savings can be calculated as described by the algorithms above. Otherwise, the savings for the mini, C7, and C9 varieties should be weighted by 0.5, 0.25 and 0.25, respectively, as in the algorithm below. Table : Holiday Lights Assumptions Parameter Unit Value Source LEDmini , Wattage of LED mini bulbs Watts/Bulb 0.08 1 INCmini , Wattage of incandescent mini bulbs Watts/Bulb 0.48 1 LEDC7 , Wattage of LED C7 bulbs Watts/Bulb 0.48 1 INCC7 , Wattage of incandescent C7bulbs Watts/Bulb 6.0 1 LEDC9 , Wattage of LED C9 bulbs Watts/Bulb 2.0 1 INCC9 , Wattage of incandescent C9 bulbs Watts/Bulb 7.0 1 %Mini , Percentage of holiday lights that are “mini” % 50% 1 %C7 , Percentage of holiday lights that are “C7” % 25% 1 %C9 , Percentage of holiday lights that are “C9” % 25% 1 #Bulbs , Number of bulbs per strand Bulbs/strand EDC Data Gathering Default: 50 per strand 3 #Strands , Number of strands of lights per package strands/package EDC Data Gathering Default: 1 strand 3 Hr , Annual hours of operation Hours/yr 150 1 The deemed savings for installation of LED C9, C7, and mini lights is 37.5 kWh, 41.4 kWh, and 3 kWh, respectively. The weighted average savings are 21.2 kWh per strand. There are no demand savings as holiday lights only operate at night. Since the lights do not operate in the summer, the coincidence factor for this measure is 0.0. F A
kWh/yr COPsys EERsys kWhcool kWhcool (RAC baseline only) kWhheat kWhheat (space heater baseline only) kWpeak = kWpeak (RAC baseline only) = GSHP Desuperheater This algorithm is used for the installation of a desuperheater for a GSHP unit. = 534 kWh kWpeak Furnace High Efficiency Fan This algorithm is used for the installation of new high efficiency furnace fans. kWh/yrheat = HFS kWh/yrcool = CFS kWpeak = PDFS Table : Residential Electric HVAC - References Component Unit Value Sources CAPYcool , The cooling capacity of the central air conditioner or heat pump being installed Btu/hr EDC Data Gathering AEPS Application; EDC Data Gathering CAPYheat , The heating capacity of the heat pump being installed Btu/hr EDC Data Gathering AEPS Application; EDC Data Gathering CAPYspaceheat , The heating capacity of the space heaters when using the de facto heating baseline Btu/hr EDC Data Gathering EDC Data Gathering CAPYRAC , The cooling capacity of the room AC units. Used only for the RAC cooling baseline Btu/hr EDC Data Gathering EDC Data Gathering Wspaceheat , The heating capacity of the space heaters in watts. Used only for the de facto heating baseline Watts EDC Data Gathering EDC Data Gathering WRAC , The cooling capacity of the room AC in watts. Used only for the RAC cooling baseline Watts EDC Data Gathering EDC Data Gathering SEERb , Seasonal Energy Efficiency Ratio of the Baseline Unit (split or package units) Replace on Burnout: 13 SEER (Central A/C) or 14 SEER (ASHP) 1 F
EFLHASHP , Equivalent Full Load Heating hours for Air Source Heat Pumps Allentown = 1,193 Erie = 1,349 Harrisburg = 1,103 Philadelphia = 1,060 Pittsburgh = 1,209 Scranton = 1,296 Williamsport = 1,251 2014 PA TRM Table 2102, in Electric HVAC section Optional An EDC can either use the Alternate EFLH Table or estimate its own EFLH based on customer billing data analysis. Alternate EFLH Table (See Table 216) or EDC Data Gathering EFLHelec furnace , Equivalent Full Load Heating hours for Electric Forced Air Furnaces Allentown = 1,000 Erie = 1,075 Harrisburg = 947 Philadelphia = 934 Pittsburgh = 964 Scranton = 1,034 Williamsport = 1,011 1 Optional An EDC can either use the Alternate EFLH Table or estimate it’s own EFLH based on customer billing data analysis. Alternate EFLH Table (See Table 217) or EDC Data Gathering EFLHelec bb , Equivalent Full Load Heating hours for Electric Baseboard systems Allentown = 1,321 Erie = 1,396 Harrisburg = 1,265 Philadelphia = 1,236 Pittsburgh = 1,273 Scranton = 1,357 Williamsport = 1,354 1 Optional An EDC can either use the Alternate EFLH Table or estimate it’s own EFLH based on customer billing data analysis. Alternate EFLH Table (See Table 218) or EDC Data Gathering EFLHfuel furnace , Equivalent Full Load Heating hours for Fossil Fuel Furnace systems Allentown = 1,022 Erie = 1,098 Harrisburg = 969 Philadelphia = 955 Pittsburgh = 985 Scranton = 1,056 Williamsport = 1,033 1 Optional An EDC can either use the Alternate EFLH Table or estimate it’s own EFLH based on customer billing data analysis. Alternate EFLH Table (See Table 219) or EDC Data Gathering
Methodology 1: Modified Blower Door Subtraction Determine Duct Leakage rate before and after performing duct sealing CFM50DL = Calculate duct leakage reduction, convert to CFM25DL and factor in Supply and Return Loss Factors ΔCFM25DL = Calculate Energy Savings Methodology 2: RESNET Test 803.7 Determine Duct Leakage rate before and after performing duct sealing ΔCFM25DB = Calculate Energy Savings Methodology 3: Evaluation of Distribution Efficiency Determine Distribution Efficiency by evaluating duct system before and after duct sealing using Building Performance Institute “Distribution Efficiency Look-Up Table” Summer Coincident Peak Demand Savings Table : Duct Sealing – Values and References Term Unit Value Source CF , Demand Coincidence Factor (See Section 1.5) for central AC systems Decimal Default = 0.647 11 CFM50whole house , Duct leakage at 50 Pascal pressure differential EDC Data Gathering EDC Data Gathering CFM25DB , Cubic feet per minute of air leaving the duct system at 25 Pascals EDC Data Gathering 12 CFM25BASE , Standard Duct Leakage test result at 25 Pascal pressure differential of the duct system prior to sealing, calculated from the duct blaster fan flow chart EDC Data Gathering 12 CFM25EE , Standard Duct Leakage test EDC Data Gathering 12
the ETDF is applied. The demand reduction is taken as the annual energy savings multiplied by the ratio of the average demand between 2 PM and 6 PM on summer weekdays to the total annual energy usage. kWpeak = ETDF ETDF (Energy to Demand Factor) is defined below: The ratio of the average demand between 2 PM and 6 PM on summer weekdays to the total annual energy usage is taken from an electric water heater metering study performed by BG&E (pg 95 of Source 6). The parameters in the above equation are listed in Table 245. Table : Heat Pump Water Heater Calculation Assumptions Component Unit Values Source , Energy Factor of baseline water heater None See Table 248 Default= 0.945 (EF for 50 gallon) 1, 7 , Energy Factor of proposed efficient water heater gallons EDC Data Gathering Default : ≤55 Gallons: 2.0 >55 Gallons: 2.2 HW , Hot water used per day in gallons 50 2 , Temperature of hot water °F 119 3 , Temperature of cold water supply °F 55 4 , COP De-rating factor Fraction Table 249 5, and discussion below , Equivalent Full Load Hours for cooling Table 246 6 , Equivalent Full Load Hours for heating Table 247 6 HSPF , Heating Seasonal Performance Factor EDC Data Gathering Default= 7.4 7 SEER , Seasonal Energy Efficiency Ratio EDC Data Gathering Default= 12 7 ETDF , Energy to Demand Factor (defined above) 0.00008047 8
