Home

Residential New Construction (RNC)

1. eecccceeeeeeeeseeeeeeeeeeeeeeeesseneeeeeeeeeeeenences B 9 Figure B 4 Attach the Fan to the Cross Bar cc ceccncceeeeeeeessneeceeeeeeeeeeeeseeneeeeeeeeeeeenees B 10 Figure B 5 Attach Pressure Gauge sscscvicnetivinactncieessnesncesini tiene en eee B 10 Figure B 6 Attaching the Pressure Tubing to the Pressure Gauge B 11 Figure B 7 Connecting Power to the Blower Door Fan ccccceeeceeeeeneeeeeeeeeeeeennneeeeeeeeeeeee B 12 Figure B 8 Fan Direction Switch issicccicncssceenttesoctencexeccesbeussducesdexadddvnadancdtceventadantnudetbevendacansics B 12 Figure B 9 Installing the Duct Blaster 222 c cccceeeeseseceeceeeeeeeeeeeeseeeeeseseeseseeeseneeneneeeeeenees B 14 Figure B 10 Connecting the Pressure Tubing to the Pressure Gauge B 15 Figure B 11 Placing Static Pressure Probe in Supply Register cceeceeeeeseeeeeeeeeeeeeeeeeee B 15 Figure B 12 Connect Red Pressure Tube to Duct Blaster Fan cceceeceeeeesetteeeeeeeeeeeeee B 16 Figure B 13 Connect Controller to Duct Blaster Fano cece eeeeeceeeeeeeeeeeeeenaaeeeeeeeeeeeeeas B 16 Figure B 14 Onset 0 50A CTV B Current TranSQuce tr cccceeeeeeeeeeneeeeeeeeeeeeennttaeeeeeeeeeeee B 18 Figure B 15 Hobo U12 006 4 Channel External LOQQe eeeeeeeeeneeeeeeeeeeeeeeennaeeeeeeeeeeeeee B 18 Figure B 16 Owl 400 Data Logger 22 cc eeecncneeeeeeeeeeeeeeeeeeeeeeeeeeesaeeeeaeeseeeeseesseeeeeeseeeeensees B 20 Figure B 17 Circ
2. Dishwasher Partial Partial Refrigerator Partial Partial Refrigerator Partial Partial Dishwasher Partial Partial Dishwasher Pure Partial Refrigerator Pure Partial Refrigerator Refrigerator Pure Partial Partial Dishwasher Partial Dishwasher Partial Refrigerator Partial Refrigerator Refrigerator Partial Partial Dishwasher CO COTNINININI OPN OINI BR WY AJS Partial Dishwasher Pl wl wl BI HI BIL AINI UJUI wl lwiIrPlnNnin m o Partial Clothes Washer pD m Pure Dishwasher 4 10 Pure Dishwasher 4 No 10 10 Pure 10 10 10 Pure 0 00 Lighting 4 No 10 10 Pure 10 10 10 Pure 0 00 Refrigerator 3 No 10 10 Pure 10 10 10 Pure 0 00 Refrigerator 4 No 10 10 Pure 10 10 10 Pure 0 00 California Public Utilities Commission G 2 February 8 2010 Appliance Question FR1 Status of plans when learned of program Question FR3 Made changes to plans in order to meet program requirements Question FR4 likelihood of purchasing same efficiency level of appliances without program Appendices Appliance Track projects Question FR5 likelihood of purchasing same quantity of efficient appliances without program Initial Free Rider Allocation Question FR6 Agreement that the program was a critica
3. California Public Utilities Commission B 27 February 8 2010 J KEMA Appendices Table B 1 Testo 327 1 Combustion Analyzer Specifications Parameter Range Resolution 02 0 21 0 1 CO 0 4 000 ppm 1 ppm Probe temp 40 F to 932 F 0 1 F Draft 16 H2O 0 001 H2O Diff pressure 80 H2O 0 01 H2O ae 0 CO2 max 0 01 Calculated In addition to the gas flow meter and flue gas analyzer a relay and insulation piercing connector was attached to the gas fuel value to measure the gas flow time Flame on The flame on times was then compared with the times of the call on events as recorded by the existing installed meter The difference between these two times under various firing regimes e g the CPU determined firing rate associated with prior short vs long calls for heat can be used to reduce the furnace operating time as recorded over the entire metering period While the lag time for many furnaces has been published our experience has shown that actual lag times can vary substantially from published values On average the lag times were 144 of published values but they were as long as 183 for one furnace The variation in lag time will make it difficult to convert runtimes to gas use rates One work around is to use the average observed value This value varies from 9 second less to 23 seconds greater For an average cycle time of about 7 minutes the error induced would be up to 5 bu
4. Homes Built under 1995 Standards 44 39 Homes Built under 1998 Standards 42 34 Homes Built under 2001 Standards 59 68 Homes Built under 2005 Standards 63 70 64 48 69 Average Glazing Homes Built under 1995 Standards 18 0 19 0 16 0 17 0 17 0 Homes Built under 1998 Standards 18 0 16 5 18 0 16 8 18 5 Homes Built under 2001 Standards 17 6 16 3 15 6 15 4 15 0 Homes Built under 2005 Standards 16 1 15 7 14 0 13 6 14 1 18 All of the housing characteristics are broken into 5 climate regions instead of 16 CEC climate zones The climate zones were collapsed in to regions because they share similar requirements in Title 24 prescriptive path compliance and because this allows us to keep the sample sizes large enough Using this approach climate zones were aggregated as follows Region 1 encompasses CEC Climate Zones 1 2 3 4 and 5 Region 2 encompasses CEC Climate Zones 6 and 7 Region 3 encompasses CEC Climate Zones 8 9 and 10 Region 4 encompasses CEC Climate Zones 11 12 and 13 Region 5 encompasses CEC Climate Zones 14 15 and 16 California Public Utilities Commission F 6 February 8 2010 J KEMA Appendices Window Types Table F 3 presents the prevalence of vinyl framed dual paned clear and Low E glass windows for single family homes built under the four sets of Standards Although there are other types of windows only these two types are
5. PROBE FOR EXPLANATION IF AP2 2 AND C5A 1 AND C5C lt 4 You said earlier that you became aware of the program after developing your building plans and that your original plans met program requirements but you were unlikely to have built to program requirements in the absence of the program How so PROBE FOR EXPLANATION IF C1 2 OR 3 AND C5C gt 5 You said that your original plans were at or below T24 code but you were likely to have built to program requirements in the absence of the program How so IF C5B 1 AND C5C gt 5 You said that you intentionally developed your plans to meet program requirements but you were likely to have built to program requirements in the absence of the program How so C6 What type of feedback did HMG provide from their review of your original plans California Public Utilities Commission H 13 February 8 2010 J KEMA Appendices C7 Did their feedback cause you to revise your original plans 1 Yes 2 No SKIP TO C11 98 Don t Know SKIP TO C11 99 Refused SKIP TO C11 PROBE FOR EXPLANATION IF C5A 1 AND C7 1 C8A What were the three most significant design changes that you made as a result of HMG s feedback Probe the type of equipment or designs involved CATEGORIZE INTO DESIGN CHANGES 1 2 3 Design Change 1 Design Change 2 Design Change 3 C8B Relative to code by what percentage did all of the revisions alter your original plans For example if the revis
6. Partial Partial O O MOI nI ni ay amp RI _woy nd Pure Partial Pure Partial Pure Partial Pure Pure Pure Pure Pure Pure Pure NIoOoJoJ ojoaju jol AJIAJ NI al rn o Pure Pure California Public Utilities Commission is A G 1 Pure February 8 2010 KEMAX Appendices Table G 2 displays the question responses and calculated values that feed into the NTG estimate for each appliance track project Appliance Question FR1 Status of plans when learned of program Table G 2 Appliance Track Net to Gross Values for Each Project Question FR3 Made changes to plans in order to meet program requirements Question FR4 likelihood of purchasing same efficiency level of appliances without program Appliance Track projects Question FR5 likelihood of purchasing same quantity of efficient appliances without program Initial Free Rider Allocation Question FR6 Agreement that the program was a critical factor in decision Question FR7 Agreement that would have paid full cost without program Question FR8 Agreement that the program was not necessary for purchase Final Free Rider Allocation Dishwasher Dishwasher No 0 Non Partial Partial Refrigerator Non Partial Clothes Washer w Partial Partial
7. Question Question FR4 FR5 Question Question Question Question FR3 likelihood likelihood FR6 Saon FR8 Status of Made of of Agreement Aoreement Agreement changes to purchasing purchasing Initial that the g that the Final Free plans A i that would s Appliance when plans in order same same Free Rider program have paid program Rider NTG to meet efficiency quantity of Allocation was a p was not Allocation learned e a full cost Sf program sah of EA bien without n requirements appliances appliances actor in or program without without decision progim purchase program program Dishwasher 4 No 0 0 Pure 5 0 0 Partial 0 90 Dishwasher 4 Yes 2 0 Non 3 3 3 Partial 0 78 Refrigerator 4 Yes 2 0 Non 3 3 3 Partial 0 78 Clothes Yes Washer 3 6 10 Partial 3 4 5 Partial 0 44 Dishwasher 2 No 6 10 Partial 3 6 4 Partial 0 42 Refrigerator 2 No 6 10 Partial 3 6 4 Partial 0 42 Refrigerator 1 No 7 10 Partial 2 8 3 Partial 0 40 Dishwasher 3 No 10 2 Partial 7 8 4 Partial 0 38 Dishwasher 3 No 8 10 Pure 3 5 7 Partial 0 34 Refrigerator 3 Yes 8 8 Pure 0 8 9 Partial 0 34 Refrigerator 3 No 8 10 Pure 3 5 7 Partial 0 34 Refrigerator 2 No 10 10 Pure 5 5 5 Partial 0 30 Dishwasher 4 No 8 10 Pure 6 7 7 Partial 0 24 Dishwasher 4 No 8 8 Pure 5 10 7 Partial 0 24 Refrigerator 4 No 8 8 Pure 5 10 7 Partial 0 24 Refrigerator 4 No 8 10 Pure 6 7 7 Partial 0 24 Refrigerator 3 No 10 10 Pure 8 3 8 Partial 0 22 Dishwasher 3 No 10 10 Pure 5 8 8 Partial 0 1
8. What aspects of the plan contributed to the design being above below code Probe issues identified in plan check documents also percent glazing water heater efficiency occupancy assumptions What percent above below code were these plans PROBE FOR BEST ESTIMATE ENTER 98 Don t Know 99 Refused Why were the plans above below code Was this original plan consistent with your standard practice for multifamily buildings prior to the HMG plan check 1 Yes 2 No 98 Don t Know 99 Refused ASK IF C5 2 How and why was it different from your standard practice ASK IF C1 1 Before the HMG review did your original plan meet the CMFNC program requirements to exceed code by 15 1 Yes California Public Utilities Commission H 12 February 8 2010 Appendices 2 No 98 Don t Know 99 Refused IF C5a 1 AND C3 lt 15 You said that your original plans met program requirements which are 15 above code but earlier you said that the plans exceeded code by less than 15 Which is correct C5b IF C5a 1 Did you intentionally try to develop your original plans in order to meet program requirements 1 Yes 2 No 98 Don t Know 99 Refused C5c Ona scale of 0 10 how likely would you have been to build this project at or above the program standard 15 above Title 24 code had there been no review and assistance from the CMFNC program RECORD RESPONSE 0 10 98 Don t Know 99 Refused
9. and in the Market Effects report All of these publications are available on http www energydataweb com cpuc default aspx http www energydataweb com cpucFiles topics 7 RNCMarketEffectsPhasel_FinalReportt 05212009 pdf It was not a part of the scope of this project to produce a complete stand alone baseline report We amended Appendix F to refer readers to the various reports that detail different aspects of the baseline results and to include additional data The complete data from the baseline study are available for further analysis for those who wish to pursue it 10 SCE Clarificatio n of Baseline results Question 10 Please provide more detailed information from Baseline study on std practice in RNC including but not limited to how it relates to code compliance how is it applied to C amp S and how is it applied to RNC What are the implications for how the IOUs allocate savings between programs Response 10 The usage of the baseline results in the RNC analysis and in the Codes and Standards analysis are detailed in those volumes We added text to Appendix F that provides an overview to these results and how they were used and refers the reader to the appropriate reports 11 PGE SCE Gross savings Question 11 Can you provide more detail on how error bound was calculated Response 11 The methodology for the calculating the relative precision and error bounds were taken
10. before learning of the program yet you were not likely to have bought the same efficiency of measure without the assistance from the program How so IF FR23 2 AND FR23C 2 AND FR24 lt 8 You said that you did not develop your original plans to qualify for program and you made no changes to your original plans yet you were not likely to have bought the same efficiency of measure without the assistance from the program How so FR25 How likely is it that you would have bought the same quantity of measures if you had not received any assistance from the program Please use the same scale RECORD RESPONSE 0 10 98 Don t Know 99 Refused California Public Utilities Commission H 10 February 8 2010 J KEMA Appendices Now I m going to read several statements about how you came to choose your product type On a scale of 0 to 10 where 0 is strongly disagree and 10 is strongly agree how much do you agree with each statement FR26 The assistance from the program was a critical factor in my decision to purchase the high efficiency product RECORD RESPONSE 0 10 98 Don t Know 99 Refused IF FR26 CONTRADICTS FR24 FR25 Earlier you indicated that you were un likely to have bought the same quantity of measures without assistance from the program but now you say the program was not a critical factor in your decision to purchase the measure How so FR27 If had not had any assistance f
11. ojojo Pure oO NO O OoO ol wl wy o R _a n ATINI Pure oO California Public Utilities Commission is A Pure J 1 February 8 2010 KEMAX Project Appendices Table J 2 Performance Track Net to Gross Values for Each Project Question C5c likelihood to have built to program requirements in absence of program Initial Free Rider Allocation Performance Track Projects Question C16 level of agreement that program was Critical to the decision to build to program requirements Final Free rider Allocation Question c3 estimated percent above code of the original plans Question c7 made changes due to HMG s review Question C8b percent change due to HMG review Non 10 Non 5 Non 10 Non 5 Pure Partial 12 Partial Partial 12 Partial Partial 10 Pure Partial 20 Partial Partial 17 Partial Partial 20 Partial Partial 36 Pure Partial 15 Pure Partial Partial 20 Pure Pure Pure Pure California Public Utilities Commission Pure February 8 2010 Appendices Table J 3 Appliance Track Net to Gross Values for Each Project Appliance Track projects
12. participants and non participants is relatively small and unknown in direction California Public Utilities Commission L 14 February 8 2010
13. 22 cccccceeesesscceeeneneeeeseeeeeeeeeeeneentenes F 9 F 5 Multiple HVAC Systems and Thermostat Types Baseline Results 05 F 10 F 6 Water Heating Baseline Results 0 2 cccccesesesseeccceeeeeeeeeeeeseneeeeeeeeeeeeeeseeeeeseneeeees F 11 F 7 Percent Duct Leakage Baseline Results cc ccceecceceeeeseeneeeeceeeeeeeeeseeeeeneeeereens F 13 G Verification Guided Programs wicccssttaiatccectcicetvxsasevasthiedaeseiannsdacnuctantsnnnansensecanninenrdasaveamicens G 1 G 1 California Multifamily New Homes Net to Gross Resullts ccccceccceeeseeetteees G 1 H California Multifamily New Homes Net to Gross Interview GUide ccccccceceeeeeeeeeeees H 1 Designed for Comfort Onsite Inspection FOrMs ccccccceeeeeeeeeeeeeneeeeeeeeeeeeeeenaaeeeeeeeeeeeeed l 1 J California Multifamily New Homes Detail Tables 20 00 0000 cece ceeeeeeeee eee eeeeeeeeeeeeeeeeeeeeeeenaaaeees J 1 K Baseline Study and RNC Evaluation Recruitment Details eee eeeeeeeeeeeeeeeeeeeeeeeeeeeees K 1 L Public Comments on the Draft Evaluation Report with Responses ccccsccceeeeeeeees L 1 List of Exhibits Figure B 1 Installation of Blower Door Frame eeccccccccceeeeeeeeceeeeeeeeeeeeeeaaeeeeeeeeeeeenenneeeeeeeeeees B 8 Figure B 2 Placement of Green Pressure TUDING 22 ccccceeseseeseecceeeeeeeeeeeeeeeeeeeeeeeeeeeeeices B 9 Figure B 3 Installation of Blower Door Fat
14. Examples of direct inputs include square footage heating and cooling equipment efficiencies and roof and wall insulation values e Default Inputs These values types etc are required MICROPAS inputs including MICROPAS run parameters for which no equivalent direct or indirect survey data value exists Examples of default inputs include slab thickness and thermal performance characteristics e Direct Defaults These are defaults for direct values that are required MICROPAS inputs but for which no value was entered on the survey form missing data Examples of direct defaults include roof insulation wall insulation and HVAC and water heating equipment efficiencies Direct inputs are inserted directly into the MICROPAS input files The methods and sources used to develop default inputs and direct defaults include the use of algorithms and mapping tables the MICROPAS User s Guide consultation with industry experts building department C 2R forms and on site survey data Each input type is used by the RNC Interface to generate the MICROPAS input files E 2 3 Features of the RNC Interface The ability to do batch compliance runs for a large number of sites from outside MICROPAS and to be able to easily extract the results for these runs is critical to performing the runs efficiently The RNC Interface controls the execution of each MICROPAS run then imports the run results into an Access database table automatically as each run is co
15. Instead of allocating resources and budget to study programs that were saving less energy we decided to revise our sample plan Despite the revised sample plan the desired relative precision was achieved on 3 out of the 6 meter to model ratios See Table 3 13 Additionally the two end use climate region combinations with the largest relative precisions were for combinations that contributed the lowest amount of savings to the overall total savings the AC Coastal and Heat Coastal combinations both had small savings compared to total savings reducing the impact of the larger relative precisions So while the effects of revising the sample plan appear to have increased the uncertainty of the results it does not compromise the validity of the results 2 The variation in the metered to modeled ratio hinges on occupant behavior Occupants are not program participants The participants in the program are builders A builder builds a participating home and then sells it Depending on how it is marketed it may or may not be sold to an energy conscious occupant And an energy conscious purchaser may or may not have different behavior on average he she might have average or greater need for heating and cooling services and simply want to reduce his energy costs So the connection between participation and occupant behavior is not a direct one The question is do people who buy homes from participating builders behave differently than people who buy f
16. PG amp E homes from program tracking data was 0 61 kW The gross annual energy savings per unit from tracking data was 259 81 The H factor was calculated as 0 61 258 81 or 0 00233 So to get ex post kWs for PG amp E coastal homes we multiplied the ex post kWh by 0 00233 7 PGE Sample P 1 1 4 Table 1 3 p1 7 Question 7 Why so few PG amp E participants in the study if there were 4500 in the program Response 7 KEMA used all of the participant compliance information from the tracking database in our study so in that sense all PG amp E participants were included in the analysis Based on our original sample plan we were going to meter 170 participant sites and 170 nonparticipant sites KEMA proposed and ED agreed to modify the methodology so that metered to modeled ratios from nonparticipants would be applied to both participants and non participants negating the need for the participant sample Data collection for participants was halted and the sample plan for non participants was revised In the end results for the 31 participant sites that were metered were combined with 131 non participant metered sites 8 PGE Time for review General Comment 8 We would like to thank the ED and its evaluators for their obvious hard work and diligence for their rapid responses to our data requests following the webinar and for their open and thoughtful approach to this study Despite ED s commenda
