Optimal Capacities of Electric Ferry Charging Stations by Hybrid Metaheuristic Algorithm

Maritime transport significantly contributes to greenhouse gas emissions, which necessitates the implementation of electric ferries and renewable energy-powered harbor charging stations to mitigate these emissions, particularly in urban coastal areas and islands. Proper planning and optimal capacity determination of the charging stations are critical to maintaining the stability and reliability of the connected distribution networks. This research emphasizes the importance of optimizing the capacity of ferry charging stations to prevent system overloads, maintain voltage levels, avoid power outages, and reduce infrastructure upgrade costs. Metaheuristic optimization algorithms are selected for their superior capability to address intricate, nonlinear problems, presenting a more adaptable and practical approach than conventional methods. This research explores the balanced hybrid PSO-BFO (Particle Swarm Optimization-Bacterial Foraging Optimization) algorithm to determine the optimal capacities of electric ferry charging stations within a simulated distribution network in regional Australia. The hybrid PSOBFO algorithm, integrated with OpenDSS (Open Distribution System Simulator) for power flow analysis, ensures compliance with voltage and current constraints while minimizing power losses and deviations in bus voltages and line currents. The simulation results underscore the co-simulation approach’s effectiveness in determining the optimal capacities for charging infrastructure, thereby facilitating the broader adoption of electric marine transportation.