Multi-objective planning of electric vehicles charging stations by integrating drivers’ preferences and fairness considerations: A case study in Halifax, Canada
Hani Pourvaziri, Majid Taghavi, Hassan Sarhadi, Hamid Afshari, Nader Azad
Abstract
• Considering user preferences and fairness in planning for EV charging stations. • Proposes a bi-objective model for the location and capacity of charging stations. • Investigate socioeconomic factors’ role in planning for EV charging stations. • Suggests managerial insights into enhancing the adoption rate of electric vehicles. • Contribute to the EV literature and a more sustainable environment. This paper addresses the optimal placement of electric vehicle (EV) charging stations (CSs) and the optimal number of chargers at each station to mitigate the operational challenges of EVs and support environmental sustainability. It proposes a multi-objective model that considers EV drivers’ preferences and fairness to maximize the overall utility of the charging network while minimizing the travel and waiting times for EV drivers. Fairness in this context is defined as ensuring the time needed to reach a preferred charging station, plus the waiting time at the station, is similar for all drivers. To achieve these goals, the study develops an integrated machine learning and heuristic approach for clustering preference points and identifying cluster centers as potential sites for CSs. A non-dominated sorting genetic algorithm (NSGA-II) with a new selection operator is developed to solve the multi-objective problem. The findings show that considering drivers’ preferences enhances network utility by minimizing travel and waiting times. Also, considering fairness allows for more equitable access to charging facilities, which results in higher EV adoption. Computational experiments based on a dataset from Halifax, Canada, demonstrate that among the developed algorithms, the K-Means algorithm has the best computational performance in clustering preference points, leading to major improvements in the efficiency and effectiveness of the proposed solution approach. From the managerial perspective, this study highlights the role of efficient allocation of financial resources and the importance of embracing demographic factors in CS location planning.