16TH ANNUAL ENERGY FORECASTING MEETING / EFG AUSTIN, TX APRIL 25-27, 2018 SAE OVERVIEW WHAT IS XHEAT ANYWAY?

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1 16TH ANNUAL ENERGY FORECASTING MEETING / EFG AUSTIN, TX APRIL 25-27, 2018 SAE OVERVIEW WHAT IS XHEAT ANYWAY?

2 SO WHAT IS XHEAT ANYWAY?» If you hang around here for ore than a day you are going to hear people talking about their XHeat, XCool, and XOther (and soeties their XWife)» And you ight wonder what is this XHeat? Think of XHeat as a fancy Heating Degree-Day but in kwh instead of teperature average heating use per onth (XHeat)

3 AND XCOOL AND XOTHER average cooling use per onth (XCool) average other stuff per onth (XOther)

4 RESIDENTIAL AVERAGE USE» If we knew what you used to cool your house, heat your house, and used for other stuff (cooking, washing clothes, watching TV, playing video gaes) we could add it up. AvgUse Cooling Heating» And if we knew what things would ipact your cooling, heating, and other stuff in the future we could forecast your average use Average Use Other e Other Use Cooling Heating

5 WHAT DRIVES AVERAGE RESIDENTIAL USE?» Weather» Types of appliances (end-uses) you own» Size and usage of these appliances (nuber of hours, loads of laundry, gallons of hot water)» House square footage and building shell integrity» End-use efficiency» Energy prices» Household incoe» Nuber of people living in your house» That is a lot of stuff How do we capture all these factors into Heating, Cooling, and Other Use?

6 STATISTICALLY ADJUSTED END-USE MODEL (SAE) AC Saturation Central Roo AC AC Efficiency Theral Efficiency Hoe Size Incoe Household Size Price Heating Saturation Resistance Heat Pup Heating Efficiency Theral Efficiency Hoe Size Incoe Household Size Price Saturation Levels Water Heat Appliances Lighting Plug Loads Appliance Efficiency Incoe Household Size Price Cooling Degree Days Heating Degree Days Billing Days XCool XHeat XOther AvgUse a b c XCool b h XHeat b o XOther Estiate onthly odel with historical billed sales data e

7 IT ISN T REALLY HARD, JUST A BUNCH OF ADDING AND MULTIPLYING

8 END-USE VARIABLES BASED ON AN END-USE MODELING FRAMEWORK» Forecast sales for each end-use» Collect and aintain detailed end-use database Nuber of units, appliance age distribution, technology options, technology costs, technology efficiency, annual use, housing square footage, theral shell integrity» Ebed assuption as to how these characteristics will change over tie with households, incoe, energy price, appliance costs, and standards» Generate and su resulting end-use energy requireents

9 END-USE MODELING FRAMEWORK» Sales for a given end-use (e): Sales e = Households Saturation e UEC e Saturation e = Nuber of hoes that own end-use e UEC e = Annual energy usage for end-use e» End-use Energy Intensity: EI e = Saturation e UEC e Average annual usage per household (kwh)

10 UNIT ENERGY CONSUMPTION (ANNUAL USAGE KWH) UEC e Size e Efficiency Usage e e Where: Size e Usage e = Average size of end use e = Measure of the intensity of appliance usage Efficiency e = Average efficiency for end use e If Size and Usage are constant, then the UEC is driven by changes in efficiency

11 NY ELECTRIC DRYER USAGE » Electric Dryers Nuber of Households: 7,320,000 Percent of households with electric dryers: 36% Annual energy use for an electric dryer (UEC): 800 kwh» Dryer Sales = 7,320,000 x 36% x 800 kwh = 2,108 GWh» Energy Intensity: 36% x 800 kwh = 288 kwh

12 ELECTRIC DRYER INTENSITY (KWH PER HOUSEHOLD) As saturation increases, intensity increases As efficiency increases, intensity decreases

13 ESTIMATE END-USE INTENSITIES FOR EACH END-USE

14 WHERE DO THE INTENSITIES COME FROM?» The Energy Inforation Adinistration develops a detailed enduse forecast for nine US census divisions» Each year, Itron ines the forecast database for: Nuber of households Nuber of appliances End-use consuption End-use saturations End-use average stock efficiency» Residential 3 housing types 11 end-uses» Coercial 11 building types 10 end-uses

15 WISCONSIN VS. EAST NORTH CENTRAL Dryer Freezer Central Air Conditioning Water Heat

16 CENTRAL FLORIDA VS. SOUTH ATLANTIC Roo AC Heat Pup Water Heat Cooking

17 HOW DO WE DO THE MATH? XHeat y, HeatIntensity y HeatUsey, HeatIntensity y Structural Index y Type EI Type 09 Sat Sat Type y Type 09 Eff Eff Type y Type 09 HeatUse y, HDD HDD y, 09 HHSize HHSize y, Incoe Incoe y, Price Price y, In the short-ter its HeatUse that oves the forecast

18 RESIDENTIAL XHEAT VARIABLE (KWH PER HSEHLD) Cobine heating Intensity and heating use variables XHeat Heatuse xheatintensity

19 RESIDENTIAL XCOOL VARIABLE (KWH PER HSEHLD) Cobine cooling Intensity and cooling use variables XCool CoolUse xcoolintensity

20 RESIDENTIAL XOTHER VARIABLE Cobine end-use intensities and other use variables (kwh per onth) XOther OtherUse xotherintensity

21 DID WE GET IT RIGHT?» But when we add up our estiates of heating, cooling, and other use in this case it s a bit higher than actual utility average use Su of XHeat, XCool, and XOther Actual Average Use

22 NOTHING A REGRESSION MODEL CAN T CLEAN UP The statistical part Su of XHeat, XCool, and XOther Actual Average Use Predicted We get a statistically adjusted average use forecast

23 STATISTICALLY ADJUSTED END-USE SALES Other Heating Cooling

24 WHY SAE? 1. The SAE odel provides a fraework for thinking about how electricity is used 2. The odel integrates econoic drivers that ipacts short-ter utilization and factors that ipact long-ter structural change. A single, robust odel for forecasting short-ter sales and custoers for financial planning and long-ter energy and deand for resource planning 3. Provides an excellent fraework for scenario analysis. Lot s of levers. This ay include alternative econoic and deographic outlooks, weather scenarios, new end-use standards, and energy efficiency progras. 4. Finally, you have to do soething. The alternative is throwing things into a regression odel and hoping soething works. The SAE odel always works.

25 QUESTIONS?

26 CONTACT US

27 THANK YOU BOSTON Eric Fox ext