Transmission Line Overload Risk Assessment Considering Dynamic Line Rating Mechanism in a High-Wind-Penetrated Power System: A Data-Driven Approach

Abstract

The dynamic line rating (DLR) can be an effective mechanism that reduces wind curtailment induced by line congestion considering its unique correlation to wind speed. However, the calculation of the DLR depends on accurate environmental parameters, which can be challenging in look-ahead decision-making applications. Consequently, transmission line overload risk (TLOR) can exist. In this paper, we propose a two-stage TLOR assessment model for high-wind-penetrated power systems considering the DLR. An overload risk index along with the risk-averse line capacity bound (RAB) for each line can be obtained from the proposed model. Meanwhile, a computationally efficient data-driven approach that combines convex-hull and box-like modeling methods is established to characterize the uncertainty during the decision-making process. The proposed model is solved by a modified column-and-constraint generation (C&CG) algorithm, and its effectiveness and scalability are illustrated by multiple simulation experiments.