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Energy Impacts of the Internet of Things

February 11, 2015

At the Itron Utility Week 2014 Conference, I reported on Itron’s foray into the Internet of Things (IoT) with the new Riva platform. Now that I am aware of the IoT, I see it everywhere in the media.

In January, Samsung’s CEO stated at the 2015 Consumers Electronic Show (CES) that 90 percent of Samsung’s products will be able to connect to the internet by 2017. While this news is exciting from a technology perspective, what are the implications for energy forecasting? After all, technology must be powered.

In my first guess, I hypothesized that the electric consumption of the sensors would be overwhelmed by the savings from energy efficiency gains from smart applications, resulting in declining electric consumption. The basis for this theory is that sensors use very little power. But, data for the future power consumption of smart appliances are hard to obtain.

Listening to interviews and reviews from CES, I now have a second projection of electric consumption impacts from SmartThings CEO Alex Hawkinson. Samsung acquired SmartThings in 2014 as a key component in the move to IoT. Buried in a CES interview, Hawkinson states, “The energy savings [by using SmartThings] can be 20 to 30 percent per month in a household.”

Assuming the average household in the United States uses about 11,800 kWh/year (EIA’s 2012 estimate), the savings is between 2,160 kWh and 3,540 kWh. That’s up to $354/year (assuming $0.10/kwh). Is Mr. Hawkinson optimistic? Pessimistic? Realistic? While I don’t know the source of Mr. Hawkinson’s estimates, I feel comfortable that IoT’s impact is at worst neutral but likely to continue contributing to the slow decline in residential average use.
 

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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