2016 forecasting benchmark surveycapabilities.itron.com/efg/reports/itronforecasting... · 2016....

2016 Forecasting Benchmark Survey

Itron, Inc.

12348 High Bluff Drive, Suite 210 San Diego, CA 92130-2650

858-724-2620

October 2016

2016 Forecasting Benchmark Survey For the fifth year, Itron surveyed energy forecasters across North America with the goal of obtaining

growth and accuracy benchmarks.

Survey results are presented by geographic region and are weighted average responses unless otherwise

noted. The geographic regions are shown in Figure 1. Weights are calculated based on the self-reported

2015 annual energy or natural gas consumption for each utility. The number of respondents and the

overall weights for the current survey is shown in Figure 2. For comparative purposes, the number of

responses from the 2012, 2013, 2014 and 2015 surveys is also included. The actual weights for each

survey question response will vary slightly from the overall weights because some utilities did not

respond to all questions.

Figure 1: Survey Regions

West

South

Midwest

Northeast

Canada


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Figure 2: Survey Respondents

The 2016 Survey includes responses for 62 electric and gas companies. The electric utility responses are

divided into regions and represent almost 2 billion kWh of annual energy consumption. The other

electric responses include Independent System Operators and Electric Retailers who forecast over a

wide geographic region. Natural Gas respondents are aggregated into a single category due to the

number of responses.


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Summary of Results The 2016 Survey examines utility forecast accuracy and growth projections. This section summarizes the

overall findings. Detailed results by customer class are presented in the remaining sections.

Forecast Accuracy Itron asked respondents about their 2015 forecast accuracy compared with weather normal actual 2015

sales. The average forecast accuracy ranges between 1.5% and 3.0%. The 2015 natural gas class

accuracy ranges between 1.8% and 3.1%. Reported accuracies are similar to prior year survey results

Accuracy measures are reported as unweighted mean absolute percent errors (MAPEs). Detailed results

are as shown later in this report in Figure 16 and Figure 22.

Electric Forecast Growth When averaged across electric utility respondents, electric system sales growth is projected to be 1.1%

over the next ten years. The calculated 10-year growth forecast for the residential, commercial, and

industrial classes is close to 0.8%. The difference between the growth rates is that the system sales

include additional classifications such as wholesale and street lighting. Long-term sales growth outlook

is similar to the Energy Information Administration’s (EIA) 2016 Annual Energy Outlook, and consistent

with Itron’s previous surveys. Sales growth continues to show a sharp contrast to historic growth in the

United States over the past 40 years.

Figure 3 shows historical sales from 1974 through 2015 as 12-month rolling sums. The red line shows

historic sales through 2015 with forecast sales based on the survey projections. The blue lines show the

long-term trend through 2008 and extrapolated from 2009 through the forecast period.

Figure 3: Survey Electric Sales Growth


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Beginning with the “Great Recession” in 2008, sales deviate from the long-term trend line. Since 2008,

sales are flat in spite of the economic recovery. With the deviation in the trend, utilities are no longer

expecting sales to return to the long-term trend line. Figure 4 shows historic annual growth rates over

various time periods from 1974 through 2015 for the major electric classes.

Figure 4: U.S. Historical Electric Sales Growth Rate (%)

Time Frame Residential Commercial Industrial Total

1974-2014 2.23% 2.78% 0.88% 1.94%

1980-1990 2.81% 3.93% 1.36% 2.56%

1990-2000 2.49% 3.23% 1.46% 2.37%

2000-2008 2.22% 2.29% -0.27% 1.49%

2009-2015 0.13% 0.15% -0.65% -0.08%

With the inclusion of 2015 data, the total average sales growth from 2009 to 2015 is negative (-0.08%).

The decline in sales is consistent with survey results (Figure 9) and an alarming contrast to the historic

pattern of positive growth. The potential for future negative growth deserves constant attention and

will be the subject of future surveys.


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Natural Gas Forecast Growth Gas respondents expect natural gas sales to grow at an average rate of 1.05% over the next ten years.

Detailed growth rates are shown later in this report in Figure 14. While there have been periods of both

growth and decline in gas sales, the overall trend is flat. Figure 5 shows a 12-month rolling sum of

monthly retail gas sales. The forecast is based on reported forecast growth rates beginning in 2015.

