WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES ONLY.

DO NOT QUOTE OR CITE AS RESULTS ARE SUBJECT TO CHANGE.

October 16, 2019

MEMORANDUM FOR: Stephen K. Nalley

Acting Assistant Administrator for Energy Analysis

FROM: Jim Turnure

Director, Office of Energy Consumption and Efficiency Analysis

SUBJECT: Summary of AEO2020 Buildings Working Group 2 held on

October 3, 2019

This memorandum provides an overview of the presentation given at the second Annual Energy Outlook 

2020 (AEO2020) Buildings Working Group meeting and summarizes the discussion. The meeting covered

preliminary AEO2020 Reference case results compared with AEO2019 Reference case results. It also 

highlighted the major modeling and data updates that were incorporated for AEO2020. The 

presentation for this meeting is available in a separate document.

AEO2020 results overview and comparison with AEO2019

The meeting began with a discussion about the preliminary delivered energy consumption projections

by fuel and sector. The U.S. Energy Information Administration (EIA) staff then compared preliminary 

AEO2020 results with AEO2019 results. Residential and commercial electricity and natural gas prices 

were shown, followed by projected heating and cooling degree day data. A participant asked how EIA 

develops its weather trends. EIA staff clarified that we use a 30-year linear trend using historical 

National Oceanic and Atmospheric Administration (NOAA) weather data from 1989 to 2018. The starting 

point for this trend (in 2021) begins from the end of NOAA’s 15-month short-term forecast.

EIA then shared residential housing stocks, which are lower in AEO2020 because of reduced housing 

starts from the Macroeconomic Activity Module of the National Energy Modeling System (NEMS). 

Commercial floorspace projections are very similar to those from AEO2019, growing at 1% per year from 

2019 through 2050.

Residential purchased electricity consumption, which does not include any distributed generation used 

onsite, and delivered natural gas consumption are both higher than AEO2019 because of lower fuel 

prices, higher heating and cooling degree days, and lower projected distributed generation—namely 

from solar photovoltaics (PV). Fuel prices and weather also affect commercial consumption although 

commercial natural gas consumption grows more slowly than in AEO2019 as a result of lower growth in 

combined heat and power (CHP).
WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES ONLY.

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

The U.S. Department of Energy (DOE) has issued a final rule to reverse a January 2017 expansion of the 

definition of general service lighting (GSL), which means that the 45 lumen per watt backstop standard

for 2020 will apply to fewer bulbs than before. We have incorporated this final rule into AEO2020.1

About two-thirds of 2015 residential lighting stock is A-type,

2 according to the 2015 Residential Energy 

Consumption Survey (RECS) and the DOE 2015 U.S. Lighting Market Characterization report.

3 EIA

assumes these lamps still qualify as GSLs, even under the narrowed definition. However, a significant 

portion of the residential market still has no applicable backstop standard, and AEO2020 projections of 

lighting consumption from 2020 to 2030 are higher than in AEO2019. By contrast, about 80% of 

commercial lighting is linear, to which the backstop standard never applied. AEO2020 commercial 

lighting consumption projections are therefore more similar to AEO2019. 

EIA has a contractor task in place to update current and projected distributed generation cost and 

performance data. EIA compared draft report data by sector and technology with existing assumptions 

to provide context for changes in projected distributed generation capacity compared with AEO2019. 

Staff also described the change in methodology for commercial distributed generation. For commercial 

solar PV, wind, and CHP projections, EIA re-estimated parameters for the shape, speed, and maximum 

levels of distributed generation diffusion to calibrate distributed generation model builds to recent 

historical data. EIA also introduced more electricity rate variation into niches for internal rate of return 

calculations and revised assumptions such as diffusion start year, treatment of existing and new 

buildings, and PV-eligible roof space by building size.

EIA then compared AEO2020 solar PV capacity with AEO2019, highlighting the incorporation of Stanford 

University’s Deep Solar data into the residential model. Staff reiterated how reductions in distributed 

generation cause increases in purchased electricity. Preliminary commercial AEO2020 PV projections are 

higher than AEO2019 projections before 2035, as a result of the recalibration of growth parameters 

along with installed cost declines. However, commercial AEO2020 PV projections level out in later years, 

falling below AEO2019 projections by 2050. Lower projections in later years are driven by lower 

electricity prices and an updated NREL Annual Technology Baseline (ATB), which predicts higher installed 

costs for PV through 2050. 

