06/11/2023

The Line Rating stands as an important factor influencing the efficient operation of the electricity market. Static Line Rating methodologies typically yield conservative capacity estimations, often derived from worst-case weather conditions scenarios. Improving the accuracy of current rating estimations can significantly boost the utilization of distribution system lines, increase the hosting capacity of Renewable Energy Sources (RES), and mitigate the need for costly DSO (Distribution System Operator) upgrades.

Accurately gauging the technical limits of power lines entails measuring air and conductor temperatures, solar heat intensity, and wind speed/direction. Achieving high accuracy and reliability in these estimations typically necessitates the installation of an array of sensors along the line, consequently increasing the cost of such solutions.

In the context of OPENTUNITY, ICCS partner is taking on the task of developing a cost-effective, real-time thermal rating algorithm. ICCS plans to employ machine learning techniques to incorporate numerical weather forecasts and data obtained from sensors within the OPENTUNITY ecosystem, including those in proximity to distribution lines such as RES plants and home automation systems. This approach aims to provide accurate line current rating estimations without the need for multiple sensors spanning the entire line.

ICCS is deeply engaged in research within this field, amalgamating conventional practices related to real-time current ratings derived from industry standards such as CIGRE and IEEE, as well as state-of-the-art research methods. This fusion of established and innovative approaches to real-time current rating is a promising step towards enhancing the efficiency of electricity market operation.