Capacity Planning for an Electric Vehicle Charging Station Considering Fuzzy Quality of Service and Multiple Charging Options

Electric vehicles (EVs) have received considerable attention in dealing with severe environmental and energy crises. The capacity planning of public charging stations has been a major factor in facilitating the wide market penetration of EVs. In this paper, we present an optimization model for charging station capacity planning to maximize the fuzzy quality of service (FQoS) considering queuing behavior, blocking reliability, and multiple charging options classified by battery technical specifications. The uncertainty of the EV arrival and service time are taken into account and described as fuzzy numbers characterized by triangular membership functions. Meanwhile, an alpha-cuts-based algorithm is proposed to defuzzify the FQoS. Finally, the numerical results illustrate that a more robust plan can be obtained by accounting for FQoS. The contribution of the proposed model allows decision-makers and operators to plan the capacity of charging stations with fuzzy EV arrival rate and service rate and provide a better service for customers with different charging options.

Automated summary

This paper presents an optimization model for charging station capacity planning to maximize fuzzy quality of service (FQoS) in the context of electric vehicles. The model considers queuing behavior, blocking reliability, and multiple charging options based on battery technical specifications. By accounting for uncertainty in EV arrival and service time, the proposed model offers decision-makers and operators a more robust plan for capacity planning of charging stations to provide better service for customers with different charging options.