Power management optimization of hybrid power systems for electric ferries

Ferries, which transport passengers, vehicles, and cargo, are encountering new opportunities and challenges in the transportation industry. In particular, fluctuations in the oil price and strict emission regulations imposed by the International Maritime Organization and other governing bodies are the main concerns of the contemporary ferry industry. Therefore, the industry and academia are actively exploring avenues for emission reduction and fuel efficiency improvement. Integration of more-electric technologies (METs), such as electric propulsion, into ferries has been identified as a promising approach to reduce emissions and operating cost. Further developments in the MET approach have decreased the fossil fuel-generated power on board ferries while renewable energy sources (RESs) such as fuel cells and solar cells are added to fill the gap. However, typical power levels and operating characteristic of these RESs do not meet load requirements in ferries and thus, battery energy storage has become an essential element in such hybrid systems to ensure reliable supply of power. The presence of various sources and different types of loads, such as propulsion and service loads, make the ferry power system a complex network. Effective and efficient management of such a system to achieve the optimal use of available energy is inaccurate with traditional approaches. This gets further complicated with the presence of various constrains and operating requirements of each individual unit. Thus, advanced power management strategies are required to achieve optimal operation of future more-electric ferries. This study aims to develop, evaluate, and compare the performance of classical and metaheuristic algorithm-based power management systems (PMSs) for hybrid power systems in short-haul electric ferries for fuel efficiency improvements and emission reductions. With the current trends in the industry, emission reduction and fuel efficiency improvement are taken as operational cost functions for the optimization. Moreover, reliability parameters such as safe operating region, available energy, and battery lifetime are taken as constraints in the optimization process. The developed PMSs should minimize the operational cost function and optimally manage the uncertainties of the short-haul ferry power system. A simulation model of a direct current (DC) ferry power system is developed in MATLAB/Simulink to validate the developed PMSs. A DC distribution system is chosen in this study due to the fact that majority of energy storage technologies are DC systems. Moreover, drawbacks of alternating current (AC) distribution system such as harmonics, reactive power, and the need for synchronizations are not present in DC systems. In addition, the elimination of rectifier stage in variable speed drives reduces the power loss and cost. Therefore, future domestic ferry power systems will use DC distribution over AC. The developed model is simulated for different scenarios and validated with actual data measured from a short-haul domestic diesel-electric driven ferry. In terms of battery sizing, the main parameters that can affect the battery size for shorthaul ferries are battery depth-of-discharge (DoD) and ferry operational profile (number of stops at terminal, number of cruising periods, and maximum load). The influence of the DoD is more significant than other parameters on the size and lifetime of the battery. This condition also affects the payback period (PBP) of the system. Large DoD value results in low battery size capacity, small PBP, and short battery lifetime. These factors are taken and embedded into the equations to get more realistic results from the optimization process. Results of the study show that, in terms of PMSs, single meta-heuristic optimization algorithm provides better fuel consumption and emission reductions compared to classical method that uses pre-determined conditions. However, hybrid meta-heuristic optimization algorithm provides further promising optimization results due to its high capability to converge to feasible solutions under different conditions, unlike single meta-heuristic optimization algorithms. In summary, this study suggests that the hybrid power system using DC distribution with battery storage and hybrid meta-heuristic-based PMS is an efficient combination to achieve low fuel consumptions, lower emissions, and reduced in-port noises for short-haul electric ferries. The insight gained from this study can assist marine coastal vehicles operating in close proximity to residential areas having high concern on gas pollutant emissions. This study also enables other researchers and designers in the field of marine power systems to adapt and extend the methods to other marine vessels.