17. and Heat Pump e AC monitoring relies on data loggers recording average amperage every 20 minutes using current transducers The current draw data are combined with an instantaneous power measurement spot watt taken at the time of the meter installation e Itis then possible to translate these current readings into estimates of annual energy consumption kWh of the air conditioner or heat pump e Fan kWh is estimated by estimating the fraction of each period that the AC is running and multiplying it by the kW input of the fan To inform the run time data with actual power demand a onetime spot power measurement of the condensing unit is taken using a Fluke 31 power meter The air conditioner monitoring approach is to record total condenser run time utilizing the OWL 400 data logger with a 0 2 5 vdc output 50 amp split core current transducer CT This monitoring configuration operates by converting the analog signal of the 50 amp CT to a digital signal usable by the OWL 400 Energy consumption of blower fans for central cooling systems will not be metered explicitly but the fan is assumed to draw constant power during any condenser run period The runtime for air conditioning and heat pump systems will then multiplied by the fan power draw to determine fan energy consumption Cooling runtime for air conditioner and heat pump systems will calculate using the data and equipment performance curves Cooling Runtime was calculated as follows
18. bought the same efficiency level of measures if you had not received any assistance from the program RECORD RESPONSE 0 10 98 Don t Know 99 Refused California Public Utilities Commission H 7 February 8 2010 J KEMA Appendices IF FR1 4 OR 5 AND FR4 lt 8 You said that you already selected or installed the measures before learning of the program yet you were not likely to have bought the same efficiency of measure without the assistance from the program How so IF FR3 2 AND FR3C 2 AND FR4 lt 8 You said that you did not develop your original plans to qualify for program and you made no changes to your original plans yet you were not likely to have bought the same efficiency of measure without the assistance from the program How so FR5 How likely is it that you would have bought the same quantity of measures if you had not received any assistance from the program Please use the same scale RECORD RESPONSE 0 10 98 Don t Know 99 Refused Now I m going to read several statements about how you came to choose your product type Ona scale of 0 to 10 where 0 is strongly disagree and 10 is strongly agree how much do you agree with each statement FR6 The assistance from the program was a critical factor in my decision to purchase the high efficiency product RECORD RESPONSE 0 10 98 Don t Know 99 Refused IF FRE CONTRADICTS FR4 FR85 Earlier you indicated th
19. facing each of the four cardinal directions North East South West and compliance is determined by the run with the smallest margin 10 MICROPAS can be run using full year weather data 365 days or reduced year data 42 days The reduced year run performs only one eighth of the calculations of the full year run Because of the reduced calculation time the reduced year weather data is used for most compliance work Very small differences in results may occur between reduced and full year calculations MICROPAS4 User s Manual 11 For details on the testing procedure please see the RNC 2003 Baseline Study Itron Inc 2004 Residential New Construction baseline Study of Building Characteristics Homes Built after 2001 Codes prepared for PG amp E available from www calmac org California Public Utilities Commission E 4 February 8 2010 J KEMA Appendices F Baseline Study Results The results of the Baseline Study informed the Residential New Construction Evaluation the Codes amp Standards Evaluation and the Residential Market Effects Study described in a separate report No single comprehensive document reporting all the baseline study results is planned Instead the analysis and results are described with the evaluation to which they were applied located in the various volumes of this report The Residential Market Effects Study report is a separate report http Awww energydataweb com cpucFiles topics 7 RNCMarketEffect
20. of a clear resolution to this issue is why KEMA focused its efforts on a Method B as described below Figure B 21 Typical Switch Diagram DualSaver This furnace is capable of the following heating modes Single Stage Factory Setting Modified Two Stage Fixed 5Min Low Stage Auto Time 1 12 Min Low Stage To change from the factory single stage operation adjust the dipswitches on the ignition control as follows Off On Mode LEE kode Dipswitch 5 Min Fixed ia it Stage Delay Dipswiich Note This furnace is designed to be used with a single stage room thermostat Call for Heat Call for Heat Safety Circuit Check Safety Circuit Check Start Furnace Start Furnace in Low Stage in Low Stage Low Heat Blower Low Heat Blower Delay Time 5 Min Delay Time 1 12 Min Gas Valve Switch Gas Valve Switch to 2nd Stage to 2nd Stage Blower Switch to Blower Switch to Hi Heat Operation Hi Heat Operation __T Siat Satisfied _ __T Stat Satisfied Method B DOE Calculations ASHRAE Standard 103 describes a methodology to determine a single stage equivalency for modulating and 2 stage furnaces which will allow different models to be analyzed together For this method we first investigated if all the variables were available to determine estimated consumption and low high stage runtimes Such variables include ratio of blower on time to average burner on time fraction of heating load at reduced fuel input rate operating m
21. presented because together they make up the vast majority of the windows installed in residential new constructions and because they most clearly demonstrate the shift from less efficient to more efficient Low E fenestration practices Table F 3 Distribution of Window Types Detached Single Family Homes Window Types State Region 1 Region2 Region3 Region4 Region5 of panes frame type glass type wide g g 2 2 2 paned Vinyl Clear Glass Homes Built under 1995 Standards 86 91 91 86 82 Homes Built under 1998 Standards 86 99 97 48 97 Homes Built under 2001 Standards 28 28 25 6 3 Homes Built under 2005 Standards 1 10 2 paned Vinyl Low E Homes Built under 1995 Standards 8 1 8 Homes Built under 1998 Standards 7 1 15 Homes Built under 2001 Standards 60 56 70 87 Homes Built under 2005 Standards 93 98 99 90 The percentage of homes built with vinyl framed dual paned clear glass windows decreased dramatically for home built under the 2001 Standards and then fell again under the 2005 Standards compared to homes built under the two previous Standards Coinciding with the decrease in the vinyl framed dual paned clear glass windows is an increase in the percentage of vinyl framed dual paned windows with Low E glass Only 5 of homes statewide built under the 2005 Standards have clear glass windows whereas 95 of homes in California built under the 2005 Sta
22. standards e Radiant barriers The percentage of homes with radiant barriers increased from 2 of homes built under the 1995 standards to 16 of homes built under the 2005 standards e Duct leakage The average duct leakage decreased from 13 5 in homes built under the 1995 standards to 11 4 of homes built under the 2005 standards California Public Utilities Commission F 3 February 8 2010 J KEMA Appendices F 1 Newly Built Single Family Homes over Time Figure F 1 presents the total number of single family homes built in California by year since 1998 Table F 1 shows the number of homes built under the ENERGY STAR Homes program for the same time period Prior to 2004 the CA IOUs worked closely with the EPA to develop California ENERGY STAR Homes specifications The CA IOU s 2004 2005 RNC Programs even incorporated ENERGY STAR in the name of the statewide program ENERGY STAR New Homes Program CESNHP As can be seen in the table below there is significant overlap between the ENERGY STAR New Homes and the IOU Program Participants When reviewing the table it is important to point out that there are inherent lag times in the data presented The CIRB represents permit data which for single family homes can have a lag of 6 months to 2 years before the home is completed typically a 6 month lag is assumed The Whole House Participants row has two different lags represented Between 2002 and 2005 the numbers represent
23. the water temperature and enables the burner to fire when the temperature drops below a pre defined set point Installing an inline gas meter to precisely measure the annual gas consumption of water heaters would not have been cost effective An economical and accurate way to measure the gas consumption is to record annual runtime of the burner The temperature of the water heater flue is an indicator that the burner is firing therefore we logged the temperature of the exhaust flue to give the number of fires and duration of each firing of the hot water burner We developed an approach to measure the temperature of the exhaust flue with help of a negative temperature coefficient NTC thermistor that provides a reliable and consistent indicator of burner run time Hobo Micro Station along with a 0 5 Volt adapter and a voltage divider was used to monitor the temperature of the exhaust flue of the water heater The voltage divider bridge circuit was used to determine the resistance of the G type 10 K ohm 25 C NTC thermistor Rt The balance resistor used with this bridge circuit is a fixed precision 2 2k ohm resistor Rb One end of the thermistor was connected to the ground terminal of the Onset 0 5 Volt Adapter and the other end was connected to the voltage input terminal of the adapter One end of the balance resistor was connected to the Trig Source terminal of the volt adapter Trig Source provides voltage from the logger s battery to
24. to program records the project received the following appliance and or lighting incentives Can you confirm that this information is correct Appliance Type Number of Units Total Incentive PB4 IF PERFORMANCE TRACK According to program records the project received the following performance incentives Can you confirm that this information is correct HSG UNITS TOTAL INCENTIVE HERS RATER INCENTIVE TOTAL ENERGY CONSULTANT INCENTIVE TOTAL PB5 What stage of participation in the CMFNC Program has been completed to date i e installed measures received incentive payments etc California Public Utilities Commission H 3 February 8 2010 J KEMA Appendices PB6 PB7 PB8 What stages in the design and construction process have been completed to date i e building is under construction completed construction occupied etc How many multifamily new construction projects in California have you been involved in since the project ENTER 98 Don t Know 99 Refused Have any of these projects participated in the CMFNC program Other energy efficiency programs Which programs AWARENESS PARTICIPATION AP1 When did you first learn about the CMFNC Program AP2 Did you learn about the program before or after you developed the building plans 1 Before 2 After 98 Don t Know 99 Refused AP3 How did you first learn about the CMFNC Program Where else did yo
25. will be collected for the following 1 Air conditioner condenser unit amps 2 Air conditioner power factor 3 Premise voltage Spot power reading and ambient air temperature from weather station measurements will be taken while on site Two spot power measurements will be taken and the average of the two will be used in the analysis California Public Utilities Commission B 20 February 8 2010 J KEMA Appendices The amperage draw of each central air conditioning condenser unit will logged at the electrical disconnect and will be representative of all power consumed for wall units and the split system outdoor components including compressor condenser fan and controls For split systems this amperage data in conjunction with the instantaneous readings of the unit s voltage and power factor along with nameplate fan power draw are used to calculate kilowatt and kilowatt hour energy use for cooling If multiple air conditioning units are found at a site all units will be summed together to produce the measure of total unit usage B 3 2 Domestic Hot Water End Use Metering B 3 2 1 Gas Storage DHW A storage tank heater maintains a set volume of hot water at a specified temperature at all times regardless of need It operates by releasing hot water from the top of the tank when a hot water tap is turned on To replace that hot water cold water enters at the bottom of the tank ensuring that the tank is always full A thermostat monitors
26. 1 First translate the measured amperage information into an estimate of runtime AMP Average Amp data 20 minute interval OWL Data Oab condenser inlet dry bulb temperature F Hourly Data California Public Utilities Commission C 1 February 8 2010 J KEMA Appendices 2 3 SysCool C x SysEIR EIRARIx 4 ewb evaporator inlet wet bulb temperature F Assumed constant at 67 F Use the DOE 2 Bi Quadratic performance curves for split systems Tonnage nominal system capacity in tons Based on nameplate and matching Cap nominal cooling capacity 12000 Tonnage Btuh EER System efficiency at standard conditions Based on nameplate and matching The EER for each system was determined from the ARI Database of system efficiencies based on the particular condenser and coil match If no match could be found the average EER for that SEER level across all manufacturers was used The EER is the amount of cooling delivered in kBtu h divided by the power input in kW at the standard condition of 95 F Oa and 67 F ew EIRARI 3 412 1 EER The bi quadratic performance curves for cooling delivered and energy input ratio as functions of condenser entering dry bulb temperature odb and evaporator entering wet bulb temperature ewb are presented below 1 191422708 0 01965 e 0 000315625 e 0 0030587499 0 0 0000093333 e 0 0 0000782499 e e 0 0 06818927 0 0222843
27. 1 4 19 3 17 22 5 12 9 13 7 8 9 47 32 21 12 5 11 1 10 5 Table F 7 Percent of Homes by Percent Duct Leakage State Region Region Region Region Region Analysis Parameter Description wide 1 2 3 4 5 Homes Built under 2005 Standards 6 Duct Leakage or Less Greater than 6 to 12 Greater than 12 Duct Leakage California Public Utilities Commission F 14 February 8 2010 KEMAX G G 1 Verification Guided Programs Appendices California Multifamily New Homes Net to Gross Results Table G 1 displays the question responses and calculated values that feed into the NTG estimate for each performance track project Project Table G 1 Performance Track Net to Gross Values for Each Project Question C5c likelihood to have built to program requirements in absence of program Initial Free Rider Allocation Performance Track projects Question C16 level of agreement that program was critical to the decision to build to program requirements Final Free rider Allocation Question Cc3 estimated percent above code of the original plans Question Cc7 made changes due to HMG s review Question C8b percent change due to HMG review 10 5 Yes 20 10 5 Yes 20 Partial 5 Partial 12 Yes 32 Partial Pure Partial Partial Partial Partial Partial Partial
28. 2 31 but only two additional business days were granted 12 18 to 12 22 We are greatly concerned that the ED s own deadlines are being only partially met in the rush to complete If the final results are to be relied on an adequate review period must be provided following the publication of a thorough report which includes all necessary appendices and supporting data to support the findings Response 8 We appreciate the utilities time and effort spent in reviewing and commenting on the draft evaluation reports However ED is working under strict deadlines as set by the Commission and that transferred into the scheduled review period 9 PGE RNC Baseline Study Appendi xF Question 9 The Baseline study consumed hundreds of thousands of evaluation dollars and its results affect the RNC C amp S and other evaluation findings It will be invaluable in planning future RNC efforts and in steering toward the statewide strategic goals Appendix F provides a mere 16 pages of summary information on this important study When will a complete and detailed report on the Baseline be prepared and published California Public Utilities Commission L 5 February 8 2010 KEMAX Appendices SOURCE Subject Section Page Type Comment or Question Response 9 In addition to the RNC report appendix baseline results are included in the body of the RNC volume in the Codes and Standards volume
29. 2 teteetetissecettnctiardstantetsnbelepdes eotad Smee cusedanchat aatiouenapiaddnaatidaacdieed B 7 B 2 1 Whole TIOUSE ei PANO Mast stadncececsaaenradseneenesearasnterinenitetua iaduatunlyatestecea taked sede B 7 B22 Total Duct Leakage Protocol incsccsacitdet tehet cesesieredebaredinieeesieatededeactoeaehieiesac B 13 B 3 End Use Meter Data Collection sucaiscccccicctassccatveceiesdeks bacocsectereanssndescnssieteaeiaanaeneans B 17 B 3 1 Cooling Equipment End Use Metering ceeceeeeeeeeeeeeeeeeeeeetneeeeeeeeeeeees B 17 B 3 2 Domestic Hot Water End Use Metering cceeecceeeeeeeeeeeennnneeeeeeeeeeeee B 21 B 3 3 Heating Equipment End Use Metering cececeeeeeeeeeeeeeeeeenntneeeeeeeeeeeee B 26 C End Use Meter Data Analysis 222 cccceseesesceeccceeeee er seneeneneeeeeeeeesseseeeeesseeeeeenennenesnenees C 1 C 1 End Use Equipment Meter Data ccccccccccccccccecceeceececeeeeeeeeeeeeeseeeeeeeeeseeeseeenaess C 1 C 1 1 Cooling EQuiprment ccccccccccccccececeeecceeeceeeceeeeeeeeeeseneceseeeseeseesseeeseeseaeeneaas C 1 C 1 2 Water Heating Equipment ccccccccccccceccceccceceeeeeeeeeeeeeeeseeeeeeeeeseeseeeeteess C 4 C 1 3 Space Heating End Use Energy siisicesc cectecnscecseeseseatsncnedeetsteeniscsecsesenvtecsseeel C 5 C2 Data SUMIMANY cxecscccesteccancisarthacateatoreccetexsnter errana dan EANN Ean ETEA ENANTA ENEKE EEA kE C 6 D Net Savings Difference of Differences Calculation Methodol
30. 262 5 Wrong Bldg Type 300 3 53 1 157 8 90 2 Wrong Address 324 3 99 2 57 3 168 3 Not a Residence 384 3 178 4 14 1 192 4 Quota Full 253 2 89 2 47 2 117 2 Other 949 8 257 6 243 13 449 8 Completed Phone Survey 1 194 11 438 11 200 11 556 10 Recruited for Visit 588 49 200 46 117 59 271 49 Recruited for Metering 353 30 121 28 65 33 167 30 Metering completed participants and nonparticipants 162 14 56 13 42 21 64 12 Subset of recruited for visit Percent of completed phone survey California Public Utilities Commission K 2 February 8 2010 J KEMA Appendices L Public Comments on the Draft Evaluation Report with Responses Table L 1 Comments on the Draft Report with Responses SOURCE Subject Section Type Comment or Question Page 1 PGE Appliance Question 1 Please explain how the gross savings estimates were adjusted because of difference with savings DEER numbers Response 1 The evaluation team was directed by ED to make sure that savings numbers where applicable conformed to the latest DEER numbers The team searched the DEER database version 2008 2 05 posted December 16 2008 for products with a similar size features and efficiency level to the products eligible for the CMFNH program If a similar DEER model was available we compared the annual electricity and gas usage per unit between DEER and program assumptions The te
