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The transition to Electric Vehicles (EVs) for reducing urban greenhouse gas emissions is hindered by the lack of public charging infrastructure, particularly fast-charging stations. Given that electric vehicle fast charging stations (EVFCS) can burden the electricity grid, it is crucial for EVFCS to adopt sustainable energy supply methods while accommodating the growing demands of EVs. Despite recent research efforts to optimize the placement of renewable-powered EV charging stations, current planning methods face challenges when applied to a complex city scale and integrating with renewable energy resources. This study thus introduces a robust decision-making model for optimal EVFCS placement planning integrated with solar power supply in a large and complex urban environment (e.g., Chicago), utilizing an advantage actor-critic (A2C) deep reinforcement learning (DRL) approach. The model balances traffic demand with energy supply, strategically placing charging stations in areas with high traffic density and solar potential. As a result, the model is used to optimally place 1,000 charging stations with a random starting search approach, achieving total reward values of 74.30 %, and estimated the capacities of potential EVFCS. This study can inform the identification of suitable locations to advance the microgrid-based charging infrastructure systems in large urban environments. 

The site selection of public electric vehicle charging stations (EVCS) will have a long-lasting impact on people’s access to and use of EV, and thus long-term social equity. Since it is hardly possible to reinstall a public EVCS once it is built, site selections for EVCS should consider a fair share of benefits. In this respect, this research explores the evaluation criteria of social equity for guiding public EVCS installations through a comprehensive systematic review. This study will provide a comprehensive social aspect which synthesizes evaluation indicators and socioeconomic and demographic variables regarding EVCS installations toward fair infrastructure investment. The proposed complete social equity criteria can be utilized to investigate the patterns of community and social features so that socially acceptable, preferable, and equitable sites for EVCS can be suggested. This study will advance the body of knowledge on planning, design, and installation decisions of equitable public infrastructure.