{"title":"了解用户对车辆到电网(V2G)的偏好:潜在类别选择分析","authors":"Jerico Bakhuis , Natalia Barbour , Eric Molin , Émile J.L. Chappin","doi":"10.1016/j.tra.2025.104610","DOIUrl":null,"url":null,"abstract":"<div><div>The vehicle-to-grid (V2G) innovation—which enables electric vehicles to return stored electricity to the grid—holds significant potential to facilitate the integration of intermittent renewable energy and support climate goals. However, user preferences and how they vary across different user groups remain poorly understood, even though V2G’s success depends on driver participation. This study addresses this gap by conducting a stated choice experiment with 1,018 participants in the Netherlands. Participants chose between hypothetical V2G contracts based on four key attributes: financial compensation, guaranteed driving range, minimum plug-in time, and battery degradation—each varied at three levels. Using a latent class choice model, the analysis identified four distinct user preference profiles (or classes). Overall, guaranteed range and plug-in time were found to outweigh financial incentives for most users. The largest class (43% of users) prioritizes guaranteed range and shows the lowest sensitivity to financial incentives. The second-largest class (29%) also prioritizes guaranteed range, while assigning the least importance to plug-in time. The third class (18%) places the greatest importance on reducing plug-in time, followed by increasing guaranteed range. The smallest class (10%) is primarily motivated by financial compensation. The study further examines how user characteristics—such as socio-demographic, household, car use, and attitude factors—relate to class membership. The analysis provides a comprehensive overview of how these characteristics influence user preferences. These findings offer valuable insights into the diversity of V2G user preferences and inform targeted policy recommendations.</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"199 ","pages":"Article 104610"},"PeriodicalIF":6.8000,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Understanding user preferences regarding vehicle-to-grid (V2G): A latent class choice analysis\",\"authors\":\"Jerico Bakhuis , Natalia Barbour , Eric Molin , Émile J.L. Chappin\",\"doi\":\"10.1016/j.tra.2025.104610\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The vehicle-to-grid (V2G) innovation—which enables electric vehicles to return stored electricity to the grid—holds significant potential to facilitate the integration of intermittent renewable energy and support climate goals. However, user preferences and how they vary across different user groups remain poorly understood, even though V2G’s success depends on driver participation. This study addresses this gap by conducting a stated choice experiment with 1,018 participants in the Netherlands. Participants chose between hypothetical V2G contracts based on four key attributes: financial compensation, guaranteed driving range, minimum plug-in time, and battery degradation—each varied at three levels. Using a latent class choice model, the analysis identified four distinct user preference profiles (or classes). Overall, guaranteed range and plug-in time were found to outweigh financial incentives for most users. The largest class (43% of users) prioritizes guaranteed range and shows the lowest sensitivity to financial incentives. The second-largest class (29%) also prioritizes guaranteed range, while assigning the least importance to plug-in time. The third class (18%) places the greatest importance on reducing plug-in time, followed by increasing guaranteed range. The smallest class (10%) is primarily motivated by financial compensation. The study further examines how user characteristics—such as socio-demographic, household, car use, and attitude factors—relate to class membership. The analysis provides a comprehensive overview of how these characteristics influence user preferences. These findings offer valuable insights into the diversity of V2G user preferences and inform targeted policy recommendations.</div></div>\",\"PeriodicalId\":49421,\"journal\":{\"name\":\"Transportation Research Part A-Policy and Practice\",\"volume\":\"199 \",\"pages\":\"Article 104610\"},\"PeriodicalIF\":6.8000,\"publicationDate\":\"2025-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Part A-Policy and Practice\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0965856425002381\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part A-Policy and Practice","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0965856425002381","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Understanding user preferences regarding vehicle-to-grid (V2G): A latent class choice analysis
The vehicle-to-grid (V2G) innovation—which enables electric vehicles to return stored electricity to the grid—holds significant potential to facilitate the integration of intermittent renewable energy and support climate goals. However, user preferences and how they vary across different user groups remain poorly understood, even though V2G’s success depends on driver participation. This study addresses this gap by conducting a stated choice experiment with 1,018 participants in the Netherlands. Participants chose between hypothetical V2G contracts based on four key attributes: financial compensation, guaranteed driving range, minimum plug-in time, and battery degradation—each varied at three levels. Using a latent class choice model, the analysis identified four distinct user preference profiles (or classes). Overall, guaranteed range and plug-in time were found to outweigh financial incentives for most users. The largest class (43% of users) prioritizes guaranteed range and shows the lowest sensitivity to financial incentives. The second-largest class (29%) also prioritizes guaranteed range, while assigning the least importance to plug-in time. The third class (18%) places the greatest importance on reducing plug-in time, followed by increasing guaranteed range. The smallest class (10%) is primarily motivated by financial compensation. The study further examines how user characteristics—such as socio-demographic, household, car use, and attitude factors—relate to class membership. The analysis provides a comprehensive overview of how these characteristics influence user preferences. These findings offer valuable insights into the diversity of V2G user preferences and inform targeted policy recommendations.
期刊介绍:
Transportation Research: Part A contains papers of general interest in all passenger and freight transportation modes: policy analysis, formulation and evaluation; planning; interaction with the political, socioeconomic and physical environment; design, management and evaluation of transportation systems. Topics are approached from any discipline or perspective: economics, engineering, sociology, psychology, etc. Case studies, survey and expository papers are included, as are articles which contribute to unification of the field, or to an understanding of the comparative aspects of different systems. Papers which assess the scope for technological innovation within a social or political framework are also published. The journal is international, and places equal emphasis on the problems of industrialized and non-industrialized regions.
Part A''s aims and scope are complementary to Transportation Research Part B: Methodological, Part C: Emerging Technologies and Part D: Transport and Environment. Part E: Logistics and Transportation Review. Part F: Traffic Psychology and Behaviour. The complete set forms the most cohesive and comprehensive reference of current research in transportation science.