{"title":"利用基于链路传输模型的电动汽车动态交通分配,主动增强电力系统的复原力","authors":"Haoyuan Yan;Tianyang Zhao;Zhanglei Guan","doi":"10.17775/CSEEJPES.2022.07470","DOIUrl":null,"url":null,"abstract":"The rapid development of electric vehicles (EVs) is strengthening the bi-directional interactions between electric power networks (EPNs) and transportation networks (TNs) while providing opportunities to enhance the resilience of power systems towards extreme events. To quantify the temporal and spatial flexibility of EVs for charging and discharging, a novel dynamic traffic assignment (DTA) problem is proposed. The DTA problem is based on a link transmission model (LTM) with extended charging links, depicting the interaction between EVs and power systems. It models the charging rates as continuous variables by an energy boundary model. To consider the evacuation requirements of TNs and the uncertainties of traffic conditions, the DTA problem is extended to a two-stage distributionally robust version. It is further incorporated into a two-stage distributionally robust unit commitment problem to balance the enhancement of EPNs and the performance of TNs. The problem is reformulated into a mixed-integer linear programming problem and solved by off-the-shelf commercial solvers. Case studies are performed on two test networks. The effectiveness is verified by the numerical results, e.g., reducing the load shedding amount without increasing the unmet traffic demand.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"10 3","pages":"1320-1330"},"PeriodicalIF":6.9000,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10520179","citationCount":"0","resultStr":"{\"title\":\"Proactive Resilience Enhancement of Power Systems with Link Transmission Model-Based Dynamic Traffic Assignment Among Electric Vehicles\",\"authors\":\"Haoyuan Yan;Tianyang Zhao;Zhanglei Guan\",\"doi\":\"10.17775/CSEEJPES.2022.07470\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rapid development of electric vehicles (EVs) is strengthening the bi-directional interactions between electric power networks (EPNs) and transportation networks (TNs) while providing opportunities to enhance the resilience of power systems towards extreme events. To quantify the temporal and spatial flexibility of EVs for charging and discharging, a novel dynamic traffic assignment (DTA) problem is proposed. The DTA problem is based on a link transmission model (LTM) with extended charging links, depicting the interaction between EVs and power systems. It models the charging rates as continuous variables by an energy boundary model. To consider the evacuation requirements of TNs and the uncertainties of traffic conditions, the DTA problem is extended to a two-stage distributionally robust version. It is further incorporated into a two-stage distributionally robust unit commitment problem to balance the enhancement of EPNs and the performance of TNs. The problem is reformulated into a mixed-integer linear programming problem and solved by off-the-shelf commercial solvers. Case studies are performed on two test networks. The effectiveness is verified by the numerical results, e.g., reducing the load shedding amount without increasing the unmet traffic demand.\",\"PeriodicalId\":10729,\"journal\":{\"name\":\"CSEE Journal of Power and Energy Systems\",\"volume\":\"10 3\",\"pages\":\"1320-1330\"},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2024-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10520179\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CSEE Journal of Power and Energy Systems\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10520179/\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CSEE Journal of Power and Energy Systems","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10520179/","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Proactive Resilience Enhancement of Power Systems with Link Transmission Model-Based Dynamic Traffic Assignment Among Electric Vehicles
The rapid development of electric vehicles (EVs) is strengthening the bi-directional interactions between electric power networks (EPNs) and transportation networks (TNs) while providing opportunities to enhance the resilience of power systems towards extreme events. To quantify the temporal and spatial flexibility of EVs for charging and discharging, a novel dynamic traffic assignment (DTA) problem is proposed. The DTA problem is based on a link transmission model (LTM) with extended charging links, depicting the interaction between EVs and power systems. It models the charging rates as continuous variables by an energy boundary model. To consider the evacuation requirements of TNs and the uncertainties of traffic conditions, the DTA problem is extended to a two-stage distributionally robust version. It is further incorporated into a two-stage distributionally robust unit commitment problem to balance the enhancement of EPNs and the performance of TNs. The problem is reformulated into a mixed-integer linear programming problem and solved by off-the-shelf commercial solvers. Case studies are performed on two test networks. The effectiveness is verified by the numerical results, e.g., reducing the load shedding amount without increasing the unmet traffic demand.
期刊介绍:
The CSEE Journal of Power and Energy Systems (JPES) is an international bimonthly journal published by the Chinese Society for Electrical Engineering (CSEE) in collaboration with CEPRI (China Electric Power Research Institute) and IEEE (The Institute of Electrical and Electronics Engineers) Inc. Indexed by SCI, Scopus, INSPEC, CSAD (Chinese Science Abstracts Database), DOAJ, and ProQuest, it serves as a platform for reporting cutting-edge theories, methods, technologies, and applications shaping the development of power systems in energy transition. The journal offers authors an international platform to enhance the reach and impact of their contributions.