Transmission line rating assessment using numerical weather prediction (NWP) models

The traditional approach for defining the line ampacity ratings of Overhead Lines (OHLs) is static and tends to be conservative. While this approach has been valuable for many years, it may not fully capture the complexities of actual line operating conditions, such as the effect of changing environmental parameters and ambient conditions. This paper proposes a sensorless Line Rating Assessment (LRA) approach to estimate the ampacity of transmission OHL. It employs the IEEE 738 standard and the weather parameters data derived from two distinct numerical weather models, the Weather Research and Forecasting (WRF) model and the Weather Research and Forecasting Chemistry (WRF-Chem) model. The model estimations are compared with weather data collected by weather mast measurements, serving as a reference to validate the numerical weather models. The proposed strategy is applied to a section of 132kV OHL in the Dubai region. Initial investigations include sensitivity analyses to explore the impact of varying weather parameters on the line ampacity ratings. Thereafter, three performance indices are utilised to evaluate the performance of the proposed approach for ampacity estimation. The results indicate that WRF-Chem surpasses WRF by delivering estimates with greater ampacity headroom in winter and ensuring safer ratings in the summer. • Proposed Line Rating Assessment solution is digital-first and entirely sensorless. • Leverage weather data derivation from two distinct numerical weather models: WRF-BC and WRF Chem. • Performance of models are evaluated using three indices: percentile, mean absolute error and relative mean absolute error. • WRF-Chem model provides a more cautious yet efficient ampacity ratings, thereby offering more head room. • Findings emphasise the value of considering WRF-Chem in providing reliable results under adverse weather conditions especially during summer.