storm
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Digital Energy STORM READINESS Predictive storm planning reduces crew costs while improving safety and customer satisfaction Accurate forecasting to improve storm response planning KEY OUTCOMES • Reduced storm safety risks • Reduced storm deployment & field labor costs • Improved storm CAIDI • Improved field personnel positioning decisions before and during weather events • Improved customer satisfaction and public relations In the last 30 years, the frequency and intensity of severe weather events has increased significantly. While utilities have made great progress in their ability to transition to storm operations and dispatch repair crews quickly and effectively, challenges remain for storm detection, prep & stage and storm management teams. Being constrained by broad area, low-fidelity weather data makes it difficult to forecast outages, facility damage and estimated time to repair by operating area. Without a clear picture of how impending weather events will impact the grid, utilities must rely on costly numbers of contingency crews to restore power quickly, or risk leaving customers without power for extended time periods Storm Readiness GE’s Digital Energy Storm Readiness application utilizes historical weather, outage, cost and facility damage data, combined with geospatial (GIS) data and high-resolution weather forecasts to deliver: KEY FEATURES • Accurate, hour-by-hour outage volume predictions at service center and enterprise level that leverages Machine Learning (ML) • Hour-by-hour high resolution outage predictions and distribution at a township level • Predicted ETR and CAIDI metrics • Visualization of high-resolution weather combined with outage predictions overlaid onto your service territory map • Geospatial overlays of high-resolution weather forecasts and predicted outages on a 6x6 mile grid over your service territory • Hour-by-hour high resolution outage predictions at a township level • Hour-by-hour outage and damage prediction forecasts by service center for the next 72 hours • Estimated time of restoration (ETR) and customer average interruption duration index (CAIDI) based on predicted outages and varia

Digital Energy Storm Readiness Predictive storm planning reduces crew costs while improving safety and customer satisfaction DIGITAL ENERGY DATA FABRIC GE’s Grid Analytics solutions run on our Digital Energy Data Fabric, a platform that standardizes the storage and consumption of data across the energy value chain, from centralized power generation to consumption by end users and prosumers. By unifying data on a secure, scalable platform that applies artificial intelligence (AI), machine learning (ML) and Big Data compute capabilities, the Digital Energy Data Fabric enables GE and our...