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Developing the Business Case for Updating the Region’s End-use Load ShapesAssessment of Findings

Presented by Curt Puckett and Lorin MolanderAugust 21, 2012

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Overview of PresentationProject Objectives

Overview of End-Use Data

Findings from Stakeholder Webinars & Interviews

Updates Since 2009

National Perspectives & Resources

Preview of Business Case

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August 21 2012

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Project Objectives Develop the business case for a comprehensive PNW electric end-use data

collection study

- Assessment of Regional Interest and Need- Assessment of Updates since 2009 KEMA Study- Assessment of National and Out-of-Region Resources- Assessment of the No Action Option- Analysis of Options for Proceeding with Study- Develop the Business Case for a Range of Viable Options

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August 21 2012

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Section 3: Overview of End-Use Data

Background and context:• What is it?• Who uses it?• How is it used?• How is it collected or developed?• Existing data sources

NEEA RBSA metering data provided by Ecotope

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Section 4: Assessment of Regional Interest and Need Objective: Lay the foundation for the business case by assessing the

current interests and needs of the region’s stakeholders.

Process: Webinars and Interviews, discussing:- How do the groups currently use end use information, - How do the they envision using the data in the future, - What are the risks associated with continuing to use the current data,- What business decisions are being made based on their analyses, and - What are their current data requirements and priorities?

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August 21 2012

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Webinar Series

Webinar Date No. of Attendees Organizations RepresentedWebinar 1 April 25, 2012 33 American Electric Power

AvistaBC HydroBonneville Power AdministrationDominion Virginia PowerElectric Power Research InstituteNortheast Energy Efficiency Partnerships

Northwest Power Council/RTFPacific Gas & ElectricPacific Northwest National LabPuget Sound EnergySnohomish PUDVermont Dept. Public Service

Webinar 1 (Repeat) May 4, 2012 7 Bonneville Power AdministrationIdaho PowerNorthwest Power Council/RTF

Pacific Northwest National LabPuget Sound Energy

Webinar 2 May 10, 2012 19 AvistaBonneville Power AdministrationDominion Virginia PowerNorthwest Energy Efficiency Alliance

Northwest Power Council/RTFPacifiCorpPacific Northwest National LabSnohomish PUDSouthern Company

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Summary of Stakeholder Input Via Webinars A general consensus that end-use data was important to their utility’s business

operation;

While difficult to quantify the monetary benefits associated with improved information, the utilities were making significant investments based on the information flowing through the analysis;

Concern with the existing data coverage, timeliness and relevance;

The importance and need for better time-differentiated information was increasing;

The availability of supporting information had significantly increased including the expansion of smart meter investments yielding access to time-differentiated whole facility information; and

There may be various approaches that could be used to help fill the existing data gaps.

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Common Concerns About Existing Data Sources The vintage (i.e., age) of the data (1980s – early 1990s);

That appliance characteristics and usage have changed (e.g., increased efficiency standards);

There are new emerging/growing technologies (e.g., computers, plasma TVs, etc.);

ELCAP did not adequately capture small “standby” loads, which is a category of load that has grown significantly since ELCAP;

Static loads are not in the majority anymore (it’s either motors or electronics);

The existing load shape data are often “problematic” and require some conditioning, (e.g., load peaking at strange times); and

There is strong interest in measure shapes, not just end-use load shapes.

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August 21 2012

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Stakeholder Interviews Based on feedback from the webinars, interview questions were developed:

- Current State;- Current or potential use(s)- Source(s) of data- Recent updates or developments of new end-use data- Concerns/issues with current sources

- Future State;- Investment(s) based on analyses using end-use information;- Specific data requirements and supporting information;- Sampling and study preferences; and- Load shape library user preferences.

17 interviews of Pacific Northwest stakeholders:- 15 organizations were represented - 38 individuals participated

- 18 were from EE - 10 were from a load forecasting/load research- 10 were from resource acquisition, smart grid, DR, transmission, regulatory

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Summary of Stakeholder Input Via Interviews Current uses of load shapes and demand statistics

- Cost effectiveness analysis- Energy efficiency and demand response planning and evaluation- Savings forecasts, conservation potential, smart grid, cost of service and rates, load

forecasting, and measure savings/load impacts - Distribution planning, resource planning, and load composition modeling

Potential uses of end-use load shapes or demand statistics- Provide the effects of energy efficiency on capacity and capacity-related charges- Better differentiate economic from appliance trends- Inform data validation routines - Provide input to new rate designs - Support dynamic profiling- Help characterize “new” loads including electric vehicles

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Business Decisions & Investments Based on Analyses Whether to add in demand-side or supply-side resources;

Which energy efficiency or demand response programs to pursue based on expected savings;

Where to set energy efficiency program incentive levels,

How to improve program forecasting, program targets, total budgets;

Cost-effectiveness, what investments should be made in which programs;

How to allocate within a cost of service study;

Analyze new rate designs, e.g., time-of-use rates; and

New technology investments related to smart grid.

