OPTIMIZING THE PLACEMENT OF ELECTRIC VEHICLE CHARGING STATIONS WITH RENEWABLE ENERGY INTEGRATION USING PARTICLE SWARM OPTIMIZATION

Abstract

The deployment of electric vehicle (EV) charging stations (EVCS) performs a crucial role in assisting the increase of electrical mobility. This observe addresses the project of strategically setting EVCS to maximise performance and sustainability by way of incorporating renewable strength sources. We suggest a Particle Swarm Optimization (PSO) method to decide ultimate locations for EVCS, considering factors along with strength demand, spatial distribution, and renewable energy potential (e.G., sun and wind). The PSO set of rules successfully navigates the solution area to stability accessibility, price, and environmental advantages, presenting a robust framework for integrating renewable power into EV charging infrastructure.

Our consequences indicate that PSO extensively complements the placement method as compared to standard techniques. By optimizing using renewable electricity, the proposed technique now not best improves the environmental effect of EVCS but also reduces dependency on non-renewable energy sources. This optimization framework provides precious insights for urban planners and policymakers, facilitating the development of sustainable and green EV charging networks that align with environmental dreams and guide the transition to easy electricity.