GE building
Photo: iStock.com/Rafael_Wiedenmeier

General Electric (GE) announced Tuesday three new grid analytics that combine domain expertise with artificial intelligence (AI) and machine learning (ML) to tackle pressing challenges in electric grid operations.

According to the announcement made in San Ramon, California, analytics use data from across transmission and distribution networks to help achieve goals for operational efficiency. The portfolio includes storm readiness, network connectivity and effective inertia, company officials said.

“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 for GE Digital and chief digital officer for GE Power.

The storm readiness component 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, officials said. They added that GE’s Storm Readiness analytic helps to reduce outage restoration time, predict future outages, reduce operational spend and improve crew safety.

Network connectivity corrects and maintains network data integrity, the announcement added. 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, officials aid. GE’s connectivity algorithms use GIS and other operational system data to detect, recommend and correct pervasive errors, it said.

“Armed with better data, utilities can more efficiently dispatch crews, reduce outage restoration time and avoid incorrect outage notifications to customers,” The announcement said.

The effective inertia dimension gives enhanced visibility into transmission system operations, according to the report. It added that the operation of transmission networks continues to grow more complex via 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,” the announcement said.

It added that GE’s Effective Inertia analytic uses ML to facilitate the measurement and forecasting of system inertia to enable a more stable grid.

According to GE, the new grid analytics are connected via the company’s common Digital Energy data fabric. The company points out that unifying data on a secure, scalable and user-friendly platform drives efficiencies, allowing data 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, the company 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,” said Brian Hurst, VP and chief analytics officer for Exelon Utilities, an early adopter of GE’s new grid analytics.

“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,” he added.

Author:
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