ORIGINAL REPORTING: Numbers Game -- Data Analytics And The Utility Community Of The Future
The biggest numbers game in the power sector: Data analytics and the utility community of the future; Software and data are transforming the utility industry and connecting energy users.
Herman K. Trabish, March 25, 2019 (Utility Dive)
Editor’s note: The use of data analytics is becoming intrinsic in electric utility planning and customer service.
Cost-effective electricity generation from variable renewables is allowing new clean transportation and other electrification initiatives. But they will make the resulting clean energy economy dependent on a burgeoning and complex power system. Automated data analytics can provide the granular, real-time situational awareness to effectively manage it. "Data is a linchpin of our collective energy future," Matt Schnugg, senior director of data and analytics for GE Power Digital, said in an email to Utility Dive. Data will optimize assets across "the energy network" for "navigating the digital transformation."
The use cases for data analytics are wide-ranging and proliferating. Data analytics-based weather forecasting is prompting pre-hardening of systems against extreme weather events. Data analytics are delivering new services and savings to customers through utility-led energy efficiency programs that cut customer bills and lower utilities' system costs. In addition, digital simulations are perfecting new hardware before it is installed.
Data analytics are also creating significant savings from predictive maintenance. OSIsoft-processed data has saved Duke Energy over $130 million by predicting transformer failures before they occurred, former Duke VP and CIO Chris Heck told an April 2018 conference. "The unprecedented interconnectedness of systems and available computational power through the cloud are allowing new system-wide data analytics applications," Clean Power Research (CPR) Executive Director Jeff Ressler told Utility Dive. "The era of siloed utilities is over, and executives are working on creating high fidelity, high quality data structured to be used throughout the company."
No one software will be the answer, as increasing amounts of data and system integration are layered and analyzed by artificial intelligence (AI) with machine learning, he added. That will lead to the next stage in data analytics in which a utility community pools data and computing power "for the deep machine learning AI requires," Electric Power Research Institute (EPRI) AI lead and VP for Transmission and Distribution Andrew Phillips, told Utility Dive. This will allow "shared, curated data and a secure platform to develop solution algorithms."
Data analytics can ultimately lead to a decentralized network that allows peer-to-peer energy transactions in a connected community, energy sector analysts told Utility Dive. But utilities must first fully assimilate and integrate the data and its capabilities. The first step toward a fully digital utility is the use of operational and third-party data "on a day-to-day basis," GE's Schnugg said. To use the "disparate and often siloed" data effectively, it must be brought into software that can process "hundreds of gigabytes of data per day" and perform "near real-time analytics on individual system assets and on the overall network."
While 91% of utility leaders see such data use as "crucial to the future success of their utilities," only 23% said their companies are making "capital expenditure decisions based on predictive analytics," according to a survey of 150 utilities released March 1 by energy research firm Zpryme and ABB. Zypryme's survey presented a three-stage, nine-step "Digital Maturity Curve" along which utilities can progress from "digitization," which is assimilating data, to "digitalization," which is using data. In "enterprise integration," the last stage, utilities will "communicate, monitor, compute, and control grid and customer operations with real-time intelligence and situational awareness," the survey reported… click here for more
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