In the new power system, with a high proportion of new energy, the uncertainty of new energy output not only makes it difficult for thermal power to meet the accuracy requirements of scheduling plans, but also poses serious challenges to the economic scheduling algorithm for wind/photovoltaic/thermal/storage systems. For this reason, a multi-objective differential evolution algorithm based on variable time period design is proposed. First, the variable time period day ahead scheduling rules of a wind/photovoltaic/thermal/storage system are constructed according to the load characteristics of each time period. Then, taking the economic cost of system operation and the amount of pollution emission as the objectives, the Pareto solution set of the day ahead scheduling model of the system with variable time periods is solved based on the multi-objective differential evolution algorithm. Finally, the IEEE 39-bus system is tested. The results show that, under the constraint conditions of wind, photovoltaic power, storage, and thermal power all meet the verification criteria. Compared to other algorithms, the objective function obtained by the proposed method tends to be optimal, and the effectiveness of the thermal power unit output tracking scheduling plan is significantly improved, verifying the effectiveness of the proposed method.