Table : Calculation Assumptions for Heat Pump Water Heater to Fossil Fuel Water Heaters Component Unit Values Source EFHP,bl , Energy Factor of baseline heat pump water heater Fraction Default = 2.0 or EDC Data Gathering 1 EFNG,inst . Energy Factor of installed natural gas water heater Fraction EDC Data Gathering Default: ≤55 Gallons= 0.67 >55 Gallons= 0.77 2 EFPropane,inst , Energy Factor of installed propane water heater Fraction EDC Data Gathering Default: ≤55 Gallons= 0.67 >55 Gallons= 0.77 2 EFTankless Water Heater , Energy Factor of installed tankless water heater Fraction EDC Data gathering Default= 0.90 2 EFOil,inst , Energy Factor of installed oil water heater Fraction >=0.585 or EDC Data Gathering 3 HW , Hot water used per day in gallons 50 4 Thot , Temperature of hot water °F 119 5 Tcold , Temperature of cold water supply °F 55 6 FDerate , COP De-rating factor Fraction Table 259 7, and discussion below , Equivalent Full Load Hours for cooling Table 257 8 , Equivalent Full Load Hours for heating Table 258 8 HSPF , Heating Seasonal Performance Factor EDC Data Gathering Default= 7.4 9 SEER , Seasonal Energy Efficiency Ratio EDC Data Gathering Default= 12 9 ETDF, Average Usage per Average Energy Usage 0.00008047 10 Table : Equivalent Full Load Hours for Cooling Season City Allentown 487 Erie 389 Harrisburg 551 Philadelphia 591 Pittsburgh 432 Scranton 417 Williamsport 422
Table : Water Heater Temperature Setback Assumptions Component Unit Values Source , Energy Factor of water heater Fraction EDC data collection Default: Electric Storage= 0.904 HPWH= 2.0 1 , value of water heater tank, EDC Data Gathering Default: 8.3 , Surface Area of water heater tank, EDC Data Gathering Default: 24.99 50 gal. value in Table 265 , Thermal efficiency of electric heater element (equiv. to COP for HPWH) Decimal Electric Storage: 0.98 HPWH: 2.1 2, 3 , Volume of hot water used per day by clothes washer, in gallons gallons/day 7.32 4, 5, 6, 7 Thot_i , Temperature setpoint of water heater initially °F EDC Data Gathering Default: 130 8 Thot_f , Temperature setpoint water heater after setback °F EDC data collection Default: 119 9 ETDF , Energy To Demand Factor (defined above) 0.00008047 10 The energy savings and demand reductions are prescriptive according to the above formulae. However, some values for common configurations are provided in Table 265 below. Table : Default Energy Savings and Demand Reductions Type Tank Size (gallons) (˚F) Energy Savings () Demand Reduction Electric Storage 50 8.3 24.99 130-119 0.98 0.904 165.9 0.0133 HPWH 50 8.3 24.99 130-119 2.1 2.0 76.2 0.0061 The most appropriate evaluation protocol for this measure is verification of water heater temperature setpoint coupled with assignment of stipulated energy savings. Previous Federal Standards from 2004-2015 are 0.97 -0.00132 x Rated Storage in Gallons. For a 50-gallon tank this is 0.904. “Energy Conservation Program: Energy Conservation Standards for Residential Water Heaters, Direct Heating Equipment, and Pool Heaters” US A
Table : Low Flow Faucet Aerator Calculation Assumptions Term Unit Value Source GPMbase , Average baseline flow rate of aerator (GPM) Default =2.2 Or EDC Data Gathering 1 GPMlow , Average post measure flow rate of aerator (GPM) Default = 1.5 Or EDC Data Gathering 1 TPerson-Day , Average time of hot water usage per person per day (minutes) Kitchen=4.5 Bathroom=1.6 Unknown=6.1 2 NPersons , Average number of persons per household Default SF=2.4 Default MF=1.9 Default Unknown=2.4 Or EDC Data Gathering 3 Tout , Average mixed water temperature flowing from the faucet (ºF) ˚F Kitchen=93 Bathroom=86 Unknown= 87.8 4 Tin , Average temperature of water entering the house (ºF) ˚F 55 5, 6 RE , Recovery efficiency of electric water heater Decimal 0.98 7 ETDF, Energy To Demand Factor 0.000134 8 , Average number of faucets in the home SF: Kitchen=1.0 Bathroom=3.0 Unknown=4.0 MF: Kitchen=1.0 Bathroom=1.7 Unknown=2.7 Unknown Home Type: Kitchen=1.0 Bathroom=2.8 Unknown=3.8 Or EDC Data Gathering 9 DF , Percentage of water flowing down drain % Kitchen=75% Bathroom=90% Unknown=79.5% 10 ISR , In Service Rate % Variable EDC Data Gathering ELEC , Percentage of homes with electric water heat % Default: Unknown=43% Or EDC Data Gathering: Electric = 100% Fossil Fuel = 0.0% 11 , percentage of daily faucet use during PJM peak period % 19.5% 8
Default unknown = 1.2 Or EDC Data Gathering Tout, Assumed temperature of water used by showerhead ° 104 Or EDC Data Gathering 5 Tin, Assumed temperature of water entering house ° 55 6,7 UH, Unit Conversion 8.3 UE, Unit Conversion 1/3412 RE, Recovery efficiency of electric water heater Decimal 0.98 7 ETDF, Energy To Demand Factor 0.00008013 8 ISR, In Service Rate % Variable EDC Data ELEC, Percentage of homes with electric water heat % Default: Unknown=43% Or EDC Data Gathering: Electric = 100% Fossil Fuel = 0.0% 9 BehavioralWasteSeconds, Time sec Default = 59 or EDC Data Gathering 5 Table : Restriction Valve Calculation Assumptions Application Baseline Flowrate (GPM) ELEC (water heater fuel) Energy Savings (kWh/yr) Peak Demand Reduction (kW) Therm Savings Single Family 2.5 Unknown (43%) 52.0 0.0042 5.3 2 Unknown (43%) 41.6 0.0033 4.3 1.5 Unknown (43%) 31.2 0.0025 3.2 Multifamily 2.5 Unknown (43%) 48.6 0.0039 5 2 Unknown (43%) 38.9 0.0031 4 1.5 Unknown (43%) 29.2 0.0023 3 Unknown / Default Housing Type 2.5 Unknown (43%) 56.3 0.0045 5.8 2 Unknown (43%) 45.1 0.0036 4.6 1.5 Unknown (43%) 33.8 0.0027 3.5 Single Family 2.5 Electric (100%) 120.9 0.0097 5.3 2 Electric (100%) 96.7 0.0077 4.3
freezer with an automatic icemaker without through-the-door ice service. 7. defrost with freezer with ice service. 24.6 643 587 56 0.0062 5A. defrost with freezer with ice service. 25.4 710 648 62 0.0070 3A. All-refrigerators—automatic defrost. 12.2 288 259 29 0.0032 Compact Size Models: Less than 7.75 cubic feet and 36 inches or less in height 11A.Compact defrost. 3.3 245 220 24 0.0027 12. Compact automatic defrost 3.3 355 320 36 0.0040 13. Compact defrost with top-mounted freezer. 4.5 392 353 39 0.0044 15. Compact defrost with bottom-mounted freezer. 5.1 399 359 40 0.0045 ENERGY STAR Most Efficient annual energy consumption (kWhme) may be determined using manufacturer’s test data for the given model. Where test data is not available, the algorithms in Table 273 for “ENERGY STAR Most Efficient maximum energy usage in kWh/year” may be used to determine efficient energy consumption for a conservative savings estimate. Baseline annual energy usage consumption (kWhbase) of the federal standard model may be determined using Table 271. Table : ENERGY STAR Most Efficient Annual Energy Usage if Configuration and Volume Known Refrigerator Category ENERGY STAR Most Efficient Maximum Annual Energy Usage in kWh/yr 1. Refrigerator-freezers and refrigerators other than all-refrigerators with manual defrost. AV ≤ 65.6, Eann ≤ 6.79*AV + 191.3 AV > 65.6, Eann ≤ 637 2. Refrigerator-freezers—partial automatic defrost AV ≤ 65.6, Eann ≤ 6.79*AV + 191.3 AV > 65.6, Eann ≤ 637 3. Refrigerator-freezers—automatic defrost with top-mounted freezer without an automatic icemaker. AV ≤ 63.9, Eann ≤ 6.86*AV + 198.6 AV > 63.9, Eann ≤ 637
