Approach of Improved Dynamic Line Rating Using Sensors on Overhead Transmission Lines

Abstract The boom of renewable energies and the constantly growing demand for energy are pushing the grid ever further to its limits, which requires a continuous expansion in transmission capacities. In addition to numerous projects dealing with far-reaching grid extensions, Austrian Power Grid (APG) attempts to strengthen the network’s capacities by implementing technologies like Dynamic Line Rating (DLR). DLR comes with the advantage of increasing the capacity of transmission lines without any bigger construction effort and thus saves on expensive congestion management. Related to the clearance older transmission lines at APG were designed for a maximum conductor temperature of 40 °C. When upgraded to 80 °C clearance, lower outside temperatures and higher windspeeds enable a temporary limit of current above the rated value of the conductor and thus lead to a higher line capacity of the overhead line. This circumstance has been taken into account by APG for already many years by determining the increased limiting current for the day ahead, using weather forecasts which can be described as ambient adjusted forecast rating. Since weather forecasts, which are based on weather stations and computer models (artificial intelligence), become more and more accurate and sophisticated, the current model applied by APG does not utilize the full potential of DLR and could be further developed. Therefore, APG started an attempt to improve DLR by installing conductor-mounted sensors from different suppliers which measure additional parameters to determine the limiting current more precisely on a selected transmission line. Based on accurate location-based measurements such as conductor temperature and local wind speed, the project aims to improve the real time capacity and especially the capacity forecast. The paper will present an analysis of the gathered sensor data and a comparison to the existing DLR system. Special focus will be taken on the potential benefits of this sensor-based technology.