An Effective Scheduling Strategy for Hybrid Wind-Energy Storage System Considering Uncertainty and Robust Optimization

Aiming at the problems of insufficient wind power(WP) capacity and the high pressure of the power grid peak shaving due to WP uncertainty, this paper takes the hybrid wind-energy storage(HWES) system as an example, establishes a coordinated scheduling optimization model for HWES system with the objective of minimum wind abandonment. The Quasi-Monte Carlo method is used to transform the optimization objective function with uncertainties of WP into an effective objective function to eliminate the influence of uncertain factors of WP. In the optimization process, low-bias sequence is introduced to improve the uniformity of sample distribution, and the optimal solution of the coordination optimization model is searched by robust optimization algorithm. The comparison experiment shows that the proposed coordinated optimization method still has strong robustness, can effectively reduce the abandonment of wind and achieve the goal of WP consumption.