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PLAN TO IMPLEMENT PROVISIONAL DATA
REQUIREMENTS IN SUPPORT OF THE STANDARD
SAVINGS PROTOCOL FOR GROCERY REFRIGERATION
SYSTEM MEASURES
Submitted to
REGIONAL TECHNICAL FORUM
Submitted by
Portland Energy Conservation Inc.
100 SW Main St, Ste 1600
Portland, OR 97204
June 28, 2011
Plan to Implement Standard Savings Protocol - Grocery Refrigeration System Energy Savings Calculator
TABLE OF CONTENTS
1. OVERVIEW.......................................................................................................... 2
1.1. Best Practice Savings Estimate and Sampling .................................................................... 2
1.1.1. Best Practice Savings Estimate ........................................................................................... 2
1.1.2. Sampling ............................................................................................................................. 3
1.2. Calculator Comparison and Adjustments .......................................................................... 4
1.3. Simplification of Protocol................................................................................................... 4
Portland Energy Conservation Inc
Plan to Implement Standard Savings Protocol - Grocery Refrigeration System Energy Savings Calculator
1. OVERVIEW
This document accompanies the provisional “Standard Savings Estimation Protocol for Grocery
Refrigeration System Measures” and assumes the reader has read the standard protocol. The document
describes the research that needs to be performed in order to meet the provisional data requirements
outlined in Section 8 of the standard protocol.
The research plan includes the following components:
•
Establish best practice savings estimates using data gathered by the application of the
provisional standard protocol to a sample of grocery refrigeration projects1.
•
Test the candidate savings estimation method,2 based on DOE 2.2 refrigeration version
(DOE2.2r), site-specific inputs and default parameters to determine whether it provides reliable
savings estimates. Determine whether the calculated refrigeration energy consumption reliably
approximates actual energy use across a wide range of system types and configurations. If the
estimates do not achieve the standard set in the Guidelines,3 determine what changes to data
collection or modeling strategy are needed to achieve reliable estimates.
•
Search for the simplest reliable method to predict savings. Determine what simplifications can
be made to data requirements or modeling strategy of the candidate method and still achieve a
reliable estimates of savings.
1.1. Best Practice Savings Estimate and Sampling
1.1.1. Best Practice Savings Estimate
Provisional data requirements are outlined in Section 8 of the “Standard Savings Estimation Protocol for
Grocery Refrigeration System Measures,” and specify end use data collection requirements. Data from
the metered equipment will be aggregated appropriately to represent overall refrigeration system
energy use. Daily or hourly energy usage models will be developed for the pre- and post-implementation
periods, depending on which level of aggregation provides the best model precision. Energy use for
refrigeration systems generally follows linear or linear change point models with outside air
temperature as the primary independent variable. In some cases, other independent variables, such as
store operation hours may be included as needed. The models will be used to estimate annual average
pre- and post-implementation energy using TMY data. The difference between the annual estimates
1
Refer to the Definition of Terms in the “Standard Savings Estimation Protocol for Grocery Refrigeration System Measures”
2
Refer to the Definition of Terms in the “Standard Savings Estimation Protocol for Grocery Refrigeration System Measures”
3
Regional Technical Forum. Guidelines for the Development and Maintenance of RTF Savings Estimation Methods. June 1, 2011.
2
Portland Energy Conservation Inc.
Plan to Implement Standard Savings Protocol - Grocery Refrigeration System Energy Savings Calculator
represents annual kWh savings, which can also be compared to the DOE2.2r results with TMY weather
input.
1.1.2. Sampling
The best practice savings estimate is only required for a sample of sites with refrigeration projects. The
sample of projects should capture measures that are frequently implemented and/or produce
significant program savings as well as a representative range of store and/or system conditions that
users of the standard protocol expect to encounter. Load measures and system measures1 have
different inputs and calculation methodologies; thus, the sample should contain a mix of these projects.
The range of store conditions is best captured through sample stratification by building size categories.
Including different building size categories in the sample ensures there are projects with different
system configurations and store types (e.g. convenience, grocery, big box). Three building size categories
are recommended: less than 10,000 square feet, 10,000 to 30,000 square feet, and greater than 30,000
square feet. These categories are based on observed break points in project size (kWh) based on 2010
program data.
It is assumed that all or most of the trend data will be collected by a third party evaluator, with support
from PECI as needed. Utility program impact evaluation staff and their third-party evaluation
contractors will have final say in the sample selected, though, the evaluation sample will likely overlap
considerably with the sample recommendations outlined in this document. Any areas that do not
overlap can be assessed and planned for accordingly. Involving program impact evaluators during data
collection and analysis will add credibility to the research.
Where available, data collection should include whole building interval meter data as well as
refrigeration temperature and pressure trends from the store Energy Management System. (The EMS
should be checked for accuracy.) These data will provide context for store operation during the
monitoring period. At the time this research plan is being written, whole building interval meter data are
available in PSE, EWEB, Seattle City Light and Tacoma service territory on a limited basis.
If system measures that are sensitive to ambient conditions are implemented (such as floating head
pressure control), data collection should account for the time required to collect a sufficient range of
ambient temperatures, schedules, and load conditions to produce reliable regressions for refrigeration
use. Shoulder seasons are more likely to provide the temperature range needed for the analysis.
Table 1 provides a proposed sample design. For an assessment of load measures, sample sizes would
ideally and at minimum be based on an 80 percent confidence level, 20 percent precision, and a
coefficient of variation (CV) of 0.5. This assumes independent samples are drawn from each store size
strata for load measures. System measures such as floating head pressure control generate significant
savings but are implemented infrequently. Given the infrequent implementation of these measures, at
least six sites should include a system measure.
Portland Energy Conservation Inc.
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Plan to Implement Standard Savings Protocol - Grocery Refrigeration System Energy Savings Calculator
Table 1. Proposed Sample Sizes
Store Floor Area
Load Measures
System
Measures
Total
Less than 10,000
10
2
12
10,000-30,000
10
2
12
Greater than 30,000
10
2
12
Total
30
6
36
1.2. Calculator Comparison and Adjustments
Once best practice savings models are derived, the following steps should be implemented to confirm
the calculator’s ability to estimate baseline and post implementation case energy use.

