Forecasting
2019 Benchmarking Survey
October 30, 2019
The end of October brings something for everyone. Fall foliage for adults, Halloween candy for children and Itron’s Annual Benchmarking Survey results for energy forecasters. While not as colorful as changing leaves or as sweet as candy corn, I believe that the survey is the best part of fall.
Since 2012, Itron has been surveying electric and gas utilities about system growth, forecast accuracy and forecasting characteristics. This year’s survey consists of 73 companies representing almost 2,067 billion kWh of annual electric sales and 1.8 BCF of annual natural gas sales across North America.
While many of this year’s findings continue patterns identified from prior years, three new findings stand out:
- Residential Average Use. Since Itron’s first survey in 2012, residential average usage has been declining. The decline is supported by energy efficiency standards and continues to be forecasted by most utilities. This year, however, residential customer growth is 1.12% and sales growth is 1.19% resulting in an increase in average usage. While average use growth is close to zero, this first “increase” data point is either an outlier or the beginning of a new trend. Most importantly, this curious result is something to watch in the coming years.
- Peak Growth. Unlike prior years, peak results are separated between summer peaking and winter peaking utilities. The separation shows that summer peaks are growing faster than winter peaks. Summer peak growth is 1.93% and winter peak growth is 1.12%. In one sense, the growth differential is not surprising since seasonal peaks occur at different times of the day and are driven by different end uses. However, the result underscores the need to capture differing growth rates in our peak models.
- Prevalence of AMI Data. While forecasting is not the primary use case for installing and collecting AMI data, the data is useful for several forecasting applications. This year, 63% of companies reported access to AMI data with two-thirds of those companies using it for forecasting applications. Among the most significant AMI forecasting applications are sales calendarization, unbilled sales calculation and daily class energy and peak modelling. As more utilities gain access to AMI data, expect to see applications in the areas of daily variance tracking, improved weather response modelling and daily models for budgets.
The 2019 Benchmarking Survey full report was just distributed and is only available to Itron’s Energy Forecast Group members and survey participants. If you want to watch these developing trends and obtain the benchmarking results firsthand, be sure to participate in the survey next year.
The survey will open for responses in February 2020. Contact Paige Schaefer at paige.schaefer@itron.com if you would like to be added to the list to participate. Preliminary results will be presented at the Annual Energy Forecasting Meeting on April 22 – 24 in New Orleans.
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Tip: It's the step after the last dot that caused this error, not those before it.
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Tip: If the failing expression is known to legally refer to something that's sometimes null or missing, either specify a default value like myOptionalVar!myDefault, or use <#if myOptionalVar??>when-present<#else>when-missing</#if>. (These only cover the last step of the expression; to cover the whole expression, use parenthesis: (myOptionalVar.foo)!myDefault, (myOptionalVar.foo)??
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