A GRU-Based Weather Forecasting and Traveling Wave Sag Calculation Method for Dynamic Line Rating in Smart Grids

This study proposes a Gated Recurrent Unit (GRU) based weather prediction model combined with the traveling wave method for sag calculation, offering an advanced dynamic line rating strategy. Traditional static capacity calculations fail to account for real-time environmental variations, limiting both efficiency and safety in power transmission. To address this, the Gated Recurrent Unit model is employed for accurate weather forecasting, while the traveling wave method estimates sag by analyzing transient electromagnetic disturbances. Experimental results demonstrate that GRU outperforms CNN and LSTM in forecasting accuracy and computational efficiency, while the traveling wave method achieves over 99% accuracy in sag estimation. By integrating these two techniques, the proposed approach enhances transmission capacity, ensures grid stability, and enables flexible power dispatching. This method overcomes the limitations of static rating techniques and provides a scalable and intelligent solution for the future development of smart grids, improving adaptability, efficiency, and safety in dynamic power transmission environments.