The impact of plug-in behavior on the spatial–temporal flexibility of electric vehicle charging load. (January 2023)

• Record Type: Journal Article
• Authors: Gschwendtner, Christine; Knoeri, Christof; Stephan, Annegret
• Is Part Of: Sustainable cities and society. Volume 88(2023)
• Publication Date: 2023-01
• Subjects: Electric vehicles -- Charging behavior -- Mobility behavior -- Distribution grids -- Agent-based model -- Load profiles; Sustainable urban development -- Periodicals; Sustainable buildings -- Periodicals; Urban ecology (Sociology) -- Periodicals; 307.76
• DOI: 10.1016/j.scs.2022.104263
• Languages: English
• ISSNs: 2210-6707

Abstract

Abstract: While electric vehicles (EVs) are expected to support decarbonizing transport, EVs can challenge the electricity system. Investigating the EV charging load and its flexibility, e.g., by shifting load, is therefore crucial to ensure a secure and sustainable energy system. We develop an agent-based model to investigate how different plug-in behaviors can affect (future) EV charging load profiles and their spatial–temporal flexibility. We contribute to extant literature by (1) revealing the effect of diverse plug-in behaviors on EV load profiles, particularly the flexibility potential resulting from different plug-in behaviors; (2) presenting the (future) charging load in different spatial structures, i.e. urban, rural, or suburban, and home, work, or public charging locations; and (3) demonstrating the effect of detailed driving profiles in high spatial and temporal resolution. We implement three future scenarios regarding EV and charging infrastructure diffusion and technology developments. We find that the impact of potential changes in plug-in behavior on EV charging load would be highest for urban areas and increases as charging infrastructure becomes more spatially diversified. Decision-makers in policy and industry can use these insights to evaluate the impact of EV charging on distribution grids and design incentives to leverage the flexibility potential of EVs. Highlights: Agent-based model with detailed mobility data to investigate EV charging loads. Focus on plug-in behavior, spatial structures, and driving profiles. Future scenarios to account for EV mass adoption. Spatially diversified charging increases flexibility potential of plug-in behavior. Greater impact of driving profiles than changes in plug-in behavior.