Using Predictive Analytics in the Power Industry
GE is applying artificial intelligence (AI) and machine learning (ML) to data analytics from power transmission and distribution networks to set new targets for operational efficiency.
The company has announced a suite of three new grid analytics solutions will be connected via the GE Common Digital Energy Data Fabric platform which provides access to unified data which can be shared across locations and solutions in the energy value chain, from generation to consumption.
It is anticipated users of the platform will benefit by improving outcomes in three areas, namely:
- Storm Readiness - utliising high-res 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. GE’s Storm Readiness analytic helps reduce outage restoration time, predict future outages, reduce operational spend and improve crew safety.
- Network Connectivity - correcting and maintaining network data integrity and 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’s Network Connectivity algorithms use GIS and other operational system data to detect, recommend and correct pervasive errors. Armed with better data, utilities can more efficiently dispatch crews, reduce outage restoration time and avoid incorrect outage notifications to customers.
- Effective Inertia - providing enhanced visibility into transmission system operations, an area that is continuing to grow in complexity, in large part due to the influx of renewable generation. 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. Ineffective management of a transmission system could result in blackouts and major financial and reputational penalties. GE’s Effective Inertia analytic uses ML to facilitate the measurement and forecasting of system inertia and enable a more stable grid.
Steven Martin, acting CEO for GE Digital and chief digital officer for GE Power, says:
"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."
Brian Hurst, VP and chief analytics officer for Exelon Utilities, an early adopter of the new grid analytics solutions, adds:
"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."
About GE Power
GE Power is a world energy leader providing equipment, solutions and services across the energy value chain from generation to consumption. Operating in more than 180 countries, our technology produces a third of the world’s electricity, equips 90 percent of power transmission utilities worldwide, and our software manages more than forty per cent of the world’s energy.
For more information, visit www.ge.com/power.