From building automation systems to electric meters, thermostats, appliances and even individual sensors, smart devices of all types now are barraging utilities with big data. Accessing and storing the data are just two of the challenges; the real quandary is how to derive value from this information explosion. Specifically, how will busy operational personnel determine that something is worthy of—indeed, is demanding—their attention?

Glen Allen, of Virginia-based SkyFoundry, has developed analytics software that enables utilities to enter “rules” into an information warehouse that automatically run against the data to recognize critical and urgent issues that must be addressed immediately.

The analytics platform is called SkySpark–and on July 2, SkyFoundry announced that Bergen, Norway-based Smart Grid Norway AS has adopted it as part of the company’s family of solutions covering the full scope of grid operations, starting with production and ranging through endpoint consumption.

Smart Grid Norway is a leading provider to utilities of intelligent solutions for measuring, collecting, processing, communication, and visualization of energy related data and events. The company helps large power users, power producers and grid operators improve energy and operational efficiency with a range of smart grid solutions.

Smart Grid Norway will use SkySpark for real-time data collection and automated analytics to detect important patterns in the data that represent faults, anomalies, and opportunities for improved operations and cost reduction.

There are three basic steps to the analytics process with SkySpark:

• Collect: The first step is to “get the utility’s data.” One of the key issues SkySpark addresses is the fact that building data are typically available for collection in a number of different formats. SkySpark accepts this multi-structured data into a specialized database called Folio, which is designed specifically to work with large volumes of time-series data.
• Manage: Data meanings and relationships—“semantics”—are derived using “tags.” Tags are added to data items, as needed, to convey definitions and associations. The tags then provide the hooks that the analytics engine uses to correlate and analyze the information.
• Analysis: A unique “engine,” called Axon, provides a comprehensive set of functions for manipulating and analyzing data. Define an issue once, save it, and activate it; SkySpark will find it forever. Create new rules based on observations or ideas at any time—all without affecting the underlying systems. And rules can be combined and linked. The value of a utility’s data engine continues to grow with every new rule created.

As a result, when Axon rules “hit” or find their target, they create a “spark”—SkyFoundry’s term for an issue that matters. Sparks then generate notifications and displays for the user. SkySpark also can send emails and alerts and output analytics results to third-party applications via published application programming interfaces (APIs).

"We are excited to have the SkySpark analytics platform adopted by such a leading smart grid company," commented John Petze, partner at SkyFoundry.

"By integrating SkySpark analytics into our complete system solution, we take a big step further in utilizing big data for effective energy flow and use. Working together with our data-processing and monitor unit SmartGuard, we are using real-time data to improve energy efficiency and facility management for our customers," commented Geir Aksdal, managing director at Smart Grid Norway.

At the beginning of 2013, over 4,000 sites were using SkySpark analytics.