Self-Recovery Capability of Power System and Its Application in Active Power Optimal Scheduling

Conventional optimal active power dispatch is usually suitable to deterministic operation condition. However, with large-scale wind farms integrated into the power system, much more spinning reserve capacity is required due to the intermittence and randomness of wind power. In this paper we aim to propose a reasonable scheduling strategy of energy storage stations (ESS) and thermal generators to deal with uncertainty during actual operation. Firstly, we define self-recovery capability of power system to evaluate system’s robustness under two major scenes based on two linear programming models respectively. Then we propose an active power optimal scheduling model based on self-recovery capability to enhance recovery ability of the power system with large-scale wind farms. A numerical example and its results demonstrate that the proposed self-recovery capability and the optimal scheduling model is able to enhance the robustness of power system by sparing itself with abundant regulating ability, which can quickly response to reduce wind power curtailment and balance power shortage.