Compare baseline best practice energy use estimate to baseline calculator-estimated refrigeration
baseline energy use.

Compare post-implementation best practice energy use estimate to calculator-estimated
refrigeration energy use after measure installation.

Compare best practice savings estimate to calculator-estimated savings.

Examine differences between the best practice savings estimate and calculator estimate, and
identify commonalities (i.e., weather, refrigeration system configuration, refrigeration system loads,
and measures implemented) between projects with large differences.

Modify influential DOE-2.2R keywords and assumptions (within the band of physically plausible
input values) to improve the model reliability. Refer to document “Standard Savings Estimation
Protocol for Grocery Refrigeration System Measures” for a list of DOE2.2R keywords.

Check baseline and post energy estimates to ensure each adjustment improves the overall
performance of the calculator. This will be an iterative process until the baseline energy use, post
energy use and energy savings at all sites are reasonable and there is no significant bias.

Run DOE2.2r input file through DOE2.2r independent of any front-end audit tool or data input
device. Confirm calculations are the same as with front-end tool to ensure there is no unintended
change to DOE2.2r calculations.
1.3. Simplification of Protocol
After empirical data is compared to the calculator, PECI will examine the calculation method for any
possible simplifications. Simplified areas could include cutting unnecessary site-specific data collection
4
Portland Energy Conservation Inc.
Plan to Implement Standard Savings Protocol - Grocery Refrigeration System Energy Savings Calculator
or other calculation steps that will provide an optimal protocol for calculating refrigeration system
savings.
Portland Energy Conservation Inc.
5
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