1 Estimating Key Parameters for the Retail Plug-Load Portfolio (RPP) Program: Recommended Methodological Approaches EM&V, Residential Programs, Products

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Estimating Key Parametersfor the Retail Plug-Load Portfolio (RPP) Program:

Recommended Methodological Approaches

EM&V, Residential Programs, Products and Channel Teams

October 23, 2014

Residential PLA Program

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Today’s Agenda

• Our Objectives

• RPP Program Review

• General Estimation Principles

• Adapting Parameter Inputs for the E3 Calculator: Key Considerations for Market Transformation

• Proposed Methods to Estimate NTGRs, EULs, and IMCs

• Our Requests to the Cal TF


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Our Objectives

• Present recommended approaches to estimate values for three key savings parameters for Cal TF approval:

Net-to-gross ratios (NTGRs)Incremental measure costs (IMCs)Effective useful life (EUL)

• Present recommended approaches to adapt parameter inputs for use with E3 calculator for Cal TF approval

• Seek Cal TF approval for UEC estimation methodology (presented at last month’s meeting)


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RPP Program Review

• Program Approach:• Utilize retailer engagement to increase the demand and supply of more

energy efficient appliance and consumer electronic products

• Measures: • RPP offers a portfolio of consumer energy efficiency measures that are

delivered through the retail channel partners

• Incentive Structure:• Incentives are paid to participating retailers for each program-qualified

product sold.

• Evaluation Framework:• While this mid-stream program is primarily a market transformation

program, it contains elements of a resource acquisition program.


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RPP Logic Model

Activities

Outputs

Short-Term Outcomes

Mid-Term Outcomes

Long-Term Outcomes

External Influences: Broad economic conditions, m

arket events, cost of energy, federal standards, Energy Star, perceived need for conservation, etc. Factors can influence program

at all levels and time fram

es.

F. PG&E and partner utilities approve retailer plans to reduce energy profile

F. PG&E and partner utilities approve retailer plans to reduce energy profile

G. Retailers implement plan employing various strategies, e.g., changes in product assortment, increase promotion, sales force education, reduce price and update as necessary.

A. PG&E contacts utility partners regarding collaboration in Program delivery

D. PG&E, utility partners and identified retailers target product categories with energy savings potential.

D. PG&E, utility partners and identified retailers target product categories with energy savings potential.

H. Reduction in customer market

barriers

B. Utility partners recruited

T. PG&E and utility partners provide data and stakeholder support regarding targeted product categories to the Energy Star and Code and Standards Programs

R. Permanent change in the availability of more energy efficient products among participating and nonparticipating retailers

R. Permanent change in the availability of more energy efficient products among participating and nonparticipating retailers

P. Increased demand experienced by manufacturers for more efficient products

P. Increased demand experienced by manufacturers for more efficient products

J. Energy and demand savings in PG&E and partner utility service territories

V. More stringent mandatory and voluntary standardsV. More stringent mandatory and voluntary standards

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I. Customers purchase more energy efficient products

M. Reduction in the SWUEC for target product categories among participating retailers in PG&E and utility partner service territories.

M. Reduction in the SWUEC for target product categories among participating retailers in PG&E and utility partner service territories.

W. Long-term energy and demand savings

W. Long-term energy and demand savings

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Q. Manufacturers increase production of the efficient models

Q. Manufacturers increase production of the efficient models

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N. Reduction in the SWUEC for target product categories among nonparticipating stores

N. Reduction in the SWUEC for target product categories among nonparticipating stores

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K. Environmental and other non-energy benefits

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U. PG&E and utility partners participate in C&S and Energy Star meetings to support more stringent mandatory and voluntary standards

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X. Long-term environmental and non-energy benefits

X. Long-term environmental and non-energy benefits

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C. PG&E and utility partners determine which retailers to recruit

C. PG&E and utility partners determine which retailers to recruit

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S. Decrease in SWUEC and increase in market share of EE measures & Environmental & Other Non-Energy Benefits

S. Decrease in SWUEC and increase in market share of EE measures & Environmental & Other Non-Energy Benefits

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L. Retailers receive incentives from PG&E and utility partners

L. Retailers receive incentives from PG&E and utility partners

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E. Utilities, partner utilities and selected retailers negotiate incentive levels for reducing the energy profile for target product categories and sign contracts

E. Utilities, partner utilities and selected retailers negotiate incentive levels for reducing the energy profile for target product categories and sign contracts

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O. Increased retailer engagement

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General Estimation Principles

For products in DEER:• Use EUL and IMC values found in DEER

For products NOT in DEER:• Use best available data for EUL and IMC estimates.

