Dynamic Thermal Rating in Diverse Climatic Conditions: Uncertainty Analysis and Fuzzy Logic Approach

Abstract

Abstract: In recent times, there has been a significant rise in the need for electricity, a trend expected to continue. This surge in demand has resulted in transmission lines operating at much higher capacities, which in turn exposes them to increased thermal and mechanical stress, ultimately impacting the reliability of the transmission network. In this paper presents a comprehensive analysis of the static thermal rating (STR) and dynamic thermal rating (DTR) of power lines across varied climatic conditions. The study encompasses a thorough investigation into the thermal behavior of power lines during both summer and winter seasons over a 24-hour period. Through rigorous computational simulations and empirical data collection, the STR and DTR profiles are determined to assess the real-time capacity of power lines under changing environmental conditions. Furthermore, the research introduces a novel approach utilizing fuzzy logic to model the dynamic thermal rating (FDTR) based on the IEEE 738 standard, in regions characterized by diverse climatic patterns. By integrating fuzzy logic with meteorological data, the FDTR model offers enhanced accuracy in predicting the thermal performance of power lines, considering factors such as ambient temperature, wind speed, and solar radiation. The proposed methodology aims to provide utilities and grid operators with a reliable tool for optimizing power transmission capacity, mitigating the risk of overheating, and ensuring grid reliability in regions with complex and fluctuating weather conditions. This study contributes to the advancement of smart grid technology and facilitates efficient energy management in diverse climate zones