Robust load restoration optimization of power system considering the Spatial-Temporal correlation of wind power

Abstract

Wind power can be incorporated with load restoration of power systems, and the robust method is usually utilized to maintain feasibility considering the uncertainty of wind power. However, traditional robust load restoration always ignores the inherent time and spatial couplings of wind generation variability, which may increase the conservativeness of the solution. Therefore, this paper proposes a robust load restoration optimization considering the spatial and temporal correlation of wind power to reduce conservativeness. To eliminate unlikely-to-appear cases in time and space, the spatial–temporal correlation budget is introduced to construct a budget-constrained uncertainty set. Based on the constructed uncertainty set, the load restoration method is established as a two-stage robust model, which aims to maximize the restored load while guaranteeing the voltage and frequency security constraints. To make the proposed model computationally tractable, the binary expansion method is utilized to linearize the two-stage robust model with quadratic terms. In addition, due to inner-level binary variables in the subproblem, the extended column-and-constraint generation (EC&CG) algorithm is employed to iteratively solve the proposed model. Finally, the proposed robust method is tested on the modified IEEE 39-bus test system, and simulation results show that the proposed method can effectively reduce conservativeness while maintaining the feasibility of a robust solution.