7. Refrigerator-freezers—automatic defrost with side-mounted freezer with ice service. AV ≤ 35.3, Eann ≤ 7.26*AV + 380.5 AV > 35.3, Eann ≤ 637 7-BI. Built-In Refrigerator-freezers—automatic defrost with side-mounted freezer with through-the-door ice service. AV ≤ 35.3, Eann ≤ 7.26*AV + 380.5 AV > 35.3, Eann ≤ 637 The default values for each ENERGY STAR Most Efficient configuration are given in Table 272. Table : Default Savings Values for ENERGY STAR Most Efficient Refrigerators Refrigerator Category Assumed Volume of Unit (cubic feet) Conventional Unit Energy Usage in kWh/yr ENERGY STAR Most Efficient Consumption in kWh/yr ΔkWh/yr ΔkWpeak 5I. Refrigerator-freezers—automatic defrost with bottom-mounted freezer with an automatic icemaker without through-the-door ice service. 24.6 619 486 133 0.01494 5A. Refrigerator-freezer—automatic defrost with bottom-mounted freezer with through-the-door ice service. 32.1 772 631 141 0.0158 For most projects, the appropriate evaluation protocol is to verify installation and proper selection of default values. For projects using customer specific data for open variables, the appropriate evaluation protocol is to verify installation and proper application of TRM protocol along with verification of open variables. The Pennsylvania Evaluation Framework provides specific guidelines and requirements for evaluation procedures. Federal Standards for Residential Refrigerators and Freezers, Effective 9/14/2014. http://www1.eere.energy.gov/buildings/appliance_standards/product.aspx/productid/43 ENERGY STAR Program Requirements Product Specifications for Residential Refrigerators and Freezers Version 5.0. Effective 9/15/2014. ENERGY STAR Recognition Criteria for Most Efficient Refrigerator-Freezers. Table 2. Assessment of Energy and Capacity Savings Potential In Iowa. Quantec in collaboration with Summit Blue Consulting, Nexant, Inc., A-TEC Energy Corporation, and Britt/Makela Group, prepared for the Iowa utility Association, February 2008. door
Table : Default Savings Values for ENERGY STAR Freezers Freezer Category Average Adjusted Volume of Qualified Units in ft3 Conventional Unit Energy Usage in kWh/yr ENERGY STAR Energy Usage in kWh/yr ΔkWh/yr ΔkWpeak 8. Upright freezers with manual defrost. Currently no qualified units 9. Upright freezers with automatic defrost without an automatic icemaker. 24.7 441 419 22 0.0025 10. Chest freezers and all other freezers except compact freezers. 18.5 243 215 28 0.0031 16. Compact upright freezers with manual defrost. 3.7 258 232 26 0.0029 17. Compact upright freezers with automatic defrost. 7.7 430 367 63 0.0071 18. Compact chest freezers. 8.9 219 177 42 0.0047 For most projects, the appropriate evaluation protocol is to verify installation and proper selection of default values. For projects using customer specific data for open variables, the appropriate evaluation protocol is to verify installation and proper application of TRM protocol along with verification of open variables. The Pennsylvania Evaluation Framework provides specific guidelines and requirements for evaluation procedures. Federal Standards for Residential Refrigerators and Freezers, Effective 9/14/2014. ENERGY STAR Program Requirements Product Specifications for Residential Refrigerators and Freezers Version 5.0. Effective 9/15/2014. Assessment of Energy and Capacity Savings Potential In Iowa. Quantec in collaboration with Summit Blue Consulting, Nexant, Inc., A-TEC Energy Corporation, and Britt/Makela Group, prepared for the Iowa utility Association, February 2008.
Table Electric Clothes Dryer to Gas Clothes Dryer – Values and Resources Term Unit Values Source , Annual electricity savings, deemed EDC Data Gathering Default = 875 Calculated , Baseline annual electricity consumption of electric dryer, deemed EDC Data Gathering Default = 905 1 , Annual electricity consumption of gas dryer, deemed EDC Data Gathering Default = 30 2 , Weighted average gas fuel increase MMBtu EDC Data Gathering Default = -2.99 Calculated, 3 0.003412, Conversion factor EDC Data Gathering Default = 0.003412 None , Number of washing machine cycles per year cycles/yr 260 4 , Percentage of homes with a dryer that use the dryer every time clothes are washed % 95% 5 , Duration of average drying cycle in hours hours EDC Data Gathering Default= 1 Assumption CF, Coincidence Factor Fraction EDC Data Gathering Default = 0.042 6 Savings estimates for this measure are fully deemed and may be claimed using the algorithms above and the deemed variable inputs. The appropriate evaluation protocol is to verify installation and proper selection of deemed values. Average annual dryer kWh without moisture sensor per 2014 PA TRM protocol 2.2 Electric Clothes Dryer with Moisture Sensor. 2011-04 Technical Support Document: Energy Efficiency Program for Consumer Products and Commercial and Industrial Equipment. Residential Clothes Dryers and Room Air Conditioners, Chapter 7. Median annual electricity consumption of gas dryers from Table 7.3.4: Electric Standard and Gas Clothes Dryer: Average Annual Energy Consumption Levels by Efficiency
Table : Calculation Assumptions for ENERGY STAR Ceiling Fans Component Unit Values Source , percentage of low setting use % 40% 1 , percentage of medium setting use % 40% 1 , percentage of high setting use % 20% 1 , Wattage of low setting, baseline Watts 15 Watts 1 , Wattage of medium setting, baseline Watts 34 Watts 1 , Wattage of high setting, baseline Watts 67 Watts 1 , Wattage of low setting, ENERGY STAR Watts EDC Data Gathering Default: 4.8 Watts 2, 3 , Wattage of medium setting, ENERGY STAR Watts EDC Data Gathering Default: 18.2 Watts 2, 3 , Wattage of high setting, ENERGY STAR Watts EDC Data Gathering Default: 45.9 Watts 2, 3 , fan daily hours of use EDC Data Gathering Default: 3.0 hours/day 1 , Demand Coincidence Factor Fraction EDC Data Gathering Default: 0.091 4 , Demand Coincidence Factor Fraction See Section 2.1 4 Table : Energy Savings and Demand Reductions for ENERGY STAR Ceiling Fans Product Type Energy Savings (kWh) Demand Reduction (kW) Fan Only 16.0 0.00132 The most appropriate evaluation protocol for this measure is verification of installation coupled with calculation of energy and demand savings using above algorithms. ENERGY STAR Lighting Fixture and Ceiling Fan Calculator. Updated September, 2013. ENERGY STAR Ceiling Requirements Version 3.0 ENERGY STAR Certified Ceiling Fan List, Accessed April 3, 2014. EmPOWER Maryland 2012 Final Evaluation Report: Residential Lighting Program, Prepared by Navigant Consulting and the Cadmus Group, Inc., March 2013, Table 50.
