A Smart Peak-Demand Curtailment Strategy for Residential Communities with Electric Vehicles

The increasing adoption of electric vehicles (EVs) has created significant challenges and opportunities in grid management. This study focuses on reducing peak load on the grid by reducing the peak demand of a community of residences having EVs. To implement this strategy practically, a Particle Swarm Optimization (PSO)-based EV charging model is proposed, tailored to curtail the peak demands. This strategy integrates real-world constraints such as EV charging behaviours and residential demand patterns to optimize energy distribution during peak periods. By dynamically adjusting charging and discharging schedules and enabling effective demand-side management, the PSO model minimizes stress on the grid and improves energy efficiency. The simulation results from a case with 5, 000 residences and 1, 000 EVs have shown a total 9.6% peak reduction, demonstrating the potential of the proposed method in supporting the grid while addressing user convenience.