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New, more-robust repositories of grid performance data offer a wealth of potential operational intelligence for utilities. An endless process of IP addresses now embedded in networked devices and sensors fill utility IT servers with constant chatter about remote grid activity and energy usage patterns. And it's not just electricity usage that is being tracked; the data torrent now includes outages, voltages, tampering and diagnostic data. Applying utility big data is not only needed, but also fundamental to a sound U.S. energy and environmental policy.

Both the Energy Independence and Security Act (EISA) of 2007 and the newly introduced U.S. Smart Grid Advancement Act of 2013 outline blueprints for modernizing the aging U.S. electric infrastructure. Stakeholders recognize that the success of these efforts hinge on the application of robust data analytics tools and expertise. To manage this information, utilities must be capable of high-volume data management and analytics designed for the sole purpose to convert data into actionable insights.

What are the best uses of this smart grid data tsunami for the utility and the energy consumer? How can terabytes of raw data most effectively be mined, interpreted and translated into easily understandable, actionable information that benefits stakeholders?

These questions are explored in a recently released eMeter - A Siemens Business INFOgraphic, 2013 Utility Data Analytics Survey.  The illustration presents results of a utility industry executive survey conducted in July 2013 by Zpryme. In the survey, 260 industry executives, vendors, public and nonprofit organizations provide a broad-strokes snapshot of utility analytics opportunities and challenges.

Among other findings, survey results reveal the following salient points:
  • 76% of respondents believe that the most important data supplied by analytics involves outage and fault detection and identifying potential grid infrastructure problems before they occur.
  • 29% of respondents, the largest segment in the question, believe power outage analysis represents the area of biggest need for utilities.
  • 58% of respondents view analytics as an important tool for forecasting demand and peak usage times.
  • 47% of respondents believe that utilities are not prepared to deal with the explosion of smart grid data. Related to that question is the 35% of respondents who believe that the biggest impediment utilities experience in the use of enhanced data analytics is not hardware or software but the lack of trained personnel.
With annual outage losses estimated in the billions of dollars - what the U. S. Department of Energy refers to as “reliability events” - the Zpryme survey results identifying the value of analytics to fault detection, isolation and restoration (FDIR) make justified sense. Data analytics will yield benefits to many systems across the grid, while offering product manufacturers the ability to identify a “needle in a haystack” in a matter of minutes rather than days.

Data is growing at an exponential rate, and power outages are filling headlines. The information the smart grid provides is only as good as the IT and personnel in the driver’s seat. With adoption by utilities no longer in its infancy stage, smarter analytic solutions are already helping utilities make more-informed (real-time) business decisions.

Michael G. Albrecht is a contributing analyst for research firm Zpryme.

Hybrid Energy Innovations

Hybrid Energy Innovations 2015
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