Adjustable Robust OPF With Renewable Energy Sources

This paper presents an adjustable robust optimization approach to account for the uncertainty of renewable energy sources (RESs) in optimal power flow (OPF). It proposes an affinely adjustable robust OPF formulation where the base-point generation is calculated to serve the forecast load which is not balanced by RESs, and the generation control through participation factors ensures a feasible solution for all realizations of RES output within a prescribed uncertainty set. The adjustable robust OPF framework is solved using quadratic programming with successive constraint enforcement and can coordinate the computation of both the base-point generation and participation factors. Numerical results on standard test networks reveal a relatively small increase in the expected operational cost as the uncertainty level increases. In addition, solutions of networks that include both uncertain wind generation and Gaussian distributed demand are shown to have less cost and a higher level of robustness as compared to those from a recent robust scheduling method.