{"title":"EVs and ERCOT: Foundations for Modeling Future Adoption Scenarios and Grid Implications","authors":"Kelsey Nelson, Pedro S. Moura, J. Mohammadi","doi":"10.1109/MSCPES58582.2023.10123430","DOIUrl":null,"url":null,"abstract":"Electric vehicles (EVs) are becoming more commonplace in Texas, mainly due to their increasing attractiveness to consumers and pushes from the state’s governing bodies to incentivize further adoption. Meanwhile, service from Texas’s electric grid, ERCOT, has been seeing increases in power demand due to a growing population, increased air conditioning use, and pushes for electrification across other industries. The electrification of vehicles will only add to this demand increase. This paper focuses on evaluating different EV adoption, charging management, and policy scenarios, and how they will be expected to impact ERCOT, particularly with respect to peak demand increases. A strong increase in peak demand makes it more difficult for grids to serve power demand at all times, making it an important consideration when seeking to electrify a sector as energy intense as transportation. This paper introduces preliminary results from modeling relevant baseline scenarios and provides insight for future models to build off of. The anticipated impacts of EV adoption on peak demand are quantified using ERCOT’s data on past generation and planned installations, the approximated effectiveness of EV incentives, EV charging profiles, and travel patterns. The results showcase the fact that the achievement of ambitious EV market share goals will be manageable on a statewide level regarding electricity supply into 2030, but will eventually necessitate ambitious charging management strategies in order to limit the EV fleet’s potentially heavy impact on peak demand looking forward into 2050 and beyond.","PeriodicalId":162383,"journal":{"name":"2023 11th Workshop on Modelling and Simulation of Cyber-Physical Energy Systems (MSCPES)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 11th Workshop on Modelling and Simulation of Cyber-Physical Energy Systems (MSCPES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MSCPES58582.2023.10123430","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Electric vehicles (EVs) are becoming more commonplace in Texas, mainly due to their increasing attractiveness to consumers and pushes from the state’s governing bodies to incentivize further adoption. Meanwhile, service from Texas’s electric grid, ERCOT, has been seeing increases in power demand due to a growing population, increased air conditioning use, and pushes for electrification across other industries. The electrification of vehicles will only add to this demand increase. This paper focuses on evaluating different EV adoption, charging management, and policy scenarios, and how they will be expected to impact ERCOT, particularly with respect to peak demand increases. A strong increase in peak demand makes it more difficult for grids to serve power demand at all times, making it an important consideration when seeking to electrify a sector as energy intense as transportation. This paper introduces preliminary results from modeling relevant baseline scenarios and provides insight for future models to build off of. The anticipated impacts of EV adoption on peak demand are quantified using ERCOT’s data on past generation and planned installations, the approximated effectiveness of EV incentives, EV charging profiles, and travel patterns. The results showcase the fact that the achievement of ambitious EV market share goals will be manageable on a statewide level regarding electricity supply into 2030, but will eventually necessitate ambitious charging management strategies in order to limit the EV fleet’s potentially heavy impact on peak demand looking forward into 2050 and beyond.