31. 29 e e 0 0001171879 e e 0 00105933e 0 0 00014816 0 0 000209999e e e o The results were then translated into power draw by multiplying the energy input ratio by the amount of cooling delivered and converting the units back to Watts from Btu h The equation below incorporates the unit conversion in the determination power draw POWER 0 29308324 SYSEIR SYSCOOL Watts The power expected for a particular system with known efficiency and cooling capacity at any given hour for a particular location is now known California Public Utilities Commission C 2 February 8 2010 J KEMA Appendices 5 6 7 By combining the spot measurements taken at the time of meter installation we can then calculate the expected amperage draw given the local weather conditions V Volts from Spot Watt Data PF Power Factor from Spot Watt Data AMPA POWER V PF If the unit was running for only a portion of the 20 minute interval the average amps divided by the expected amps will yield the percentage of the interval the unit was running at full power Multiplying the percentage by one third of an hour 20 minutes or 1 4 if at 15 min intervals allowed for runtimes to be calculated in units of hours The equation below will be used for this analysis RUNTIME20 AMP AMPA 1 3 Hours The system s energy consumption can then be calculated as the measure energy consumption plus the fan energy consumption T
32. 7 3 MICROPAS7 version 7 3 is the version used to generate the 2005 results for this study The 2001 Standards results were generated using MICROPAS6 version 6 5 E 2 2 Developing MICROPAS Inputs from the On Site Survey Data The on site survey database contains detailed information on HVAC and water heating equipment and building envelope characteristics Some of these data were taken directly out of the database and written to the MICROPAS input file However the on site survey did not e Assembly Bill 970 is a measure passed by the California State Legislature in January 2001 Contractor s Report 2001 Update Assembly Bill 970 CEC Volume 1 Summary November 2000 California Public Utilities Commission E 2 February 8 2010 J KEMA Appendices collect all of the information needed to create a valid MICROPAS input file Where possible changes were made to the survey instrument for Project Year 2 2001 and Project Year 3 2003 to collect additional information in order to limit the number of defaults required Even with the changes some of the information needed to create the input file was not able to be collected at some sites or had to be manipulated in order to be utilized in the MICROPAS run As such the transformation of survey data to MICROPAS inputs can be characterized in the following three categories e Direct Inputs These values types etc are mapped directly from the survey database into the MICROPAS input file
33. 8 Dishwasher 1 No 10 10 Pure 3 10 10 Partial 0 14 California Public Utilities Commission J 1 February 8 2010 Appliance Question FR1 Status of plans when learned of program Question FR3 Made changes to plans in order to meet program requirements Question FR4 likelihood of purchasing same efficiency level of appliances without program Appendices Appliance Track projects Question FR5 likelihood of purchasing same quantity of efficient appliances without program Initial Free Rider Allocation Question FR6 Agreement that the program was a critical factor in decision Question FR7 Agreement that would have paid full cost without program Question FR8 Agreement that the program was not necessary for purchase Final Free Rider Allocation Clothes Washer No 10 10 10 10 10 Dishwasher No 10 10 10 10 10 Dishwasher No 10 10 10 10 10 Lighting No 10 10 10 10 10 Refrigerator No 10 10 10 10 10 Refrigerator No 10 10 10 10 10 Refrigerator No 10 10 10 10 10 Refrigerator ww AJAJAJA A No California Public Utilities Commission 10 10 J 2 5 9 10 February 8 2010 J KEMA Appendices K Baseline Stu
34. Development Information Age and Number of Residents Number of residents home during the day time 2 HVAC and Ventilation Systems a Primary Heating and Cooling Systems California Public Utilities Commission B 1 February 8 2010 b c Appendices i System type central room unit hydronic etc ii Equipment type split packaged heat pump furnace baseboard etc iii Manufacturer iv Model number Indoor and Outdoor for split systems v Cooling capacity vi Cooling efficiency SEER and EER vii TXV thermostatic expansion valve or non TXV viii Refrigerant Type R 22 R 410a ix Heating capacity kBtuh x Heating efficiency AFUE HSPF or COP xi Evaporative cooling xii Supply fan type CV two speed ECM VSD xiii Presence of whole house fan Smart Vent Economizer mechanical ventilation xiv Indoor fan motor HP if available HVAC Schedules for each system i Thermostat Manufacturer Type ii Thermostat Model Number iii Thermostat set points for heating and cooling during occupied and unoccupied periods Duct Systems i Location of Ducts ii Location of Registers California Public Utilities Commission B 2 February 8 2010 J KEMA Appendices iii Duct Types iv Duct Sealant Types v Insulation R Value vi Duct and Plenum Condition vii Total duct leakage duct blaster test 3 Envelope Characteristics a Exterior Walls i Exterior wall construction Type ii Surface T
35. E Sample Pg 1 11 Question 19 The report states that the reduced savings did not justify the level of rigor that had originally size been planned for the evaluation and the CPUC ED approved calling a halt to participant on sites after only 33 on sites out of the original 170 planned participants This seems like an arbitrary approach to arriving at a final sample size particularly given that the participant samples for SCE were either a 1 or 0 with an original sample target of 45 We would have expected that the evaluation team would have developed a new sampling plan with a reasonable sample size for each IOU rather than accepting a sample size arrived at based on an arbitrary date in time How is this defensible based on the M amp E protocols and standards of good judgment and best practice in the program evaluation field At the very least we feel that there should be notations in the report that explain how the sample you arrived at impacts the reliability and validity of the findings Response 19 The only planned purpose for the participant metered data in the analysis was to calculate participant metered to modeled ratios All participant modeled information was available from program records Once the decision was made to use the non participant ratios for both participants and non participants the sample design for the metered participant sample became moot It is not necessary to have a statistically representative sample for da
36. Figure F 3 AFUE Distribution Average Statewide Homes Built Under Homes Built Under Homes Built Under Homes Built Under 1995 Standards 1998 Standards 2001 Standards 2005 Standards m gt 90 AFUE E gt 80 and lt 90 AFUE E gt 78 and lt 80 AFUE F 4 Space Cooling System Baseline Results Results for cooling system efficiencies are presented in Table F 5 for detached single family homes As can be seen the average SEER increased significantly for homes built under the 2005 Standards and all regional averages are now greater than 13 SEER This is due to the Federal regulation stating that all air conditioning units manufactured after January 2006 must have a SEER of at least 13 Table F 5 Average SEER Region Region Region Region Region Analysis Parameter Description Statewide 1 2 3 4 5 Average Efficiency SEER Homes Built under 1995 Standards Homes Built under 1998 Standards Homes Built under 2001 Standards Homes Built under 2005 Standards California Public Utilities Commission F 9 February 8 2010 J KEMA Appendices Figure F 4 illustrates the distribution of efficiency levels for air conditioning units statewide When comparing the distribution to the minimum SEER levels available at the time approximately half of the homes built under any given Standard are installing the minimum allowable SEER level Figure F 4 SEER Distribution Average Statewide Homes Built Under Homes Built Unde
37. IANCE 1 and APPLIANCE 2 you installed through the program APPLIANCE 1 FR1 At the time that you first heard about the assistance from the program for measure had you READ LIST California Public Utilities Commission H 6 February 8 2010 J KEMA Appendices Not done any research on product type Already been thinking about purchasing product type Already begun collecting information about product type Already selected the measure you were going to get Already installed the energy efficient measure SKIP TO FR21 DON T READ Other 98 DON T READ Don t Know 99 DON T READ Refused oahwNnh FR3 Did you have to make any changes to your existing plans for product type in order to receive this assistance through the program 1 Yes 2 No SKIP TO FR3C 98 Don t Know SKIP TO FR3C 99 Refused SKIP TO FR3C FR3B How did your plans change FR3C IF FR3 2 98 99 Did you intentionally develop your original plans for product type in order to meet program requirements 1 Yes 2 No 98 Don t Know 99 Refused IF FR1 4 OR 5 AND FR3C 1 You said that you had already selected or installed the measures before learning of the program yet you intentionally developed the original plans in order to meet program requirements How so FR4 Ona 0 to 10 scale with 0 being not at all likely and 10 being very likely how likely is it that you would have
38. Participants Home Market Territories Homes 1998 38 93 585 94 236 1999 612 100 800 101 615 2000 567 104 673 105 546 2001 1 563 105 727 106 498 2002 6 450 1 043 0 8 122 741 123 815 2003 15 291 5 807 4 2 137 407 138 706 2004 14 455 13 461 9 0 149 676 151 332 2005 18 956 17 652 11 5 153 667 155 222 2006 18 534 419 0 4 106 479 107 939 2007 6 365 1 226 1 8 67 645 68 348 2008 5 381 3 947 12 1 32 664 33 204 Data represents new permits Construction Industry Research Board CIRB For 2006 2008 PY only completed units are reported In prior Program years it was the practice to include completed and committed units in the annual reports California Public Utilities Commission F 5 February 8 2010 J KEMA Appendices F 2 Fenestration Baseline Results Percent Glazing Percent glazing refers to the total glazing area of a home expressed as a percent of the total conditioned floor area Average percent glazing values are presented in Table F 2 by region As can be seen the average percentage of glazing has decreased in all regions for homes built under the 2001 and again for homes built under the 2005 Standards A lower percentage glazing allows less solar heat gains and less heat loss and is therefore more compliant with the Standards Table F 2 Percent Glazing Analysis Parameter Description Statewide Region1 Region2 Region3 Region4 Region 5 Percentage of Higher Performance Glazing
39. Percent Duct Leakage Baseline Results Duct blaster tests to determine duct leakage rates were conducted for a sub sample of the sites surveyed for homes built under the 1995 1998 and 2005 Standards They were not performed on homes built under the 2001 Standards An estimate of percent duct leakage requires that the total supply fan system flow rate be known Percent duct leakage is the ratio of the measured duct leakage rate over the total supply fan system flow rate The percent of duct leakage decreased between homes built under the 1998 Standards and the 2005 Standards in all regions except for region 5 Test results are contained in Table F 6 which presents the average percent duct leakage by region The percent duct leakage decreased statewide and in most regions between the homes built under the 1998 and 2005 Standards Of the homes duct tested in the most recent round of on sites one fifth had leakage of 6 or less California Public Utilities Commission F 13 February 8 2010 Appendices Table F 6 Average Percent Duct Leakage State Region Region Region Region Region Analysis Parameter Description wide 1 2 3 4 5 Homes Built under 1995 Standards Number of Sites Average Duct Leakage valid tests Homes Built under 1998 Standards Number of Sites Average Duct Leakage valid tests Homes Built under 2005 Standards Number of Sites Average Duct Leakage valid tests 16 19 9 14 15 4 19 20 7 11 7 1
40. Residential New Construction RNC Programs Impact Evaluation Appendices to Volume I California Investor Owned Utilities Residential New Construction Program Evaluation for Program Years 2006 2008 Final Evaluation Report Prepared by KEMA Inc The Cadmus Group Inc Itron Inc Nexus Market Research Inc Prepared for California Public Utilities Commission Energy Division February 8 2010 Experience you can trust Experience you can trust KEMAX Appendices Table of Contents A Calculation of Adjusted Tracking Savings Estimates cceeeseeeeeeeeeeeeeennneeeeeeeeeeeeeneea A 1 A 1 Orientation Adjustments ais sates oceccneta saci coeedtaniuetcntesdncghehmndpd seal snduseoetbinielsiaalitealitmadadats A 1 A 2 Ratio Estimation and B RaAV OSs eresscscsntictccnrncssastrarannanenteceeeneiusacutldneishatanyciadatnbuetmaesaes A 1 A3 Summary of Results caste Ste ccd genset aa a Aa aaan aa aga coated cade cde taints A 2 A 4 Interpretation and COnclUuSiOns ceeeeceeeeeee cece eeeeeeeeeeeeeeeeeeeeeeeeeseeeeeeeeeeeeeeeeeees A 2 A 5 Single Family Adjusted Gross Energy Savings cccceceeeeseneeeeeeeeeeeeeeeneneeeeeeeeees A 3 B Residential New Construction Onsite Data Collection ee eeeeeeeeeeeeeeeeeeeenntnaeeeeeeeeeeee B 1 B 1 Building Characteristics ce i etadosn caer tSeeed veveh a ater neveridgpacatendeicenndeanedlenbsadectdeecsietdanbtdechetnd B 1 B 2 Performance Testing 2
41. The California Evaluation Framework Prepared for the California Public Utilities Commission and the Project Advisory Group California Public Utilities Commission A 2 February 8 2010 J KEMA Appendices energy orientation Even greater energy savings could be achieved by orienting homes to their best orientation or by selecting designs specific to the orientation of the site This is nota new discovery as the advantages of passive solar design and home orientation have been known for centuries but the orientation adjustment b ratios based on analysis of thousands of homes provide a quantitative estimate of the energy cost to builders of ignoring orientation Conversely water heating orientation b ratios are 1 0 since the orientation of a home does not impact modeled energy water heating usage A 5 Single Family Adjusted Gross Energy Savings B ratios were multiplied by gross savings from CalCERTS tracking data to arrive at the Orientation Adjusted Tracking Savings The overall impact of the orientation adjustment on gross tracking savings is presented in Table A 2 Gross tracking savings from the raw data for which savings estimates could be obtained increases by 6 42 as a result of the adjustment We multiplied the CalCERTS portion of gross savings by the b ratios for orientation adjustments to arrive at the orientation adjusted gross savings Table A 2 Single Family Tracking Savings and Orientation Adjusted Savin
42. This difference is positive for most comparison groups for heating cooling and water heating indicating positive savings in most climate zones California Public Utilities Commission D 4 February 8 2010 J KEMA Appendices E The RNC Interface E 1 Introduction This section briefly describes the development and testing of the RNC Interface The RNC Interface was first developed in 2000 during the first year of the Statewide RNC Baseline Study The primary purpose of the RNC Interface is to generate MICROPAS compliance runs which are then used to examine the compliance status for each residential building and to explore the energy conservation potential of some key energy saving technologies Since the RNC Interface was initially developed it has been updated and upgraded during the two subsequent RNC Baseline studies and for various other work relating to California s Title 24 Low Rise Residential Energy Standards the California ENERGY STAR New Homes Program and the statewide energy savings potential in constructing more energy efficient residential buildings E 2 Overview of the RNC Interface The RNC Interface uses the data collected from on site surveys to create a MICROPAS input file This is accomplished by interpreting the on site survey data then writing it to a file in the required MICROPAS input format The RNC Interface then passes the input file to MICROPAS Then it runs a MICROPAS simulation and stores the simu
43. Under Homes Built Under Homes Built Under 1995 Standards 1998 Standards 2001 Standards 2005 Standards m Statewide Region 1 Region 2 m Region 3 m Region 4 m Region 5 Figure F 7 presents the percentage of homes with multiple water heating units which increased for homes built under the 2005 Standards Approximately two thirds of the homes with more than one water heater have instantaneous water heaters Region 2 has the highest percentage of homes with multiple water heating units Figure F 7 Homes with More than One Water Heating Unit Homes Built Under Homes Built Under Homes Built Under 1995 Standards 1998 Standards 2005 Standards Statewide Region 1 Region 2 Region3 Region 4 Region 5 California Public Utilities Commission F 12 February 8 2010 J KEMA Appendices Radiant Barriers Figure F 8 presents the percentage of homes with radiant barriers for homes built under the four sets of Standards For homes built under the 2005 Standards Region 5 had the greatest percentage of homes with radiant barriers with radiant barriers being present in one fourth of the homes Statewide 16 of home built under the 2005 Standards has radiant barriers Figure F 8 Percentage of Homes with Radiant Barriers Homes Built Under Homes Built Under Homes Built Under Homes Built Under 1995 Standards 1998 Standards 2001 Standards 2005 Standards Statewide Region1 Region2 Region3 Region 5 F 7
44. am found similar DEER models only for clothes washers and refrigerators where DEER savings values were higher and lower respectively The team believes these discrepancies are due to the fact that HMG developed program assumptions using an earlier version of the DEER database Next the team multiplied the difference in energy savings per unit by the number of incentivized units There was a net decrease in gross program savings because the program incentivized many more refrigerators than clothes washers 2 PGE Explanatio Table 1 Question 2 Ex post KWh realization rates are shown Table 1 7 to range from 1 5 to 4 67 Given that n of 7 the KWh metered to modeled ratios Table 3 9 only range from 1 06 to 1 4 can the results evaluators explain why the realization rates are so high We expect that this ties into the baseline study However the baseline study is so briefly documented that we are unable to confirm or deny this assumption Response 2 While the metered to modeled ratios influence the final realization rates they are not directly associated with each other So the fact that the ranges of values between the realization rates and the metered to modeled ratios are fairly different is not an issue There are a number of possible explanations for the high realization rates The metered to modeled ratios for kWh are greater than 1 This indicates that the Micropas models are California Public Utilities Co
