In order to cope with the intermittency and volatility of natural resources such as wind energy and solar energy

improve the new energy consumption rate of the wind-photovoltaic-thermal-storage integrated energy system

and maintain the safe and stable operation of the power grid

a scheduling model of the wind-photovoltaic-thermal-storage integrated energy system is established

and an adaptive stochastic model predictive control(SMPC) scheduling strategy is proposed in this paper. The strategy is mainly composed of four parts: supply and demand prediction model

scenario reduction

rolling optimization and feedback correction. By reasonably reducing initial scenarios and changing the rolling optimization cycle step size in real time

the scheduling accuracy is improved. At the same time

taking a typical day as an example

the advantages and disadvantages of three scheduling strategies

namely adaptive SMPC

model predictive control(MPC) and SMPC are compared and analyzed. The results show that the adaptive SMPC scheduling strategy proposed in this paper can effectively deal with the fluctuation and uncertainty of wind and solar output and load. With this strategy

the scheduling accuracy and speed are high

and the total scheduling cost changes little.