In order to improve the wind power consumption and ensure the economic operation of the offshore integrated energy system, a day-ahead hierarchical scheduling strategy should be formulated. Firstly, a wind power forecasting model with auto-regressive integrated moving average method is built to obtain the data. Secondly, take the total cost as the multi-energy control layer and take the wind power curtailment cost as the energy efficiency optimization layer to establish the hierarchical optimal model. And a modified particle swarm optimization algorithm is used to obtain the optimal solution. Then two schemes are proposed to explore the impact on system. Finally, a certain offshore platform in China is taken as an example to calculate. The results show that the proposed method can realize the optimal scheduling of the system. And the application of P2G technology can better accommodate wind power and greatly reduce the economic cost.