Figure 6 shows average annual growth rates for selected periods of time.

Figure 5: U.S. Historical Natural Gas Sales

Figure 6: U.S. Historical Natural Gas Sales Growth Rate (%)

Time Frame Residential Commercial Industrial Total

1974-2014 0.30% 0.80% -0.19% 0.10%

1980-1990 -0.50% 0.23% -0.99% -0.58%

1990-2000 0.29% 1.50% 1.94% 1.32%

2000-2008 0.51% 0.25% -1.57% -0.64%

2009-2015 0.64% 1.46% 2.07% 1.59%


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Customers Historic and forecast customer growth rates for the residential and commercial classes are shown in

Figure 7 and Figure 8. Reported growth rates from the 2012, 2013, 2014, and 2015 surveys are

combined with the 2016 survey.

Reported 2015 electric customer growth is 0.87% for the residential class and 0.89% for the commercial

class. Natural gas customer growth is 0.96% for the residential class and 0.64% for the commercial class.

Coming out of the recession, customer growth increases to about 0.9% with the strongest growth in the

South and West and weakest growth in the Midwest and Northeast. Over the next ten years, utilities

expect customer growth to be consistent with recent growth patterns.

Figure 7: Residential Average Customer Growth (%)

Figure 8: Commercial Average Customer Growth (%)


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Residential Sales Figure 9 shows past and current reported weather-normal residential sales growth. The figure also

shows respondents’ 2016 forecasts and average growth forecast for the next ten years.

Electric Growth. On a total basis, utilities report a decline in weather normalized residential sales (down

0.38%). Sales are down across all the regions except the South. The Northeast and Midwest regions see

the largest decline. The new lighting standards are a significant contributor to the decline in sales.

Overall utilities expect to see low, but positive residential electric sales growth. However, the Northeast

expects long-term declines in residential sales growth, and the Midwest projects flat sales growth over

the next ten years.

Figure 9: Residential Sales Growth

Projected residential customer growth of 0.9% coupled with long-term residential sales growth of 0.5%

implies that average use declines by 0.4% annually over the next ten years. Northeast respondents

expect declining average use of 1.0% annually. Projected declines in average use are consistent with

recent trends and EIA’s 2016 AEO Reference Case (Figure 10).


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Figure 10: AEO Residential Electric Use Intensity Index (kWh/Household)

Natural Gas. The 2016 Survey is the third year natural gas utilities were asked for weather normalized

sales. The 2015 annual growth is 0.72% and the long-term forecast is 0.51%. The survey represents a

weighted average of 8 respondents and is subject to large variances.

Commercial Sales Figure 11 shows historic and forecast commercial sales growth rates. Historic growth rates are weather

normalized.

Electric Growth. Commercial weather normalized sales growth in 2014-2015 (2015 Actual) is 0.28%.

Forecasted growth is 0.56% in the near-term and 0.60% in the long-term. Since Itron’s 2012 survey,

actual growth has increased from 0.15% in 2011 to 0.80% in 2014. However, 2015 shows a significant

slowing of growth. While the growth rate is not negative like the residential class, the dramatic change

may signal the start of a new trend.

Average-use growth based on the sales and customer growth rates continues to decline. The decline is

not a new development and can be seen in all of Itron’s past surveys as well as in the EIA’s 2016 AEO

Release Reference Case (Figure 12).


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Figure 11: Commercial Sales Growth

Figure 12: AEO Commercial Electric Use Intensity (kWh/Square Foot)

Natural Gas. The 2015 Survey shows a 0.58% decline in weather-normal sales growth. Respondents

expect the drop in sales to be short-lived with commercial gas sales increasing 0.42% annually over the

next ten years.

Industrial Sales The responses to historic and forecast industrial growth are shown in Figure 13. This figure combines

the reported growth rates from the 2012, 2013, 2014 and 2015 surveys with the reported and

forecasted growth rates from the 2016 Survey.

Electric Growth. Across all respondents, reported 2015 industrial electric sales declines 0.33%.

However, the current decline is short-lived as respondents expect industrial sales growth to rebound in

2016 with a long-term average annual sales growth of 1.19%. The South shows the strongest industrial


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sales growth while the Northeast projects a long-term decline in industrial sales. Respondents project

industrial sales growth to exceed residential and commercial sales growth which this is consistent with

EIA’s long-term energy outlook.

