The energy industry today “is leveraging a small fraction of its operational data” according to Steven Martin, chief digital officer for GE Power.
To respond to this, GE this week has unveiled three new grid analytics that combine domain expertise with artificial intelligence and machine learning to tackle challenges in electric grid operations.
The analytics use data from across transmission and distribution networks to help achieve goals for operational efficiency.
The three analytics are called Storm Readiness, Network Connectivity and Effective Inertia.
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 by using GIS and other operational system data to detect, recommend and correct pervasive errors. Data errors, which often arise due to manual input of information at the customer or equipment level, can hinder emergency and outage response and lead to poor customer experience. GE said that “armed with better data, utilities can more efficiently dispatch crews, reduce outage restoration time and avoid incorrect outage notifications to customers”.
Effective Inertia is designed to give enhanced visibility into transmission system operations. The operation of transmission networks is continuing to grow in complexity, in large part due to the influx of renewable generation, and GE says this has led to a massive displacement of ‘system inertia’, or the resiliency of power generation, given spikes in customer demand or reduced supply, due to unforeseen decreases in wind or sunlight. Effective Inertia analytic uses machine learning to measure and forecast system inertia and enable a more stable grid.
Steven Martin, who is also acting chief executive for GE Digital, said: “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.”
An early adopter of GE’s new grid analytics was Exelon Utilities, and its chief analytics officer Brian Hurst said: “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.
He added: “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.”