Nameplate EDC Data Gathering EERGSHP , Energy Efficiency Ratio of existing home ground source heat pump Default for Ground Source Heat Pump = 13.4 Default for Groundwater Source Heat Pump = 16.2 5 Nameplate EDC Gathering GSER , Factor to determine the SEER of a GSHP based on its EER None 1.02 6 COPGSHP , Coefficient of Performance for existing home ground source heat pump None Default for Ground Source Heat Pump = 3.1 Default for Groundwater Source Heat Pump = 3.6 5 Nameplate EDC Gathering GSOP , Factor to determine the HSPF of a GSHP based on its COP 3.412 7 GSHPDF , Ground Source Heat Pump De-rate Factor None 0.885 (Engineering Estimate - See 2.2.1) CFCAC , Demand Coincidence Factor for central AC systems Fraction 0.647 8 CFRAC , Demand Coincidence Factor for Room AC systems Fraction 0.647 9 CFASHP , Demand Coincidence Factor for ASHP systems Fraction 0.647 8 CFGSHP , Demand Coincidence Factor for GSHP systems Fraction 0.647 8 FRoom,AC , Adjustment factor to relate insulated area to area served by Room AC units None 0.38 Calculated CDD , Cooling Degree Days Table 2107 10 HDD , Heating Degree Days Table 2107 10 EFLHcool , Equivalent Full Load Cooling hours for Room AC Table 2107 11 EFLHcool RAC, Equivalent Full Load Cooling hours for Central AC and ASHP Table 2107 12
Table : ENERGY STAR Windows - References Component Unit Value Sources ESavHP , Electricity savings (heating and cooling) with heat pump installed 2.2395 1 HP Time Period Allocation Factors None Summer/On-Peak 10% Summer/Off-Peak 7% Winter/On-Peak 40% Winter/Off-Peak 44% 2 ESavRES/CAC , Electricity savings with electric resistance heating and central AC installed. 4.0 1 Res/CAC Time Period Allocation Factors None Summer/On-Peak 10% Summer/Off-Peak 7% Winter/On-Peak 40% Winter/Off-Peak 44% 2 ESavRES/NOCAC , Electricity savings with electric resistance heating and no central AC installed 3.97 1 Res/No CAC Time Period Allocation Factors None Summer/On-Peak 3% Summer/Off-Peak 3% Winter/On-Peak 45% Winter/Off-Peak 49% 2 DSavHP , Summer demand savings with heat pump installed. 0.000602 1 DSavCAC , Summer demand savings with central AC installed. 0.000602 1 DSavNOCAC , Summer demand savings with no central AC installed. 0.00 1 CF , Demand Coincidence Factor Decimal 0.647 3 For most projects, the appropriate evaluation protocol is to verify installation and proper selection of default values. For projects using customer specific data for open variables, the appropriate evaluation protocol is to verify installation and proper application of TRM protocol along with verification of open variables. The Pennsylvania Evaluation Framework provides specific guidelines and requirements for evaluation procedures. From REMRATE Modeling of a typical 2,500 sq. ft. NJ home. Savings expressed on a of window area basis. New Brunswick climate data. Time period allocation factors used in cost-effectiveness analysis.
Table : Residential New Construction – References Component Unit Value Sources Heating kWhbase, Annual heating energy consumption of the baseline home, from software. kWh Software Calculated 1 Heating kWhq, Annual heating energy consumption of the qualifying home, from software. kWh Software Calculated 2 Cooling kWhbase, Annual cooling energy consumption of the baseline home, from software. kWh Software Calculated 1 Cooling kWhq, Annual cooling energy consumption of the qualifying home, from software. kWh Software Calculated 2 PLbase, Estimated peak cooling load of the baseline home, from software. kBtu/hr Software Calculated 3 EERbase. Energy Efficiency Ratio of the baseline unit. EDC Data Gathering or SEERb * BLEER 4 EERq, Energy Efficiency Ratio of the qualifying unit. EDC Data Gathering or SEERq * BLEER 4 SEERbase, Seasonal Energy Efficiency Ratio of the baseline unit. 13 14 (ASHP) 5 BLEER, Factor to convert baseline SEERb to EERb. 0.87 6 PLq, Estimated peak cooling load for the qualifying home constructed, from software. kBtu/hr Software Calculated 7 SEERq, SEER associated with the HVAC system in the qualifying home. EDC Data Gathering 8 CF , Demand Coincidence Factor (See Section 1.5) Decimal 0.647 9 The following table lists the building envelope characteristics of the baseline reference home based on IRC 2009 for the three climate zones in Pennsylvania. Table : Baseline Insulation and Fenestration Requirements by Component (Equivalent U-Factors) Climate Zone Fenestration U-Factor Skylight U-Factor Ceiling Frame Wall Mass Wall Floor U-Factor Basement Wall U-Factor Slab R-Value &Depth Crawl Space Wall 4A 0.35 0.60 0.030 0.082 0.141 0.047 0.059 10, 2 ft 0.065 5A 0.35 0.60 0.030 0.060 0.082 0.033 0.059 10, 2 ft 0.065 6A 0.35 0.60 0.026 0.060 0.060 0.033 0.059 10, 4 ft 0.065 Table : Energy Star Homes - User Defined Reference Home Data Point Value Source
Table : ENERGY STAR Manufactured Homes– References Component Unit Value Sources Heating kWhbase, Annual heating energy consumption of the baseline home kWh Software Calculated 1 Heating kWhee, Annual heating energy consumption of the qualifying home kWh Software Calculated 1 Cooling kWhbase, Annual cooling energy consumption of the baseline home kWh Software Calculated 1 Cooling kWhee, Annual cooling energy consumption of the qualifying home kWh Software Calculated 1 PLb, Estimated peak cooling load of the baseline home kBtu/h Software Calculated 1 EERb, Energy Efficiency Ratio of the baseline unit. EDC Data Gathering or SEERb * BLEER 2 EERq, Energy Efficiency Ratio of the qualifying unit. EDC Data Gathering or SEERq * BLEER 2 SEERb, Seasonal Energy Efficiency Ratio of the baseline unit. 13 14 (ASHP) 4 BLEER, Factor to convert baseline SEERb to EERb. EDC Data Gathering Default = ASHP Default = 3 PLq, Estimated peak cooling load for the qualifying home constructed, in kBtu/hr, from software. kBtu/h Software Calculated 1 SEERq, SEER associated with the HVAC system in the qualifying home. EDC Data Gathering 5 CF, Demand Coincidence Factor (See Section 1.5) Decimal EDC Data Gathering Default = 0.647 6 The HUD Code defines required insulation levels as an average envelope Uo value per zone. In Pennsylvania zone 3 requirements apply with a required Uo value of 0.079. This value cannot be directly used to define a baseline envelope R-values because the Uo value is dependent on both the size of the manufactured homes and insulating levels together. However because manufactured homes are typically built to standard dimensions baseline U-values can be estimated with reasonable accuracy. Figure : Uo Baseline Requirements The HUD Code required insulation levels can be expressed as a set of estimated envelope parameters to be used in REM/Rate’s user defined reference home function. Using typical
