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UBC Theses and Dissertations

Numerical weather prediction for electrical transmission lines Campbell, Margaret

Abstract

Joule heating from electrical currents causes the conductor temperature of a transmission line to increase. Weather can further heat or cool the line. Wind speed and direction have the largest effect (CIGRE 2006), followed by air temperature. Utility companies need to know the maximum current they can transmit without exceeding critical temperature thresholds for transmission line safety (e.g., excess sag or metallurgical damage). The maximum transmittable electrical current for safe transmission (ampacity) must be estimated from wind speed, direction, temperature, insolation, and maximum conductor temperature. Power utilities apply this thermal rating to all powerlines. Traditional thermal rating methods do not monitor the weather surrounding powerlines, but assume relatively constant weather, leading to either overly conservative or unsafe thermal ratings. Dynamic thermal ratings (DTRs) take into account varying weather conditions in an effort to more realistically represent ampacity variations. To demonstrate the potential of DTR forecasts based on numerical weather prediction (NWP) forecasts to improve powerline safety, increase transmission capacity, and provide power utilities a means of advanced planning, this thesis 1) evaluates and compares seven bias-corrected, calibrated DTR forecast configurations to two traditional thermal rating methods to determine the most skillful DTR forecast method as well as to show the usefulness of probabilistic forecasts. 2) Determines raw DTR forecasts along a powerline to assess the degree and cause of spatial DTR forecast variability. The most skillful DTR forecasts start with bias-corrected NWP forecasts from which DTRs are calculated and combined into an ensemble average, which is then bias-corrected again and calibrated. The 1st, 5th, and 10th DTR forecast percentiles are safer than traditional thermal rating methods, while the 20th - 50th DTR forecast percentiles allow higher transmission capacity. Extensive temporal and spatial DTR forecast variability along a powerline results from wind speed forecast variability. Based on this research, it is recommended that utility companies use hourly DTR forecasts at their transmission line to maximize both current and safety.

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Attribution-NonCommercial-NoDerivatives 4.0 International

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