Research on Day-ahead Optimal Scheduling of Wind-photovoltaic-thermal-energy Storage Combined Power Generation System Based on Opportunity-constrained Programming

In order to reasonably quantify the influence of wind and photovoltaic power output uncertainty on optimal scheduling, a day-ahead optimal scheduling model of wind-photovoltaic-thermal-energy storage combined power generation system considering opportunity-constrained programming is established. The model takes the system operation cost, which contains the operation cost of thermal power units, the penalty cost of pollutants, the operation cost of energy storage system and the penalty cost of new energy curtailment, as the optimization goal. In order to characterize the influence of wind and photovoltaic power prediction errors on the optimal scheduling, an opportunity-constrained programming method is used to calculate the rotating reserve capacity of the system in each period. The simulation calculation is performed on a typical day. The results show that the established model can realize the multi-energy complementary operation of the wind-photovoltaic-thermal-energy storage system. By reasonably quantifying the influence of the wind and photovoltaic power prediction error on the optimal scheduling, the system operation cost can be reduced, which verifies the validity of the model.