Distributionally Robust Congestion Management With Dynamic Line Ratings

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.