Kristoffer Christensen, Bo Nørregaard Jørgensen, Zheng Grace Ma
{"title":"基于多代理的模拟研究集中充电策略及其对电动汽车家庭充电生态系统的影响","authors":"Kristoffer Christensen, Bo Nørregaard Jørgensen, Zheng Grace Ma","doi":"arxiv-2408.10773","DOIUrl":null,"url":null,"abstract":"This paper addresses the critical integration of electric vehicles (EVs) into\nthe electricity grid, which is essential for achieving carbon neutrality by\n2050. The rapid increase in EV adoption poses significant challenges to the\nexisting grid infrastructure, particularly in managing the increasing\nelectricity demand and mitigating the risk of grid overloads. Centralized EV\ncharging strategies are investigated due to their potential to optimize grid\nstability and efficiency, compared to decentralized approaches that may\nexacerbate grid stress. Utilizing a multi-agent based simulation model, the\nstudy provides a realistic representation of the electric vehicle home charging\necosystem in a case study of Strib, Denmark. The findings show that the\nEarliest-deadline-first and Round Robin perform best with 100% EV adoption in\nterms of EV user satisfaction. The simulation considers a realistic adoption\ncurve, EV charging strategies, EV models, and driving patterns to capture the\nfull ecosystem dynamics over a long-term period with high resolution (hourly).\nAdditionally, the study offers detailed load profiles for future distribution\ngrids, demonstrating how centralized charging strategies can efficiently manage\ngrid loads and prevent overloads.","PeriodicalId":501315,"journal":{"name":"arXiv - CS - Multiagent Systems","volume":"113 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-Agent Based Simulation for Investigating Centralized Charging Strategies and their Impact on Electric Vehicle Home Charging Ecosystem\",\"authors\":\"Kristoffer Christensen, Bo Nørregaard Jørgensen, Zheng Grace Ma\",\"doi\":\"arxiv-2408.10773\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper addresses the critical integration of electric vehicles (EVs) into\\nthe electricity grid, which is essential for achieving carbon neutrality by\\n2050. The rapid increase in EV adoption poses significant challenges to the\\nexisting grid infrastructure, particularly in managing the increasing\\nelectricity demand and mitigating the risk of grid overloads. Centralized EV\\ncharging strategies are investigated due to their potential to optimize grid\\nstability and efficiency, compared to decentralized approaches that may\\nexacerbate grid stress. Utilizing a multi-agent based simulation model, the\\nstudy provides a realistic representation of the electric vehicle home charging\\necosystem in a case study of Strib, Denmark. The findings show that the\\nEarliest-deadline-first and Round Robin perform best with 100% EV adoption in\\nterms of EV user satisfaction. The simulation considers a realistic adoption\\ncurve, EV charging strategies, EV models, and driving patterns to capture the\\nfull ecosystem dynamics over a long-term period with high resolution (hourly).\\nAdditionally, the study offers detailed load profiles for future distribution\\ngrids, demonstrating how centralized charging strategies can efficiently manage\\ngrid loads and prevent overloads.\",\"PeriodicalId\":501315,\"journal\":{\"name\":\"arXiv - CS - Multiagent Systems\",\"volume\":\"113 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Multiagent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2408.10773\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Multiagent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.10773","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-Agent Based Simulation for Investigating Centralized Charging Strategies and their Impact on Electric Vehicle Home Charging Ecosystem
This paper addresses the critical integration of electric vehicles (EVs) into
the electricity grid, which is essential for achieving carbon neutrality by
2050. The rapid increase in EV adoption poses significant challenges to the
existing grid infrastructure, particularly in managing the increasing
electricity demand and mitigating the risk of grid overloads. Centralized EV
charging strategies are investigated due to their potential to optimize grid
stability and efficiency, compared to decentralized approaches that may
exacerbate grid stress. Utilizing a multi-agent based simulation model, the
study provides a realistic representation of the electric vehicle home charging
ecosystem in a case study of Strib, Denmark. The findings show that the
Earliest-deadline-first and Round Robin perform best with 100% EV adoption in
terms of EV user satisfaction. The simulation considers a realistic adoption
curve, EV charging strategies, EV models, and driving patterns to capture the
full ecosystem dynamics over a long-term period with high resolution (hourly).
Additionally, the study offers detailed load profiles for future distribution
grids, demonstrating how centralized charging strategies can efficiently manage
grid loads and prevent overloads.