Distributionally Robust Chance-constrained Optimal Power-Gas Flow under Bidirectional Interactions Considering Uncertain Wind Power

Abstract

This article proposes a distributionally robust chance-constrained (DRCC) model for the optimal power-gas flow (OPGF) problem with uncertain wind power. In the proposed model, a unified affine policy is introduced to adjust the flexible resources in both systems for uncertainty mitigation. Gas-fired units and power-to-gas facilities are considered to exploit the benefits of bidirectional interactions, and distributed gas storage is also incorporated to facilitate the coordinated operation of power and gas systems. Wind power uncertainty is described by an ambiguity set with any distribution built on only the mean and covariance. The distributionally robust chance constraint, especially the two-sided form, is reformulated to an exact second-order cone program. A binary expansion approach is employed to address the bilinear equality constraints. A sequential convexification method is developed to address the nonconvex quadratic equality constraints. Thus, the DRCC-OPGF model is reformulated as a tractable mixed-integer convex programming problem. Numerical results validate the effectiveness of the proposed DRCC-OPGF approach.