Dynamic long-term expansion planning of electric vehicle parking lots considering lost opportunity cost and energy saving

In this paper, a practical approach is presented to long-term expansion planning of electric vehicle (EV) parking lots which aims to maximize the parking lot operator's profit. The optimal number, location, capacity, and time for construction or expansion of EV parking lots have also been determined. Moreover, a method based on drivers’ travel patterns is proposed to estimate the number of EVs referring to each area, in which the unscented transformation method (UTM) is used to calculate the annual growth rate of EVs. An innovative and real-time method for optimal charge and discharge scheduling of EVs is also provided, which can calculate the parking lots’ demand at different times. The most important advantages of this method are its independence from iterative-based optimization algorithms and from modeling some input parameters such as the initial state of charge (SOC) and the arrival time of EVs into the parking lot as uncertain parameters. Also, a Lagrange interpolation-based method is proposed to minimize the energy consumption required for EVs to reach a parking lot. In addition, in order to prevent the reduction of parking lot operator's profit in case of non-fulfillment of the obligations of the EV owners, an approach based on paying the lost opportunity cost (LOC) is presented. Real-world data has been used for numerical studies. The results show that based on travel patterns and estimating the number of EVs available in each municipal district and using the proposed real-time scheduling method, parking lot's demand can be calculated as the main prerequisite for parking lots expansion planning. Also, the proposed method for parking selection compared to two other methods will save energy by 26.6% and 8.33%, respectively. Moreover, the proposed approach increases the total parking lot operator's profit by 4.23%