Appendix A: Usage & Efficiency

Appendix A: Usage & Efficiency

Usage & Efficiency The Energy Information Administration publishes the Annual Energy Outlook (AEO) which utilizes the EIA's National Energy Modeling System (NEMS). NEMS is an integrated model of the U.S. energy system that has multiple modules (residential, commercial, etc) to reflect different dimensions. Itron partners with EIA and synthesizes the data into a ready-to-use format with information on equipment/appliance saturation and their associated efficiency at the Census division level. Zones are assigned to a Census division based on geography. 2

Projections Projections are made for a number of different classes of equipment/appliances, within which there are different types. Cooling Residential: Heat Pumps, Central Air Conditioners, Room Air Conditioners Commercial represented by a single cooling index Heating Residential: Furnaces, Heat Pumps, etc Commercial represented by a single heating index 3

Projections Other Residential: Water Heaters, Electric Cooking, Refrigerators, Freezers, Dishwashers, Clothes Washers, Clothes Dryers, Televisions, Lighting, and Miscellaneous Commercial: Ventilation, Water Heaters, Electric Cooking, Refrigerators, Lighting, Office Equipment (PCs), Miscellaneous 4

Energy Usage Index Construction Projections are then combined to form different equipment indexes representing the different classes of Heating, Cooling and Other Equipment Index (Residential & Commercial) Weighted average across equipment types of saturation (share) normalized for efficiency Equipment Index = (Share y /Eff y )/(Share 1998 /Eff 1998 ) Zonal Weighting Using FERC FORM 1 weighting, sector indices are combined to form an index for each usage type (heating, cooling, other) 5

Equipment Index Examples 6

Additional Documentation AEO website http://www.eia.gov/forecasts/aeo/ NEMS Documentation http://www.eia.gov/forecasts/aeo/nems/documentation/ 7

Appendix B: Weather Splines

Weather Splines With its proposed new specification, PJM is utilizing a spline method by which it can have a more granular weather-to-load relationship to provide the potential of picking up points at which that relationship might shift. New weather parameters are defined by season. Summer (Months 5-9): Transformed Temperature-Humidity Index Winter (Months 1, 2, and 12): Transformed Wind-Adjusted Temperature (aka Winter Weather Parameter) Shoulder (Months 3, 4, 10, and 11): Combination of Wind- Adjusted Temperature and Temperature-Humidity Index 9

Summer 10

Summer In a pre-processing step, multiple regressions are run of load on THI over different ranges of THI (Less than 65, 65 to 70, 70 to 75, 75 to 80 and greater than 80). Coefficients are used to get powers defined as Coef (i)/max(coef (1):Coef (5)) THI Range Coefficient Power Less than 65-2.68-0.01 65 to 70 70.93 0.31 70 to 75 172.53 0.76 75 to 80 228.30 1.00 Greater than 80 199.37 0.87 11

Summer Weights are then calculated from these pieces weight1 = power1 weight2 = power2 power1 : weight5 = weight5 weight4 THI Range Weight Less than 65-0.01 65 to 70 0.32 70 to 75 0.45 75 to 80 0.24 Greater than 80-0.13 12

Summer Weights are then used in the formula: THISpline = Weight1 * THI_lt65 +Weight2 * THI_65_70 +Weight3 * THI_70_75 +Weight4 * THI_75_80 +Weight5 * THI_gt80 Where THI_lt65 = THI If THI > 65 then THI_65_70 = THI 65; Else THI_65_70 = 0 If THI > 70 then THI_70_75 = THI 70; Else THI_70_75 = 0 If THI > 75 then THI_75_70 = THI 75; Else THI_75_80 = 0 If THI > 80 then THI_gt80 = THI 80; Else THI_gt80 = 0 13

Winter 14

Summer In a pre-processing step, multiple regressions are run of load on THI over different ranges of THI (Greater than 40, 35 to 40, 30 to 35, 25 to 30, and Less than 25). Coefficients are used to get powers defined as Coef (i)/min(coef (1):Coef (5)) WWP Range Coefficient Power Greater than 40-20.98 0.31 35 to 40-44.37 0.65 30 to 35-22.07 0.33 25 to 30-67.87 1.00 Less than 25-42.94 0.63 15

Summer Weights are then calculated from these pieces weight1 = power1 weight2 = power2 power1 : weight5 = weight5 weight4 WWP Range Weight Greater than 40 0.31 35 to 40 0.34 30 to 35-0.33 25 to 30 0.67 Less than 25-0.37 16

Winter Weights are then used in the formula: WWPSpline = Weight1 * WWP_gt40 +Weight2 * WWP_35_40 +Weight3 * WWP_30_35 +Weight4 * WWP_25_30 +Weight5 * WWP_lt25 Where WWP_gt40 = WWP If WWP < 40 then WWP_35_40 = WWP 40; Else WWP_35_40 = 0 If WWP < 35 then WWP_30_35 = WWP 35; Else WWP_30_35 = 0 If WWP < 30 then WWP_25_30 = WWP 30; Else WWP_25_30 = 0 If WWP < 25 then WWP_lt25 = WWP 25; Else WWP_lt25 = 0 17

Shoulder 18

Shoulder The Shoulder period uses a combination of Wind-Adjusted Temperature (WAT) and Temperature-Humidity Index (THI) to capture that seasonal conditions split between cold/blustery type days and hot/humid type days If WAT < 50 then Shldr_WAT19_50lt = WAT 50; Else Shldr_WAT19_50lt = 0 If WAT >= 50 and WAT <= 70 then Shldr_WAT19_Base = WAT; Else Shldr_WAT19_Base = 0 If Shldr_WAT19_50lt = 0 and Shldr_WAT19_Base = 0 then Shldr_THI = Max THI; Else Shldr_THI = 0 19