45. an accurate comparison with the modeled usages In light of this weather normalization techniques were developed for the heating and cooling end uses to fill in the missing data for loggers with less than a year of recorded usage To calculate a year of data a regression analysis was done based on the average daily temperature and daily kBtu Heating Degree Days HDD were calculated using the reference temperature of 65 degrees F and were used in the regression against kBtu Daily total usage for the missing data was estimated using the equation below or similar form thereof where BO and 61 are constants based on the regression analysis BO is the average daily baseline usage and 61 is the temperature response of temperature dependant heating usage Daily Total Usage site Bo 61 HDD California Public Utilities Commission C 5 February 8 2010 J KEMA Appendices The predicted Average Daily Usages were combined with the actual Average Daily Usage to create a full year of daily usage for each site For the meter adjustment factor estimation these daily usages were aggregated into annual kBtu heating usages for the 365 days following the meter installation date C 1 3 2 Heat Pump There were no Heat Pumps in the meter data sample so no methodology was developed or used C 1 3 3 Hydronic Heating System The data analysis developed a methodology to determine if hot water usage was attributed to the space heating or domestic hot w
46. ant weighted average Compliance Margin N np x Sm SF i l These compliance margins were computed and compared separately for each CEC climate zone The savings from each climate zone were then aggregated for each end use What is the justification for equation 2 The Total Savings of the participant homes above standard must equal the sum of the savings of each individual home or N Savings of the participant homes above standard DS F Jol 5 i l Is this equal to equation 2 Is Np N SFp Sp CM p J 8 P SF i l By substitution into 2 N N N 2 SF 2 Sy i SF 2 S A JSF Savings of participant homes above Standard N el r N T 285 2o i l i l N DVS P SF SO yes i l Similarly equation 3 is derived and the difference between the two sums in 4 is justified as the Net Savings The non participant weighted average Compliance Margin is also weighted by conditioned floor area of each home California Public Utilities Commission D 3 February 8 2010 J KEMA Appendices Comparisons for compliance margins were done CEC to CEC climate zone For example participants from CEC climate zone 2 were compared to non participants from CEC climate zones 2 The difference in the compliance margins between the participant and the non participant homes is the key factor driving estimated savings using the difference of differences methodology
47. at you were un likely to have bought the same quantity of measures without assistance from the program but now you say the program was not a critical factor in your decision to purchase the measure How so FR7 IfI had not had any assistance from the program would have paid the additional amount of program incentive subsidy to buy the measure on my own RECORD RESPONSE 0 10 98 Don t Know California Public Utilities Commission H 8 February 8 2010 J KEMA Appendices 99 Refused IF FR7 CONTRADICTS FR4 FR5 Earlier you indicated that you were un likely to have bought the same quantity of measures without assistance from the program but now you say you would not have paid the additional incentive to buy the measure How so FR8 At the time bought my new product type the assistance from the program was not necessary to persuade me to purchase the higher efficiency product RECORD RESPONSE 0 10 98 Don t Know 99 Refused IF FR8 CONTRADICTS FR4 FR5 Earlier you indicated that you were un likely to have bought the same quantity of measures without assistance from the program but now you say the program was not necessary to persuade you to buy the measure How so APPLIANCE 2 FR21 At the time that you first heard about the assistance from the program for measure had you READ LIST Not done any research on product type Already been thinking abou
48. ater end uses Hydronic Separation Methodology Note Only one site was identified as having a hydronic heating system Additionally there was an issue with the site data that failed to pass the QC standards set for the analysis Subsequently the site was dropped C 2 Data Summary The actual number of each type of system and the status and quality of the data obtained are described in the following tables As mentioned previously single family homes used the same metering approach for the three end uses at every site Table C 1 below describes the number of installed loggers for each end use and the status of the data obtained Table C 1 Single Family Metering Summary Installed Bad Used in Unit Type Retrived Missing Analysis AC 142 Furnace 96 DHW 57 There were a few reasons that sites were removed from the end use analysis A handful of loggers appeared to contain corrupt or incorrect data A few appeared to be improperly installed or configured Another QC measure was based on the system tracking data If a site appeared to contain multiple units AC or Furnace but there were fewer loggers than systems the entire California Public Utilities Commission C 6 February 8 2010 J KEMA Appendices site had to be removed in order to ensure that the level of usage in the metered data was consistent with the estimated model usage It should be noted that the necessity of removing a site from one of the end use analyses do
49. ators have enough confidence in the H factors used for the CPUC to rely upon the results Response 6 Under the original sample plan the size of the metered participant sample would have been large enough to conduct an independent verification of kW savings Unfortunately with the reduction in the sample size of metered participants homes for reasons detailed in the report this was not possible Instead KEMA used a simplified approach called the H factor approach This approach has been used in previous studies where kW verification was not a goal of the study The H factor approach is quite simple KEMA used utility California Public Utilities Commission L 3 February 8 2010 KEMAX Appendices SOURCE Subject Section Page Type Comment or Question tracking data for gross per unit kWh and gross per unit kW to calculate the ratio of kW to kWh that was assumed by the utilities for their program planning These ratios are called H factors KEMA then estimated ex post net kW savings by applying these H factors to the ex post net energy savings value This method does not provide any independent verification of actual kW savings It is only as accurate as the IOU ex ante calculations were and only adheres to the definition of demand reduction definition in DEER to the extent that the IOU claimed savings did For example the gross coincident peak demand reduction per unit for coastal
50. be collected for all exterior lights i Fixture type ii Fixture wattage iii Control strategy 5 Appliances and Other Equipment a Hot Water Heaters i Type storage instantaneous heat pump ii Manufacturer iii Model number iv Tank capacity v Input kBtuh gas kW electric vi Fuel type vii Location vili Insulation Jacket ix Insulation on pipes x Presence of hot water reclaim xi Efficiency California Public Utilities Commission B 5 February 8 2010 J KEMA Appendices b c d xii Low flow fixtures xiii Temperature settings low medium high xiv Recirculation control type and pump HP Refrigerators and Freezers i Manufacturer ii Model Number iii Configuration top mount freezer side by side etc iv Location conditioned unconditioned space v Volume vi Age vii Energy Star viii Presence of through the door water or ice ix Automatic ice maker x Energy Factor ft3 kWh day Dishwasher i Manufacturer ii Model Number iii Energy Star iv Builder Installed Purchased New Installed Used Clothes Washer Dryer i Manufacturer ii Model Number California Public Utilities Commission B 6 February 8 2010 J KEMA Appendices iii Energy Star iv Builder Installed Purchased New Installed Used v Axis Type Fuel Type e Oven Range Pool Spa Heater i Fuel Type f Pool Pump i HP ii Speed g Number of televisions and size and number of comp
51. ble efforts the very abbreviated two week review period was wholly inadequate to complete a meaningful review of the evaluation The time was only adequate to read the reports and ask questions It became California Public Utilities Commission L 4 February 8 2010 KEMAX Appendices SOURCE Subject Section Page Type Comment or Question apparent the report left out much of the important explanation and data that would be needed for that purpose The abbreviated review time forces hurried data requests and though the ED responded with admirable swiftness there was hardly time to digest and sift through the numbers provided before these comments were due to be filed In addition we are left with the distinct impression that the evaluators are still scrambling to complete their findings An e mail from Ms Osman on Dec 15th indicated that the NRNC whole building analysis had been found to have errors requiring that the models be re run This occurred during the final review period mere days before the comment period was set to close As of COB Dec 18th the results of this re analysis were still unpublished Meanwhile additional appendix material was only first made available by that date Comments were due a mere two working days later and given our own requirements for the review of those comments there was virtually no opportunity to review these late posted materials PG amp E requested a time extension to 1
52. cts 1 by facilitating construction that is more efficient than required by the current code and 2 by improving compliance with existing code a third way is by contributing to code upgrades Delphi panels of Title 24 12 KEMA Nexus Market Research Inc Summit Blue Consulting Itron Inc The Cadmus Group Inc 2009 Phase Report Residential New Construction Single Family Home Market Effects Study Available at http www energydataweb com cpuc default aspx 13 Residential New Construction Study RER 2001 for details of the sample design California Public Utilities Commission F 1 February 8 2010 J KEMA Appendices Consultants and building industry experts will be used to estimate the proportion of gross savings attributable to the IOU programs i e net savings Phase II is expected to be completed in Spring of 2010 Codes amp Standards The RNC baseline study carried out onsite surveys of program participant and non participant homes The site survey information of 194 non participant samples was provided to C amp S to be used in comparative energy software modeling to derive compliance rates A subset of this population was used to compare Title 24 compliance as permitted vs as built The sample of 194 was also part of a lighting survey which was used to derive compliance rates for the residential hardwire lighting building standard Detailed information on how the baseline study results were used in the C amp S eval
53. dices Data Logger Properties e U12 4 External Channel Logger accepts a wide range of external sensors including temperature AC current AC voltage CO2 4 20mA and 0 2 5 VDC 12 bit resolution provides great data accuracy e One channel will be used for real time amp monitoring of the AC unit Installation Procedure e Connect the CT to channel 1 of the logger e Open up the CT and slip in the CT in one leg of the HVAC unit Select the leg that includes supply condenser fan e Logger will launch using delay launch settings set in the office before bringing to the field 5 OWL 400 Data Logger Data Logger Properties e These loggers combine with a 50A current transducer to measure AC current e To setup the Owl 400 data logger you must have ACR trend reader software installed and running on your computer e Used in conjunction with either Hobo Micro Station or Hobo Temperature loggers California Public Utilities Commission B 19 February 8 2010 J KEMA Appendices Figure B 16 Owl 400 Data Logger Installation Procedure 1 First make sure that the secondary end of the Sentran current transducer is plugged into the data port of OWL400 2 Open up the split core CT and slip in the CT in one leg of the HVAC unit Select the leg that includes supply condenser fan 3 Logger will launch using delay launch settings set in the office before bringing to the field Additionally one time hand recorded field measurements
54. dy and RNC Evaluation Recruitment Details We took a number of measures to minimize the potential for systematic biases in who had the opportunity willingness to be metered visited for on site surveys Recruitment efforts were conducted using a Computer Aided Telephone Interview CATI system We attempted to contact a household multiple times over different times of the day up until 8 pm different days of the week including weekends and different weeks of the recruiting periods In addition we offered incentives of 50 and 10 to the occupants in order to overcome any lack of interest on their part thus making it less likely we would only attract a biased subset of respondents Detailed disposition codes were updated after each attempted contact The final disposition of the sample is shown in Table K 1 California Public Utilities Commission K 14 February 8 2010 Appendices Table K 1 RNC Site Recruitment Sample Disposition Total Sample PG amp E SDG amp E SCE and SCG Number of of Number of of Number of of Number of of Households Sample Households Sample Households Sample Households Sample Total Sample Sent 11 287 3 971 1 898 5 418 Max Attempts 3 103 27 1 059 27 611 32 1 433 26 Refuse 1 633 14 546 14 317 17 770 14 Unobtainable 1 285 11 412 10 143 8 730 13 Designated Respondent Not Available 1 372 12 670 17 51 3 651 12 Language 490 4 170 4 58 3
55. e estimates which are created by the program managers and utilities to estimate site level savings during implementation are used to estimate program savings These are un verified inaccurate estimates The entire point of doing the evaluation was to verify the program savings and provide a method to adjust the ex ante estimates to better reflect real world savings If anything the finding that the ex ante estimates do not accurately reflect actual savings demonstrates the need for the study 22 SDGE S_ Participant Question 22 1 Samples sizes are extremely small which raises the question of whether any real CG Non Part inference can be drawn about the population This issue is heightened when small state Behaviors level sample sizes are used to make inferences about specific utility service territories and or specific climate zones Moreover because the study was forced to reduce the sample size due to the economic downturn the target precision for the meter to model ratios were significantly reduced Specifically the original plan prior to the reduction in sample size called for target precision for the calculation of meter to model ratios of 25 at the 90 level of confidence 90 25 However due to the small actual sample sizes the achieved level of precision for the meter to model ratio was only 70 to 18 at the 90 confidence level Thus the small sample sizes added a significant amount of uncertainty to the meter to model rati
56. e population such that y Bx In statistical jargon the ratio model is a usually heteroscedastic regression model with zero intercept Beta 8 is referred to as a b ratio In the case of orientation adjustment B is the sum of all homes average orientation energy savings divided by the sum all homes worst orientation energy savings within a stratum A thorough description of ratio estimation can be found in the 2004 California Evaluation Framework The orientation adjustments are based on a sample size of over 5 500 single family homes from the CHEERS registry A 3 Summary of Results Orientation adjustment results are presented in Table A 1 Table A 1 B ratios for Orientation Adjustments Sa Heating Cooling Coastal 1 11 1 28 Desert 1 16 1 06 Inland 1 14 1 29 B ratios less than one indicate less energy savings than computed from the tracking data while b ratios greater than one yield increased savings All of the B ratios were greater then one implying that the worst orientation reports less savings then the average orientations used in the CHEERS registry A 4 Interpretation and Conclusions These findings although not the focus of this report are very significant For example the orientation results show that inland energy savings can be increased by 29 for space cooling and 14 for space heating by orienting a home from its worst energy orientation to its average TecMarket Works 2004
57. e program Extremely dissatisfied Dissatisfied Neither satisfied nor dissatisfied Satisfied Extremely satisfied oan S7 IF PERFORMANCE TRACK Why do you say that S8 Taking everything into consideration how satisfied are you overall with the CMFNC Program California Public Utilities Commission H 5 February 8 2010 Appendices a Extremely dissatisfied b Dissatisfied c Neither satisfied nor dissatisfied d Satisfied e Extremely satisfied S9 Why do you say that APPLIANCE FREERIDERSHIP FOR PROJECTS WITH APPLIANCE INCENTIVES PRODUCT TYPE MEASURE Program Energy ASSISTANCE Criteria Efficiency Criteria Dishwasher ENERGY STAR CEE Tier 1 EF gt 0 65 30 unit Fed Std EF 0 46 dishwasher CEE Tier 2 EF gt 0 68 50 unit Clothes washer ENERGY STAR CEE Tier 2 MEF gt 2 0 35 unit Fed Std MEF 1 26 clothes washer WF lt 6 0 CEE Tier 3 MEF gt 2 2 75 unit WF lt 4 5 Refrigerator ENERGY STAR ENERGY Exceed Fed Std 50 unit refrigerator STAR by 20 Clothes dryer Natural Gas clothes Include 50 unit dryer moisture sensor Hard wired interior High efficacy hard Exceed T24 10 fixture light fixture w control wired interior light requirements fixture w control Randomly select up to two appliances for this section We will monitor completed interviews to ensure that all appliances are reasonably represented would like to ask you some questions about the APPL
58. eeeeeeeeeeeeeeeeeeeennneeeeeeeeeeeeae F 13 Table A 1 B ratios for Orientation Adjustments ccc cece eee eeeeeeeeeeeeeeeeeeeeeneeeeeeeeeeeeeeeeaaaaees A 2 Table A 2 Single Family Tracking Savings and Orientation Adjusted SavingsS 000 A 3 Table B 1 Testo 327 1 Combustion Analyzer Specifications ccceeeeceeeeeeeeeeeeeeeeeeeennaaes B 28 Table C 1 Single Family Metering Summary cccececeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeaeeeeeeeeeneeeaaaeees C 6 Table F 1 California Single Family Home Construction and Participation 0 eee F 5 Table F 2 Percent Glazing raisin ss saccccsenfozan saccuocttnectaascancssaiigesac eeiqsseanticectaediaaydascuueadsceadassaytenaes F 6 Table F 3 Distribution of Window Types Detached Single Family Homes eee F 7 Table F 4 Central Gas Space Heating System Efficiency c ccceeceeeeceeeeeeeeeeeeeeeeeeeeenaaeees F 8 Table F 5 Average SEER esac acesdee nani capaiseraaentecenetnadhdedinntcun eraeeetuanenadtateestetdaaatiyatiieneetiarat wieamecnets F 9 Table F 6 Average Percent Duct Leakage 2 cccceceeeeeeeeeeeeeeeeeeeeenenneeeeneeeeeeeseeeneneenenes F 14 WOAH HT n a E E E a A emia cartes rte ee F 14 Table G 1 Performance Track Net to Gross Values for Each Project G 1 Table G 2 Appliance Track Net to Gross Values for Each Project 0 eeeeeeeeeeeeeees G 2 Table J 1 Performance Track Net to Gross Values for Each Pro
59. ems with installed units Yes No 1 22 Comments if 1 21 is yes California Public Utilities Commission l 2 February 8 2010 CPUC DFC Onsite Verification Survey Form Heating and Cooling System Data 2 11 Enter type unit Packaged at Pepperwood ASHP at MiraVista 2 12 Matches Manufacturer s data Y N 2 13 Indication of Recent Service Y N 2 14 If Yes Date of recent service mm dd yyyy 2 15 of visible duct work not sealed 2 16 Programmable Thermostat Y N 2 17 Occupant controlled thermostat Y N 2 18 Thermostat setting heat F 2 19 Thermostat setting cool F 2 20 Hot air output Y N 2 21 Cool air output Y N 2 22 Unusual Sounds Y N 2 23 of wall grille area obstructed MiraVista only 2 24 of inadequate wall seal around packaged unit Pepperwood 2 25 Thermostat location Describe Comments California Public Utilities Commission l 3 February 8 2010 CPUC DFC Onsite Verification Survey Form Unit Water Heating Data 3 11 inadequate visible pipe insulation 3 12 Temperature setting Describe scale and set point 3 13 Water temperature F 3 14 Matches manufacturer s data Y N 3 15 Indication of recent service Y N 3 16 If 3 15 yes Date of recent service mm dd yyyy 3 17 Unusual Sounds Y N 3 18 Comments California Public Utilities Commission l 4 February 8 2010 J KEMA Appendices CPUC DFC Onsite Verification Survey Form Wi
