Two-stage optimization of route, speed, and energy management for hybrid energy ship under sea conditions

As future ship system, hybrid energy ship system has a wide range of application prospects for solving the serious energy crisis. However, current optimization scheduling works lack the consideration of sea conditions and navigational circumstances. Therefore, this paper aims at establishing a two-stage optimization framework for hybrid energy ship power system. The proposed framework considers multiple optimizations of route, speed planning, and energy management under the constraints of sea conditions during navigation. First, a complex hybrid ship power model consisting of diesel generation system, propulsion system, energy storage system, photovoltaic power generation system, and electric boiler system is established, where sea state information and ship resistance model are considered. With objective optimization functions of cost and greenhouse gas (GHG) emissions, a two-stage optimization framework consisting of route planning, speed scheduling, and energy management is constructed. Wherein the improved A-star algorithm and grey wolf optimization algorithm are introduced to obtain the optimal solutions for route, speed, and energy optimization scheduling. Finally, simulation cases are employed to verify that the proposed two-stage optimization scheduling model can reduce load energy consumption, operating costs, and carbon emissions by 17.8%, 17.39%, and 13.04%, respectively, compared with the non-optimal control group.