Smart allocation and sizing of fast charging stations: a metaheuristic solution

ABSTRACT

The widespread adoption of electric vehicles (EVs) hinges significantly on effective network management, particularly the allocation and sizing of fast-charging stations (FCS) for EV users. Applying queuing theory based on M/M/c, the model seeks to identify the most effective number of chargers to minimise waiting time for electric vehicle users and ensure optimal utilisation of the FCS. The problem is formulated as a multi-optimisation problem where finding the optimal solution is done by implementing the non-dominated sorting genetic algorithm focusing on EV user satisfaction, voltage stability, and carbon dioxide emissions. Simulation results indicate that the model successfully enhances EV user satisfaction, environmental impact, and overall FCS utilisation. In a comparative analysis with state-of-the-art models, the proposed approach demonstrates a notable 40% improvement in EV user satisfaction and a significant 45% enhancement in FCS utilisation. This proves the effectiveness of the proposed model in optimising the performance of the network.

KEYWORDS:

• Fast charging station
• electrical vehicles
• network management
• queuing theory
• charging station utilisation
• CO₂ emissions

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data used to support the findings of this study are available from the corresponding author upon request.