A novel bi-level optimization model-based optimal energy scheduling for hybrid ship power system

With the rapid growth of energy consumption and greenhouse gas emissions, the application of traditional ships brings more and more serious pollution problems to the marine environment. For this reason, this paper aims at developing a novel optimal energy scheduling for hybrid ship power system based on bi-level optimization model to reduce fossil fuel consumption and protect the environment. Firstly, a hybrid ship power system model including the diesel generator system, energy storage system, propulsion system, service load system, and photovoltaic generation system is established. Taking the nonlinear and non-convex constraints in solving power generation scheduling and speed scheduling problems into account, an improved genetic algorithm-based bi-level energy optimization strategy is developed. Considering the mileage constraints in coupling constraints, an upper level model for ship energy scheduling is established with the objective of reducing fuel consumption; a lower level optimization model with the goal of minimizing mileage deviation is established through constraint decomposition and fed back to the upper level optimization model. Considering the normal and fault navigation conditions, simulation results verify that the proposed method can significantly minimize operating costs and greenhouse gas emissions by 5.33% and 2.46%, respectively.