A sequential conic relaxation based OPF incorporating Dynamic Line Rating considering uncertainty

The Dynamic Line Rating (DLR) is a promising asset optimization technique that effectively utilizes the transmission line. Due to non-convexity introduced by radiative cooling equations, incorporating DLR directly into Alternating Current Optimal Power Flow (ACOPF), solving real-time dispatch, is challenging even when Heat Balance Equations (HBE) are discretized. Hence, this paper proposes an iterative conic relaxation based technique, which transforms the original non-convex model into a series of conic convex problems. The real time dispatch is effected by errors in forecast, hence, to increase system security a data driven robust chance constrained based optimization with an exact reformulation of joint constraints is proposed. Frequency Restoration Reserve (FRR) requirement to compensate for the power mismatches due to forecast error are also evaluated. The proposed method is proven to converge to the local optimal point, and joint constraint reformulation is demonstrated to be less conservative than Bonferroni’s approximation.