Conductor Temperature Estimation and Prediction at Thermal Transient State in Dynamic Line Rating Application

Abstract

The traditional methodology for defining the ampacity of overhead lines is based on conservative criteria regarding the operating conditions of the line, leading to the so-called static line rating. Although this procedure has been considered satisfactory for decades, it is nowadays sensible to account for more realistic line operating conditions when calculating its dynamic ampacity. Dynamic line rating is a technology used to improve the ampacity of overhead transmission lines based on the assumption that ampacity is not a static value but a function of weather and line's operating conditions. In order to apply this technology, it is necessary to monitor and predict the temperature of the conductor over time by direct or indirect measurements. This paper presents an algorithm to estimate and predict the temperature in overhead line conductors using an Extended Kalman Filter, with the aim of minimizing the mean square error in the current and subsequent states (temperature) of the conductor. The proposed algorithm assumes both actual weather and current intensity flowing along the conductor as control variables. The temperature of the conductor, mechanical tension and sag of the catenary are used as measurements because the common practice is to measure these values with dynamic line rating hardware. The algorithm has been validated by both simulations and measurements. The results of this study conclude that it is possible to implement the algorithm into Dynamic Line Rating systems, leading to a more accurate estimation and prediction of temperature.