Refrigeration Subcommittee

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

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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 - PowerPoint PPT Presentation

Transcript of Refrigeration Subcommittee

Page 1: Refrigeration Subcommittee

July 26, 2014

Refrigeration SubcommitteeProposed Revision of Refrigeration Provisional Data Requirements

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Data Collection for demonstration projects

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Demonstration project data collection best practices method

Compressor power (kW) and energy15 minute interval data compressor current

15 minute interval data compressor current

15 minute interval data compressor current

15 minute interval data compressor current

Condenser fan electric power (and pump motor for evaporative-cooled condensers) (kW) and energy

15 minute interval data fan current

15 minute interval data fan current

Display case electric power (kW) and energy

15 minute interval data for lighting and ASH circuits

15 minute interval data for lighting and ASH circuits

Walk-in electric power (kW) and energy

15 minute interval data for motor circuits

15 minute interval data for motor circuits

Outside air temperature Available online / from EMS Available online / from EMS Available online Available online

Suction Pressure (psig)From EMS, 3 day samples pre and post

From EMS, 3 day samples pre and post

Discharge pressureFrom EMS, 3 day samples pre and post

From EMS, 3 day samples pre and post

Outside relative humidity Available online Available online Available online Available online

TMY3 NOAA data for weather site used in DOE2.2r

Available online Available online Available online Available online

Project #1 (FHPC LT/MT) Project #2 FHPC LT/MT)Project #3 (Case LED, ASHC and WI ECM)

Project #4 (Case LED, ASHC and WI ECM)Measurement

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Demonstration project data collection best practices method

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 timeo Maximum 5-minute interval datao 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 onceo Amps measured over timeasured onceo 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 datao Volts and power factor (3-phs) measured one timeo 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 datao Volts and power factor (3-phs) measured one timeo 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 typeo Shaded to prevent solaro Maximum 30-minute log data, maximum sampling time 1-minuteo Accuracy +/- 1 F

Suction Pressure (psig) o From EMS, 3 day samples pre and post

o Pressure sensor with +/- 2% of FSo 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 FSo Maximum sampling time 5 seconds, maximum 5-minute log data

Outside relative humidityo Hourly weather data from Vancouver airport NOAA station

o Accuracy of +/- 2% RH between 10% and 90%o Maximum sampling time 1-minuteo 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

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Project #1

Data Collection and Calibration

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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

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Regression analysis

Pre measure implementation

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Regression analysis

Post measure implementation

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Regression analysis

Pre measure implementation

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Regression analysis

Post measure implementation

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Best Practice model results

Pre: kWh = 3.4238(Temp) +422.39Post: kWh=-1.486(Temp) + 584.74

kWhPre 221,697Post 184,123Savings 37,573% Savings 17%

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Simplest reliable method

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SRM analysis

• Audit data collected (See protocol appendix)

• DOE2 Simulation with TMY3

kWhPre 375,103Post 320,687Savings 54,416% Savings 14.5%

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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

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SRM Results

kWhPre 229,914Post 192,988Savings 36,926% Savings 16%

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Comparison of BP and SRM

Best Practices Original SRM % BP to SRM Adjusted SRM % BP to SRMPre 221,697 375,103 69% 229,914 4%Post 184,123 320,687 74% 192,988 5%Savings 37,573 54,416 45% 36,926 -2%

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©2014 PECI All rights reserved.

Thank you [email protected]

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Demonstration project data collection simplest reliable method

Compressor power (kW) and energy15 minute interval data compressor current

15 minute interval data compressor current

15 minute interval data compressor current

15 minute interval data compressor current

Condenser fan electric power (and pump motor for evaporative-cooled condensers) (kW) and energy

15 minute interval data fan current

15 minute interval data fan current

Display case electric power (kW) and energy

15 minute interval data for lighting and ASH circuits

15 minute interval data for lighting and ASH circuits

Walk-in electric power (kW) and energy

15 minute interval data for motor circuits

15 minute interval data for motor circuits

Project #1 (FHPC LT/MT) Project #2 FHPC LT/MT)Project #3 (Case LED, ASHC and WI ECM)

Project #4 (Case LED, ASHC and WI ECM)Measurement

Remove what was not used for model, a

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Revisions: Table 8.1 Provisional Data Collection

Best Practice Method

Requirement

Measurement of electrical energy use of each compressor.

