{"title":"Optimal Planning of Distribution Systems and Charging Stations Considering PV-Grid-EV Transactions","authors":"Haotian Yao;Yue Xiang;Chenghong Gu;Junyong Liu","doi":"10.1109/TSG.2024.3429371","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":13331,"journal":{"name":"IEEE Transactions on Smart Grid","volume":"16 1","pages":"691-703"},"PeriodicalIF":9.8000,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Smart Grid","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10599533/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
The IEEE Transactions on Smart Grid is a multidisciplinary journal that focuses on research and development in the field of smart grid technology. It covers various aspects of the smart grid, including energy networks, prosumers (consumers who also produce energy), electric transportation, distributed energy resources, and communications. The journal also addresses the integration of microgrids and active distribution networks with transmission systems. It publishes original research on smart grid theories and principles, including technologies and systems for demand response, Advance Metering Infrastructure, cyber-physical systems, multi-energy systems, transactive energy, data analytics, and electric vehicle integration. Additionally, the journal considers surveys of existing work on the smart grid that propose new perspectives on the history and future of intelligent and active grids.