Itron Has Been Busy this Summer Helping Utilities Keep the Lights On

This summer has been particularly steamy in certain parts of the country, unfortunately resulting in periodic blackouts as utilities struggle to get enough supply resource online to meet the extreme demand.

Demand response is a clean energy resource frequently used by utilities to keep the lights on during these periods of extreme heat. While demand response is used as a year-round resource, it’s during summer heat waves when residential customers test the limits of their air conditioners that it becomes increasingly important. Demand response programs provide financial incentives to customers who agree to allow the utility to curtail appliances in their homes, such as air conditioners, water heaters and pool pumps.

Itron has deployed more than 3 million energy management devices for residential and small business customers on a range of appliances—such as water heaters and pool pumps—with the vast majority on central air conditioners. Itron technology gives electric utilities the ability to aggregate and then remotely curtail these high-energy use appliances. Many of our utility clients have amassed more than 100 megawatts of load, which is a substantial operational resource they can leverage when the grid is most strained. This summer, Itron was busy curtailing load for our utility clients, executing 126 control events during June, July and August. These events provided more than 300 hours of reliable resources when our utility clients were experiencing severe constraints.

Itron provides a range of solutions to electric utilities that help them improve grid reliability, including our demand response solutions, which are the perfect option for combating the extreme temperatures we saw this summer. As the number one ranked demand response vendor in the industry, we lived up to our reputation and delivered grid relief when our electric utility customers needed it the most. As utilities look to strengthen customer relationships and increase J.D. Power customer satisfaction scores, there’s no better driver than keeping the power on.


Using the Right Weather Data

I recently reviewed a customer’s monthly weather normalization model. The regression model included cooling degree days (CDD), heating degree days (HDD), and a few other minor variables. The monthly CDD and HDD variables were summed from the daily CDD and HDD variables, which were calculated from daily average temperature. In this case, the daily average temperature was calculated as the average of the maximum and minimum values. Further, the CDD and HDD variables were both specified with a single breakpoint of 65 degrees. The model’s Mean Absolute Percent Error (MAPE) was 1.08%. (Remember, a lower MAPE is preferable to a higher MAPE.)

Because the hourly temperature data were available (and because I am a curious person), I modified the calculation of the average temperature to be the average of the 24 hourly values, rather than the average of the maximum and minimum values. When I did this, the MAPE dropped from 1.08% to 1.03%. The improvement is not tremendous, but it is something.

By reviewing a scatter plot that related the daily energy to the daily average temperature, I determined that heating in this area starts at 55 degrees, rather than 65 degrees. When I changed the HDD breakpoint from 65 to 55, the MAPE dropped to 0.72%. I also determined that cooling in this area starts at 70 degrees. When I changed the CDD breakpoint from 65 to 70 degrees, the MAPE dropped to 0.63%.

In total, I reduced the model’s MAPE from 1.08% to 0.63% by using more appropriate weather data and without making any changes to the model structure.

There are two lessons here. First, we cannot assume that 65 degrees is the correct breakpoint just because it is used by the National Oceanic and Atmospheric Administration (NOAA). The best and easiest way to identify the breakpoints is to view them in a scatter plot. Second, the model informs us about the data. Specifically, if the model improves when we make a particular change, that change is probably a good idea.


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