Maritime transportation industry is one of the major contributors to CO2 emissions. Energy conservation and emissions reduction in this industry are crucial for mitigating global warming. In recent years, the proportion of multi-energy ships in maritime transportation has been increasing, making energy management of multi-energy ship a hot research area. However, most scholars focus on energy management in propulsion systems of multi-energy ship, neglecting energy management in accommodation area. Therefore, we propose a two-stage energy management strategy for accommodation area of multi-energy ship. The proposed energy management strategy based on reinforcement learning and intelligent optimization algorithm to achieve rational scheduling of electrical appliances in ship accommodation area. To validate the effectiveness of the proposed method, we designed and conducted simulation experiments. The results indicate that the energy management strategy can effectively reduce energy consumption in multi-energy ship accommodation area, decrease pollutant emissions, and lower operating costs while meeting the needs of the crew.