Capacity Planning Frameworks for Electric Vehicle Charging Stations with Multi-Class Customers

TL;DR

This paper introduces two innovative capacity planning frameworks for electric vehicle charging stations that accommodate multiple customer classes, ensuring grid reliability and optimizing resource allocation across different network sizes.

Contribution

It presents two novel frameworks tailored for large and small EV charging networks, integrating pricing and resource computation to improve efficiency and reliability.

Findings

Frameworks ensure grid reliability

Significant savings in capacity planning

Effective management of multi-class EV charging

Abstract

In order to foster electric vehicle (EV) adoption, there is a strong need for designing and developing charging stations that can accommodate different customer classes, distinguished by their charging preferences, needs, and technologies. By growing such charging station networks, the power grid becomes more congested and, therefore, controlling of charging demands should be carefully aligned with the available resources. This paper focuses on an EV charging network equipped with different charging technologies and proposes two frameworks. In the first framework, appropriate for large networks, the EV population is expected to constitute a sizable portion of the light duty fleets. This which necessitates controlling the EV charging operations to prevent potential grid failures and distribute the resources efficiently. This framework leverages pricing dynamics in order to control the EV customer request rates and to provide a charging service with the best level of quality of service. The second framework, on the other hand, is more appropriate for smaller networks, in which the objective is to compute the minimum amount of resources required to provide certain levels of quality of service to each class. The results show that the proposed frameworks ensure grid reliability and lead to significant savings in capacity planning.