A stochastic approach to size EV charging stations with support of second life battery storage systems

This paper proposes a stochastic approach to determine the number of different types of charging stations for electric vehicles (EVs) in urban parking lots: our approach minimize annual cost of energy (ACOE) while ensuring a good satisfaction level for EV users. The proposed method takes also into account a stationary energy storage system that supports the EV parking lot and consists of traction batteries no longer usable by EVs, but still performing in their so-called second life. The effectiveness of the proposed sizing method is shown by simulation results characterized by real data, gathered in the European research project CO.S.MO. By using Monte Carlo simulations, we verified the features of the electric parking lot in terms of probability that all charging stations are busy and the average waiting time to start a new charging session.