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Internet of Things (IoT), the Cloud, Edge Analytics…

November 11, 2014

As my eyes wandered through the Knowledge Center at this year’s recent Itron Utility Week (IUW), I was captivated by the future. Stretching from one end of the floor to the other were a mix of Itron products, solutions and partner displays. I could have stopped and discussed meters or fixed networks, but I was drawn to the analytics section and potential of new devices.

As a forecaster, I track emerging trends and economic news. While I’ve heard about the Cloud and Internet of Things (IoT), I haven’t bothered to understand their implications beyond storing photos and getting my iPad connected. With Itron’s announcement of the Riva Platform, the Cloud and IoT move to the forefront of my mind.

If you don’t know, the Riva Platform brings distributed computing power, control, and analytics for automated decision-making. You can read about platform here.

In a nutshell, analytics and intelligence are being pushed to the edge removing the need for centralized cloud or utility control -- thus the phrase “Edge Analytics.” The Star Trek-ian vision of the future places intelligent sensors in every device making decisions that are both useful and efficient. Who wouldn’t want their house door to unlock when it senses you approaching (gone are key chains and time searching for lost keys)? Why do I need to follow my kids around the house turning off lights when sensors can detect an empty room (unlike my office where the sensor only detects movement often leaving me in the dark when I sit still typing)? The only thing I might not want is the tight Star Fleet uniform...

But as a forecaster, I realize that these new products will require electricity to power the chips and sensors. How much will it increase loads? When will all this occur? Is this load growth represented in my forecast?

Checking with Itron engineers, I confirm that the energy requirement for the new chip is negligible. Still, billions of negligible chips are not negligible. But for now, I’m content to believe that (1) billions of chips are outside my forecast time horizon and (2) any negligible increase in energy consumption will be offset by gains in efficiency. After all, I’m willing to sacrifice the load of a few chips against hours of lighting empty rooms.

By Mark Quan

Principal Forecast Consultant

Mark Quan is a Principal Forecast Consultant with Itron’s Forecasting Division. Since joining Itron in 1997, Quan has specialized in both short-term and long-term energy forecasting solutions as well as load research projects. Quan has developed and implemented several automated forecasting systems to predict next day system demand, load profiles, and retail consumption for companies throughout the United States and Canada. Short-term forecasting solutions include systems for the Midwest Independent System Operator (MISO) and the California Independent System Operator (CAISO). Long-term forecasting solutions include developing and supporting the long-term forecasts of sales and customers for clients such as Dairyland Power and Omaha Public Power District. These forecasts include end-use information and demand-side management impacts in an econometric framework. Finally, Quan has been involved in implementing Load Research systems such as at Snohomish PUD. Prior to joining Itron, Quan worked in the gas, electric, and corporate functions at Pacific Gas and Electric Company (PG&E), where he was involved in industry restructuring, electric planning, and natural gas planning. Quan received an M.S. in Operations Research from Stanford University and a B.S. in Applied Mathematics from the University of California at Los Angeles.

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