Robust Optimal Power Flow under Renewable Uncertainty with Pairwise Convex Hull and Non-Affine AGC Redispatch Strategy

Abstract

To accommodate the intermittent and uncertain renewable energy resources (RESs) in the power system, a novel robust optimal power flow (ROPF) method under RES uncertainty is proposed in this paper. A novel convex set, the pairwise convex hull, is applied to characterize the RES uncertainty. Then, an adjustable ROPF model is built to integrate RESs, where non-affine re-dispatch constraints are designed to cope with the situation when the automatic generation control (AGC) units’ power outputs hit their lower or upper bound during the re-dispatch process. The resulting ROPF problem is then solved with an adversarial approach (constraint generation) in which the potential binding constraints are identified to speed up the calculation. By solving the proposed ROPF model, the base point can be obtained to not only serve the forecasted load, but also ensure a feasible solution for all realizations of RES outputs within the pre-defined uncertainty set. Numerical studies on the 39-bus and 500-bus systems show that the proposed pairwise convex hull can capture the complicated distribution of RES outputs and is computationally very efficient. The binding constraint identification scheme can further dramatically speed up the computation. In addition, the non-affine AGC power re-dispatch scheme can achieve a lower objective value, for example, the proposed non-affine AGC re-dispatch-based ROPF method saves 0.389% and 0.1665% of the total costs for the 39-bus and 500-bus systems.