GE has made available three new grid analytics that combine domain expertise with artificial intelligence and machine learning. With this availability, the company hopes to alleviate the pressing challenges in electric grid operations. The analytics use data from across transmission and distribution networks to help achieve goals for operational efficiency.
“When it comes to storm restoration, it will enable the utilities to become more surgical in prepositioning crews in advance of weather events – saving time, money, improving customer satisfaction and enhancing safety for employees. We are just beginning to scratch the surface on the value of analytics, and when we look at Distributed Energy Resources and the Internet of Things, it becomes increasingly important for the future,” said Brian Hurst, VP and chief analytics officer, Exelon Utilities. This company has been an early adopter of GE’s new grid analytics.
What does the GE portfolio include? Storm readiness utilizes high-resolution weather forecasts, outage history, crew response and geographic information system (GIS) data to accurately forecast storm impact and prepare response crews and equipment ahead of impending weather. Network connectivity corrects and maintains network data integrity. GE also offers effective inertia, which gives enhanced visibility into transmission system operations. The operation of transmission networks is continuing to grow in complexity. This is because of the influx of renewable generation.
“The energy industry today is leveraging a small fraction of their operational data. Our grid analytics enable utilities to use more of that data and orchestrate their networks and the workers who operate them in ways previously unimagined – not only for current processes, but also for future unforeseen scenarios,” said Steven Martin, acting CEO, GE Digital and chief digital officer, GE Power.
Where are the new grid analytics connected? The new grid analytics are connected via GE’s common Digital Energy data fabric. Using data on a secure, scalable and user-friendly platform drives efficiencies to allow data to be stored in one location to be utilized by many solutions across the energy value chain, from generation to consumption. Users can in turn realize a network-effect of value, where improvements from one application amplify the benefits of another.
Chrissie Cluney has been a correspondent for IoT Evolution World since 2015. She holds a degree in English with a concentration in writing from the College of Saint Elizabeth.Edited by
Ken Briodagh