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Business Decisions & Investments Based on Analyses (cont.)

Importance of end-use load shape data to analyses overall - On a scale of 1 to 7 (with 1 being not at all important

and 7 being very important)- About half ranked the importance of end-use load

shape data to their analyses overall as a 5, 6, or 7 0

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How much investment does your organization make overall related to analyses - While difficult to quantify a direct link, the overall level of investment made, in part, based on

the end-use data was significant- Numbers in the “millions” of dollars were commonly stated- What was unclear is how better or more current information would have altered those

decisions

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Importance of Accurate Load Shapes

Importance of accuracy of end-use information to overall results- Slightly more than half said that the accuracy ranked a

6 or a 7 in importance to the overall results of their analyses 0

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Rank - Scale 1 to 7

Risks of using potentially inaccurate load shapes - Making poor investment decisions;- Implementing energy efficiency programs that are not cost effective;- System operations (i.e., managing load) are at risk without better information;- Potentially target too much or too little conservation;- Not saving what we think we are during peak hours; and- Forecasting errors resulting in being too “long” or “short” on resources.

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Results of Priority Ranking – Residential End-Uses

1 2 3 4 5 6 7

Res End-use Water Heating Domestic Hot Water 1 1 1 3 5 11 5.7 Highest

Res End-use HVAC HVAC - Heating 1 1 3 1 5 11 5.5 Highest

Res End-use Other Plug Loads (Electronics) 1 1 2 2 2 3 11 4.9 Medium

Res End-use Lighting Lighting - Interior 1 1 3 1 2 3 11 4.8 Medium

Res End-use Appliances Appliances - Refrigerators 2 2 3 4 3 14 4.7 Medium

Res End-use HVAC HVAC - Cooling 2 4 2 3 11 4.6 Medium

Res End-use Appliances Appliances - Laundry 2 2 1 1 5 11 4.5 Medium

Res End-use HVAC HVAC - Fan Energy 2 1 2 1 3 2 11 4.5 Medium

Res End-use HVAC HVAC - Ventilation 2 2 3 1 3 11 4.3

Res End-use Lighting Lighting - Exterior 2 1 1 2 1 1 3 11 4.3

Res End-use HVAC HVAC - Other 2 3 2 1 1 2 11 4.0

Res End-use Appliances Appliances - Kitchen 2 2 2 2 1 2 11 3.8

Res End-use Other Pool Pump 6 1 2 9 1.6

CategoryEnd-use/MeasureClass (Number of Rankings)

Priority Ranking

N AvgGroup

PRIORITY

LOW <-------------------------------> HIGH Summary

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Results of Priority Ranking – Residential Measures

1 2 3 4 5 6 7

Res Measure Water Heating Heat Pump WH 2 1 2 2 4 11 5.1 High

Res Measure Water Heating High Effi ciency WH 3 1 2 3 3 12 4.7 MediumRes Measure Lighting Lighting Controls 2 1 1 3 1 3 11 4.6 Medium

Res Measure Lighting LEDs 2 1 1 2 2 2 10 4.5 Medium

Res Measure Refrig/Misc.EE Refrigerators, Clothes Washers, & Dishwashers 2 2 4 1 1 10 4.3

Res Measure Refrig/Misc. Smart Power Strips 2 3 2 2 1 10 4.3Res Measure HVAC AC or Heat Pump Tune-ups 3 2 2 1 2 10 4.1Res Measure Lighting Compact Fluorescent 2 2 1 1 1 1 3 11 4.1Res Measure HVAC Duct Sealing & Insulation 3 1 1 2 1 2 10 4.0Res Measure Water Heating LF Showerheads 3 1 1 3 1 1 10 3.8

Res Measure HVAC Attic, Basement, and Wall Insulation 3 4 1 1 1 10 3.7Res Measure Lighting HID Lighting 3 1 1 2 1 2 10 3.6