Figure 13: Industrial Sales Growth

Natural Gas. The 2015 Survey shows a second year of negative growth. However, long-term sales are

expected to track industrial electricity sales with industrial gas growth averaging 1.12% annually over

the next ten years.

System Sales The historic and forecast system and peak growth are shown in Figure 14 and Figure 15. These figures

combine the reported growth rates from the 2012, 2013 and 2014 surveys with the reported and

forecasted growth rates from the 2015 survey. System sales include all utility classes and may include

wholesale, resale, and agricultural classes.

Electric Growth. 2015 weather-normal system energy requirements fell 0.13%. The decline in system

energy requirements is consistent with the declines in residential and industrial sales and weak

commercial sales growth. Only the South sees positive 2015 energy growth. In total, respondents

expect energy sales to average 1.12% annual growth over the next ten years.

Peak demand growth has historically shown large variations across regions and over time. While Itron

asks for weather normal peak demand growth, the variation in response indicates challenges in data

reporting and weather normalization calculations. Overall, forecast peak demands are consistent with

forecasted energy requirements. Peak demand is expected to increase at a 1.22% annual rate increasing

slightly faster than the energy 1.1% forecasted growth rate.


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Figure 14: System Energy Growth

Figure 15: System Peak Demand Growth

Natural Gas. The natural gas system shows consistently positive growth with 1.5% in 2015 and long

term projections above 1.05%. As with the other gas classes, the low number of responses makes the

growth number subject to high variances.

Distribution of Electric Forecast Errors The survey asked respondents about their 2015 forecast accuracy. Companies were asked for two error

calculations. First, companies were to compare their forecast for 2015 (generated in 2014) against

weather normalized sales in 2015. Second, companies were to compare their forecast for 2015 against

actual sales in 2015. The average forecast errors calculated as the Mean Absolute Percent Error (MAPE)

are shown in Figure 16. This figure compares the MAPEs from the 2012, 2013, 2014, 2015, and 2016

surveys. All MAPE values are unweighted.

Figure 16: Electric Error Results (Unweighted)

For residential, commercial, and system sales, the average forecast error against normalized 2015 sales

is less than 2.0%. This result is consistent with past surveys. The 2015 forecast MAPEs which are


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compared against actual values are slightly higher than when compared against normal values due to

differences between actual and normal weather.

The distributions of the forecast errors are shown in Figure 17 through Figure 21. The forecast error

distributions are measured against normalized sales (left chart) and actual sales (right chart). When the

error is below zero the forecast is higher than actual sales. When the forecast error is above zero the

forecast is lower than actual sales. The graphs indicate that the majority of respondents under-

forecasted 2015 weather-normalized sales. The under-forecast is likely due to optimistic economic

forecasts and stronger than anticipated impacts from increasing lighting standards.

Figure 17: Residential Electric Error Distributions

Figure 18: Commercial Electric Error Distributions


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Figure 19: Industrial Electric Error Distributions

Figure 20: Electric System Error Distributions

Figure 21: Peak Error Distributions


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Natural Gas Forecast Errors Similar to the electric forecasting errors, natural gas companies were asked to compare their forecast

for 2015 (generated in 2014) against actual and weather normalized sales in 2015. Figure 22 shows the

respondents’ unweighted MAPEs. Overall, the 2015 forecasts are more accurate than in prior years.

Figure 22: Natural Gas Error Results (Unweighted)

Key Forecast Drivers As part of the annual forecast survey Itron continues to track changes in forecasting practices. These

changes include accounting for new technologies, changing methods, and business processes. This

section includes responses to questions about electric vehicles, photovoltaics, timing of the forecast,

and forecasting techniques. This year, two additional questions are included. These questions address

the size of forecasting staff and the strength of DSM programs.

Electric Vehicles.

The percentage of respondents who explicitly include electric vehicles (EVs) in their forecast continues

to increase. In 2016, 55% of respondent account for EVs. The number of respondents including EVs has

nearly doubled since the 2012 survey. Figure 23 shows the 2016 survey result compared to prior year

results.


