An optimal resource allocation for future parking lots with charger assignment considering uncertainties

•A new planning approach for different types of smart electric vehicle (EV) chargers’ allocation in conjunction with photovoltaic (PV) panels.•Markov chain monte carlo simulation technique is utilized to account for the uncertainties from the PV generation and the power demand.•New resource allocation of different types of EV chargers and PV units in a smart parking lot considering coordinated charging/discharging, EV battery heterogeneity, and charging pricing.•A new routing mechanism is incorporated to assign the suitable EV charger for each candidate EV. This paper proposes a new planning approach for different types electric vehicle (EV) chargers’ allocation in conjunction with photovoltaic (PV) panels. The proposed approach helps to upgrade the infrastructure satisfying the demand for high penetration of EVs with least expansion cost. This approach proposes a routing signal for the arriving EV at the parking lot to guide them to a suitable charger according to the charger and EV battery statuses. The proposed signal increases the utilization EV chargers. Also, the planning approach jointly considers the PV allocation to provide more energy and power capacity for chargers and to reduce overall energy cost. This proposed approach considers coordinated charging /discharging, creating bidirectional power flow between the grid and the EVs. The planning problem is formulated as a mixed-integer nonlinear program to maximize the net annual revenue. A Markov Chain Monte Carlo (MCMC) simulation technique is utilized to account for the uncertainties associated with the PV generation and the power demand. The outcome of the approach can be described as the optimal quantity and types of EV chargers, along with the optimal sizing of the allocated PV panels. A Multi-case simulation is done to demonstrate the effectiveness of the proposed approach.