Prediction of Intra-Period Minimum Thermal Rating of Overhead Conductors

Abstract

Regarding power system dispatch decisions, the current-carrying limits of transmission lines in each dispatch period in the look-ahead time horizon should be represented by the intra-period minimum thermal rating (IMTR) for the sake of security. In this paper, the IMTR prediction issue of the overhead conductor is raised, and the predictability of the IMTR is investigated. Specifically, for the overhead conductor, the distribution and correlation characteristics of the IMTR and its corresponding meteorological elements are analyzed based on the measured meteorological data around an overhead conductor. On this basis, the quantile regression neural network (QRNN) and copula model are employed to make probability predictions on IMTRs of multiple periods in the prediction time horizon considering the temporal correlation of the IMTR. Also, the influences of the time period length, prediction time horizon, and the consideration of the temporal correlation of the IMTR on prediction results are analyzed. The work presented in this paper reveals the predictability of the IMTR, which is of significance to guide the prediction of the IMTR of the overhead conductor. Thus, it can help operators safely exploit the current-carrying capability of the overhead line.