{"title":"A framework for analyzing the spatiotemporal distribution of urban electric vehicle charging load: A case study of Shanghai","authors":"Zeyu Liu, Wenhang Yin, Donghan Feng, Yun Zhou","doi":"10.1016/j.scs.2025.106392","DOIUrl":null,"url":null,"abstract":"<div><div>Electric vehicles (EVs), as a critical component of sustainable cities, require a thorough understanding of the spatiotemporal distribution of charging demand. This paper proposes a spatiotemporal analysis framework for EV charging load. The proposed framework is based on a dynamic simplified road network model, driving behavior model, and energy replenishment model, and it analyzes the charging load patterns through large-scale Monte-Carlo simulations. The case study in Shanghai reveals the overall curve and spatiotemporal distribution of EV charging load. The results show that the charging load can account for 7.8 % of Shanghai's total grid load, forming a spatial pattern of concentration in the central urban area and radiation towards the suburbs. Charging infrastructure accessibility analysis indicates the necessity of more aggressive charging infrastructure construction for the central urban area west of the Huangpu River. These findings offer valuable insights for both real-time operations of power system and long-term planning of charging infrastructures. Furthermore, a projection for the 2035 long-term scenario discusses the future development trends of charging loads and corresponding strategies.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"127 ","pages":"Article 106392"},"PeriodicalIF":10.5000,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Cities and Society","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2210670725002689","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Electric vehicles (EVs), as a critical component of sustainable cities, require a thorough understanding of the spatiotemporal distribution of charging demand. This paper proposes a spatiotemporal analysis framework for EV charging load. The proposed framework is based on a dynamic simplified road network model, driving behavior model, and energy replenishment model, and it analyzes the charging load patterns through large-scale Monte-Carlo simulations. The case study in Shanghai reveals the overall curve and spatiotemporal distribution of EV charging load. The results show that the charging load can account for 7.8 % of Shanghai's total grid load, forming a spatial pattern of concentration in the central urban area and radiation towards the suburbs. Charging infrastructure accessibility analysis indicates the necessity of more aggressive charging infrastructure construction for the central urban area west of the Huangpu River. These findings offer valuable insights for both real-time operations of power system and long-term planning of charging infrastructures. Furthermore, a projection for the 2035 long-term scenario discusses the future development trends of charging loads and corresponding strategies.
期刊介绍:
Sustainable Cities and Society (SCS) is an international journal that focuses on fundamental and applied research to promote environmentally sustainable and socially resilient cities. The journal welcomes cross-cutting, multi-disciplinary research in various areas, including:
1. Smart cities and resilient environments;
2. Alternative/clean energy sources, energy distribution, distributed energy generation, and energy demand reduction/management;
3. Monitoring and improving air quality in built environment and cities (e.g., healthy built environment and air quality management);
4. Energy efficient, low/zero carbon, and green buildings/communities;
5. Climate change mitigation and adaptation in urban environments;
6. Green infrastructure and BMPs;
7. Environmental Footprint accounting and management;
8. Urban agriculture and forestry;
9. ICT, smart grid and intelligent infrastructure;
10. Urban design/planning, regulations, legislation, certification, economics, and policy;
11. Social aspects, impacts and resiliency of cities;
12. Behavior monitoring, analysis and change within urban communities;
13. Health monitoring and improvement;
14. Nexus issues related to sustainable cities and societies;
15. Smart city governance;
16. Decision Support Systems for trade-off and uncertainty analysis for improved management of cities and society;
17. Big data, machine learning, and artificial intelligence applications and case studies;
18. Critical infrastructure protection, including security, privacy, forensics, and reliability issues of cyber-physical systems.
19. Water footprint reduction and urban water distribution, harvesting, treatment, reuse and management;
20. Waste reduction and recycling;
21. Wastewater collection, treatment and recycling;
22. Smart, clean and healthy transportation systems and infrastructure;