A proposed approach for combined wind and temperature loading of power transmission lines considering climate change effect

Abstract

This paper presents a framework to derive bivariate hazard curves for minimum temperature and maximum concurrent wind speed to characterize the combined wind and temperature loading of power transmission lines. Hazard curves are extracted for mean recurrence intervals (MRIs) of 50, 150, and 500-years, following IEC-60826 standard criteria. The framework employs the Joint Probability-Based Approach (JPBA) and Force-Based Approach (FBA) using numerical sampling of basic meteorological variables from historical data. It incorporates climate change effects by modeling minimum daily temperature trends through SARIMA time series analysis and Neural-Prophet machine learning. Correcting environmental effects is crucial for reliable meteorological simulations and accurate climate change trend capture. Considering climate change at the studied station, the framework shows minimum temperature extremes rise by 5 °C, 3 °C and 1 °C for 500, 150, and 50-year MRIs respectively. It models maximum daily wind speed probability distributions with monthly parameter variations. Simulations over 5000 years produce hazard curves based on JPBA and FBA and comparisons with IEC-60826 standard loading cases indicate conservative estimates in the JPBA-based approach. The IEC-60826 standard's first loading case for the 50 and 150-year MRIs is lower than the FBA-based hazard curves for all spans, with increasing underestimation as span length decreases.