60. es not require that the site be removed from all the end uses analyses Each end use was analyzed separately so bad data from one end use did not affect the integrity of the other end use analyses California Public Utilities Commission C 7 February 8 2010 J KEMA Appendices D Net Savings Difference of Differences Calculation Methodology and Comparison Groupings D 1 Methodology and Equations for Computing Net Savings The essence of the difference of differences analysis is to compare participant homes to non participant homes standard construction practices While gross savings is defined as the difference between standard package D and proposed modeled energy consumption net savings is defined as the gross savings less naturally occurring savings due to industry standard practice If for one home S Participant CF 1R standard energy use kBTU sf yr P Participant CF 1R proposed energy use kBTU sf yr Snp Non participant CF 1R standard energy use kKBTU sf yr Pap Non participant CF 1R proposed energy use kKBTU sf yr SF Conditioned floor area of the home Then the Net Savings Gross savings Natural savings S P SF Snp Pap SF And the equation can be seen to motivate the name as the net savings is indeed a difference of differences Snp Pnp SF represents the naturally occurring non participant energy savings due to current standard building practice Unfortunately Sn
61. essure tubing to the Channel B Input Tap and connect the other end to the pressure tap located on the blower door fan see Figure B 6 California Public Utilities Commission B 10 February 8 2010 J KEMA Appendices 7 Connect the Green pressure tubing to the Channel A Reference Tap see Figure B 6 Figure B 6 Attaching the Pressure Tubing to the Pressure Gauge 3 5 4 DG 700 Gauge Connect the Red tubing to the Channel B Input tap Channel B is used to measure Fan pressure and flow Connect the Green tubing to the Channel A Reference tap Channel A is used to measure building pressure with reference to outside 3 5 b DG 3 Gauge Connect the Red tubing to the Channel B Input tap Channel B is used to measure Fan pressure and flow Connect the Green tubing to the Channel A Reference tap Channel A is used to measure building pressure with reference to outside oe Bike California Public Utilities Commission B 11 February 8 2010 J KEMA Appendices 8 Insert plug into blower door fan and connect to power supply Make certain the fan speed controller is off when connecting to power see Figure B 7 Figure B 7 Connecting Power to the Blower Door Fan 9 Make certain fan direction switch is positioned towards the direction of airflow see Figure B 8 Connecting power to the blower door fan Figure B 8 Fan Direction Switch 10 Perform Blower Door Test B 2 1 2 Blower Door Depressu
62. from The California Evaluation Framework A basic breakdown of the calculation is presented below gt ratio sum xi sum yi gt se sqrt sum xi ratio yi 2 sum xi gt rp se 1 645 ratio Where California Public Utilities Commission L 6 February 8 2010 J KEMA Appendices SOURCE Subject Section Type Comment or Question Page xi is the metered data yi is the modeled data ratio is the meter to modeled ratio se is the standard error and rp is the relative precision 12 PGE metered to 3 4 3 Question 12 The metered to modeled rates for RNC are not explained very well except to assert that SCE modeled Micropas does a very poor job of estimating actual energy use On average this is shown ratios to be true However in the detailed scatter plots of metered to modeled results a huge variability is evident in the actual energy use compared to Micropas Although the averages end up being substantially different from reality there are significant numbers of houses where Micropas overestimates electricity use or under estimates gas use Can you provide more explanation of why this is the case How can these results be used to improve future program efforts and ex ante estimates Are they reliable enough for the program managers to change the way they estimate their savings Please provide your recommendations Response 12 There is variability The compliance models Micropa
63. gs Single Tracking before Tracking after Family orientation orientation Dwelling adjustment adjustment Units source kBtu source kBtu 93 393 552 8 146 578 1 455 735 102 995 866 Note that the percent change was zero for SCG This is because all of SCG participants were on the CHEERS database and no adjustments were needed 3 Although coastal space cooling savings increases by a dramatic 28 with orientation adjustment the actual energy savings due to this adjustment are small since the coastal region has much smaller cooling loads and many fewer new homes California Public Utilities Commission A 3 February 8 2010 J KEMA Appendices B Residential New Construction Onsite Data Collection B 1 Building Characteristics Data collection for each site includes information on the building s characteristics HVAC equipment serving the home lighting and major appliances per the IOU s prescriptive measures This data will be used to inform Micropas input files The details of these input parameters are described below For a given residential site modeling parameters fall into the following hierarchy 1 Site Overview Information a b c d e f g h k Overall floor area Number of floors Type of residence single family attached etc Vintage of Residence Number of bedrooms bathrooms City CIMIS weather data Utility Meters and Accounts Title 24 Documents if available Builder
64. he Title 24 calculations IF NO GET CONTACT INFORMATION FOR THE CORRECT PERSON Did you work with HMG to ensure that the project met program requirements IF NO GET CONTACT INFORMATION FOR THE CORRECT PERSON Ideally we would find the single person who is responsible for all the above areas If not then the person responsible for recommending participation should be able to answer all of the survey except the Code NTG section The Code NTG section should be completed by the person who was responsible for the Title 24 modeling and worked with HMG this person is likely the Title 24 consultant am part of the evaluation team and our job is to determine how people involved in the program think it is operating and to what extent the program influenced the efficiency of your project California Public Utilities Commission H 2 February 8 2010 J KEMA Appendices Please be aware that the information you provide will be held completely confidential The interview will take about 20 minutes PROJECT BACKGROUND PB1 What were are your roles and responsibilities with the project PB2 Can you confirm some basic information about the project Town or city Number of buildings Number of housing units Approximate size in square feet of all units Type of housing units Apartments condos other Affordable market rate senior special needs aE Oe Anything unique about the buildings PB3 IF APPLIANCE TRACK According
65. he fan kW draw is assumed constant and will be taken from nameplate data The equations below show how energy is computed using measured time series amperage data and instantaneous power factor and voltage data along with computed runtime and nameplate fan power FANKW Fan Power for the system from nameplate data ENERGY 1 3 AMP PF V RUNTIME20 FANKW Heat Pump Separation Methodology There were only six heat pumps installed at the 454 homes that were visited None of these homes were selected for metering and therefore no Heat Pump methodology was used in this analysis Filling in values for missing dates Meter Data on Air Conditioners For the meters that were collected before a full year had passed between the time of installation a method for filling in the missing data to create an annual usage profile was California Public Utilities Commission C 3 February 8 2010 J KEMA Appendices needed In light of this weather normalization techniques were developed for the cooling end uses to fill in the missing data for loggers with less than a year of recorded usage To calculate a year of data a regression analysis was done based on the average daily temperature and daily kWh Cooling Degree Days CDD were calculated using the reference temperature of 65 degrees F and were used in the regression against kWh Daily total usage for the missing data was estimated using the equation below where BO and 1 are con
66. ices CPUC DFC Onsite Verification Survey Form MiraVista Only Central Water Heating Data 7 11 Percent of inadequate visible pipe 7 12 Temperature setting Describe insulation Enter Percent scale and set point 7 15 IF YES Date of recent service mm dd yyyy 7 14 Indication of recent service Yes No 7 13 Matches manufacturer s data Yes No 7 16 Comments California Public Utilities Commission l 8 February 8 2010 KEMAX J Project Appendices California Multifamily New Homes Detail Tables Table J 1 Performance Track Net to Gross Values for Each Project Question C5c likelihood to have built to program requirements in absence of program Initial Free Rider Allocation Performance Track Projects Question C16 level of agreement that program was critical to the decision to build to program requirements Question Cc3 Question Question estimated Cc7 C8b Final percent made percent Free rider above changes change Allocation code of due to due to the HMG s HMG original review review plans Non 10 Non 5 Yes 20 Non 10 Non 5 Yes 20 Pure ol Partial 12 Yes 32 Partial Partial 12 Yes 19 Partial Partial 10 Yes 6 Pure Partial 20 Yes 8 Partial Partial 17 No Partial Partial 20 No Partial Partial Partial Pure Pure OoO as oa oao o a AJAJ ajojo kl
67. ies Commission F 2 February 8 2010 J KEMA Appendices The average percent of glazing in new homes fell from 17 in homes built under the 1995 standards to 14 in homes built under the 2005 standards The percentage of glass that was two paned vinyl and low e increased from 5 in homes built under the 1995 standards to 95 in homes built under the 2005 standards e Space heating The average furnace efficiency increased from 80 in homes built under the 1995 standards to 83 in homes built under the 2005 standards The percentage of 90 AFUE furnaces increased from 2 in homes built under the 1995 standards to 19 in homes built under the 2005 standards e Space cooling The average central air conditioner SEER level increased from 10 5 SEER in homes built under the 1995 standards to 13 3 SEER in homes built under the 2005 standards 13 SEER became the federal minimum standard in January of 2006 The percentage of central air conditioners with SEER levels greater than 13 increased from 0 in homes built under the 1995 standards to 34 in homes built under the 2005 standards e Water heating The percentage of water heaters that were instantaneous increased from 0 in homes built under the 1995 standards to 24 in homes built under the 2005 standards e Ceiling insulation The average R value of ceiling insulation increased from 29 1 in homes built under the 1995 standards to 33 1 in homes built under the 2005
68. in an appendix that includes the calculations Inputs 41 used to derive H factors for each of the IOUs Response 17 The following text has been added to the report The H factor approach is quite simple KEMA used utility tracking data for gross per unit kWh and gross per unit kW to calculate the ratio of kW to kWh that was assumed by the utilities for their program planning These ratios are called H factors KEMA then estimated ex post net kW savings by applying these H factors to the ex post net energy savings value This method does not provide any independent verification of actual kW savings It is only as accurate as the IOU ex ante calculations were and only adheres to the definition of demand reduction definition in DEER to the extent that the IOU claimed savings did 18 SCE Sample Pg 3 16 Question 18 Table 3 4 does not include the original sample size for non metered Please include that information in the final report Response 18 All participant on sites called for metering That is the number of planned non metered participant sites was zero We have amended the table to reflect this The two unmetered participant sites were unplanned i e when a homeowner backed out of the agreement to allow metering when staff was already on site California Public Utilities Commission L 9 February 8 2010 J KEMA Appendices SOURCE Subject Section Type Comment or Question Page 19 SC
69. ions altered the plans from 5 below code to 15 above code the total percentage change equals 20 PROBE FOR BEST ESTIMATE ENTER 98 Don t Know 99 Refused C11 Were there any other factors that influenced changes to your design after it was submitted to HMG for review 1 Yes 2 No SKIP TO C16 98 Don t Know SKIP TO C16 99 Refused SKIP TO C16 C12 What other factors influenced the design changes C13 What were the three most significant design changes that you made as a result of these factors Probe the type of equipment or designs involved California Public Utilities Commission H 14 February 8 2010 J KEMA Appendices Design Change 1 Design Change 2 Design Change 3 C14 C16 Relative to code by what percentage did all of these revisions alter your original plans For example if the revisions altered the plans from 5 below code to 15 above code the total percentage change equals 20 PROBE FOR BEST ESTIMATE ENTER On a scale of 0 to 10 where 0 is strongly disagree and 10 is strongly agree how much do you agree with the following statement The review and assistance from the program was a critical factor in your decision to build to program requirements 15 above Title 24 code RECORD RESPONSE 0 10 98 Don t Know 99 Refused IF C16 CONTRADICTS C5C Earlier you said were un likely to have built to program requirements in the absence of the program but now
70. ject J 1 Table J 2 Performance Track Net to Gross Values for Each Project J 2 Table J 3 Appliance Track Net to Gross Values for Each Project 0 eseseeeeeeeeeeeeeeees J 1 Table K 1 RNC Site Recruitment Sample Disposition 00eccee cece eeeee eect tees eeeeeeeeeeneeeeees K 2 Table L 1 Comments on the Draft Report with RESPONSES ee ceeeceeeeeee tees eset eeeeeeeeeeeees L 1 California Public Utilities Commission iii February 8 2010 J KEMA Appendices A Calculation of Adjusted Tracking Savings Estimates A 1 Orientation Adjustments Orientation adjustments were only necessary for homes recorded in the CalCERTS registry The orientation of a home can significantly affect its space cooling and heating energy requirements chiefly due to solar gain through windows However when RNC participating homes are built and entered into the tracking registries CHEERS and CalCERTS their actual orientations are not recorded Instead production builders design homes which are built in all possible orientations usually dependent upon the layout of the streets in a development To accommodate this style of planning and to satisfy the RNC program requirements builders model their homes in north east south and west orientations to show that energy consumption meets minimum program requirements in all four cardinal orientations The CHEERS registry contains the modeled energy consumpti
71. kW realization rates and Realizatio 15 low therm realization rates This indicates that ex ante estimates are far off both low and n Rates high Please discuss your recommendations based on this result How can the research be applied to support the development of new ex ante estimates Should program managers increase and decrease their ex ante estimates appropriately Would you recommend applying the 06 08 realization rates as is Response 14 There are alternatives to using Micropas for modeling building energy use The Department of Energy s DOE2 and EnergyPlus simulation tools are two such options The IOUs could use the data from this study to test alternative simulation tools in order to find one that aligns more closely with metered usage over the range of California climates and thus to provide more reliable ex ante expectations 15 SCE Sample 1 1 2 Question 15 Section 1 1 2 describes the development sample designs but never makes clear how the design p 1 3 designs were actually executed It is conventional to report on the plan s the number of attempts to recruit the number of refusals the numbers of final surveys and the numbers used in the final analysis with explanations for how and why reality deviated from the ideal In this case these would be broken out by surveyed on sites metered by utility This is typically related to the population with the sample weights indicated In this case it would also be useful to show how
72. ke sure HVAC is turned off and blower compartment door is in place e Remove all air filters e Tape all registers Use appropriate tape Long Mask for friable surfaces Performing Total Duct Pressurization Test Setup 1 Install the duct blaster at the duct system at the central return or air handler cabinet the return will be the most common installation see Figure B 9 In the case of multiply returns seal off the smaller return and use the largest return for test Figure B 9 Installing the Duct Blaster 2 Connect the Green pressure tubing to the Input tap on Channel A and the Red pressure tubing to the Input tap on Channel B see Figure B 10 California Public Utilities Commission B 14 February 8 2010 KEMAX Appendices Figure B 10 Connecting the Pressure Tubing to the Pressure Gauge Connect the Green tubing to the Channel A Input tap The other end of the Green tubing will be connected to the duct system section 5 5 a Channel A Reference tap should be connected to the inside of the building if the Duct Blaster fan is installed inside the building leave the tap open Connect the Red tubing to the Channel B Input tap The other end of the Red tubing will be connected to Brass tap on the Duct Blaster fan section 5 6 4 Channel B Reference tap should be connected to the space where the Duct Blaster fan is installed If the fan and gauge are in the same space leave the tap open 3 Connec
73. l factor in decision Question FR7 Agreement that would have paid full cost without program Question FR8 Agreement that the program was not necessary for purchase Final Free Rider Allocation Refrigerator No 10 10 10 10 Refrigerator No 10 California Public Utilities Commission 10 G 3 5 10 February 8 2010 J KEMA lt Appendices H California Multifamily New Homes Net to Gross Interview Guide California Public Utilities Commission H 1 February 8 2010 J KEMA Appendices CMFNC Participant Interview Guide Date Interviewer Name Organization Title Phone Email Program Track 1 Performance 2 Appliance 3 Performance Appliance My name is calling from Nexus Market Research on behalf of the California Public Utilities Commission lm calling to discuss the project which was part of the California Multifamily New Construction program CMFNC operated by Heschong Mahone Group HMG You are listed as the primary contact person for this project is that correct IF NO ARRANGE TO INTERVIEW THE PROPER PERSON Were you responsible for recommending that this project participate in the CMFNC program IF NO GET CONTACT INFORMATION FOR THE CORRECT PERSON Were you responsible for developing the building plans IF NO GET CONTACT INFORMATION FOR THE CORRECT PERSON Were you responsible for modeling t