Res Measure HVACDouble Pane Low-e Argon-filled Windows 3 4 1 2 10 3.6

Res Measure HVAC Programmable Thermostats 3 1 2 1 2 1 1 11 3.5Res Measure Lighting T8 with electric ballast 3 2 1 1 1 2 10 3.4Res Measure Water Heating Temp Turndown 4 2 3 1 10 3.4Res Measure HVAC EE Room Air Conditioners 3 2 1 1 2 2 11 3.3Res Measure Water Heating Faucet Aerators 4 1 3 1 1 10 3.1Res Measure Water Heating Tank Wrap 4 1 1 4 10 3.1Res Measure HVAC Pipe Insulation 4 1 2 1 1 9 2.8Res Measure Water Heating Pipe Insulation 3 3 2 1 9 2.8Res Measure HVAC Storm Windows & Doors, 5 2 1 1 9 2.7Res Measure HVAC Caulking & Weather Stripping 5 1 3 1 10 2.5Res Measure Refrig/Misc. Waterbed covers 7 1 1 1 10 1.6Res Measure Refrig/Misc. Coil Cleaning kit 7 1 1 1 10 1.6

(Number of Rankings)

Priority Ranking

End-use/Measure

LOW <-------------------------------> HIGH Summary

Class Category Group N Avg

PRIORITY

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Results of Priority Ranking – Non-Residential End-Uses

1 2 3 4 5 6 7

NonRes End-use HVAC HVAC - Cooling 3 3 5 11 5.9 HighestNonRes End-use HVAC HVAC - Heating 1 2 2 7 12 5.8 HighestNonRes End-use HVAC HVAC - Fan Energy 1 1 3 2 5 12 5.6 HighestNonRes End-use HVAC HVAC - Reheat 1 2 2 1 6 12 5.6 HighestNonRes End-use Lighting Lighting - Interior 2 2 3 6 13 5.5 HighestNonRes End-use Lighting Lighting - Controls 2 2 3 6 13 5.54 HighestNonRes End-use HVAC HVAC - Ventilation Only 1 3 2 1 5 12 5.3 Highest

NonRes End-use Process Motors - Drives 2 3 3 4 12 5.3 Highest

NonRes End-use Refrigeration Refrigeration 2 3 3 4 12 5.3 HighestNonRes End-use Other Water Heating 1 1 5 1 3 11 5.2 HighestNonRes End-use Process Pump 2 1 3 2 3 11 4.9 MediumNonRes End-use Process Industrial - Process 2 1 4 1 3 11 4.8 MediumNonRes End-use Other Compressed Air 2 1 3 3 2 11 4.8 MediumNonRes End-use Other Data Center Equipment 2 1 3 4 1 11 4.7 Medium

NonRes End-use Other Data Center Cooling 2 2 3 4 1 12 4.7 MediumNonRes End-use Lighting Lighting - Exterior 2 2 1 3 2 3 13 4.6 MediumNonRes End-use HVAC HVAC - Other 1 1 1 3 1 3 10 4.5 MediumNonRes End-use Other Food Service Equipment 2 1 2 3 2 2 12 4.4NonRes End-use Agricultural Agricultural - Pumping 1 2 1 2 4 10 4.4NonRes End-use Appliances Appliances - Laundry 2 2 3 1 3 11 4.3NonRes End-use Other Plug Load (Electronics) 2 1 3 1 2 2 11 4.3NonRes End-use Other Clean Room 5 1 2 3 1 1 13 3.3NonRes End-use Agricultural Agricultural - Process 4 2 1 1 2 10 2.5

Category Group N Avg(Number of Rankings)

PRIORITY

Priority Ranking

End-use/Measure

LOW <-------------------------------> HIGH Summary

Class

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Results of Priority Ranking – Non-Residential Measures

1 2 3 4 5 6 7

NonRes Measure HVAC Heat pumps 1 1 1 5 3 11 5.5 HighestNonRes Measure HVAC Chillers 1 1 1 5 3 11 5.5 Highest

NonRes Measure HVAC Controls 2 1 4 5 12 5.5 HighestNonRes Measure HVAC Economizer 2 1 3 5 11 5.4 High

NonRes Measure Indoor Lighting Controls 2 3 2 5 12 5.3 High

NonRes Measure HVAC AC units 1 3 1 3 3 11 5.2 High

NonRes Measure Motors VSD 2 3 3 3 11 5.1 High

NonRes Measure Indoor Lighting LED (screw in and troffer) 2 1 2 2 5 12 5.1 High

NonRes Measure HVAC Demand control ventilation 2 1 2 4 3 12 5.0 HighNonRes Measure Indoor Lighting highbay T5 2 1 3 1 5 12 5.0 High

NonRes Measure Indoor LightingContinuous dimming flourescent fixtures 2 1 1 2 2 4 12 4.9 Medium

NonRes Measure Outdoor Lighting Controls 2 1 1 1 3 4 12 4.9 MediumNonRes Measure Building Envelope EMS 3 5 3 11 4.9 Medium