NTGRs for resource acquisition programs:• DEER values reflect 3-5 year timeframes, and are applicable to

downstream resource acquisition programs.

NTGRs for market transformation programs:• DEER values are not applicable, NTGRs must be derived through other

methods that involve long-term forecasting.


7Adapting Inputs for the E3 Calculator: Market Transformation Considerations

• Gross Savings:• The total of the stream of savings for all of the measures adoption

forecasted over the projected initiative term times each measure’s EUL.

• TRC costs:• Input the stream of administrative and incremental measure costs that

match the time frame of the savings impacts.

• NTG Inputs:• Use the ratio of forecast total market change minus the forecast of the

baseline changes divided by the total market change for the same time period used for both the costs and savings.


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Net-to-Gross Ratios (NTGRs)

• NTGRs represent net program load impacts divided by gross program load impacts.

• NTGR is sometimes used to convert gross measure costs to net measure costs.

• The relationship between program-driven and naturally-occurring adoptions evolves over the life of the program.

• This dynamic must be captured and entered into the B/C calculator.

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RPP

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Hypothetical example


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NTGRs: Our Recommendation

• Preferred: Estimate NTGRs over time using an analogic diffusion model

For each product category, long-term forecasts over the life of the RPP Program can be used

Scenarios (using the Bass diffusion model) with and without the RPP Program can be forecasted over the life of the program

The resulting differences in these two scenarios represent the expected net impacts of the RPP

The net impacts divided by the gross impacts yield the NTGRs

• Alternative: Use a Delphi panel

• Ideal but costly: Combine the two


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Incremental Measure Cost (IMC)

• Incremental measure cost is defined as the difference in the cost of an efficient measure and a baseline measure attributable to the difference in efficiency.

• Methods must be developed to capture the fact that IMCs decline over the life of the program

• Historical trends of IMCs—traditionally observed to decline over time—will be reviewed for measures with characteristics similar to those in the RPP suite (e.g., CFLs, DVD-Rs, transistor radios, desktop PCs, laptop PCs, lower-volume laser printers, and multi-function devices).

• Declining IMCs must be entered into the B/C calculator over the life of the program.


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Using Webcrawlers to obtain IMC information

• Many retail-focused webcrawlers track price trends for specific products, such as pricegrabber.com

• The IOU C&S team recently developed a custom webcrawler to determine IMC for residential lighting products.

• The webcrawler collected a wide range of product features, then the team conducted a multiple regression analysis to better understand how product features contribute to pricing.

• The team is considering expanding this approach to additional products


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IMCs: Our Recommendation

• We recommend using webcrawlers to estimate IMC. For each product, we would identify key product features, including retail

price and Energy Star qualification status. Using these data, we could then develop a regression analysis to estimate

the incremental cost of an energy efficient product (hedonic price models) Data collection can be easily replicated to identify changes over time.

• Retailer price data also holds promise. Price data provided by retailers for each model sold along with key product

characteristics could be used to estimate the IMC using hedonic price models

• Targeted in-store shelf surveys While they have very limited value, given that the RPP is based on a

dynamic product mix that is expected to change over time, they can be used to selectively calibrate webcrawler results.


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Effective Useful Life (EUL)

• The effective useful life is an estimate of the median number of years that a measure installed under a program is still in place and operable.

• While EULs could conceivably change over the over the life of the program, such changes might be difficult and costly to track reliably.

• Consistent with retention and persistence studies, the focus of RPP EUL estimates is to estimate the effective useful life for installed equipment, since this is what is producing program-generated savings.


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EULs: Our Recommendation

• First choice: Use available research data For products that are federally-regulated, EUL should be based on

research data used in the standards proceeding. Where this is not a federal standard, we will use best available research

(e.g., EPA, manufacturers or other research).

• Delphi panel Use a formal consensus approach for generating EUL estimates from a

group of experts.

• Ideal but more costly: Combine available research data and Delphi panel.


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Our Requests to the Cal TF

• Do you agree with our recommended approaches to estimating these three parameters?

• Would you like any additional information about the proposed estimation approaches?

• Do you have any changes you would recommend to our proposed methods?

• Are there any additional approaches that you could recommend?

• Do you have suggestions about how to input parameter estimates into the E3 calculator?


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Next Steps

• Approval of the UEC methodology

• Approval of methodologies for estimating key parameters

• RPP work paper draft review

• Review of parameter estimates

• RPP work paper approval

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Questions?

Documents

1 Estimating Key Parameters for the Retail Plug-Load Portfolio (RPP) Program: Recommended Methodological Approaches EM&V, Residential Programs, Products