distribution network expansion planning (DNEP). This paper proposes an optimal planning method for EV charging stations (EVCS) and distribution systems to accommodate the ever-increasing uncertainties. It is achieved by entailing PV-grid-EV transactions, which enables EVCS and PV prosumers to trade energy to make profits while complying with grid securities. It offers a cost-effective operational alternative to long-term planning, which would otherwise result in PV curtailment or unnecessary DNEP. The transactive market operates on a peer-to-peer (P2P) basis and is cleared via a decentralized algorithm to protect privacy and enable autonomous decision-making. EVCS is incentivized by a designed network charge, quantifying its impact on adhering to security constraints from both long-term and short-term perspectives. Considering EV users' charging decisions, we derive optimal EV charging prices to regulate EV charging flow. We employ multiple linearization techniques to ensure the convergence of the non-convex model. Results demonstrate that the proposed method enables the distribution networks to accommodate the large-scale integration of EV and PV more effectively.
引用
收藏
页码:691 / 703
页数:13
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