A multi-ship power sharing strategy: Using two-stage robust optimization and Shapley value approach

In recent years, the use of cold ironing (CI) has effectively reduced the carbon emissions of ships in port areas. However, due to the limitation of port CI quantity and power supply capacity, the power demand of some ships cannot be met. To solve this problem, this paper proposes a multi-ship power sharing strategy based on two-stage robust optimization and improved Shapley value method. Firstly, considering the uncertainty of ship photovoltaic power generation, a multi-ship power sharing model based on two-stage robust optimization is established. This model is a three-level optimization model with mixed integer variables, which is a NP-hard problem. In this paper, the nested column-and-constraint generation algorithm combined with duality theory and big-M method is used to obtain the optimal scheduling strategy of ship shared power, CI power and load demand response power. Secondly, an improved Shapley value method considering berth and remaining berthing time is proposed to realize the cost allocation in the process of ship power sharing. Finally, the effectiveness of the multi-ship power sharing strategy in reducing berthing costs and carbon emissions is verified by simulation. This method is expected to provide a new idea for the development of green ports.