Rethinking smart grid data analytics to get both tactical and strategic advantage
Editor's note: Smart Grid News is working with experts from Elster and other leading smart grid companies to create the ultimate guide to AMI -- a full-scale, start-to-finish, everything-including-the kitchen-sink compendium of best practices, lessons learned, and future directions. When it's complete, we will make it available to you as an eBook. In the meantime we're publishing select excerpts. In this seventh installment, Bob Ritchie drills down on data analytics and how utilities can turn the colossal amounts of data they are amassing into profitable business insights. Be sure to scroll to the end of today's article (which continues on page 2) to access additional installments in this series. -- Jesse Berst
By Bob Ritchie
You don’t need to collect data on the number of times data analytics is discussed throughout our industry to know that this has become a red-hot topic -- and with good reason. In the era of the smart grid, the amount of data that’s now being amassed is colossal - and growing. It’s data analytics -- the process of analyzing data to identify significant, useful and otherwise interesting trends and patterns - that will enable your utility to transform this vast volume of information into profitable business insights.
What’s driving the boom in data? Why is it becoming more urgent to unlock its value? And how can your utility approach data analytics not only from a tactical, day-to-day operational perspective, but also from a more long-term, strategic vantage point? A quick look at these questions and their answers follows.
Challenge or opportunity?
Over the last few decades, changes in technology, market and regulatory forces have rattled a utility industry accustomed to slow, predictable changes. A few of the major trends include:
Â· One data point vs. thousands: For each meter today, we have the ability to collect thousands of data elements per month with multiple types of measurements and events. This shift was enabled by improvements in communications and metering, and supported by plummeting costs for storage and processing power.
Â· Increased competition: Improved technology and regulatory mandates have introduced solar and wind generation across widely distributed geographical areas. Results from increased competition range from requirements to accept and compensate alternative energy suppliers to completely eliminating vertical utilities in some markets.
Â· Shifting fuel sources: There is a growing dependence on natural gas for generation due to increased production and lower costs. Meanwhile, large coal and nuclear plants are closing in response to regulatory and financial pressures.
Â· Electric vehicles (EVs): A forecasted surge in the number of EVs and the associated increase in charging requirements threaten to radically alter historical demand patterns.
The cumulative effect on utilities because of these changes is immense. More supply sources (many with no means of central control) coupled with increased demand volatility will complicate grid management. Utilities will need to improve existing capabilities and introduce new disciplines to predict future supply and infrastructure needs. To meet the growing expectations of consumers, utilities will need to deliver a broader range of information, faster service and near instantaneous status updates.
Laying the foundation
At this early stage of introducing analytics to address business issues, what should you do to prepare the foundation for analytic applications?
Â· Develop the people resources to implement analytics effectively. Most utilities will use a combination of strategies, such as training existing staff with deep utility domain knowledge, bringing in experts from other industries and the academic world, and seeking out vendors and consultants with proven expertise.
Â· Put systems in place to capture and store the data that will yield the greatest benefit. Most initial analytic applications incorporate AMI data, leveraging the ability of AMI systems to capture and register data at 5- or 15-minute intervals, as well as other data such as power quality measurements. Adding GIS location data and grid relationships greatly magnifies the potential usefulness of the data. Some utilities are adding sub-metering for tenants in commercial or residential facilities, individual equipment components such as heating or refrigeration, or customer generation equipment.
Â· Ensure the quality of the data. While utilities have systems and processes in place to insure reliable data for billing, validation and estimation processes might need to be established for the additional meter data being captured.
Thinking bigger about data analytics
In the age of the smart grid, turning data into insight and actionable intelligence is essential for a utility’s survival and success. To be sure, data analytics is the key to this transformation. Supplementing operational data processing with tactical and strategic data analytics ensures that you can unlock the value of your data in a way that’s least disruptive and most advantageous for your operations.
Bob Ritchie is a product manager with Elster Solutions with responsibility for capturing and defining software and services offerings for Elster’s North American utility customers.
Elster Solutions is the North American electricity business unit of Elster, a multi-national, 7500-person company providing electricity, gas and water meters and related communications, network and software solutions to customers in more than 130 countries. Headquartered in Raleigh, NC, Elster Solutions is focused on delivering the vital connections utilities need to achieve the greatest possible value from their meter data.
Earlier installments from the ultimate guide to AMI...