74. lation results into a database table for further analysis The interface stores the results in fields that correspond to the C 2R or the CF1R forms used for compliance documentation The interface was initially designed to batch process many sites at one time During the first RNC Baseline Study 2000 800 on site surveys of low rise residential buildings were conducted Instead of using the MICROPAS interface to develop each input file by hand one at a time a decision was made to automate the process The system that was developed became extremely useful during the last few months of the project when the focus changed to include analyzing the then upcoming 2001 Standards Without the RNC Interface it would have been necessary to manipulate each MICROPAS input file one at a time to run under the new version 7 MICROPAS was chosen as the compliance tool because it is the tool of choice among energy consultants for performing low rise residential compliance analysis Interviews with MICROPAS developers indicate that more than 75 of energy professionals use their product Further two subsequent studies by Itron indicate that more than 90 of energy compliance documentation was completed using MICROPAS California Public Utilities Commission E 1 February 8 2010 J KEMA Appendices of MICROPAS Similarly over the last four years requests have been made for new types of analysis that would have been either impossible or extremely costly to c
75. lf report analysis Question 4 Were any secondary sources used to confirm participant responses It appears that all results are solely based on participant interviews surveys Response 4 The evaluation team also reviewed program documents regarding the HMG review of the projects Title 24 energy modeling analyses in order to guide the decision maker survey Most useful were the files that included the HMG reviewer s comments regarding the discrepancies questions or other feedback provided to the T24 consultant However these comments were not available for every project In most cases the respondents provided a reasonably accurate description of the level of feedback whether it was major or minor but without the details listed in the HMG review documents California Public Utilities Commission L 2 February 8 2010 KEMAX Appendices SOURCE Subject Section Page Type Comment or Question 5 PGE MF Self report analysis 4 5 2 Question 5 Program managers experience working with participants strongly differs from the self reported experiences Given the weaknesses in a self report method administered several years after the fact shouldn t the managers experience be given some credence especially as it was backed with records of program interactions with customers Doesn t the self report method as applied tend to bias the findings in a consistently downwa
76. m is transferred via a gear to the crankshaft This shaft moves valves that measure the volumetric gas flow Rotations of the gear are transferred via a magnetic coupling to the index thus assuring proper sealing of the meter s internal mechanisms Figure B 19 shows the G4 gas meter California Public Utilities Commission B 24 February 8 2010 J KEMA Appendices Figure B 19 G4 Gas Sub Meter Field Installation Authorized plumbers were hired to install the gas meter on the water heater All gas safety codes and regulations will abide by all terms and conditions imposed by the utilities and governmental authorities 1 2 3 4 5 6 7 Turn off the gas service to the house and cut the gas pipe before it enters the tankless water heater Blowout the gas service line before the meter is installed so that no dirt debris or liquids of any kind can be carried into the meter when gas is flowing through the pipe Place a new connection washer on each open end of the gas pipe Support the meter so that both hubs are against the connection washers and run the connection nuts down hand tight In alternating fashion tighten the nuts to an appropriate torque for the connection size Before turning the gas on in a new installation check the system downstream of the meter to be sure that all connections are made up and tight or that the downstream valve if there is one is closed Now reset the gas meter
77. mmission L 1 February 8 2010 KEMAX Appendices SOURCE Subject Section Page Type Comment or Question underestimating the cooling based usage and therefore understating the savings associated with the cooling end use Additionally the Net to Gross ratios for PG amp E were greater than 1 for kWh This implies that there was a lower level of compliance among the non participant homes and therefore a higher level of savings over baseline Finally the ex ante savings estimates for the program may have been understated These three factors all contribute to the high realization rates increased savings due to underestimated usage in the models increased savings due to low levels of compliance among baseline homes and low ex ante savings estimates 3 PGE MF Micropas results 3 4 1 Question 3 The residential new construction metering results showed large kWh and kW realization rates purportedly due to inaccuracies in Title 24 simulations Shouldn t those same realization rate findings be applicable to the multifamily gross savings estimates for MF projects using Micropas primarily low rise Response 3 Multifamily buildings even low rise buildings have significantly different energy characteristics than single family homes typically having less glazing shared walls etc We do not believe that it is appropriate to apply single family results to multifamily buildings 4 PGE MF Se
78. mpleted In addition to performing batch runs the RNC Interface has several other useful capabilities e Select individual or multiple sites e Select the version of MICROPAS 4 5 5 6 6 5 7 0 or 7 3 California Public Utilities Commission E 3 February 8 2010 J KEMA Appendices e Select whether to run a Cardinal e Select the weather data set to use FullYear or ReducedYear and e Specify the source input database this feature was used for the testing phase and during the Statewide Multifamily Study to read in building department C 2R data E 3 Testing the RNC Interface Considerable effort was made in 2000 to ensure that the RNC Interface produced accurate MICROPAS simulation results given the limitations of the available data and the design of the RNC Interface A testing procedure was developed to evaluate the default parameters underlying algorithms and structure of the RNC Interface Building department compliance forms C 2Rs were collected for a sample of the sites surveyed and the data was mapped to the 2000 on site database These data then were passed through the RNC Interface The error band used in 2000 was calculated by comparing the compliance margins from these runs to the compliance margins from the C 2R forms As noted above the Interface has been updated with each change to Title 24 and each new version of MICROPAS A Cardinal run is actually four runs a run is performed for the home
79. naccurate and subject to relatively wide variation much of which is unexplained The authors of the study note this directly on page 1 20 Specifically they state The metered data indicate that the MICROPAS compliance software on average overestimates the amount of heating energy consumed at a site and underestimates the amount of cooling energy consumed Because the baseline for the utilities ex ante estimates of energy savings is a home that meets the minimum of California s building code and the compliance software that is used to estimate baseline energy use for this purpose does not accurately predict energy use ex ante energy savings from the utility tracking databases may not reflect actual savings This raises serious questions concerning the reliability of the study Can this be corrected If not should this study continue to be used in the VRT process California Public Utilities Commission L 11 February 8 2010 J KEMA Appendices SOURCE Subject Section Type Comment or Question Page Response 21 To clear up some confusion in regards to the quote of the report used in the comment The last sentence in the quote states ex ante energy savings from the utility tracking databases may not reflect actual savings This should be revised in the report to say ex ante energy savings from the utility tracking DO not accurately reflect actual savings The ex ant
80. nal input Btuh was obtained from the manufacturers specifications and utilized to inform the run time data with actual gas input During the pilot sites the main burner gas pressure was tested at each furnace unit to verify that the gas supply pressure was within the manufacturer s specifications By doing this we demonstrated that the gas supply pressure is sufficient and RLW can confidently use the nameplate input Btuh rating for the fuel consumption calculations Field Installation Figure B 20 below shows the typical logger installation implemented for forced air furnaces For two stage heating units we installed a second relay and OWL 200 to capture run time for each stage California Public Utilities Commission B 26 February 8 2010 J KEMA Appendices Figure B 20 Typical Logger Installation for Forced Air Furnaces 90 AFUE Forced Air Furnace Method A Additional Measurements Measurement of furnace inlet gas flow can performed during both high and low burn stages This could then be used to compute approximate gas usage Using the flue gas analysis kit the combustion efficiency will be analyzed to ensure that the furnace is operating near its rated efficiency This is not equivalent to an AFUE rating The flue gas analysis kit determines O2 CO probe temp draft and diff pressure then calculates CO2 CO Air Free and Combustion Efficiency The Testo 327 1 Combustion Analyzer specifications are presented in Table B 1
81. ndards had these higher efficiency windows The increase in Low E windows is illustrated in Figure F 2 California Public Utilities Commission F 7 February 8 2010 J KEMA Appendices Figure F 2 Percentage of SF Homes with 2 paned Vinyl Low E Windows Homes Built Under Homes Built Under Homes Built Under Homes Built Under 1995 Standards 1998 Standards 2001 Standards 2005 Standards Statewide Regioni1 Region2 Region3 Region4 Region 5 F 3 Space Heating Systems Baseline Results Table F 4 presents a summary of gas space heating system efficiencies for detached single family homes The average AFUE has increased slightly for homes in every region Table F 4 Central Gas Space Heating System Efficiency Region Region Region Region Region Analysis Parameter Description Statewide 1 2 3 4 5 Average Efficiency AFUE Homes Built under 1995 Standards 80 80 80 80 81 80 Homes Built under 1998 Standards 81 81 80 80 81 80 Homes Built under 2001 Standards 81 85 82 80 81 81 Homes Built under 2005 Standards 83 85 82 82 83 83 Figure F 3 presents the distribution of AFUEs under the four Standards for the entire state of California The portion of space heating with the lowest level of efficiency has fallen while the highest level of efficiency has increased California Public Utilities Commission F 8 February 8 2010 J KEMA Appendices
82. ndows 4 11 Model information if visually available 4 12 of windows that are not different from old windows 4 13 of windows that are not double paned 4 14 of windows that do not open properly 4 15 of windows that do not have adequate interior seal 4 16 of windows that do not have adequate exterior seal 4 17 of windows not securely installed to building frame 4 18 of total windows in unit 4 19 Comments California Public Utilities Commission l 5 February 8 2010 J KEMA Appendices CPUC DFC Onsite Verification Survey Form Building Data 5 11 Project 5 12 Bldg 5 13 Field Staff Name 5 14 Date mm dd yy 5 15 Time 5 16 Comments California Public Utilities Commission l 6 February 8 2010 CPUC DFC Onsite Verification Survey Form MiraVista Pepperwood Attic Insulation 6 12 Enter material 6 13 Enter material fiberglass foam cellulose fiberglass foam cellulose 6 11 Enter material fiberglass foam cellulose 6 14 Enter average depth of insu 6 15 of space with inadequate insula lated attic space Enter number of tion depth Enter percent inches 6 16 of inadequate corner eave roofline coverage Enter percent 6 17 Enter approximate R Value of in 6 18 of ventilation systems obscured sulated attic space Enter number Enter percent 6 19 Comments California Public Utilities Commission l 7 February 8 2010 J KEMA Append
83. ode annual household heating load and blower motor electrical power consumption California Public Utilities Commission B 29 February 8 2010 J KEMA lt Appendices According to resources from EERE DOE calculated the gas consumed by the burner and electricity consumed by the circulating air blower motor at the two firing rates This calculation method is based on the procedure in the ASHRAE Standard 103 Summaries of the methodology are available at the following sites Uniform Test Method for Measuring the Energy Consumption of Furnaces http www fire nist gov bfrlpubs build02 PDF b02022 pdf http www eere energy gov buildings appliance_standards residential pdfs furnaces_boilers fur nace_boiler_ app7 7 pdf http www1 eere energy qov buildings appliance_standards residential pdfs furnrbod pdf http edocket access gpo gov cfr_2009 janqtr pdf 1 Ocfr4 30BAppN pdf Using the equations and explanations available above and also through ASHRAE Standard 103 the AFUE of the furnace can be calculated This procedure will also allow calculation of the estimated gas usage of the furnace on an annual basis which can be found by dividing the annual household heating load by the AFUE and converting from BTUs to therms California Public Utilities Commission B 30 February 8 2010 J KEMA Appendices C End Use Meter Data Analysis C 1 End Use Equipment Meter Data C 1 1 Cooling Equipment C 1 1 1 Split System Air Conditioner
84. ogy and Comparison Cl co 18 61 4 6 enaane Rete eRe ener ener TieePene rehire FRU Tr CHT eer et vent EE erenrrr E a aE D 1 D 1 Methodology and Equations for Computing Net SavingS cccceeeeeeeeeeereeeeeees D 1 E The RNG Aptera Enonsiad tinea dtscdugatesddeahetectetenitacatieacetat eraised E 1 EN ntrod ctoM sai aana a eer rr ten AE Ea EE E 1 E 2 Overview of the RNC Interface eccicaccnsssudeestcostsciuancvialiacnede teed ctadssnsestecceciatuandsenddcasedaees E 1 E 2 1 MICROPAS Version 4 5 5 1 6 0 6 5 7 0 and 7 3 nocens E 2 E 2 2 Developing MICROPAS Inputs from the On Site Survey Data E 2 E 2 3 Features of the RNC Interface cccccceccecceeeneeeeneesceeeneneeeeseeeneeeneenerens E 3 E 3 Testing the RNC Interface i c62 cvetcats dastcentencwtedadsaradssenecacetanchieassbenesddecl dadeiuebastaectiacesd E 4 F Baseline Study Results icccccsescicnc lt tecatvaiaincnancuctdcnconcnessaanede teens Selalsetdebdeepaieiadtennmeecumtansaaanes F 1 F 1 Newly Built Single Family Homes over Time eeeeeeeeeeeeeeeeerrrssssrrrrrrrssssrrrrrern F 4 California Public Utilities Commission i February 8 2010 KEMAX Appendices Table of Contents F 2 Fenestration Baseline Results 2 2 cccceeeseseseeeceeeeeeeereeseseceeeeeneeeeseeseeeeeenseserennees F 6 F 3 Space Heating Systems Baseline Results 2 0 cccceceeeeeeeeenneeeeeeeeeeeeeteeeneeeeeeeeeees F 8 F 4 Space Cooling System Baseline Results
85. on for all four orientations and the average was used to calculate the gross energy savings for each home The CalCERTS registry only contains modeled energy for each plans worst orientation but clearly not all homes are actually built in the worst possible orientation To adjust for this the CHEERS data were used to estimate average orientation energy as a function of worst orientation energy Unique orientation adjustment b ratios were estimated for the single family homes A 2 Ratio Estimation and B Ratios Ratio estimation was used to adjust gross tracking energy savings through the use of b ratios in six stratum three end uses heating cooling and water heating in each of three climate regions inland coastal and high desert The target variable of analysis denoted y is the energy use of the project home The primary stratification variable the estimated energy savings of the project is denoted x and is obtained from the tracking database A ratio model 1 A home was classified as either coastal desert or inland based on its CEC climate zone Homes modeled or built in CEC climate zones 1 7 were classified as coastal homes in CEC climate zone 15 was classified as desert and homes modeled in CEC climate zones 8 14 and 16 were classified as inland California Public Utilities Commission A 1 February 8 2010 J KEMA Appendices was formulated to describe the relationship between y and x for all projects in th
86. onduct without the many capabilities of the interface Specifically the interface was designed to do the following e Translate the on site survey data into MICROPAS input files e Run MICROPAS in a batch mode e Facilitate the use of either MICROPAS 4 5 1995 Stds 5 1 1998 Stds 6 0 amp 6 5 2001 Stds or 7 0 amp 7 3 2005 Stds e Extract the MICROPAS compliance results and e Provide a platform for the technical potential analysis and e Conduct several other what if analyses E 2 1 MICROPAS Version 4 5 5 1 6 0 6 5 7 0 and 7 3 It was recognized early on that the RNC Interface needed to be able to generate results for multiple versions of MICROPAS At first it was designed to use two versions of MICROPAS MICROPAS4 v4 5 for the 1995 Standards and MICROPASS v5 1 for the 1998 Standards The Residential Standards are normally revised on a three year cycle However during the first year of the project emergency revisions were made to the Standards under AB 970 Therefore the capability to generate results for a third version of MICROPAS using the 2001 standards MICROPAS6 v6 0 amp v6 5 was added to the interface These standards were implemented in January 2002 for all low rise residential homes and superseded the 1998 Standards Then in order to evaluate the 2005 Standards adopted in November of 2005 the RNC Interface was again upgraded to generate results using MICROPAS6 v6 58 and MICROPAS7 v7 0 amp v
87. os and cast doubt on the validity of the results Do the authors agree with this interpretation If so should the study continue to be used in the VRT process 2 The application of the non participant meter to model ratio to participants undermines the notion that participants are different from non participants That is one would expect that participants have characteristics and behaviors that separate them from non participants If that is not the case how do we explain participation for some individuals and not others This casts doubt on the results since there is no data available to inform us as to whether this is a valid assumption or how the results would vary with alternative California Public Utilities Commission L 12 February 8 2010 KEMAX Appendices SOURCE Subject Section Page Type Comment or Question assumptions Again should the study continue to be used in the VRT process Response 22 1 In this evaluation study the original sample plan was drawn up based upon our past experiences with RNC EM amp V Based upon the costs and precision of past studies an estimate of precision and the required sample size for this study was made based on the budget available Unfortunately past performance does not guarantee future results When participation in the program turned out to be lower than expected the amount of claimed savings from this program dropped
88. p and Prp do not exist since non participant homes of the exact same size location and other building characteristics were not constructed To estimate them a baseline sample of 422 residential new construction homes inspected by KEMA was utilized The subscript p is used to denote Participants and np is used for Non Participants California Public Utilities Commission D 1 February 8 2010 J KEMA Appendices The Net savings of the population of participant homes was calculated as follows 1 Net savings savings of participant homes above standard naturally occurring savings due to current practice 2 Savings of participant homes above standard VN SF S CM p and 3 Estimated naturally occurring savings N SF a Sp CM m 4 So Net Savings N SF S CM N SF S CM mp 5 N SF p Sp CM p CM Where N Number of participant homes N SSF SF Participant homes average conditioned floor area 1 N gt S 5F Sp Participant homes weighted average Standard energy consumption zL sk i l N 2S DSF CM Participant homes weighted average Compliance Margin T s SF R Participant weighted average Compliance Margin is weighted by conditioned floor area of each home California Public Utilities Commission D 2 February 8 2010 J KEMA Appendices Nip ps Sip Py JSF p CM m Non particip