AEO2020 also projects lower CHP growth than AEO2019. Most current CHP capacity is in mature 

technologies such as natural gas turbines and reciprocating engines. These technologies have not 

experienced large capacity growth in recent years and are not anticipated to experience rapid cost and 

performance improvements in the future. In addition, commercial mid-scale (100 kilowatt to 1

megawatt) wind turbines have largely disappeared from the U.S. market. Although some large 

commercial customers have adopted turbines greater than 1 megawatt, growth in commercial wind 

capacity has slowed considerably. As a result, AEO2020 projects much slower growth in commercial 

wind than AEO2019. 

 1DOE has also issued a notice of proposed rulemaking that would effectively eliminate the backstop standard 

altogether. Because this rule is still a proposal as of October 3, 2019, we have not incorporated it into AEO2020 

projections.

2 A-type bulbs are the pear-shaped bulbs most commonly found on the residential market. 3 U.S. Energy Information Administration, 2018, 2015 Residential Energy Consumption Survey, available at 

https://www.eia.gov/consumption/residential/data/2015/. U.S. Department of Energy, 2017, 2015 U.S. Lighting 

Market Characterization, available at https://www.energy.gov/sites/prod/files/2017/12/f46/lmc2015_nov17.pdf.
WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES ONLY.

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

EIA then discussed other model updates, including revisions to parameters for commercial minor fuel 

estimation based on recent historical data. EIA staff described how our collaborative discussions about 

specific unpublished data led the U.S. Census Bureau to publically release air-source versus groundsource heat pump installation data for the first time. These data were incorporated into AEO2020. A 

participant asked whether reintroducing EIA’s retired geothermal heat pump manufacturer survey 

(Form EIA-902) could be useful to stakeholders. The buildings team noted how we have received various 

questions about ground-source heat pumps and agreed that the survey data could fill an existing data 

void.

Staff mentioned the incorporation of 2015 RECS wood consumption data that were released following 

AEO2019 modeling updates. We also discussed the update of sub-census division niches using average 

2015 RECS electricity expenditure data, as well as distributed generation interconnection limitations 

based on the Database of State Incentives for Renewables & Efficiency® (DSIRE) and records from state 

legislatures.

Finally, EIA staff discussed updates affecting energy efficiency rebates and incentives. AEO2020 energy 

efficiency assumptions incorporate more data from a greater variety of sources. For a second year, EIA 

has worked with the Northeast Energy Efficiency Partnerships (NEEP) to gather detailed data on utility 

and state energy efficiency program incentives from the Northeast. Nevertheless, the updated 

assumptions cause only minor changes in end-use consumption relative to AEO2019. 

Discussion

A participant asked if EIA incorporates state-level incentives for fuel switching. EIA responded that NEMS

does not currently incorporate any explicit incentives for fuel switching. However, modeled incentives 

for electric space and water heating appliances such as air-source heat pumps can encourage the 

adoption of these appliances in place of natural gas appliances, effectively increasing electricity 

consumption and decreasing natural gas consumption. 

The RECS survey manager shared that 2020 RECS is hoping to publish data for all 50 states (plus 

Washington, DC, and possibly Puerto Rico). An EIA employee asked if state-level RECS data would help 

to better characterize sub-census division trends in fuel switching, and buildings team staff said that any 

increase in granularity of RECS could potentially feed into and improve the ability to model such trends 

in NEMS.
WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES ONLY.

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

Onsite attendees

Name Affiliation

Jared Langevin Lawrence Berkeley National Laboratory (LBNL)

Aven Satre-Meloy Lawrence Berkeley National Laboratory (LBNL)

Aaron Ng U.S. Department of Energy

Remote attendees (Webex/phone)

Name Affiliation

Alan Cooke Pacific Northwest National Laboratory (PNNL)

Alex Maki U.S. Department of Energy

Amir Roth U.S. Department of Energy

Ben King Rhodium Group

Cara Marcy U.S. Environmental Protection Agency

Chioke Harris National Renewable Energy Laboratory (NREL)

Elizabeth Titus Northeast Energy Efficiency Partnership (NEEP)

Eric Mackres World Resources Institute (WRI)

Hannah Kolus Rhodium Group

Ian Hoffman Lawrence Berkeley National Laboratory (LBNL)

Mike Russo Itron

Nora Wang Pacific Northwest National Laboratory (PNNL)

Paul Donohoo-Vallett U.S. Department of Energy

Peter Kobylarek Leidos
WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES ONLY.

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

EIA onsite attendees

Stacy Angel

Chip Berry

Greg Lawson

Katie Lewis

Bill McNary

Eileen O’Brien

Jay Olsen

Jennifer Palguta

Terry Yen

Team Members

Erin Boedecker

Meera Fickling (Webex/phone)

Behjat Hojjati

Kevin Jarzomski

Courtney Sourmehi

EIA remote attendees (Webex/phone)

Carolyn Hronis

Angelina LaRose

Joelle Michaels

Manussawee Sukunta