Double layer rolling based optimization model for joint operation of wind-hydro- storage system

With the gradual increase in the penetration rate of wind power and other renewable energy sources, the uncertainty of power grids operation has intensified accordingly. How to safely and efficiently exert the regulating effect of hydropower is of great significance to the stable operation of power grids. To this end, a bi-level rolling optimal scheduling method for the joint operation of wind-hydro-storage systems is proposed. First, a bi-level rolling optimal control model for wind-hydro-storage joint operation is constructed. The upper-level optimization is based on a long time scale, with the goal of minimizing the system operation cost; the lower-level optimization is based on a short time scale, aiming to minimize the system output deviation. Second, the model predictive control (MPC) method is adopted to solve the optimization model. The real-time rolling optimization of the lower level is used to feedback and correct the upper-level scheduling plan, thereby reducing the impact of uncertainty on the system. Finally, a case study is carried out on a cascade hydropower system in South China. The simulation results verify the effectiveness of the proposed method in improving energy utilization efficiency, reducing operation costs and addressing system uncertainty.