期刊
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
卷 105, 期 -, 页码 46-58出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ijepes.2018.08.001
关键词
Electric vehicle (EV); Fast-charging station; Monte Carlo method; Genetic algorithm and renewable energy
资金
- Government of Aragon
- FEDER funds
The development of electric vehicles (EVs) depends on several factors: the EV's acquisition price, autonomy, the charging process and the charging infrastructure. This paper is focused on the last factor: the design of an EV fast-charging station. In order to improve the profitability of the fast-charging stations and to decrease the high energy demanded from the grid, the station includes renewable generation (wind and photovoltaic) and a storage system. Unlike other papers, this one uses a detailed model of the charging process that considers the arrival time and state of charge of electric vehicles. First, the Monte Carlo method is used to model the EV demand and the renewable generation. Later, a genetic algorithm (GA) optimizes the installation and operation of the EV fast-charging station. It finds the optimal solution that maximizes the profit measured by its net present value (NPV). Several cases are studied to analyse the influence of renewable energies and storage systems. The obtained results show that a mix of renewable energies and storage systems attains the best cost efficient solution.
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