Optimizing renewable energy-based plug-in hybrid electric vehicle charging stations for sustainable transportation in India

Abstract

India's burgeoning population necessitates innovative transportation solutions, with electric vehicles (EVs) emerging as a locally viable and urgent need. However, a significant obstacle lies in the improper deployment of charging stations, which strains the power distribution system. Recognizing the environmental benefits of Renewable Energy Sources (RES), high-priority buses are now equipped with Plug-in Hybrid Electric Vehicle (PHEV) charging stations, bolstering effective utilization. This study leverages meta-heuristic optimization techniques to propose an efficient allocation strategy for PHEV charging stations powered by RES. The core objective is to establish a cost-effective charging infrastructure while upholding the effective integrity of the network in distribution system. To address these challenges, the study employs meta-heuristic optimization algorithms and optimizes forecasting around sustainable energy systems to achieve desired output. Consequently, the research introduces a novel approach, conceptualizing the distribution of optimal charging stations as a multi-objective problem with added parameters. Furthermore, this study tackles the RES PHEV and charging station site challenge by introducing the innovative Walrus Optimization Algorithm (WaOA), which effectively overcomes issues related to slow convergence and local optima. Experimental findings demonstrate the superiority of the proposed model in terms of minimizing the cost function. This research offers a promising pathway toward sustainable transportation in India's evolving landscape.

Keywords

• Charging stations
• Renewable energy sources
• Plug-in hybrid electric vehicle
• Meta-heuristic Optimization
• Walrus Optimization Algorithm (WaOA)