Optimal Scenarios of Renewables and Chargers for an Electric Vehicle Charging Station using Public Data

Jieun Ihm, Sejin Chun, Herie Park (2022). 2022 IEEE 5th Student Conference on Electric Machines and Systems (SCEMS)

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Abstract

As the penetration rate of electric vehicles (EVs) is increasing, it becomes necessary to investigate a renewable energy-based EV charging stations generating electric power from renewable energy resources. This paper proposes optimal sizing and mix scenarios of renewable energy resources and electric chargers for a renewable energy-based EV charging station using local climate and load data provided for the public. For this purpose, a methodology to obtain optimal scenarios using local characteristics and related public data is introduced. As a case study, Daegu in Korea is selected, and the economic analysis is conducted with the help of HOMER software. Finally, optimal sizing and mix scenarios of power generation facilities and electric chargers are demonstrated. This study will help expand the eco-friendly complex charging stations and infrastructure.