1. July 26, 2014 Refrigeration Subcommittee Proposed Revision of Refrigeration Provisional Data Requirements

2. Data Collection for demonstration projects

3. 3 Demonstration project data collection best practices method

4. 4 Measurement Projects actual measurements Best Practices from Table 8.1 Compressor power (kW) and energy o 15 minute interval data compressor current (3-phs). Volts measured once. o Electric power (kW) measured over time o Maximum 5-minute interval data o Data collection must use watt meter as compressor efficiency and power factor varies with load on motor. Condenser fan electric power (and pump motor for evaporative-cooled condensers) (kW) and energy o 15 minute interval data fan current (3-phs). Volts measured once. o Same interval as compressor data. o Volts and power factor (3-phs) measured once o Amps measured over timeasured once o If there is a VFD or 2-speed fan, watt meter data is needed as motor efficiency and power factor varies with load Display case electric power (kW) and energy o 15 minute interval data for lighting and ASH curcuits o Maximum 15-minute interval data o Volts and power factor (3-phs) measured one time o Amps measured over time to estimate kWh Walk-in electric power (kW) and energy o 15 minute interval data for motor circuits o Maximum 15-minute interval data o Volts and power factor (3-phs) measured one time o Amps measured over time to estimate kWh Outside air temperature o Hourly weather data from Vancouver airport NOAA station o Drybulb or wetbulb, depending on condenser type o Shaded to prevent solar o Maximum 30-minute log data, maximum sampling time 1-minute o Accuracy +/- 1 F Suction Pressure (psig) o From EMS, 3 day samples pre and post o Pressure sensor with +/- 2% of FS o Maximum sampling time 5 seconds, maximum 5-minute log data Discharge pressure o From EMS, 3 day samples pre and post o Pressure sensor with +/- 1% of FS o Maximum sampling time 5 seconds, maximum 5-minute log data Outside relative humidity o Hourly weather data from Vancouver airport NOAA station o Accuracy of +/- 2% RH between 10% and 90% o Maximum sampling time 1-minute o Maximum log time 30 minutes TMY3 NOAA data for weather site used in DOE2.2r o Hourly weather data from Vancouver airport NOAA station o Temperature o Correlation between site temperatures and weather station data

5. Project #1 Data Collection and Calibration

6. 6 Regression analysis (Best Practices) Collection Periods: Pre: 2/27 to 4/22 Post: 4/22 to 7/9 Methodology for regression Average daily temp from NOAA as independent Averaged hourly compressor power Compressor power as dependent Linear regression Method for calculating annual savings Applied linear regression to average daily TMY3

7. 7 Regression analysis Pre measure implementation

8. 8 Regression analysis Post measure implementation

9. 9 Regression analysis Pre measure implementation

10. 10 Regression analysis Post measure implementation

11. 11 Best Practice model results Pre: kWh = 3.4238(Temp) +422.39 Post: kWh=-1.486(Temp) + 584.74 kWh Pre221,697 Post184,123 Savings37,573 % Savings17%

12. Simplest reliable method

13. 13 SRM analysis Audit data collected (See protocol appendix) DOE2 Simulation with TMY3 kWh Pre375,103 Post320,687 Savings54,416 % Savings14.5%

14. 14 Calibration adjustments Focused on rated compressor power and capacity Used manufacturer’s selection tool as a guide Increased capacity and power to adjust baseline and savings

15. 15 SRM Results kWh Pre229,914 Post192,988 Savings36,926 % Savings16%

16. 16 Comparison of BP and SRM

17. ©2014 PECI All rights reserved. Thank you subcommittee! bowens@peci.org

18. 18 Demonstration project data collection simplest reliable method Remove what was not used for model, a

19. 19 Revisions: Table 8.1 Provisional Data Collection

20. 20 Revisions: 8.1 Provisional Data Collection

21. 21 Revisions: 8.1 Provisional Data Collection

22. Calibration: Model parameter examples Compressors  Rated power  Rated refrigerant flow  Evaporator superheat  Return gas temperature  COP curves Loads  Fixture infiltration  Light, fan, and ASH absorbed into fixtures  Sales space humidity levels

23. Calibration: Keyword adjustments

24. Calibrated model results

25. 25 Data Collection Individual compressor data

26. Next Steps Recommendations on approach, documentation Review next projects as available