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Figure 23: Include Electric Vehicles in the Forecast

While EV sales represent less than 1% of all new car sales, the industry is quickly growing. Figure 24

shows cumulative number of EV and plug-in EV sales, compiled from the Department of Energy and

InsideEV data reports.

Figure 24: Electric and Plug-In Electric Vehicles Sales

28%23%

30%

44%

55%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2012 2013 2014 2015 2016

Include Electric Vehicles in Forecast


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Photovoltaics.

Figure 25 shows 66% of respondents explicitly include photovoltaics (PV) in their forecasting process. As

with EVs, the PV forecast is now a standard component in most utilities long-term energy and demand

forecasts.

Figure 25: Include Photovoltaics in the Forecast

Figure 26 shows the cumulative growth in installed solar capacity across the United States showing a

doubling of installed capacity since 2013. The speed of the industry requires the inclusion of a solar

forecast into the energy forecasts.

21% 20%

34%

51%

66%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2012 2013 2014 2015 2016

Include Photovoltaics in Forecast


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Figure 26: Solar Installations


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Timing of the Forecast Process.

Figure 27 shows the number of months prior to finalizing the 2016 sales and load forecast. The majority

of respondents show the forecast cycle is completed in the October time frame. Almost 80% of

respondents complete their forecasts within 6 months prior the start of the budget period.

Figure 27: Timing of Forecast Process

Modeling Technique.

Figure 28 through Figure 31 identify the modeling techniques used by companies to forecast the near

term (1 year ahead) and long term (10 years ahead or longer) sales. Additionally, these figures compare

the 2015 and 2016 survey results. In the figures, Economic refers to using a regression model and SAE

refers to using Itron’s Statistically Adjusted End-Use (SAE) modeling approach.


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Figure 28: Residential Sales Forecast Model Technique – 1 Year Ahead

Figure 29: Residential Sales Forecast Model Technique – 10 Year Ahead


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Figure 30: Commercial Sales Forecast Model Technique – 1 Year Ahead

Figure 31: Commercial Sales Forecast Model Technique – 10 Year Ahead

The 2016 survey shows utility forecasters moving towards the SAE modeling approach. The driving

factor is the need to capture declining average use as a result of new end-use technology standards and

state and utility energy efficiency (EE) programs. Declining sales cannot be captured with general

macroeconomic drivers which grow through the forecast time horizon. Figure 32 highlights the


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changing relationship between one macroeconomic driver, GDP, and electric sales. This figure shows

the relationship between GDP and electric consumption began deviating in 1995 with a further

deviation in 2008. The SAE model removes the over-reliance on macroeconomic drivers by integrating

end-use intensity trends which account for the historic deviations.

Figure 32: Relationship between GDP and Electric Sales

Forecasting Staff Size.

In the 2016 survey, Itron asked respondents about the size of their forecasting staff. Respondents were

asked to include analysts as well as managers. Results show that 50% of forecasting staffs include 5 or

fewer members. The responses are shown in Figure 33.


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Figure 33: Size of Forecasting Staff

DSM Impacts.

For the past decade, companies have discussed the challenges of accounting for DSM programs in their

forecast. In 2016, the survey asked whether the cumulative impacts of the DSM programs are now

visible considering the size of their overall sales. Figure 34 shows the responses. While the survey does

not define the term “visible”, allowing respondents to self-define the term, the results indicate that DSM

impacts are sufficiently large that their impact should be addressed in estimating forecast models.

Figure 34: Visibility of DSM Impacts


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Conclusion The Itron Forecasting Benchmark Survey provides insight into the changing outlook for future energy

demand, evolving usage trends, and forecast accuracy. The 2016 survey respondents represent half of

electric sales in North America and provides a strong representation of the industry.

This year’s survey identified an industry-wide decline in electric sales. While it is still too early to

conclude that electric sales are on a new trajectory, the need to monitor this development is increasing.

Energy efficiency programs, end-use efficiency gains as the result of new standards, and behind-the-

meter solar installation growth may be causing this development and will continue to put downward

pressure electric and gas sales.

The challenges of forecasting in a slow growth environment places a renewed emphasis on forecast

accuracy, improved modeling techniques, and technology awareness. This survey provides insights into

the latest techniques and best practices through the industry.

2016 forecasting benchmark surveycapabilities.itron.com/efg/reports/itronforecasting... · 2016....

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