A User- and Utility-Aware Ranking Method for Electric- Vehicle-to-Charging-Station Assignment

The rapid growth of electric vehicles (EVs) has spurred the need for efficient charging station allocation strategies. In this paper, we provide a balanced user-utility EV assignment model based on different ranking algorithms to compare their respective performance. The main performance metric is the average service time, defined as the average time a user spends from initiating the request until terminating the recharging service. Our approach aims to balance both utility welfare and user convenience, by adhering to predefined quality of service standards while offering alternatives that maximize each aspect individually. The methodology we use depends on defining a ranking parameter between the requesting EV and all reachable charging stations. An assignment framework is then formulated, consisting of a central aggregator with a request accumulation period to facilitate the management of a dynamic population of EVs. The performance of our proposed assignment model is compared to that of other dynamic assignment schemes, including the nearest-station policy, join-the-shortest queue policy and the benchmark Lyapunov optimization EV assignment algorithm. The superiority of the proposed model is confirmed.