Accelerating electric vehicle adoption: techno-economic assessment to modify existing fuel stations with fast charging infrastructure

With the increasing electric vehicle (EV) penetration, there arises an immediate need for charging infrastructure. In the future, the electrification of transportation will reduce the requirement of existing fuel stations, thereby rendering them obsolete. However, they are best suited to cater to the charging demand of EVs as the drivers are accustomed to the locations and the incremental cost of providing this service will be lower. In this paper, we propose a novel methodology to assess the techno-economic feasibility of retrofitting an existing fuel station with EV charging infrastructure also known as Electric Vehicle Supply Equipment (EVSE). To further enhance the value proposition, the potential of integrating Battery Energy Storage System (BESS) with EV charging infrastructure, which results in the reduction of grid connection costs, is studied. The sustainability of the proposed system is improved with additional onsite Photovoltaic (PV) generation. The proposed methodology is implemented for the UK as a case study. The configurations in this study are designed based on the technical considerations involved in retrofitting a typical fuel station as a fast charging facility for EVs. From the results, it is observed that the configurations with 4 EVSE, 1 BESS, and 8 h of operation and the configuration with 4 EVSE, 1 BESS, and 1 PV system for 8 h of operation are economically viable. The abovementioned configurations are the most economically feasible configurations in terms of the Net Present Value (NPV), Internal Rate of Return (IRR) and the Discounted Payback Period (DPP) amongst the other configurations considered in this study. The proposed methodology indicates that though the connection cost is the dominant factor affecting the feasibility, the use of BESS with or without PV can reduce the connection cost by almost 90% depending on the capacity of BESS. The methodology acts as a decision support tool to select a technoeconomically feasible configuration of EVSE, BESS, and PV. [GRAPHICS] .