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Phase 1: Cataloguing Available End-Use and Efficiency Load Data

September 15, 2009

End-Use Load Data Update Project

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Agenda

Project Objectives

Determining usability of data

Summary of promising studies

Gap analysis

Transferability ratings

Prioritization of near-term activities

Next steps

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Project Objectives

1. Research and inventory existing load shape data available

2. Determine data attributes necessary to meet needs of energy efficiency, capacity markets and air quality

3. Identify weaknesses and gaps in existing available data

4. Evaluate transferability and applicability of load shape data to the Regions

5. Provide road map for meeting short term and long term end-use metering needs

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Develop list of end-use categories Break down end-uses into “Analysis Groups” Analysis Groups intended to include measure

savings shapes, as well as end use shapes

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Data Search

Objectives:

Identify relevant studies that conducted field studies (metering) of end uses/measures (Analysis Groups)

Collect enough information on associated “data properties” to assess usability

Activities:

Web survey of 102 industry contacts List of studies identified in California (2006 Load Shape

Update Initiative) Follow up with contacts to collect data properties

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Data Search - Challenges

Key challenges to data search:

– Difficult to engage industry contacts to share relevant studies they are aware of

– Even when proper survey contact identified - contact did not typically have detailed information on data properties (e.g. vintages of equipment metered, NAICS/SIC codes of facilities)

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Data Search - Results

110 studies identified, across three general types:

– Load research

– Evaluation

– Compilation

List of “Promising Studies” – high level review

– Sample size

– Vintage of studies (2000 or more recent)

– Studies that developed load profiles

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Defining Usability of End Use Data

Interviews with stakeholders from energy efficiency, capacity markets and air quality

Energy efficiency and greenhouse gas reporting have similar requirements – Statistically valid sample design – Unbiased data collection procedures– Reasonable Baseline definitions

ISO/RTO Capacity Markets add a Prescriptive Layer– Specific Relative Precision Requirements– Specific Metering Requirements

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Defining Usability of End Use Data

Ratings: A – Meets capacity market standards, usable as

stand alone study within region B – Meets efficiency planning standards, usable

as part of a compilation study C – Has some issues, could be used as a last

resort or to guide modeling efforts IP – Study is currently in progress

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Summary of Promising Studies Pacific Northwest

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Summary of Promising Studies Pacific Northwest

Three studies rated a B - one old load research with diminishing sample, other targeted thermostat study with small sample and ELCAP.

Three promising studies in progress

– Most promising = BC Hydro Power Smart Residential End Use Study

No promising non-residential studies identified

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Summary of Promising Studies Eastern, Mid-Atlantic, California Regions

Eastern: 18 Promising Studies identified

– Non-Residential studies were all program evaluation studies that had smaller sample sizes

– Seven Residential studies primarily Lighting some HVAC, appliance and water heating

Mid-Atlantic: 2 studies with large sample sizes but all demand response participants

California: 10 studies, including DEER as roll-up of many studies covering almost all end uses

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Gap Analysis

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Gap Analysis Overview

Gap Analysis developed end use analysis group level sample size data

Sample size data includes studies that have not yet been completed or fielded and results could change dramatically if plans change

Some studies are included under the end use analysis group that have no sample size data

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Data Availability – Pacific NorthwestResidential

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Gap Analysis – Pacific NorthwestNon-Residential

Only one non-residential study identified– Limited Hourly Metering Pilot (BPA): Only 3 sites

metered ALL non-residential end uses have a high need

for data

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Transferabilty of Data from Other Regions

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Is end use data readily transferable?

