Session Category : Advanced Analytics
CPS Energy spends hundreds of thousands of dollars in directing field crews to trim trees in the areas of potentially biggest impact to the electric grid reliability. This action is both pro-active and re-active as our vegetation management crews could not physically inspect all circuit lines across our service territory at a speed and frequency that match the growth of vegetation and field crews regularly must trim trees not only before but after the impact has occurred. As a result, an alternative view that accounts for our unique circuit configuration and vegetation growth patterns was needed. In 2018 CPS Energy has spent time and effort to automate vegetation data ingestion and is now beginning to couple this with distribution grid overhead line spatial analytics to quickly visualize the 1-km grid that need furthest attention in order of priority. The data source (i.e. NOAA’s Green Vegetation Fraction) is a derivative product from Visible Infrared Imager Radiometer Suite (VIIRS) sensor onboard Suomi National Polar-orbiting Partnership (SNPP) satellite, for applications in numerical weather and seasonal climate prediction models at the National Centers for Environmental Prediction (NCEP). The data is produced as a daily rolling weekly composite at 4-km resolution (global scale) and 1-km resolution (regional scale), and subsequently combined with our distribution grid metadata to then visualize our vegetation management priorities.
- Audience will gain an understanding about the utility’s maturation and synergies at the IT/OT intersection. |
- Audience will see how data governance has played a key role in defining a sustainable production-ready environment.
- Audience will learn about the specific use case of using GIS and satellite data for practical decision-enabled insights that improve quality and depth of customer experience.