Wednesday, 25 January 2017: 11:15 AM
615 (Washington State Convention Center )
Electric power utilities make critical decisions in the days prior to hurricane landfall that are primarily based on the estimated impact to their service area. Accurate forecasts of the impact of an approaching hurricane within their service area are critical for utilities in balancing the costs and benefits of different levels of resources. The Spatially Generalized Hurricane Outage Prediction Model utilizes predictions of tropical cyclone windspeed and duration of strong winds, along with power system and environmental variables (e.g., soil moisture, long-term precipitation), to forecast the number and location of power outages. This project assesses whether using NASA SMAP soil moisture improves the accuracy of power outage forecasts as compared to using model-derived soil moisture from NLDAS-2. A sensitivity analysis is employed since there have been very few tropical cyclones making landfall in the United States since SMAP was launched. Our results demonstrate that using SMAP soil moisture can have a significant impact on power outage predictions. SMAP has the potential to enhance the accuracy of power outage forecasts, which can reduce the duration of power outages which reduces economic losses.
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