Table : Residential Air Sealing – Values and References Term Unit Values Source , Baseline infiltration at 50 Pa Measured, EDC Data Gathering , Infiltration at 50 Pa post air sealing Measured, EDC Data Gathering , Unit Energy Savings per CFM50 of air leakage reduction See Table 12 1 , Unit Demand Savings per CFM50 of air leakage reduction, coincident with PJM peak See Table 13 2 Savings may be claimed using the algorithms above and the algorithm’s input default values below, in conjunction with customer-specific blower door test data. Site specific data from blower door testing is required to be used in conjunction with these default energy savings values, as outlined in the algorithms. Table : Default Unit Energy Savings per Reduced CFM50 for Air Sealing City Air Source Heat Pump Electric Resistance Ground Source Heat Pump ASHP Cooling ASHP Heating Central AC Cooling Resistance Heating GSHP Cooling GSHP Heating Allentown 0.0230 1.2340 0.0277 2.2568 0.0054 0.8389 Erie 0.0114 1.5913 0.0163 2.6453 0.0 0.9851 Harrisburg 0.0322 1.0529 0.0377 2.0176 0.0098 0.7432 Philadelphia 0.0548 0.9090 0.0621 1.8348 0.0221 0.6644 Pittsburgh 0.0200 1.3483 0.0244 2.2112 0.0023 0.8190 Scranton 0.0125 1.3074 0.0163 2.2380 0.0 0.8341 Williamsport 0.0155 1.2712 0.0199 2.1716 0.0 0.8052 Table : Default Unit Coincident Peak Demand Savings per Reduced CFM50 for Air Sealing City ASHP Cooling Central AC Cooling GSHP Cooling
96” Standard 4 F84ILL 219 96” Standard 6 F86ILL 328 96” High-Output 1 F81LHL 85 96” High-Output 2 F82LHL 160 96” High-Output 3 F83LHL 253 96” High-Output 4 F84LHL 320 96” High-Output 6 F86LHL 506 For all lighting fixture improvements (without control improvements), the following algorithms apply: Table : Variables for Retrofit Lighting Term Unit Values Source ,Connected load of the baseline lighting as defined by project classification kW See Fixture Identities in Appendix C: Lighting Audit and Design Tool Appendix C: Lighting Audit and Design Tool , Connected load of the post-retrofit or lighting system kW See Fixture Identities in Appendix C: Lighting Audit and Design Tool Appendix C: Lighting Audit and Design Tool , Savings factor for existing lighting control (percent of time the lights are off) None EDC Data Gathering EDC Data Gathering Default: See Table 33 See Table 33 , Demand Coincidence Factor Decimal EDC Data Gathering EDC Data Gathering Default Bulbs: See Table 35 Default Other General Service: See Table 36 See Table 35 and Table 36 , Hours of Use – the average annual operating hours of the baseline lighting equipment, which if applied to full connected load will yield annual energy use. EDC Data Gathering EDC Data Gathering Default Bulbs: Table See Table
Office 2,294 0.48 8 Parking Garage 6,552 0.62* 7 Restaurant 4,747 0.77 8 Retail 2,915 0.66 8 Street Lighting See Table 37 0.00 See Table 37 Warehouse 2,545 0.48 8 * 0.62 represents the simple average of all coincidence factors listed in the 2012 Mid-Atlantic TRM Table : Street lighting HOU by EDC EDC HOU Source Duquesne 4,200 9 PECO 4,100 10 PPL 4,300 11 Met-Ed 4,200 12 Penelec 4,200 13 Penn Power 4,070 14 West Penn Power 4,200 15 Table : Interactive Factors for All Bulb Types Term Unit Values Source None Comfort Cooled = See Table 39 8 Cooled space (60 °F – 79 °F) = 0.34 3 Freezer spaces (-35 °F – 20 °F) = 0.50 Medium-temperature refrigerated spaces (20 °F – 40 °F) = 0.29 High-temperature refrigerated spaces (40 °F – 60 °F) = 0.18 Un-cooled space = 0 None Comfort Cooled = See Table 39 8 Cooled space (60 °F – 79 °F) = 0.12 3 Freezer spaces (-35 °F – 20 °F) = 0.50 Medium-temperature refrigerated spaces (20 °F – 40 °F) = 0.29 High-temperature refrigerated spaces (40 °F – 60 °F) = 0.18 Un-cooled space = 0
Where n is the number of spaces and: Table : Variables for New Construction Lighting Term Unit Values Source , The baseline space or building connected load as calculated by multiplying the space or building area by the appropriate Lighting Power Density (LPD) values specified in either Table 311 or Table 312 kW Calculated based on space or building type and size. Calculated Value , The calculated connected load of the energy efficient lighting kW Calculated based on specifications of installed equipment using Appendix C: Lighting Audit and Design Tool Calculated Value SVG, Savings factor for the new lighting control (percent of time the lights are off) None Based on Metering EDC Data Gathering Default: See Table 314 1 , Demand Coincidence Factor Decimal Based on Metering EDC Data Gathering Default Screw-based Bulbs: See Table 35 Default Other General Service: See Table 36 See Table 35 and Table 36 , Hours of Use – the average annual operating hours of the facility Based on Metering EDC Data Gathering Default Screw-based Bulbs: See Table 35 Default Other General Service: See Table 36 See Table 35 and Table 36 , Interactive Factor None Vary based on building type and space cooling details. See Table 38 and Table 39
Table : LED: Refrigeration Case Lighting – Values and References Term Unit Values Source , Connected wattage of baseline fixtures W EDC Data Gathering EDC Data Gathering , Connected wattage of efficient fixtures W EDC Data Gathering EDC Data Gathering , Number of doors None EDC Data Gathering EDC Data Gathering , Annual operating hours EDC Data Gathering Default: 6,205 1 , Interactive Effects factor for energy to account for cooling savings from efficient lighting None Refrigerator and cooler: 0.41 Freezer: 0.52 2 , Coincidence factor Decimal 0.92 3 , Conversion factor from watts to kilowatts 1000 Conversion Factor Default savings may be claimed using the algorithms above and the variable defaults. EDCs may also claim savings using customer specific data. For most projects, the appropriate evaluation protocol is to verify installation and proper selection of default values. For projects using customer specific data for open variables, the appropriate evaluation protocol is to verify installation and proper application of TRM protocol along with verification of open variables. The Pennsylvania Evaluation Framework provides specific guidelines and requirements for evaluation procedures. Theobald, M. A., Emerging Technologies Program: Application Assessment Report #0608, LED Supermarket Case Lighting Grocery Store, Northern California, Pacific Gas and Electric Company, January 2006. <>. Assumes 6,205 annual operating hours and 50,000 lifetime hours. Most case lighting runs continuously (24/7) but some can be controlled. 6,205 annual hours of use can be used to represent the mix. Using grocery store hours of use (4,660 hr) is too conservative since case lighting is not tied to store lighting. Values adopted from Hall, N. et al, New York Standard Approach for Estimating Energy Savings from Energy Efficiency Measures in Commercial and Industrial Programs, TecMarket Works, September 1, 2009. Methodology adapted from Kuiken et al, “State of Wisconsin Public Service Commission of Wisconsin Focus on Energy Evaluation Business Programs: Deemed Savings Parameter Development”, KEMA, November 13, 2009, assuming summer coincident peak period is
