Adaptive robust AC optimal power flow considering intrahour uncertainties

Given the increasing share of variable renewable energy resources (VREs), power system operations need to account for associated uncertainty with a fine resolution. This paper formulates an adaptive robust optimal flow, which secures hourly schedule against uncertain intrahour injections. The is characterized by spatially correlated polytopic sets. Second-order cone programming relaxation employed address nonconvexity flow constraints. A sequential convex (SCP) procedure developed close gaps. Due convexity, vertices fully represent sets, alleviates computational complexity stemming from full recourse. effectiveness proposed solution framework verified on 14-, 118-, and 588-bus systems 80% VRE penetration various sizes. SCP recovers high-quality AC-feasible solutions in 3–17 iterations within 0.1%–41.4% planning horizon time span, makes it suitable practical use. optimization can prevent load shedding reduce operational costs 2.0%–13.6%, while incurring 2.5%–5.0% reduction utilization.