Distributionally Robust Congestion Management With Dynamic Line Ratings

Abstract

Dynamic line rating based on real time meteorological data has been shown to be useful in transmission line capacity management. Based on a binary rating forecast, we propose a distributionally robust congestion management model that selectively uses dynamic ratings on critical lines and keeps the risk of thermal overloading below a prescribed level. A case study illustrates that the proposed model can effectively alleviate transmission congestion with a low error rate.