Time and Money Matters for Sustainability: Insights on User Preferences on Renewable Energy for Electric Vehicle Charging Stations

2025-12-09

AI Summary

This study addresses the spatial heterogeneity in energy composition at public charging stations induced by renewable energy intermittency, investigating how dynamic renewable energy availability influences electric vehicle (EV) users’ charging station choice behavior. Employing a within-subjects survey and semi-structured interviews across urban and rural contexts, we empirically examine the interaction effects among energy source type, time cost, and economic cost. Results show that user preference for renewable-powered stations is significantly moderated by their primary decision objective—time efficiency versus cost minimization: selection likelihood increases markedly when renewable stations concurrently offer superior performance in the user’s prioritized dimension. Based on these findings, we propose user-value-oriented navigation interface design principles and a backend station-ranking algorithm optimization framework. This work delivers the first empirically grounded, methodology-innovative support for integrating real-time renewable energy information with behavioral preferences in green mobility navigation systems.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Humans and AI: Intelligent User Interfaces
• Knowledge Representation and Reasoning: Preferences

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience
• Economics, Online Markets and Human Computation: The sharing economy

Abstract

Charging electric vehicles (EVs) with renewable energy can lessen their environmental impact. However, the fluctuating availability of renewable energy affects the sustainability of public EV charging stations. Nearby public charging stations may utilize differing energy sources due to their microgrid connections - ranging from exclusively renewable to non-renewable or a combination of both - highlighting the substantial variability in energy supply types within short distances. This study investigates the near-future scenario of integrating dynamic renewable energy availability in charging station navigation to impact the choices of EV users towards renewable sources. We conducted a within-subjects design survey with 50 car users and semi-structured interviews with 10 EV users from rural, suburban, and urban areas. The results show that when choosing EV charging stations, drivers often prioritize either time savings or money savings based on the driving scenarios that influence drivers' consumer value. Notably, EV users tend to select renewable-powered stations when they align with their main priority, be it saving money or time. This study offers end-user insights into the front-end graphic user interface and the development of the back-end ranking algorithm for navigation recommender systems that integrate dynamic renewable energy availability for the sustainable use of electric vehicles.

Problem

• Investigates user preferences for renewable energy at EV charging stations
• Examines how dynamic renewable availability influences EV driver choices
• Studies integration of renewable energy data into navigation systems

Innovation

• Dynamic renewable energy integration in navigation systems
• User-centric algorithm prioritizes time or cost savings
• Survey-informed interface design for sustainable EV charging