Enhancing dynamic line rating using fuzzy based ultracapacitor

Abstract

The efficiency and reliability of power transmission networks are increasingly challenged by the limitations of static line ratings, which often lead to underutilization of transmission capacity and increased congestion. This research focuses on Enhancing Dynamic Line Rating (DLR) Using Fuzzy-Based Ultracapacitor Technology to address these challenges. The proposed system integrates a fuzzy logic controller with an ultracapacitor energy storage system to provide rapid and intelligent support to transmission lines under fluctuating environmental and load conditions. The fuzzy controller dynamically assesses real-time parameters such as conductor temperature, wind speed, and solar radiation to optimize the use of the ultracapacitor, thereby enhancing the dynamic line capacity safely and efficiently. Simulation results demonstrate that the fuzzy-based ultracapacitor system significantly improves the responsiveness of DLR mechanisms, reduces thermal overload risks, and maximizes line utilization without compromising system stability. The study offers a novel approach for modernizing power transmission infrastructure, enabling smarter, more adaptive grid operations, and paving the way for higher integration of renewable energy sources. The findings suggest that intelligent energy storage-based compensation can be a key driver in the future development of resilient and efficient transmission networks. The conventional High Ambient Temperature that causes poor dynamic line rating was25%. On the other hand, when Fuzzy based ultracapacitor was incorporated into the system, it drastically reduced to21.7% and the conventional high solar radiation that causes poor dynamic line rating was 10%. Meanwhile, when Fuzzy based ultracapacitor was imbibed into the system, it simultaneously reduced to8.7%. Finally, with these results obtained, it showed that percentage enhancement dynamic line rating when Fuzzy based ultracapacitor was integrated in the system was 1.3%.