We establish a general rating system for transferability of end use analysis groups

Criteria evaluated were– Potential for schedule variability between regions– Potential for weather variability between regions

Assumed that saturation of energy efficient equipment could be decoupled

Implicitly addressed regional variations in construction practices

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General Transferability - Residential

Schedule Variability – Low is better Weather Variability – Low is better Transferability Rating - High is better

Analysis Group Schedule Variability Weather Variability Transferability RatingAppliances - Kitchen Medium Low HighAppliances - Laundry Medium Low HighAppliances -Refrigerators Low Medium HighHVAC – Cooling Medium High LowHVAC – Fan Energy Medium High LowHVAC - Heating Medium High LowHVAC - Ventilation Medium Medium MediumHVAC - Other Medium High LowLighting - Exterior Medium Low HighLighting - Interior Low Low HighPlug Load Low Low HighPool Pump Low Medium MediumWater Heating Low Medium Medium

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General Transferability – Non-residential

Analysis Group Schedule Variability Weather Variability Transferability RatingAgricultural - Process Medium Medium MediumAgricultural - Pumping Medium Medium MediumAppliances - Laundry Low Low High

Clean Room Low High LowCompressed Air Low Low High

Data center equipment High High MediumData center cooling Medium High Low

Food Service Equipment Low Low HighHVAC - Cooling Low High Low

HVAC - Fan Energy Low High LowHVAC - Heating Low High LowHVAC - Other Low High Low

HVAC - Ventilation Only Low High LowHVAC - Reheat Medium High Low

Industrial - Process Medium Medium MediumLighting - Exterior Low Low HighLighting - Interior Low Low HighMotors - Drives Medium Medium Medium

Plug load Low Medium MediumPump Low Medium Medium

Refrigeration Low High LowWater Heating Low Medium Medium

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Prioritization of Load Shape Activities

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Relative importance of end use and measure load shapes (Analysis Groups) Developed an end use Analysis Group Importance

Level Rating system using– Input from RTF subcommittee and EMV Forum– Web survey respondent importance rankings– CA 2006-08 EE portfolio percentages– CT Market potential study percentages

Rating system as follows– Tier 1 – Most Important, high % of savings & high need

– Tier 2 – Moderately Important, moderate % of savings and/or

need

– Tier 3 – Lower Importance, lower % of savings

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Load Shape Development Activities - Overview Generally there are five options that could be

followed– Option 1 - Combine existing end use studies of

common measure types into meta studies within regions– Option 2 - Look to transfer meta studies from other

regions to fill in gaps within a region– Option 3 - Work to develop database for regionally

customized DOE Models using (DEER) as starting point – Option 4 – New metering– Option 5 – Do nothing, end use unimportant at this time

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Strategies to Improve End Use Data

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Underlying assumption: Where no existing end use data, near term priority activities will be directed first at Tier 1 end use groups

Where data available – Option 1 and 2 (if transferable) Where no data – Option 2 or 3 (if transferable) Where no data – Option 4 (if not transferable)

That Option 5 “do nothing” is viable near term for the end use analysis groups that had no metering activity

Load Shape Development Activities - Overview

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Near-term Activities – Pacific NorthwestResidential (Tiers 1 and 2)

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Near-term Activities – Pacific NorthwestResidential (Tier 3)

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Near-term Activities – Pacific NorthwestNon-Residential

End Use Groups with “high” transferabilityUtilize data sources from other regions

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Near-term Activities – Pacific NorthwestNon-Residential

Recommended new metering

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Conclusions and RecommendationsNear-term (up to 12 months)

Support useful studies in progress:– BC Hydro Power Smart Res End Use Study – large end use

research study in planning stages Ensure that smaller studies (e.g. evaluation studies) collect

necessary information – Consistent protocol for load shapes can ensure that small

studies collect necessary ancillary data to be compiled Evaluate whether some ELCAP data still usable

– Focus new research on identifying which ELCAP data can be leveraged

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Conclusions and RecommendationsMid-term (1-3 years)

Implement multi-region end-use data repository Plan other study types (non-metering) to support

transfer of data from other regions– Saturation studies (typical building characteristics,

inventory of system types and efficiencies)

Assess feasibility of disaggregating end-use information from AMI whole-premise data– Identify utilities open to partnership opportunities

Experience you can trust.

Betty SetoProject ManagerKEMA510-891-0446 x4133Betty.Seto@kema.com

Further questions or comments?

Steve CarlsonSenior Principal ConsultantKEMA860-346-5001 x207Steve.Carlson@kema.com