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Refrigeration Subcommittee

Refrigeration Subcommittee. Proposed Revision of Refrigeration Provisional Data Requirements. July 26, 2014. Data Collection for demonstration projects. Demonstration project data collection best practices method. Demonstration project data collection best practices method. Project #1

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Refrigeration Subcommittee

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

  2. Data Collection for demonstration projects

  3. Demonstration project data collection best practices method

  4. Demonstration project data collection best practices method

  5. Project #1 • Data Collection and Calibration

  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. Regression analysis Pre measure implementation

  8. Regression analysis Post measure implementation

  9. Regression analysis Pre measure implementation

  10. Regression analysis Post measure implementation

  11. Best Practice model results Pre: kWh = 3.4238(Temp) +422.39 Post: kWh=-1.486(Temp) + 584.74

  12. Simplest reliable method

  13. SRM analysis Audit data collected (See protocol appendix) DOE2 Simulation with TMY3

  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. SRM Results

  16. Comparison of BP and SRM

  17. Thank you subcommittee! bowens@peci.org

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

  19. Revisions: Table 8.1 Provisional Data Collection

  20. Revisions: 8.1 Provisional Data Collection

  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. Data Collection Individual compressor data

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

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