Fuzzy Optimization for the Operation of Electric Vehicle Parking Lots

Integrating electric vehicles (EVs) into the smart grid has become a topic of great interest lately due to the potential benefits it provides. Since EVs are expected to be parking most of the time, it is expected that EVs will play a role in competitive business environments like parking lots (PLs). However, the parking lot operator (PLO) is exposed to many uncertainties, including those associated with the electric energy market and EV mobility. This paper proposes a fuzzy optimization model that aims at maximizing the PLO's profit while satisfying EV owners' charging requirements. It is assumed that the PLO bids EV charging schedules in the day-ahead market of energy. The PLO can, then, balance any deviation from its day-ahead schedule in the real-time market. The uncertainties of the profits due to market price fluctuations are taken into consideration. Also, the uncertainties associated with the EV mobility, such as the EV type mix using the parking lot (PL), their initial and final states of charge, and their departure time, are also considered. In addition, the effect of the charging efficiency is investigated. The simulation results show that the proposed fuzzy optimization algorithm leads to higher realized profits than those of the deterministic benchmark algorithm. Also, the results show that the proposed algorithm is robust and offers high profitability even with high levels of uncertainty.