NonRes Measure Motors ECM 2 5 2 2 11 4.8 MediumNonRes Measure Indoor Lighting CFLs 3 2 1 1 5 12 4.8 MediumNonRes Measure Indoor Lighting Fluorescent Fixtures (T5-HE, T8-HE) 2 1 2 1 1 4 11 4.7 MediumNonRes Measure Refrigeration Effi cient Compressor Reftrofit 2 5 3 1 11 4.7 MediumNonRes Measure Refrigeration Floating Head Pressure Controls 2 1 4 2 2 11 4.7 MediumNonRes Measure Outdoor Lighting LED street and garage lighting 2 2 6 2 12 4.7 MediumNonRes Measure Indoor Lighting HID 3 2 2 1 4 12 4.6 MediumNonRes Measure Water Heating Heat pump water heater 1 1 1 2 2 2 2 11 4.5 MediumNonRes Measure Indoor Lighting ceramin metal halide flood 2 1 2 3 2 2 12 4.5 MediumNonRes Measure Refrigeration LED Lighting 2 1 1 1 2 2 3 12 4.5 MediumNonRes Measure Refrigeration Anti-sweat controls 2 1 2 2 4 1 12 4.5 MediumNonRes Measure HVAC Energy recovery ventilation 2 2 3 2 2 11 4.5 Medium

Priority Ranking

End-use/Measure

LOW <-------------------------------> HIGH Summary

PRIORITY

Class Category Group N Avg(Number of Rankings)

Note: This table does not depict entire list of measures provided to respondents, only those measures that ranked medium, high, or highest

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August 21 2012

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Data Granularity Level of granularity

- One hour or 15 minute increments- Shorter increments if feasible- The need for shorter intervals was specifically due to DR

Future data granularity needs - About half said no different than now- About one-third expected to need five minutes

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Sampling and Precision, Study Length Precision Requirements

- About half had specific precision requirements, same as PURPA

Single vs. Multiple End-Uses - About a third of the group said their analyses focused on multiple end-uses

Importance of Research- Case Study of Individual End-Uses

- Most ranked this low in importance - Statistical Sample of Single End-Uses

- About half valued this research higher in importance- Statistical Sample of Multiple End-Uses

- This option was ranked high by most respondents

Length of End-Use Study - At least a year - Limited timeframe would be acceptable in certain cases

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Load Shape Library Load Shape Library Accessibility

- online option - FTP - searchable database

Load Shape Library Format - Almost half preferred Excel - CSV, SAS or Access.

Site versus Aggregated Data - both raw site-level data and aggregated data

Most Useful Pre-aggregated Data- Lots of answers for how to summarize data

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Section 5: Regional End-Use Research Activities (Post 2009)

NEEA’s Residential Building Stock Assessment (RBSA)

BC Hydro’s Residential End-Use Metering Project (REUMP)

NorthWestern Energy’s End-Use and Load Profile Study

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NEEA RBSA Metering Project This study is currently underway

Plans to meter 90% of the end-uses within about 100 homes

Metering for two years

5-minute interval energy for:- whole premise, - the sub-metered end-uses, - indoor temperature for the main living area, - outdoor temperature,

Other measurements:- 5-minute snapshots of service voltages, true power, and power factor - Gas furnace and gas water heater run-times- Lighting cycles

Region Sample

Eastern Washington 16

Idaho 14

Montana 5

Puget Sound 36

Western Oregon 30

Total 101

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BC Hydro’s Residential End-Use Metering Project (REUMP) 13 employee volunteer households sub-metering about 40 end-uses per home

This project is being developed in four phases: 1. Proof of Concept (2008-2009): Test the idea of using a Zigbee wireless network to

collect interval data in a home.2. Testing (2009-2010): Equipped three homes with about 100 of these end-use recorders

(Ploggs) to test the software and data collection procedures.3. Pilot (Current): Goal of covering about 20 homes (currently 13) fully end-use metered

with about 800 devices. 4. Full Implementation (Future): If the Pilot phase is successful, implement a statistical

sample of about 300 residential homes across the Province.

BC Hydro staff indicated they are open to collaborating with other organizations in the region for the full implementation phase of the study.