89. power the bridge circuit The other end of the voltage adapter was connected to a Hobo Micro Station logger The details of the circuit are shown in Figure B 17 below California Public Utilities Commission B 21 February 8 2010 J KEMA Appendices Figure B 17 Circuit Details Your G10K3D116 S VIA CM14 thermistor 11 GROUND TRIG OPEN COLL VOLTAGE INPUT TRIG SOURCE 2 2K NC 2200 SHIELD ohms 5 Volt Adapter The HOBO Micro Station logger s excitation voltage Vexc is the switched DC output coming from the logger Vexc provides 1 mA current at 2 5 volt DC The 1 mA current flows through the resistors to provide voltage across the bridge circuit The voltage output from our bridge circuit as seen by the logger input is Vout Thermistor to balance resistor ratio is Rt Rb Vout Vexc Vout Now multiply the value of our Balance resistor Rb by this ratio to get the resistance of the thermistor Rt To derive temperature from thermistor resistance plug values into the Steinhart Hart equation The Steinhart and Hart equation is an empirical expression that is used to determine the resistance temperature relationship of NTC thermistors An Excel spreadsheet developed by the vendor named Thermistor hotplate can be used to convert voltage recorded by your Onset HOBO logger into temperature Field Installation 1 Drill a 3 8 hole on the exhaust flue of the hot water and insert the 2 threaded end of the thermi
90. r Homes Built Under Homes Built Under 1995 Standards 1998 Standards 2001 Standards 2005 Standards E gt 14 SEER mE gt 13 and lt 14 SEER gt 12 and lt 13 SEER E gt 11 and lt 12 SEER m gt 10 and lt 11 SEER m lt 10 SEER F 5 Multiple HVAC Systems and Thermostat Types Baseline Results A summary of the percent of homes with multiple units is presented in Figure F 5 for detached single family homes The number of homes with multiple HVAC systems has increased between homes built under the 2001 Standards and the 2005 Standards California Public Utilities Commission F 10 February 8 2010 J KEMA Appendices Figure F 5 Multiple HVAC System Statewide Average Homes Built Under Homes Built Under Homes Built Under Homes Built Under 1995 Standards 1998 Standards 2001 Standards 2005 Standards m4 HVAC Systems m 3 HVAC Systems m2 HVAC Systems m1 HVAC System F 6 Water Heating Baseline Results Figure F 6 presents the saturation of instantaneous water heaters both gas and electric in new homes built under the four sets of Standards The percentage of homes with instantaneous water heaters increased greatly under the 2005 Standards Many of the homes with instantaneous water heaters also had storage water heaters California Public Utilities Commission F 11 February 8 2010 J KEMA Appendices Figure F 6 Percentage of Instantaneous Water Heaters Gas and Electric Homes Built Under Homes Built
91. rd direction Response 5 We recognize that the impressions of program staff in working with participants may differ from the experience reported by the participants themselves However the evaluation team believes that the participants know their own motivations better than program staff does even if the interview occurred a year or more after project completion Note that some respondents clearly reported that the program strongly influenced their project design though likely not as many participants as the program staff may believe The evaluation team believes that self report interviews were the appropriate methodological choice for assessing NTG for this program and did not find information to support the contention that the self report method yields reduced estimates of program influence The methods we developed were consistent with the Evaluator Protocols adopted by the Commission and build upon methods employed in prior evaluations The methods also include checks for internal consistency and reliability both in the course of conducting the interviews and the analysis and calculation of the results We believe that the reliability of these methods are an improvement upon past studies and the consistency in approaches makes the reliability across the portfolio greater 6 PGE Net savings Question 6 Can you provide more detail on the H factor analysis We were not given enough information to review the analysis Do the evalu
92. ring the pilot sites to verify proper delivery pressure Figure B 18 Domestic Hot Water Data Logger Installation California Public Utilities Commission B 23 February 8 2010 J KEMA Appendices Data Processing The recorded voltage data from the logger shall be downloaded to a PC The voltage data is converted into temperature with the help of Thermistor hotplate Excel spreadsheet for further analysis B 3 2 2 Tankless Water Heaters Instantaneous tankless water heaters operate without storage tanks Cold water travels through a pipe into the unit and either a gas burner or an electric element heats the water only when needed As there are multiple controls to regulate the gas flow to the burner and the flow is variable the most economical and accurate way to measure the annual gas consumption is to install an inline gas sub meter at the gas supply pipe of the water heater We used Elster Amco G4 gas meters to measure the annual gas consumption of the water heater This meter s small size and lightweight design is ideally suited for sub metering applications The G4 is a 200 cubic foot per hour non temperature compensated gas meter with a cyclometer register Despite its small size the G4 is accurate and reliable when measuring either natural or LP gas The design of the G4 consists of four measuring chambers separated by synthetic diaphragms The chambers are filled and emptied periodically and the movement of the diaphrag
93. rization Test Procedures Using the DG 700 1 Press the Mode button twice for PR FL 50 2 If BD3 is not displayed on Channel A push Device until BD3 is displayed 3 Push Configure button to select a flow ring displayed on Channel B Typically you should start with ring B2 Open No Ring A1 ring A B1 ring B the rings on the blower door fan are labeled as such California Public Utilities Commission B 12 February 8 2010 J KEMA Appendices 4 If you cannot get an accurate flow you will need to add or remove flow rings on the blower door fan as well as change the Config for the appropriate ring If LO appears in the Channel B window it means that the gauge cannot accurately calculate and a different flow ring should be used 5 Turn on Fan and increase the fan speed until you get a pressure reading on Channel A between 45 and 55 Pa The gauge when in PR FL 50 mode will automatically adjust so don t worry about getting exactly to 50 Pa 6 Once you have reached a pressure that is acceptable press the Hold button 7 Record the BD ring used House pressure near 50Pa on Channel A and the BD CFM 50 value on Channel B 8 Press HOLD Button again to release and PRESS MODE button to PR PR and record BD FAN PRESSURE value from CHANNEL B 9 Repeat test at 25Pa and QC using the flow exponent equation make sure to set the Mode to PR FL 25 10 If Flow exponent checks out no further tests are required To check test calculate
94. rom non participating builders The evaluation of the 04 05 California Energy Star Homes Program found that almost half of California Public Utilities Commission L 13 February 8 2010 KEMAX Appendices SOURCE Subject Section Page Type Comment or Question Energy Star homes owners did not know that their home was Energy Star at the time they purchased it from Evaluation Measurement and Verification of the 2004 amp 2005 California Statewide Energy Star New Homes Program Twenty nine respondents currently knew their home was an ENERGY STAR home and fourteen did not However when asked if they knew their home was an ENERGY STAR home before they purchased or rented it only 24 said they knew their home was an ENERGY STAR home while 19 said they did not know We can assume that those who did not know who did not purposefully choose a high efficiency home have the same behavior on average as owners of non participating homes Of the ones who did know we do not know what percentage would actually behave differently than non participants The two main behavioral factors in home energy use are occupancy and set points One would not expect occupancy to vary by energy and environmental attitudes Set points however could vary significantly Of the two effects however occupancy is much more significant Based on these factors we believe that the difference in behavior between
95. rom the program would have paid the additional amount of program incentive subsidy to buy the measure on my own RECORD RESPONSE 0 10 98 Don t Know 99 Refused IF FR27 CONTRADICTS FR24 FR25 Earlier you indicated that you were un likely to have bought the same quantity of measures without assistance from the program but now you say you would not have paid the additional incentive to buy the measure How so FR28 At the time bought my new product type the assistance from the program was not necessary to persuade me to purchase the higher efficiency product RECORD RESPONSE 0 10 98 Don t Know 99 Refused IF FR28 CONTRADICTS FR24 FR25 Earlier you indicated that you were un likely to have bought the same quantity of measures without assistance from the program but now you say the program was not necessary to persuade you to buy the measure How so California Public Utilities Commission H 11 February 8 2010 J KEMA Appendices CODE NTG FOR PROJECTS WITH PERFORMANCE INCENTIVES REVIEW PLAN CHECK DOCUMENTS FROM HMG PRIOR TO INTERVIEW IN ORDER TO INFORM QUESTIONS AND PROBES C1 C2 C3 C4 C5 C51 C5a Were the original building plans submitted to HMG for review above below or just meeting 2005 Title 24 code for the project 1 Above code 2 Below code 3 Just meeting code SKIP TO C5 98 Don t Know SKIP TO C5 99 Refused SKIP TO C5
96. s take building characteristics as inputs but underlying the model are behavioral assumptions occupancy and set points that are fixed Of course in reality behavior can vary widely from household to household We believe that the gap between metered and modeled usage has its origins primarily in the way orientation is treated and the gap between actual behavior and modeled behavior The compliance models are designed to determine whether a building complies with the building code and are not designed to accurately predict energy use For future program efforts There are alternatives to using Micropas for modeling building energy use The Department of Energy s DOE2 and EnergyPlus simulation tools are two such options Since the data collected in this study were based on field work they can be used in the future to test alternative simulation tools in order to find one that aligns more closely with metered usage over the range of California climates California Public Utilities Commission L 7 February 8 2010 KEMAX Appendices SOURCE Subject Section Type Comment or Question Page 13 PGE program table Question 13 What was the market penetration of the program for each IOU SCE participati 3 5 on Response 13 We feel that the utilities are in the best position to answer this question 14 PGE RNC Table 3 Question 14 One key finding of the study is that there are very high kWh and
97. s odometer and make sure that it reads zero California Public Utilities Commission B 25 February 8 2010 J KEMA Appendices 8 Note down the date and time of installation 9 Record the nameplate information of the hot water heater such as make model number serial number and nominal input Btuh 10 At the end of the monitoring period record the cubic feet on the meter and also the date and time of retrieval B 3 3 Heating Equipment End Use Metering B 3 3 1 Forced Air Furnace Heating systems monitored may include central forced air furnaces and central heat pumps Owl 400 data loggers are used for heat pump heating mode and Owl 200 data loggers are used for forced air furnaces Considering the safety concerns and difficulty of measuring natural gas consumption a unique approach is necessary to capture the forced air furnace run time Inside the air handler section of each furnace there is a low voltage 24 VAC control board with a terminal block consisting of separate relay contacts for heating cooling and fan operation Upon receiving a call for heat signal from the thermostat the heating relay contact undergoes a change of state resulting in the operation of the furnace KEMA determined that by slaving a small relay off of the call for heating circuit and logging the change of state of the heating relay contact we were able to precisely log the percentage run time of the furnace on an hourly basis The furnace nomi
98. sPhasel_ FinalReportt_052 12009 pdf The following paragraphs describe the various applications of the baseline data and where the analyses and results can be found This appendix goes on to report additional results not reported elsewhere Residential Market Effects Study In January 2009 the Study Team conducted an initial analysis of the building characteristics found during the on site surveys conducted during Phase 1 of the Baseline Study in preparation for the RNC Market Effects Report The report contains information on the 422 completed homes The purpose of this analysis for the RNC Market Effects report was to summarize historic building characteristics over the last ten years using data from on sites conducted under the three previous Residential New Construction Baseline Studies and the current 2008 Residential New Construction Baseline Study Phase II of the Residential New Construction Market Effects Study will use the baseline of non program homes to estimate the gross energy and demand savings associated with observed above code practices compared to code and the savings associated with observed homes just meeting code compared to the average noncompliant home and apply the savings to the number of non program homes These will provide estimates of gross energy and demand savings for two of the three primary ways in which IOU programs can lead to the ultimate goal of reduced energy use demand and emissions i e market effe
99. seasonal California Public Utilities Commission C 4 February 8 2010 J KEMA Appendices C 1 2 2 Instantaneous Non Storage Domestic Hot Water DHW Heater The G4 gas meter provided the total cubic feet gas consumed per year We multiplied the total cubic feet of natural gas by 1 020 to obtain total gas consumption of the water heater during the installation period This usage was then extrapolated based on the installation period and the removal date to get an annualized estimate of gas consumption C 1 3 Space Heating End Use Energy C 1 3 1 Forced Air Furnace The gas input and fan power draw was taken from nameplate data and applied to the unit runtime to determine energy consumption By slaving a small relay off of the call for heating circuit we were able to precisely log the duration of a heating cycle The relay contact change of state indicates runtimes The final stored data was percent time on during each 20 minute interval The furnace nominal gas input rate Btu h was obtained from the manufacturers specifications and utilized to inform the run time data with actual gas input The runtimes were multiplied by the input rating to estimate hourly gas consumption Filling in values for missing dates Meter Data on Furnaces A handful of meters were collected before a full year had passed between the time of installation For the purposes of the analysis a full year of metered data was required in order to create
100. ss 10 Check attic hatch position 11 Put garage door in normal position 12 If dryer is not installed seal off dryer vent Performing Blower Door Test Setup 1 Setup and install Blower door frame in an exterior doorway do not put fan in opening yet see Figure B 1 Figure B 1 Installation of Blower Door Frame California Public Utilities Commission B 8 February 8 2010 J KEMA Appendices 2 Put the Green pressure tubing through one of the opening in the door run it approximately 3 5 feet away making sure that the end of the tubing is placed well away from the exhaust flow of the Blower Door fan see Figure B 2 Figure B 2 Placement of Green Pressure Tubing Outside pressure tubing should be placed away from fan exhaust gt 3 Install the Blower door fan in the opening making certain the elastic band fits snuggly around the fan with the collar resting in between the two sides of the electrical box see Figure B 3 Figure B 3 Installation of Blower Door Fan California Public Utilities Commission B 9 February 8 2010 J KEMA Appendices 4 Attach the fan to the cross bar with the Velcro strap the fan should now be suspended in the door with the flow plate side facing towards you see Figure B 4 Figure B 4 Attach the Fan to the Cross Bar 5 Attach pressure gauge to mounting board and put on gauge hanger see Figure B 5 Figure B 5 Attach Pressure Gauge 6 Connect the Red pr
101. stants based on the regression analysis BO is the average daily baseline usage and 1 is the temperature response of temperature dependant cooling usage Daily Total Usage site fo 61 CDD The predicted Average Daily Usages were combined with the actual Average Daily Usage to create a full year of daily usage for each site For the meter adjustment factor estimation these daily usages were aggregated into annual kWh C 1 2 Water Heating Equipment C 1 2 1 Storage Tank Domestic Hot Water DHW Heater Temperature Cutoff Methodology DHW heater The voltage readings from the DHW loggers were converted into temperatures using the following equation Temperature C 1 0 001126733 log 2200 VDC 2 5 VDC 0 000234594 0 0000000850781 log 2200 VDC 2 5 VDC 273 15 The Temperature values were converted to Fahrenheit from Celsius and after a careful examination of the Temperature profiles converted from the logger data a cut point of 185 8F was established to differentiate between the on and off periods From the estimated on and off periods an hourly percent runtime was calculated for each heater For the adjustment factor analysis these hourly usage totals will be summed for the 8760 hours following the meter installation date to yield an annual total usage for the study period For sites that had less than a year of data the usage was extrapolated to estimate the annual usage It was determined that the
102. stor into the flue and cover it with metal tape to secure the thermistor for the duration of the study Make sure the thermistor is in the exhaust air stream and not making contact with the sides of the flue 2 Insert PC interface cable to the communication port of the Hobo Micro Station to configure the logger 3 Follow the step by step process to setup the logger a Open the Hobo pro status window by double clicking the task bar or the logger icon California Public Utilities Commission B 22 February 8 2010 J KEMA Appendices 4 5 b Once status menu is displayed select launch logger option from device menu c Set the sample monitoring interval to 90 seconds d Then select launch options such as instant start delayed start or push button e To start the logging session select the launch button The HOBO Micro Station data loggers record an instantaneous flue temperature every ninety seconds The ninety second logging configuration permits 350 days of monitored data The loggers are configured to stop recording data when the memory reaches capacity to avoid overwriting previously collected data Figure B 18 shows the typical logger installation implemented for storage domestic hot water heaters with a standard flue Record the name plate information of the hot water heater such as make model number serial number and nominal input Btuh Note that the manifold main burner pressure will be measured on several units du