Electric power (kW) measured over time

Determining compressor capacity using compressor performance data (kW/ton)

Maximum 5-minute interval data

Data collection must use watt meter as compressor effi ciency and power factor varies with load on motor.

Same interval as compressor data.

Volts and power factor (3-phs) measured once

Amps measured over time

If there is a VFD or 2-speed fan, watt meter data is needed as motor effi ciency and power factor varies with load

Maximum 15-minute interval data

Volts and power factor (3-phs) measured one time Amps measured over time to estimate kWh.

Maximum 15-minute interval data

Volts and power factor (3-phs) measured one time Amps measured over time to estimate kWh.

Walk-in electric power (kW) and energy

Measurement of fan, l ights, and defrost

Diagnostic

Regression Input for walkin-specific load measures. For all other measures, provides insight as regression input where available

Condenser fan electric power (and pump motor for evaporative-cooled condensers) (kW) and energy

Measurement of electrical energy use of condenser fans and pumps.

Diagnostic

Regression Input for system measures. For all other measures, provides insight as regression input where available

Display case electric power (kW) and energy

Measurement of fan, l ight, defrost, and ASH electrical energy use

Diagnostic

Regression Input for case-specific load measures. For all other measures, provides insight as regression input where available

Measurement UseCandidate Simplified Method Requirement

Description

Compressor power (kW) and energy Diagnostic

Regression Input for system measures. For all other measures, provides insight as regression input where available

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Revisions: 8.1 Provisional Data Collection

Drybulb or wetbulb, depending on condenser type

Shaded to prevent solar Maximum 30-minute log data, maximum sampling time 1-minute Accuracy +/- 1 F Maximum 15-minute interval data (for electric and gas use) Electric energy (kWh)

Data collection must use watt meter as compressor effi ciency and power factor varies with load on motor.

Gas energy (cu ft and energy content from utility) Can use whole building gas meter if other uses of gas are identified as being constant (e.g. water heating).

Pressure sensor with +/- 2% of FS

Maximum sampling time 5 seconds maximum 5-minute log data

Discharge pressure Pressure sensor with +/- 1% of FS

(psig) Maximum sampling time 5 seconds maximum 5-minute log data

Accuracy of +/- 2% RH between 10% and 90% Maximum sampling time 1-minute

Maximum log time 30 minutes

Determining compressor capacity using compressor performance data (need kW/ton)

To test that compressor performance data is correct and same load

Provides insight as regression input where available

Outside relative humidityEvaporative cooled condensers performance regression

Diagnostic for applicable measures (Evap cond)

Provides insight as regression input where available

HVAC end-use (kWh) and ThermsEnergy savings for measures with interactive effects

DiagnosticRegression Input for applicable measures

Suction Pressure (psig)Determining compressor capacity using compressor performance data (need kW/ton)

To test that compressor performance data is correct and same load

Provides insight as regression input where available

Outside air temperature Variable in regression model, diagnostics on condenser energy use

Diagnostic Regression input

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Revisions: 8.1 Provisional Data Collection

Maximum 15-minute log data, maximum sampling time 1-minute Drybulb Temperature Accuracy +/- 1 F Accuracy of +/- 2% RH between 10% and 90% Maximum log time 15 minutes, maximum sampling time 1 minute

Local real-time data for the measurement period:

Temperature

Temperature, Relative Humidity, For refrigeration

Correlation between site temperatures and weather station data

Local solar cloud cover for HVAC loads.Calculator diagnostics For a sample of display cases and walk-insCalculator diagnosticsA trend log per l ine-up. One time line-up checked for consistency in temp

Indoor temperature (store and next to walk-ins)

Infiltration of the cases acting with the indoor air. Also indicates what HVAC setpoints are and when it is operating

Yes, for measures that change infiltration

Yes, for measures that change infiltration

Indoor humidity (store and next to walk-ins)

Infiltration of the cases acting with the indoor air

Yes, for measures that change infiltration

Yes, for measures that change infiltration

TMY3 NOAA data for weather site used in DOE2.2r

Yes Yes

Door open time (display case and walk-in)

Not required but provides insight if available

Not required but provides insight if available

Provides diagnostics on walk-in load and display case load

Display case and walk-in air temperature

Not required but provides insight if available

Not required but provides insight if available

Provides diagnostics on walk-in load and display case load

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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

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Calibration: Keyword adjustments

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Calibrated model results

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Data Collection

Individual compressor data

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Next Steps

• Recommendations on approach, documentation• Review next projects as available