An Jiang , Jiehong Qiu , Aiyuan Li , Guangnan Zhang
{"title":"An empirical analysis framework to evaluate the impact of residential electric vehicles on power grid","authors":"An Jiang , Jiehong Qiu , Aiyuan Li , Guangnan Zhang","doi":"10.1016/j.tranpol.2025.07.038","DOIUrl":null,"url":null,"abstract":"<div><div>This paper proposes an empirical analysis framework to model the charging behavior of electric vehicles (EVs) and estimate the impact on power grid. This method relies solely on residential charging data and is universally applicable to power grids in different regions. Moreover, the approach enables the simulation of the charging demand under varying EV ownership rate levels and the calculation of the maximum number of EVs that a given area can support without overloading the power grid. As a case study, we collect data on residential charging behavior from a city in Central China to estimate model parameters. Combining with load data, we find that even with a 5 % ownership rate, EVs will not significantly burden the grid load on most days throughout the year or during off-peak hours of the day. However, attention must be given to peak months and peak hours of the day. Additionally, we analyze the ownership rate of EVs that the city can sustain and determine that, with 6 % of the available capacity of distribution transformers, the city can accommodate EVs for 8.12 % of its population. This paper contributes to the engineering management of EVs charging, EVs promotion strategies, and the stability of power grid.</div></div>","PeriodicalId":48378,"journal":{"name":"Transport Policy","volume":"173 ","pages":"Article 103757"},"PeriodicalIF":6.3000,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transport Policy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0967070X25002914","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper proposes an empirical analysis framework to model the charging behavior of electric vehicles (EVs) and estimate the impact on power grid. This method relies solely on residential charging data and is universally applicable to power grids in different regions. Moreover, the approach enables the simulation of the charging demand under varying EV ownership rate levels and the calculation of the maximum number of EVs that a given area can support without overloading the power grid. As a case study, we collect data on residential charging behavior from a city in Central China to estimate model parameters. Combining with load data, we find that even with a 5 % ownership rate, EVs will not significantly burden the grid load on most days throughout the year or during off-peak hours of the day. However, attention must be given to peak months and peak hours of the day. Additionally, we analyze the ownership rate of EVs that the city can sustain and determine that, with 6 % of the available capacity of distribution transformers, the city can accommodate EVs for 8.12 % of its population. This paper contributes to the engineering management of EVs charging, EVs promotion strategies, and the stability of power grid.
期刊介绍:
Transport Policy is an international journal aimed at bridging the gap between theory and practice in transport. Its subject areas reflect the concerns of policymakers in government, industry, voluntary organisations and the public at large, providing independent, original and rigorous analysis to understand how policy decisions have been taken, monitor their effects, and suggest how they may be improved. The journal treats the transport sector comprehensively, and in the context of other sectors including energy, housing, industry and planning. All modes are covered: land, sea and air; road and rail; public and private; motorised and non-motorised; passenger and freight.