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NorthWestern Energy’s End-Use and Load Profile Study Completed in December 2009

Supports conservation potential assessment

Based on on-site surveys and past studies

Monthly load shapes for residential

Monthly and hourly load shapes for commercial- Hourly shapes based on modeled data

Residential Commercial

Central AC Heating

Central Heat Cooling

Cooking Oven Ventilation

Cooking Range Water Heating

Dryer Lighting

Freezer Plug Load

HVAC Aux Cooking

Heat Pump Refrigeration

Lighting Process Loads

Other Other

Plug Load

Refrigerator

Room AC

Room Heat

Water Heat

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August 21 2012

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Section 6: National Perspectives Eight respondents

Not as much representation from EE as PNW interviews

Uses of the data and types of decisions being made from results were generally the same as the PNW- Magnitudes of decisions were also in $M, like the PNW

Concerns about data were similar - vintage- Specifically plug loads and new appliance trends

Risks of using inaccurate load data were still mostly associated with mis-characterizing cost effectiveness of EE (even though most were not from EE)

The priority rankings for end-uses and measures all came in generally lower in rank than for the PNW, especially for measures.

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National Resources – Load Shapes NEEP Commercial Lighting Load Shape Study

- Assembled information across a wide range of EE evaluation studies

NEEP Commercial Unitary HVAC- Large sample of Unitary HVAC from Maryland to New England (n>400)

Glasgow Electric Plant Board- 30 home sample metering WH, HVAC, Refrigerator, Range, Dishwasher, Washer, and Dryer- 20 home Grid Smart appliance change-outs including HPWH and Energy Smart appliances

EPRI Load Shape Library and Customer Load Insights Interest Group

Residential End-Use Metering Program, Australia

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National Resources – Data Collection Protocols NEEP Draft Protocols

International Performance Measurement and Verification Protocol

ASHRAE Guideline 14

California Evaluation Protocols

Federal Energy Management Program Guidelines

ELCAP

Other Relevant Projects

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Section 7: Preview of Business Case Development Considerations for an Effective Study

- End-Use and Measure Priorities- Review of Updates Since 2009 - Sample Size and Design Issues- Types of Data and Information to Collect- Transferability- Sustainability of the Approach- Data Library and User Interface

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Section 8: No Action Option Challenges with No-Action Option

- Lack of current load shape data for electronics- Increasing value of demand impacts- Concerns about current load shapes reflecting current behavior (e.g., TOU rates)- Interaction and load shape dependence on occupancy

Risks with the No-Action Option- Lack of understanding what drives customer load patterns- Poor planning- Inaccurate projections- Inaccurate forecasts- Resulting in the “wrong” type of investment

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Section 9: Business Case Development The Minimal Case

- meets the highest priority needs - lower range estimate in terms of cost and level of effort

The Base Case- meets a greater range of stakeholder needs- attention still given to project costs, time and resource (i.e. staff) requirements

The Premium Case - relaxes concerns about data acquisition costs and resource requirements- focusing on what the stakeholders could obtain through a multi-year end-use data collection

effort, unconstrained by costs, time and/or resource limitations

A description of each including costs and benefits will be presented in September

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Residential Options A Minimal Case

- Energy shares developed from CDA- Whole facility metering by housing type- Hourly load shapes for HVAC and WH

(expand RBSA sample)- Simulation modeling by housing type

(conditioned to whole facility load)- Simulation modeling for SFR

(conditioned to RBSA end-use metering)

The Base Case (Builds on Minimal Case)- Expansion of RBSA within Region

The Premium Case (Builds on Base Case)- Extension of RBSA to multi-family- Extension of RBSA to manufactured housing- Simulation modeling by housing type conditioned to end-use metering

Tier 2: Demographic Survey Data for Large Samples

Tier 1: Billing Information Available for Full Population

Tier 3: Whole Facility Metering Data

Tier 4: On-Site Coupled with Building Simulation Modeling

Tier 5: End-Use Metering

Energy Shares

Whole Facility Profiles by

Housing Type

Building Simulation Models Calibrated to Whole Facility Load

Calibrated Models

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Non-Residential Options A Minimal Case

- Whole facility metering by facility type- Large survey to secure facility information- On-site sample to secure information for

simulation modeling (selected facility types)- Simulation modeling by facility type

conditioned to whole facility load

The Base Case (Builds on Minimal Case)- Add: End-use metering for selected end-uses within selected business types- Simulation modeling for selected facility type conditioned to end-use metering

The Premium Case (Builds on Base Case)- Add: End-use metering for additional end-uses within additional business types- Simulation modeling for additional facility type conditioned to end-use metering

Whole Facility Profiles by

Business Type

Building Simulation Models Calibrated to Whole Facility Load

Tier 2: Whole Facility Metering Data

Tier 1: Billing Information Available for Full Population

Tier 3: Demographic Survey Data for Large Samples

Tier 4: On-Site Coupled with Building Simulation Modeling

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August 21 2012

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