Smart allocation and sizing of fast charging stations: a metaheuristic solution
Nivine Güler
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 multioptimisation 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.