Design of a Decision-Based Multicriteria Reservation System for the EV Parking Lot

Abstract

In metropolitans, the problem of finding available parking slots has changed as finding available parking slots having charging stations due to increasing electric vehicle (EV) deployment. Smart management systems can be used in this manner for obtaining an optimum parking slot in EV parking lots (PLs) considering EV users’ preferences. This article proposes a smart reservation system considering the behavior of EV users, parking slot availability (PSA), state-of-charge (SoC) value of EVs, and PL usage history of EV users. In order to handle weighting the behavior of EV users according to a comprehensive criteria comparison, the analytical hierarchy process (AHP) from multicriteria decision-making (MCDM) techniques is used in the smart reservation system. Thereafter, the proposed ranking function is presented to develop the mentioned quality-of-experience (QoE)-based charging slot allocation considering the reservation requests of EV users sent via a mobile application and to accept the optimal EVs in accordance with the weights assigned by AHP. The proposed concept is tested under different cases generated by changing the individual importance degree of EV user’s criteria. The different case studies demonstrate the effectiveness of the proposed decision-based multicriteria reservation system in terms of EV users’ acceptance ratio. Simulation results show that not only the importance degree related to the EV users’ criteria has an important effect in accepting appropriate EV users but also PSA management is another vital criterion especially in peak-load hours.