, Seasonal energy efficiency ratio of the baseline unit. For units > 65,000 , EER should be used for cooling savings. Early Replacement: Nameplate data EDC Data Gathering New Construction or Replace on Burnout: Default values from Table 321 See Table 321 , Seasonal energy efficiency ratio of the energy efficient unit. For units > 65,000 , EER should be used for cooling savings. Nameplate data (AHRI or AHAM) EDC Data Gathering , Coefficient of performance of the baseline unit. For ASHP units < 65,000, HSPF should be used for heating savings. None Early Replacement: Nameplate data EDC Data Gathering New Construction or Replace on Burnout: Default values from Table 323323323323 See Table 321 , Coefficient of performance of the energy efficient unit. For ASHP units < 65,000 HSPF should be used for heating savings. None Nameplate data (AHRI or AHAM) EDC Data Gathering , Heating seasonal performance factor of the baseline unit. For units > 65,000 , COP should be used for heating savings. Early Replacement: Nameplate data EDC Data Gathering New Construction or Replace on Burnout: Default values from Table 321 See Table 321 , Heating seasonal performance factor of the energy efficiency unit. For units > 65,000 , COP should be used for heating savings. Nameplate data (AHRI or AHAM) EDC Data Gathering , Demand Coincidence Factor Decimal See Table 323 1 , Equivalent Full Load Hours for the cooling season – The kWh during the entire operating season divided by the kW at design conditions. Based on Logging, BMS data or Modeling EDC Data Gathering Default values from Table 322 1 , Equivalent Full Load Hours for the heating season – The kWh during the entire operating season divided by the kW at design conditions. Based on Logging, BMS data or Modeling EDC Data Gathering Default values from Table 324 1
, Coefficient of Performance of the new ground source, groundwater source, or water source heat pump being installed None Nameplate data (ARI or AHAM) EDC Data Gathering , Cooling annual Equivalent Full Load Hours EFLH for Commercial HVAC for different occupancies Based on Logging, BMS data or Modeling EDC Data Gathering Default values from Table 322 2 , Heating annual Equivalent Full Load Hours EFLH for Commercial HVAC for different occupancies Based on Logging, BMS data or Modeling EDC Data Gathering Default values from Table 324 2 , Demand Coincidence Factor for Commercial HVAC Decimal See Table 323 2 , Demand Coincidence Factor for ground source loop pump Decimal If unit runs 24/7/365, CF=1.0; If unit runs only with heat pump unit compressor, See Table 323 2 , Horsepower of base case ground loop pump motor HP Nameplate EDC Data Gathering , Load factor of the base case ground loop pump motor; ratio of the peak running load to the nameplate rating of the pump motor. None Based on spot metering and nameplate EDC Data Gathering Default: 75% 1 , efficiency of base case ground loop pump motor None Nameplate EDC Data Gathering If unknown, assume the federal minimum efficiency requirements in Table 333 3 , efficiency of base case ground loop pump at design point None Nameplate EDC Data Gathering If unknown, assume program compliance efficiency in Table 332 See Table 332 , Run hours of base case ground loop pump motor Hours Based on Logging, BMS data or Modeling EDC Data Gathering Default values from Table 324 and Table 326 2 , Horsepower of retrofit case ground loop pump motor HP Nameplate EDC Data Gathering
unit >= 95% (natural gas/propane steam boiler) >= 95% (natural gas/propane hot water boiler) >= 85% (oil furnace) >= 85% (oil steam boiler) >= 85% (oil hot water boiler) Nameplate data (AHRI or AHAM) EDC Data Gathering , Equivalent Full Load Hours for the heating season – The kWh during the entire operating season divided by the kW at design conditions Based on Logging, EMS data or Modeling EDC Data Gathering Default values from Table 324 1 , Gas furnace blower motor horsepower HP Default: ½ HP for furnace Average blower motor capacity for gas furnace (typical range = ¼ HP to ¾ HP) Nameplate EDC Data Gathering , Efficiency of furnace blower motor None From nameplate EDC Data Gathering Default: 0.50 for furnace Typical efficiency of ½ HP blower motor for gas furnace
Figure : Energy to Demand Factors for Four Commercial Building Types The parameters in the above equation are listed in Table 377. Table : Commercial Water Heater Fuel Switch Calculation Assumptions Term Unit Values Source , Energy Factor of baseline water heater None Default: See Table 378 1 Nameplate EDC Data Gathering , Energy Factor of installed fossil fuel water heater* None Default for Natural Gas and Propane: ≤55 Gallons = 0.67, >55 Gallons = 0.77 Default for Oil: >=0.585 1, 5 Nameplate EDC Data Gathering , Energy Factor of installed tankless water heater None Default: >=0.90 5 Nameplate EDC Data Gathering , Fossil fuel water heaters derating adjustment factor None Storage Water Heaters: 1.0 Tankless Water Heaters: 0.91 7 , Average annual load kBtu Default: See Table 369 DEER Database , Temperature of hot water °F 119 2 , Temperature of cold water supply °F 55 3 , Average annual gallons of use Gallons Default: See Table 369 Calculation EDC Data Gathering EDC Data Gathering ETDF, Energy To Demand Factor None 0.000178 4 RDF, Resistive Discount Factor None 1.0 6 Energy Factors based on Tank Size As of 4/16/2015, Federal Standards for electric water heater Energy Factors are equal to for tanks ≥20 gallons and ≤55 gallons. For tanks >55 gallons and ≤120 gallons, the minimum Energy Factor is . The following table shows the Energy Factors for various tank sizes.