103. t purchasing product type Already begun collecting information about product type 9 Already selected the measure you were going to get 10 Already installed the energy efficient measure SKIP TO C1 11 DON T READ Other 98 DON T READ Don t Know 99 DON T READ Refused os FR23 Did you have to make any changes to your existing plans for product type in order to receive this assistance through the program 1 Yes 2 No SKIP TO FR23C 98 Don t Know SKIP TO FR23C 99 Refused SKIP TO FR23C California Public Utilities Commission H 9 February 8 2010 J KEMA Appendices FR23B How did your plans change FR23C IF FR23 2 98 99 Did you intentionally develop your original plans for product type in order to meet program requirements 1 Yes 2 No 98 Don t Know 99 Refused IF FR21 4 OR 5 AND FR23C 1 You said that you had already selected or installed the measures before learning of the program yet you intentionally developed the original plans in order to meet program requirements How so FR24 Ona 0 to 10 scale with O being not at all likely and 10 being very likely how likely is it that you would have bought the same efficiency level of measures if you had not received any assistance from the program RECORD RESPONSE 0 10 98 Don t Know 99 Refused IF FR21 4 OR 5 AND FR24 lt 8 You said that you already selected or installed the measures
104. t the other end of the Green pressure tube to the static pressure probe and insert probe into a supply register and re tape to secure probe in place see Figure B 11 Figure B 11 Placing Static Pressure Probe in Supply Register 4 Connect the other end of the Red pressure tube to the duct blaster fan see Figure B 12 California Public Utilities Commission February 8 2010 J KEMA Appendices Figure B 12 Connect Red Pressure Tube to Duct Blaster Fan 5 Next connect the controller to the duct blaster fan by the female power receptacle and plug into power supply see Figure B 13 Make certain fan controller is off when connecting to power Figure B 13 Connect Controller to Duct Blaster Fan 6 Perform Duct Leakage Test B 2 2 2 Total Duct Pressurization Test Procedures Using the DG700 1 Turn on Duct blaster Fan and Pressure Gauge 2 Push Mode button to PR FL 3 Push the Device button until DB B is displayed on the Channel A side California Public Utilities Commission B 16 February 8 2010 J KEMA Appendices 4 Next push the Config button to select a flow ring Open no ring A1 ring 1 B2 ring 2 C3 ring 3 5 Adjust duct blaster fan speed control until Channel A reads 25 PA or as close as possible 6 Record values 7 Repeat steps 1 6 with duct blaster test pressure of 50 PA 8 Record values and check flow exponent 9 If flow exponent is within range test is complete 10 Note any unusual
105. t would be lower in most cases While the improved observations of lag would improve the overall calculation a greater source of uncertainty relates to the CPU controlled firing of stages There is significant uncertainty around the duration and frequency of low fire and high fire events from two stage units The determination of the cycle and the shift from low fire to high fire in some cases is controlled by proprietary algorithms programmed into the furnaces control circuitry While the theory is relatively consistent the programmed logic learns the demands of the space and will respond consistently to calls from the thermostat based on the past calls a precise reproducible model appears to be unachievable and despite numerous attempts we have been unable to gain access to the proprietary algorithms from manufacturers One way in which it might be possible to check the operational delay of low versus high output modes is to modify the DIP switches in accordance with the furnace owners manual See Figure B 21 below for a typical switch diagram In two stage mode this particular furnace will California Public Utilities Commission B 28 February 8 2010 J KEMA Appendices have a 1 12 minute delay which will vary based on previous usage The other DIP option will produce a 5 minute delay between low and high firing modes regardless of previous usage Unfortunately this solution will not work for all makes and models The lack
106. ta that you do not intend to use In the end the participant and non participant data were combined to calculate the meter ratios in order to maximize the pool of available data 20 SCE Savings Page 3 Question 20 In the report it states that SCE s per unit savings were not broken down by region and Estimates 6 therefore the weighted average of estimates was applied across the Inland and Coastal regions In our 4th Quarter report we provided per unit ex ante estimates that were climate zone dependent and therefore did vary by region If you can t find that information can you please submit a data request to SCE so we can provide that to you again to have it addressed in the final report California Public Utilities Commission L 10 February 8 2010 J KEMA Appendices SOURCE Subject Section Type Comment or Question Page Response 20 Our copy of the SCE 4th Quarter report downloaded from the EEGA website does not show measures by region for SCE 2505 whole building measures We did see inland coastal and desert measures for some measures for SCE 2510 and SCE 2517 but not for SCE 2505 We have double checked the report posted on the website and found nothing to contradict our findings in any of our tracking data sources 21 SDGE S Complianc p 1 20 Question 21 The result from the compliance models relative to the metered data suggests that the CG e Models models are highly i
107. testing conditions wind etc 11 If flow exponent is within range test is complete 12 Note any unusual testing conditions wind etc To check each test calculate flow exponent as for the blower door test previous page The flow exponent n In Q Q In P P If flow exponent not between 0 50 and 0 75 repeat test B 3 End Use Meter Data Collection This plan entails equipment monitoring at the primary residence s for the following equipment comprising the three Title 24 end uses over the course of one year 1 Central and wall air conditioning units 2 Domestic hot water heaters and boilers 3 Central and wall heating systems B 3 1 Cooling Equipment End Use Metering 1 Data points to be metered a Time series current logging of the unit California Public Utilities Commission B 17 February 8 2010 J KEMA Appendices 2 Monitoring equipment to be used a Hobo U12 006 4 channel logger with appropriate Or b Owl 400 with appropriate CT for current monitoring 3 Sampling interval and Duration of metering a Loggers are typically set at 15 or 20 minute sampling interval b Duration of metering is for a full year 4 Hobo U12 006 Logger and Associated Sensors see Figure B 14 Onset 0 50A CTV B Current Transducer Figure B 14 Onset 0 50A CTV B Current Transducer Figure B 15 Hobo U12 006 4 Channel External Logger California Public Utilities Commission B 18 February 8 2010 J KEMA Appen
108. the flow exponent n Use the following formula n IN Qs0 Qz25 IN Pso P25 Note Qso and Q25 are the flows through the blower door at the testing pressures which are denoted P5 and P25 Depending on the test you may not get the house to exactly 50 or 25 Pa WRT outside Use the exact AP you measure when checking the flow exponent For example if the house gets to 48 Pa for the high AP use this as the Ps in the equation If the flow exponent is not between 0 50 and 0 75 repeat the test Note testing conditions if windy inaccessible room s garage door open or closed etc B 2 2 Total Duct Leakage Protocol To measure the HVAC system duct leakage a Minneapolis Duct Blaster was used The Minneapolis Duct Blaster measures the amount of leakage in the duct system by pressurizing the ducts with a calibrated fan and simultaneously measuring the air flow through the fan The duct blaster fan is connected directly to the duct system in a house typically at a central return or at the air handler cabinet The remaining registers and grilles are taped off The duct system is then pressurized to 25 Pa and duct system leakage is measured using a digital pressure California Public Utilities Commission B 13 February 8 2010 J KEMA Appendices gauge The test is done in order to measure total duct leakage which includes leakage inside the thermal envelope of the home B 2 2 1 Setup Procedure for Total Duct Pressurization Test 1 Ma
109. the number of participant homes that were committed under the Programs not actually constructed during that time frame However for the 2006 2008 Program Cycle the CPUC required the IOUs to only report units that were completed Therefore there is no lag for the 2006 and 2007 Whole House Participants 15 Construction Industry Research Board CIRB 16 Participant data was collected from the following sources EVALUATION MEASUREMENT AND VERIFICATION OF THE 2002 amp 2003 CALIFORNIA STATEWIDE ENERGY STAR NEW HOMES PROGRAM June 2006 RLW Analytics EVALUATION MEASUREMENT AND VERIFICATION OF THE 2004 amp 2005 CALIFORNIA STATEWIDE ENERGY STAR NEW HOMES PROGRAM July 2007 RLW Analytics California IOU program tracking data for 2006 2007 17 RAISING THE BAR THE EFFECT OF THE CALIFORNIA 2005 ENERGY EFFICIENCY STANDARDS ON RESIDENTIAL NEW CONSTRUCTION PROGRAM DESIGN 2006 AESP Harcharik Wolf Blanke California Public Utilities Commission F 4 February 8 2010 J KEMA lt Appendices Figure F 1 Single Family Homes Built in California since 1998 180 000 160 000 140 000 120 000 100 000 80 000 60 000 40 000 20 000 0 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 E Single Family Homes Table F 1 California Single Family Home Construction and Participation All New ENERGY Whole House of New Homes IOU All SF New STAR Homes
110. these varied by utility and by whole building systems analysis industrial participants Can this information be included and clearly explained in the report Response 15 We added an Appendix K to the final version of the report that provides these statistics The second to last sentence of the comment seems to be written for non residential while we can break out these statistics by utility all the residential participants were whole house participants California Public Utilities Commission L 8 February 8 2010 J KEMA Appendices SOURCE Subject Section Type Comment or Question Page 16 PGE self 3 3 Question 16 How was self selection bias addressed SCE selection bias Response 16 We took a number of measures to minimize the potential for systematic biases in who had the opportunity willingness to be metered visited for on site surveys First we offered 50 100 in incentives to overcome resistance from less interested occupants Further recruitment efforts were conducted using a Computer Aided Telephone Interview CATI system We attempted to contact a household multiple times over different times of the day up until 8 pm different days of the week including weekends and different weeks of the recruiting periods Detailed disposition codes were updated after each attempted contact 17 SCE H Factor Page 3 Question 17 There needs to be an analysis in the report or
111. u get information about the program AP4 What aspects of the program were most important in your decision to participate AP5 Were there any aspects of the program that caused you concern What helped you overcome your concerns enough to participate AP6 What benefits did you receive from participating in the program SATISFACTION S1 IF APPLIANCE TRACK How satisfied were you with the types of energy efficient appliances that were covered by the program California Public Utilities Commission H 4 February 8 2010 J KEMA Appendices Extremely dissatisfied Dissatisfied Neither satisfied nor dissatisfied Satisfied Extremely satisfied ooo 2 IF APPLIANCE TRACK Why do you say that S3 IF APPLIANCE TRACK How satisfied were you with the amounts of the incentives for each of the following energy efficient appliances and or lighting READ ONLY APPLIANCE TYPES CONFIRMED IN PB3 DW CW RF CD Lighting Extremely dissatisfied Dissatisfied Neither satisfied nor dissatisfied Satisfied Extremely satisfied D 2j ojoj v S4 IF APPLIANCE TRACK Why do you say that IF LEVELS OF SATISFACTION ARE DIFFERENT FOR DIFFERENT APPLIANCES ASK ABOOUT INDIVIDUAL LEVELS S5 IF PERFORMANCE TRACK What type of design technical assistance did the program provide to your project S6 IF PERFORMANCE TRACK How satisfied were you with the design technical assistance provided through th
112. uation is presented in the NCCS report Vol Ill section 5 2 2 Residential New Construction Evaluation A subset of baseline study on site homes in addition to the standard on site data collection had one or more major end use air conditioning heating or water heating metered The energy use for these homes was also modeled using software typically used to determine compliance with California s Title 24 building code The RNC evaluation used this information to estimate the ratio between metered energy use and modeled energy use These ratios calculated by climate region were used to adjust the modeled energy that was available for all participant homes to more accurately reflect actual usage patterns Detailed information on how the baseline study data were analyzed and used for the RNC evaluation is reported in the NCCS report Vol sections 3 1 methodology and 3 4 3 results This appendix presents additional information of interest that was not included in the other analyses The information is similar to that included in the Phase 1 RNC Market Effects Report but has been updated to include all 422 on sites completed as part of the Baseline Study e Glazing 14 Refer to the Residential New Construction Market Effects Study Phase Draft Report March 2009 for background information on the detailed methodology and the building characteristics listed relate to the Residential Title 24 Standards California Public Utilit
113. uit Details cc8etissataiscedarecdatanansstdntscenel ates detds utecitmedald Jooieet eect laut dance ueecsnatseeade B 22 California Public Utilities Commission ii February 8 2010 KEMAX Appendices Table of Contents Figure B 18 Domestic Hot Water Data Logger Installation cece ceeeeeeeeeeeeeeetttteeeeeeeeteeeeee B 23 Figure B 19 G4 Gas Sub Meter ei cctisncnceretdsienmsenteendctsnneldadubdenenddeniniinnuatnoslenlbiawnsncatltmediaebanss B 25 Figure B 20 Typical Logger Installation for Forced Air Furnaces B 27 Figure B 21 Typical Switch Dara acciccsentissancistecocaincena iedactsnes cudedscavsunchincdietecsddeaedicedetauseaece B 29 Figure F 1 Single Family Homes Built in California Since 1998 eee eeseteeeeeeeeeeeeeeeee F 5 Figure F 2 Percentage of SF Homes with 2 paned Vinyl Low E Windows cccceeeeeees F 8 Figure F 3 AFUE Distribution Average Statewide eeccccceeeeesseeecceeeeeeeeeeeeenaaeeeeeeeeeeeeaaa F 9 Figure F 4 SEER Distribution Average Statewide ccccceeeeeeeenneeeeeeeeeeeeeeenaaeeeeeeeeeeee F 10 Figure F 5 Multiple HVAC System Statewide Average eeeeeeeeeeeeeeeeeeeeeeeenttaeeeeeeeeeeeeee F 11 Figure F 6 Percentage of Instantaneous Water Heaters Gas and Electric F 12 Figure F 7 Homes with More than One Water Heating Unit eee cieeeeeeeeeeneeneeeeeeeeeeeeee F 12 Figure F 8 Percentage of Homes with Radiant Barriers 0 eee
114. uters h Number of non lamped ceiling fans and location B 2 Performance Testing B 2 1 Whole House Infiltration To measure the infiltration of a home we used the Minneapolis blower door The Minneapolis blower door uses a fan and frame assembly that is temporarily sealed into an exterior doorway The testing was performed at a pressure difference of 50 Pa 0 2 inches of water column to create a slight pressure difference between the inside of the home and outside Using a digital pressure gauge to measure the air flow that is required to maintain 50 Pa the air tightness of the house can be gauged B 2 1 1 Setup Procedure for Blower Door Test 1 Close all windows and doors to the outside 2 Open all interior doors and supply registers 3 Close all dampers and doors on wood stoves and fireplaces Seal fireplace or woodstove as necessary to prevent ash blowback into occupied spaces 4 Make certain furnace and water heater cannot come on during test California Public Utilities Commission B 7 February 8 2010 J KEMA Appendices 5 Put water heater and or gas fireplace on pilot setting if they are within the conditioned space 6 Make certain all exhaust fans and clothes dryer are off 7 Make certain any other combustion appliances will not be backdrafted by the blower door 8 Make certain doors to interior furnace cabinets are closed 9 Also make certain crawlspace hatch is on even if it is an outside acce
115. you say the program was not a critical factor in your decision to build to program requirements How so C17 C19 C18 Subsequent to your participation in the CMFNC program has what you learned about multifamily energy code from the HMG plan review affected your design of any non program multifamily buildings 1 Yes 2 No SKIP TO W1 98 Don t Know SKIP TO W1 99 Refused SKIP TO W1 How has have the design s been affected How many multifamily building designs have been affected How many housing units are in each of these buildings California Public Utilities Commission H 15 February 8 2010 J KEMA Appendices WRAP UP have just a few more questions then we are done with the interview W1 Overall what aspects of the CMFNC Program do you think work best W2 What about the program needs the most improvement W3 Is there anything else you would like to tell me about the program THANK YOU VERY MUCH California Public Utilities Commission H 16 February 8 2010 J KEMA lt Appendices I Designed for Comfort Onsite Inspection Forms California Public Utilities Commission l 1 February 8 2010 J KEMA Appendices CPUC DFC Onsite Verification Survey Form MiraVista Pepperwood 1 11 Case 1 12 Project 1 13 Bldg 1 14 Housing Unit 1 15 of Bdrms 1 16Lg Small MiraVista 1 17 Field Staff Name 1 18 Date mm dd yy 1 19 Time 1 20 Occupied 1 21 Bldg mgr have any probl
116. ype iii R value iv Orientation N S E W v Shading vi Number and Type of Doors vii Wall Area b Windows i Number of panes ii Glass type clear tinted reflective LowE using EKT detector iii Frame type metal vinyl wood iv Frame Style fixed slider etc v Height and width of each window vi Quantity of each type vii Internal External Shading California Public Utilities Commission B 3 February 8 2010 J KEMA Appendices viii Orientation c Interior Walls i Height and width d Roofs i 1 Type ii 2 Surface area iii 3 Surface Tile Shingle etc iv 4 Color v 5 Ceiling insulation R value or type e Floors i Number of Floors ii Total Conditioned Floor Area 1 Ground Floor Area iii Construction Type slab crawl space open iv Area of Exposed Slab or perimeter v Area Over Unconditioned Garage vi Raised floor R Value if available 4 Lighting a Interior Lighting to be catalogued in Title 24 spaces defined by usage The following parameters will be collected for all interior lights i Fixture type ii Fixture wattage California Public Utilities Commission B 4 February 8 2010 J KEMA Appendices b iii Lamps per fixture iv Lamp wattage v Mounting type recessed direct indirect direct indirect track plug in task or furniture integrated task vi Control strategy switch dimmer occupancy sensor etc Exterior Lighting The following parameters will

Residential New Construction (RNC)

Contents

Download Pdf Manuals

Related Search

Related Contents