Ahmed Abd Elaziz Elsayed;Shivam Saxena;Hany Essa Zidan Farag
{"title":"通过需求响应实现车辆建设和电网服务的规划和合同框架的优化设计","authors":"Ahmed Abd Elaziz Elsayed;Shivam Saxena;Hany Essa Zidan Farag","doi":"10.1109/TTE.2025.3529346","DOIUrl":null,"url":null,"abstract":"Bidirectional electric vehicle (EV) charging enables stored energy to reduce peak loads for vehicle to buildings (V2Bs) and the vehicle to grid (V2G). However, building owners investing in V2B infrastructure while generating revenue from V2G services face challenges in planning and coordinating with EV owners due to uncertainties in their schedules and profit-sharing expectations. Additionally, misaligned building and grid peak times can create conflicts between V2B and V2G goals, which may negatively impact the building electricity bill. Unlike previous studies that used a contract-free approach for aggregating V2B and V2G, resulting in inconsistent participation, this article proposes a novel planning and contracting framework that enables building owner to determine the optimal contract parameters with EV owners. These parameters include minimum participation time in DR events, minimum arrival state of charge (SoC), and permitted emergency departure hours. The framework supports V2B aggregation with on-site distributed energy resources (DERs) for DR and V2G services, ensuring transparency and fairness through shared profits and performance-based penalties, while compensating building electricity bills due to V2G activities. The framework is composed of a tri-stage optimization process that uses Monte Carlo simulations to generate EV owner profit assessments, select optimal EV candidates based on charger availability, estimate contract parameters with profit/penalty sharing, and assign contracts between power system operators (PSOs), building owners, and EV owners under multiple virtual scenarios. Simulation results validate the contract parameter assessment and its performance via a 3-day case study with real-world datasets that demonstrates net revenue generation of <inline-formula> <tex-math>${\\$}$ </tex-math></inline-formula>209 for each EV owner and <inline-formula> <tex-math>${\\$}$ </tex-math></inline-formula>950 for building owners during DR events with a return on investment (ROI) of 134.5% and 130.7% for the EVs and Building owners, respectively.","PeriodicalId":56269,"journal":{"name":"IEEE Transactions on Transportation Electrification","volume":"11 3","pages":"7542-7556"},"PeriodicalIF":8.5000,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimal Design of a Planning and Contracting Framework to Enable Vehicle to Building and Grid Services via Demand Response\",\"authors\":\"Ahmed Abd Elaziz Elsayed;Shivam Saxena;Hany Essa Zidan Farag\",\"doi\":\"10.1109/TTE.2025.3529346\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Bidirectional electric vehicle (EV) charging enables stored energy to reduce peak loads for vehicle to buildings (V2Bs) and the vehicle to grid (V2G). However, building owners investing in V2B infrastructure while generating revenue from V2G services face challenges in planning and coordinating with EV owners due to uncertainties in their schedules and profit-sharing expectations. Additionally, misaligned building and grid peak times can create conflicts between V2B and V2G goals, which may negatively impact the building electricity bill. Unlike previous studies that used a contract-free approach for aggregating V2B and V2G, resulting in inconsistent participation, this article proposes a novel planning and contracting framework that enables building owner to determine the optimal contract parameters with EV owners. These parameters include minimum participation time in DR events, minimum arrival state of charge (SoC), and permitted emergency departure hours. The framework supports V2B aggregation with on-site distributed energy resources (DERs) for DR and V2G services, ensuring transparency and fairness through shared profits and performance-based penalties, while compensating building electricity bills due to V2G activities. The framework is composed of a tri-stage optimization process that uses Monte Carlo simulations to generate EV owner profit assessments, select optimal EV candidates based on charger availability, estimate contract parameters with profit/penalty sharing, and assign contracts between power system operators (PSOs), building owners, and EV owners under multiple virtual scenarios. Simulation results validate the contract parameter assessment and its performance via a 3-day case study with real-world datasets that demonstrates net revenue generation of <inline-formula> <tex-math>${\\\\$}$ </tex-math></inline-formula>209 for each EV owner and <inline-formula> <tex-math>${\\\\$}$ </tex-math></inline-formula>950 for building owners during DR events with a return on investment (ROI) of 134.5% and 130.7% for the EVs and Building owners, respectively.\",\"PeriodicalId\":56269,\"journal\":{\"name\":\"IEEE Transactions on Transportation Electrification\",\"volume\":\"11 3\",\"pages\":\"7542-7556\"},\"PeriodicalIF\":8.5000,\"publicationDate\":\"2025-01-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Transportation Electrification\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10839413/\",\"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}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Transportation Electrification","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10839413/","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}
Optimal Design of a Planning and Contracting Framework to Enable Vehicle to Building and Grid Services via Demand Response
Bidirectional electric vehicle (EV) charging enables stored energy to reduce peak loads for vehicle to buildings (V2Bs) and the vehicle to grid (V2G). However, building owners investing in V2B infrastructure while generating revenue from V2G services face challenges in planning and coordinating with EV owners due to uncertainties in their schedules and profit-sharing expectations. Additionally, misaligned building and grid peak times can create conflicts between V2B and V2G goals, which may negatively impact the building electricity bill. Unlike previous studies that used a contract-free approach for aggregating V2B and V2G, resulting in inconsistent participation, this article proposes a novel planning and contracting framework that enables building owner to determine the optimal contract parameters with EV owners. These parameters include minimum participation time in DR events, minimum arrival state of charge (SoC), and permitted emergency departure hours. The framework supports V2B aggregation with on-site distributed energy resources (DERs) for DR and V2G services, ensuring transparency and fairness through shared profits and performance-based penalties, while compensating building electricity bills due to V2G activities. The framework is composed of a tri-stage optimization process that uses Monte Carlo simulations to generate EV owner profit assessments, select optimal EV candidates based on charger availability, estimate contract parameters with profit/penalty sharing, and assign contracts between power system operators (PSOs), building owners, and EV owners under multiple virtual scenarios. Simulation results validate the contract parameter assessment and its performance via a 3-day case study with real-world datasets that demonstrates net revenue generation of ${\$}$ 209 for each EV owner and ${\$}$ 950 for building owners during DR events with a return on investment (ROI) of 134.5% and 130.7% for the EVs and Building owners, respectively.
期刊介绍:
IEEE Transactions on Transportation Electrification is focused on components, sub-systems, systems, standards, and grid interface technologies related to power and energy conversion, propulsion, and actuation for all types of electrified vehicles including on-road, off-road, off-highway, and rail vehicles, airplanes, and ships.