Calculate using the nameplate amperage and voltage and a power factor. Measure the input kW fan using a power meter reading true RMS power. Table : Evaporator Fan Controller Calculations Assumptions Term Unit Values Source , Energy savings due to evaporator being shut off kWh Calculated Calculated , Heat energy savings due to reduced heat from evaporator fans kWh Calculated Calculated , Control energy savings due to electronic controls on compressor and evaporator kWh Calculated Calculated , Power demand of evaporator fan calculated from any of the methods described above kW Calculated Calculated , Power demand of compressor motor and condenser fan calculated from any of the methods described above kW Calculated Calculated , Conversion from kW to tons 0.28 Conversion Factor 5%, Reduced run-time of compressor and evaporator due to electronic controls None 5% 7 , Conversion factor from kW to horsepower 0.746 Conversion Factor PF, Power Factor of the motor None Fan motor: 0.75 Compressor motor: 0.9 1, 5, 6 %Off, Percent of annual hours that the evaporator is turned off None 46% 2 , Efficiency of typical refrigeration system 1.6 3 , Equivalent annual full load hours of compressor operation EDC Data Gathering EDC Data Gathering 4,072 1, 4
Table : Floating Head Pressure Controls – Values and References Term Unit Values Source , Rated horsepower (HP) per compressor HP EDC Data Gathering EDC Data Gathering , Annual savings per HP See Table 3104 1 , Coefficient of Performance None Based on design conditions EDC Data Gathering Default: Condensing Unit; Refrigerator (Medium Temp: 28 °F – 40 °F): 2.55 COP Freezer (Low Temp: -20 °F – 0 °F): 1.32 COP Remote Condenser; Refrigerator (Medium Temp: 28 °F – 40 °F): 2.49 COP Freezer (Low Temp: -20 °F – 0 °F): 1.45 COP 2 , Refrigeration tonnage of the system Tons EDC Data Gathering EDC Data Gathering , Conversion factor to convert from tons to HP None Engineering Estimate 3
Factor Refrigerator/Cooler , Per door power consumption of cooler case ASHs without controls kW 0.109 1 , Percent of time cooler case ASH with controls will be off during the peak period None 20% 1 , Percent of time cooler case ASH with controls will be off annually None 85% 1 , Demand diversity factor of cooler, accounting for the fact that not all anti-sweat heaters in all buildings in the population are operating at the same time. None 1 3 , Coefficient of performance of cooler None 2.5 1 Freezer , Per door power consumption of freezer case ASHs without controls kW 0.191 1 , Percent of time freezer case ASH with controls will be off during the peak period None 10% 1 , Percent of time freezer case ASH with controls will be off annually None 75% 1 , Demand diversity factor of freezer, accounting for the fact that not all anti-sweat heaters in all buildings in the population are operating at the same time. None 1 3 , Coefficient of performance of freezer None 1.3 1 , Typical percent of cases that are medium-temperature refrigerator/cooler cases None 68% 4
Table : Strip Curtain Calculation Assumptions for Restaurants Term Unit Values Source Cooler Freezer , Efficacy of the new strip curtain – an efficacy of 1 corresponds to the strip curtain thwarting all infiltration, while an efficacy of zero corresponds to the absence of strip curtains. None 0.80 0.81 1 Efficacy of the old strip curtain with Pre-existing curtain with no Pre-existing curtain unknown None 0.58 0.00 0.33 0.58 0.00 0.26 1 Discharge Coefficient: empirically determined scale factors that account for differences between infiltration as rates predicted by application Bernoulli’s law and actual observed infiltration rates None 0.383 0.442 1 Minutes walk-in door is open per day 45 38 1 , Doorway area 21 21 1 , Doorway height 7 7 1 , Dry-bulb temperature of infiltrating air, Rankine = Fahrenheit + 459.67 70 67 1 and 2 , Dry-bulb temperature of refrigerated air, Rankine = Fahrenheit + 459.67 39 8 1 , Density of the infiltration air, based on 55% RH 0.074 0.074 3 , Enthalpy of the infiltrating air, based on 55% RH. 26.356 24.678 3 , Density of the refrigerated air, based on 80% RH. 0.079 0.085 3 , Enthalpy of the refrigerated air, based on 80% RH. 13.750 2.948 3 , Time-dependent (weather dependent) coefficient of performance of the refrigeration system. Based on nominal COP of 1.5 for freezers and 2.5 for coolers. None 3.07 1.95 1 and 2
Table : Ice Machine Reference Values for Algorithm Components Term Unit Values Source , Baseline ice machine energy usage per 100 lbs. of ice Table 3132 1 , High-efficiency ice machine energy usage per 100 lbs. of ice Table 3133 2 , Ice harvest rate per 24 hrs. Manufacturer Specs EDC Data Gathering , Duty cycle of ice machine expressed as a percentage of time machine produces ice None Custom EDC Data Gathering Default: 0.4 3 365, Days per year 365 Conversion Factor 100, Conversion to obtain energy per pound of ice 100 Conversion Factor 8760, Hours per year 8,760 Conversion Factor Ice maker type None Manufacturer Specs EDC Data Gathering , Demand Coincidence Factor Decimal 0.77 4 Table : Batch-Type Ice Machine Baseline Efficiencies (PY8-PY9) Ice machine type Ice harvest rate (H) Baseline energy use per 100 lbs. of ice Ice-Making Head <450 10.26 – 0.0086*H ≥450 6.89 – 0.0011*H Remote-Condensing w/out remote compressor <1000 8.85 – 0.0038*H ≥1000 5.1 Remote-Condensing with remote compressor <934 8.85 – 0.0038*H ≥934 5.3 Self-Contained <175 18 – 0.0469*H ≥175 9.8
Table : Batch-Type Ice Machine Baseline Efficiencies (PY10-PY12) Ice machine type Ice harvest rate (H) Baseline energy use per 100 lbs. of ice Ice-Making Head <300 10 - 0.01233*H ≥300 and <800 7.05 - 0.0025*H ≥800 and <1,500 5.55 - 0.00063*H ≥1,500 and <4,000 4.61 Remote-Condensing w/out remote compressor ≥50 and <1,000 7.97 - 0.00342*H ≥1,000 and <4,000 4.55 Remote-Condensing with remote compressor <942 7.97 - 0.00342*H ≥942 and <4,000 4.75 Self-Contained <110 14.79 - 0.0469*H ≥110 and <200 12.42 - 0.02533*H ≥200 and <4,000 7.35 Table : Continuous Type Ice Machine Baseline Efficiencies (PY10-PY12) Ice machine type Ice harvest rate (H) Baseline energy use per 100 lbs. of ice Ice-Making Head <310 9.19 - 0.00629*H ≥310 and <820 8.23 - 0.0032*H ≥820 and <4,000 5.61 Remote-Condensing w/out remote compressor <800 9.7 - 0.0058*H ≥800 and <4,000 5.06 Remote-Condensing with remote compressor <800 9.9 - 0.0058*H ≥800 and <4,000 5.26 Self-Contained <200 14.22 - 0.03*H ≥200 and <700 9.47 - 0.00624*H ≥700 and <4,000 5.1
