WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES ONLY.

DO NOT QUOTE OR CITE AS RESULTS ARE SUBJECT TO CHANGE.

September 29, 2017

MEMORANDUM FOR: Ian Mead

Assistant Administrator for Energy Analysis

FROM: Jim Turnure 

Director, Office of Energy Consumption and Efficiency Analysis

SUBJECT: Summary of AEO2018 Buildings Working Group 2 held on September 

20, 2017

The purpose of this memorandum is to provide an overview of the presentation given at the second 

AEO2018 Buildings Working Group meeting and a summary of the discussion between participants. The 

meeting covered updates for AEO2018, including major updates, policy assumptions, energy efficiency 

modeling refinements, and potential side cases. The full presentation associated with the working group 

is available in a separate document. 

Model updates

Major updates include refining and updating historical distributed generation capacity and generation. 

Specifically, the residential ZIP code-level solar photovoltaic (PV) penetration model was updated with 

additional historical data and a contagion effect was added. For commercial distributed generation, subCensus divisions were updated to include 2012 CBECS data. Commercial combined heat and power and 

wind capacity was updated with new data sources including the U.S. Department of Energy, Office of 

Energy Efficiency and Renewable Energy and EIA-860 data. Utility energy efficiency program rebates are 

in the process of being updated and tested.

Discussion

The main discussion centered on distributed generation, updates to commercial miscellaneous end uses,

utility energy efficiency programs, and behavioral parameters.

Distributed Generation

Participants wanted to know why projected residential solar PV capacity is lower between 2040 and 

2050 in preliminary AEO2018 runs than in AEO2017. EIA staff explained that the updated parameters for 

the econometric residential PV penetration model and lower projected electricity prices result in less 

residential adoption relative to AEO2017 during that time period.

Commercial "Other"’ and "Computing" End uses

EIA staff explained that the Other end-use category in AEO2018 will be indexed to non-industrial and 

service gross output as a basis for projecting non-explicitly modeled consumption. In response to 

questions, EIA staff noted that commercial computing has been reweighted to eliminate doublecounting the effect of floorspace growth on energy use for computing. 
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Utility Energy Efficiency Programs

EIA staff outlined a draft methodology and preliminary results for modeling utility energy efficiency 

program rebates. In preliminary runs, lighting is the most heavily subsidized end use, and rebates are 

higher in Census division 1 (New England) than in other regions. Rebate spending is loosely 

benchmarked to the utility rebate spending reported through the EIA-861 survey.

Participants asked for more detail on how energy efficiency rebates were applied in the model. EIA staff 

clarified that the rebates are applied to specific technology vintages as a percentage of installed cost. 

Rebates are not applied for individual years, but each technology vintage is available during a specific 

time frame (e.g., a certain vintage of light bulb might be available between 2020 and 2029). Rebates are 

applied to technology vintages that achieve efficiencies greater than or equal to ENERGY STAR

equipment. 

Participants asked for clarification on the methodology for capturing utility rebate penetration across 

Census divisions and asked why this method was chosen. EIA staff explained that they initially tried 

breaking down rebate levels by Census division, but the sample size was too small to draw robust 

conclusions about rebate amounts at that level of disaggregation. Therefore, in the most recent analysis, 

national average technology rebates are used. These are adjusted by Census division based on available 

data on penetration of utility rebates within divisions. Given how the model is currently structured, it is 

more feasible to adjust average rebates than to adjust the number of people subject to the rebates. 

However, according to the current model design, some consumers will not respond to certain rebates if 

their hurdle rates are too high or if they are programmed to choose within the same fuel or technology 

type. 

A participant noted that light emitting diode (LED) lighting technologies are achieving penetration very 

quickly, and that Massachusetts is therefore looking at phasing out LED rebates as early as 2020. EIA 

staff acknowledged that we are monitoring such trends and will adapt to policy changes like these as 

they arise. 

A participant asked why utility rebates are being modeled at all, given the level of uncertainty 

surrounding them. EIA staff responded that despite the uncertainty, we are interested in enhancing our 

capability to understand the impacts of utility rebates. With the architecture to incorporate utility 

rebates explicitly, EIA can better model sub-federal energy efficiency policies in the future. There are 

also certain technologies, such as LEDs, that do not gain as much market share in our model as observed 

in the real world unless they are subsidized in the model. A participant also requested that EIA release a

No Utility Rebate side case to better enable utilities to apply their own energy efficiency assumptions to 

projections and to prevent double-counting. Although EIA is not planning to undertake a No Utility 

Rebate side case, we do plan to release a one-time report on utility energy efficiency rebates and their

projected impacts. 

Hurdle rates and other behavioral parameters

Participants were interested in more information on behavior rules, regionalization, and about how 

hurdle rates are developed and used. EIA staff presented supplemental slides at the meeting describing 

how behavior rules and hurdle rates are applied to energy efficiency decisions. Participants asked how 

the lifetime of the technology is taken into account and whether costs like lamp replacement are taken 

into consideration in the Commercial Demand Module (CDM). EIA staff explained that operating and 
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DO NOT QUOTE OR CITE AS RESULTS ARE SUBJECT TO CHANGE.

maintenance costs are considered, including material and labor costs for items like lamp replacement. 

Participants also asked about the data sources for behavior rule parameters that govern the set of 

technologies commercial consumers consider when purchasing equipment in the CDM. EIA staff 

explained that the behavior rules are based on 2012 CBECS data about building ownership and 

occupants. 

Additional issues

Participants asked about potential side cases for AEO2018. The side cases for AEO2018 have not been 

officially set other than the core side cases, but EIA does plan to include alternative policy cases in 

AEO2018.
WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES ONLY.

DO NOT QUOTE OR CITE AS RESULTS ARE SUBJECT TO CHANGE.

Attendees

Guests (in person) Affiliation

John Agan DOE 

Robert Fares DOE 

Valerie Nubbe DOE 

Jack Mayernik NREL

David Feldman NREL

Guests (WebEx/phone)

Youngsun Baek Union of Concerned Scientists

Austin Brown UC Davis

Beth Conlin EPA

Alan Cooke PNNL

Eric Fox Itron

Chioke Harris NREL

Jared Langevin LBNL

Aris Marantan Navigant

Oleg Moskatov Itron

Andrew Nicholls PNNL

Janet Reyna DOE

Kurt Roth Fraunhofer

Mike Russo Itron

Erick Tucker Leidos

David White Synapse Energy

Frances Wood OnLocation

Evelyn Wright Sustainable Energy Economics

EIA Attendees (in person)

Chip Berry

Jay Olsen

Greg Lawson

Perry Lindstrom

Manussawee Sukunta

Team Members:

Erin Boedecker

Meera Fickling

Kevin Jarzomski

Kimmie Klaiman

David Peterson

EIA Attendees (WebEx/phone)

Behjat Hojjati

Carolyn Hronis

Janice Lent

Eileen O’Brien