Table : No-loss Condensate Drains – Values and References Term Unit Values Source , Air Loss Rate; an hourly average rate for the timed drain dependent on drain orifice diameter and system pressure. CFM EDC Data Gathering Default: See Table 3159 1 , Compressor kW / CFM; the amount of electrical demand in KW required to generate one cubic foot of air at 100 PSI. EDC Data Gathering Default See: Table 3160 2 , Hours per year drain is open EDC Data Gathering Default: 146 3 , Adjustment Factor; accounts for periods when compressor is not running and the system depressurizes due to leaks and operation of time drains. None EDC Data Gathering Default: See Table 3161 4 , Percent Not Condensate; accounts for air loss through the drain after the condensate has been cleared and the drain remains open. None EDC Data Gathering Default: 0.75 4 , Annual hours of compressor operation EDC Data Gathering Default: See Table 3162 5 , Coincidence Factor EDC Data Gathering Default: Table 3163 6
Table : ENERGY STAR Server Measure Assumptions Term Unit Values Source , Power draw of ENERGY STAR server in idle mode kW EDC Data Gathering 1 , utilization of ENERGY STAR server None EDC Data Gathering Default: See Table 3165 EDC Data Gathering 2,3,4 , percentage ENERGY STAR server is more efficient than “standard” or “typical” unit None Fixed = 30% or most current ENERGY STAR specification 5 , ratio of idle power to full load power for an ENERGY STAR server None EDC Data Gathering Default: See Table 3166 EDC Data Gathering 6 , number of ENERGY STAR servers Servers EDC Data Gathering EDC Data Gathering , peak demand savings kW Calculated per algorithm 7 Table : ENERGY STAR Server Utilization Default Assumptions Server Category Installed Processors (%) A, 1 15% C, 2 40%
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18080 Allentown 18081 Philadelphia 18083 Allentown 18084 Philadelphia 18085 Allentown 18086 Allentown 18087 Allentown 18088 Allentown 18091 Allentown 18092 Allentown 18098 Allentown 18099 Allentown 18101 Allentown 18102 Allentown 18103 Allentown 18104 Allentown 18105 Allentown 18106 Allentown 18109 Allentown 18175 Allentown 18195 Allentown 18201 Scranton 18202 Scranton 18210 Scranton 18211 Allentown 18212 Allentown 18214 Allentown 18216 Allentown 18218 Allentown 18219 Scranton 18220 Allentown 18221 Scranton 18222 Scranton 18223 Scranton 18224 Scranton 18225 Scranton 18229 Allentown 18230 Allentown 18231 Allentown 18232 Allentown 18234 Scranton 18235 Allentown 18237 Allentown 18239 Scranton 18240 Allentown 18241 Allentown 18242 Allentown 18244 Allentown 18245 Allentown 18246 Scranton 18247 Scranton 18248 Allentown 18249 Scranton 18250 Allentown 18251 Scranton 18252 Allentown 18254 Allentown 18255 Allentown 18256 Allentown 18301 Scranton 18302 Scranton 18320 Scranton 18321 Scranton 18322 Allentown 18323 Scranton 18324 Scranton 18325 Scranton 18326 Scranton 18327 Allentown 18328 Scranton 18330 Allentown 18331 Allentown 18332 Scranton 18333 Allentown 18334 Scranton 18335 Scranton 18336 Scranton 18337 Scranton 18340 Scranton 18341 Allentown 18342 Scranton 18343 Allentown 18344 Scranton 18346 Scranton 18347 Scranton 18348 Scranton 18349 Scranton 18350 Scranton 18351 Allentown 18352 Allentown 18353 Allentown 18354 Allentown 18355 Scranton 18356 Allentown 18357 Scranton 18360 Allentown 18370 Scranton 18371 Scranton 18372 Scranton 18373 Scranton 18401 Scranton 18403 Scranton 18405 Scranton 18407 Scranton 18410 Scranton 18411 Scranton 18413 Scranton 18414 Scranton 18415 Scranton 18416 Scranton 18417 Scranton 18419 Scranton 18420 Scranton 18421 Scranton 18424 Scranton 18425 Scranton 18426 Scranton 18427 Scranton 18428 Scranton 18430 Scranton 18431 Scranton 18433 Scranton 18434 Scranton 18435 Scranton 18436 Scranton 18437 Scranton 18438 Scranton 18439 Scranton 18440 Scranton 18441 Scranton 18443 Scranton 18444 Scranton 18445 Scranton 18446 Scranton 18447 Scranton 18448 Scranton 18449 Scranton 18451 Scranton 18452 Scranton 18453 Scranton 18454 Scranton
18455 Scranton 18456 Scranton 18457 Scranton 18458 Scranton 18459 Scranton 18460 Scranton 18461 Scranton 18462 Scranton 18463 Scranton 18464 Scranton 18465 Scranton 18466 Scranton 18469 Scranton 18470 Scranton 18471 Scranton 18472 Scranton 18473 Scranton 18501 Scranton 18502 Scranton 18503 Scranton 18504 Scranton 18505 Scranton 18507 Scranton 18508 Scranton 18509 Scranton 18510 Scranton 18512 Scranton 18514 Scranton 18515 Scranton 18517 Scranton 18518 Scranton 18519 Scranton 18522 Scranton 18540 Scranton 18577 Scranton 18601 Scranton 18602 Scranton 18603 Scranton 18610 Scranton 18611 Williamsport 18612 Scranton 18614 Williamsport 18615 Scranton 18616 Williamsport 18617 Scranton 18618 Scranton 18619 Williamsport 18621 Scranton 18622 Scranton 18623 Scranton 18624 Scranton 18625 Scranton 18626 Williamsport 18627 Scranton 18628 Scranton 18629 Scranton 18630 Scranton 18631 Williamsport 18632 Williamsport 18634 Scranton 18635 Scranton 18636 Scranton 18640 Scranton 18641 Scranton 18642 Scranton 18643 Scranton 18644 Scranton 18651 Scranton 18653 Scranton 18654 Scranton 18655 Scranton 18656 Scranton 18657 Scranton 18660 Scranton 18661 Scranton 18690 Scranton 18701 Scranton 18702 Scranton 18703 Scranton 18704 Scranton 18705 Scranton 18706 Scranton 18707 Scranton 18708 Scranton 18709 Scranton 18710 Scranton 18711 Scranton 18761 Scranton 18762 Scranton 18763 Scranton 18764 Scranton 18765 Scranton 18766 Scranton 18767 Scranton 18768 Scranton 18769 Scranton 18773 Scranton 18774 Scranton 18801 Scranton 18810 Williamsport 18812 Scranton 18813 Scranton 18814 Williamsport 18815 Scranton 18816 Scranton 18817 Williamsport 18818 Scranton 18820 Scranton 18821 Scranton 18822 Scranton 18823 Scranton 18824 Scranton 18825 Scranton 18826 Scranton 18827 Scranton 18828 Scranton 18829 Scranton 18830 Scranton 18831 Williamsport 18832 Williamsport 18833 Williamsport 18834 Scranton 18837 Scranton 18840 Williamsport 18842 Scranton 18843 Scranton 18844 Scranton 18845 Scranton 18846 Scranton 18847 Scranton 18848 Williamsport 18850 Williamsport 18851 Scranton 18853 Scranton 18854 Scranton 18901 Philadelphia 18902 Philadelphia 18910 Philadelphia 18911 Philadelphia 18912 Philadelphia 18913 Philadelphia
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