EnergyScore U.S. Department of Energy U.S. Department of Housing and Urban Development April 19, 2010.

EnergyScore

U.S. Department of Energy U.S. Department of Housing and Urban Development

April 19, 2010

Agenda

I. Overview

II. EnergyScore Demo

III. Platform Backend

IV. Next Steps

I. Overview

An Information Barrier

Residential Retrofits: Widely accepted that access to information is a barrier to widespread uptake of energy efficiency retrofits.

Real Estate Market: The value of retrofits is usually not reflected in the value of a home due to the lack of reliable, easily communicable information.

EnergyScore: A Tool for Homeowners and the Real Estate Market

Calculates and displays a home’s energy performance “score”, based on actual usage and building structure data

Provides customized recommendations for retrofit improvement

Connects the homeowner to contractors and resources to pay for retrofits

Provides feedback loop to stakeholders

Over time, a goal is to develop a reliable score for a home and sub-scores for its individual energy systems that can be reflected in the value of the home

EnergyScore Approach Easy to use functionality and interface for homeowners. The user does

NOT need to input any home or energy use info as the tool pre-loads data automatically with the address.

Design of tool uses a methodology that can be replicated in other housing markets and climates.

Launch Regionally Ensures accuracy and quality control over data. Enables testing the uptake in the market.

EnergyScore approach complements existing tools and building labeling initiatives (both asset and operational ratings).

Want to collaborate and share our experience and data with others working on residential tools and labeling initiatives (HESPro, etc).

In addition to homeowner uses, tool enables collection of “existing conditions” data on housing markets.

Context: EnergyScore Alongside Existing and Developing Tools

[Add graphic representing spectrum of tools]

Comparison of Single Family Housing Datasets

    2005 RECS 2005 RECS EnergyScore

Characteristic Statistic NationalEast North

CentralSample Queried

for Yardstick

Number of Homes in Sample (unweighted) 3,102 486 127,359

(Note: remaining statistics below are all weighted)

Electric Usage, KWH Median 11,003 9,674 9,197

Natural Gas Usage, KBTU Median 67,624 92,713 130,400

Building Square Footage Median 1,676 1,845 1,268

Number of Bedrooms Mean 3.12 3.11 3.13

Querying EPA Yardstick

We queried the Yardstick tool using actual data for 127,359 single family homes in 95 municipalities across Cook County (roughly 10% of total housing stock).

II. EnergyScore Demo

Site Tree Design

Your Energy Score

RS add screenshot

Go To Live Demo

III. Platform Backend

Platform BackendCore Datasets Data Inventory Retrofit Model Core Outputs

Obtained via- House-level inventory records- User input on platform- Statistical imputation

Tax Assessor Data• House structure

Utility Data• Electric andnatural gas usage

HistoricalRetrofit Data• Date, Type, andCost of Retrofit

Home Inventory• House Structure• Systems• Appliances• Household

Savings TablePotential savings fora given retrofit,segmented by:• House Architecture• Energy Use Quartile• Initial energy characteristic

EUI Score

RetrofitRecommend• Type of retrofit• Range of expected savings

Obtained via- Building/retrofit analysis- Analysis on pre/post-retrofit usage

Additional outputs:- Link to additional info, contractors, etc- Written recommendations and savings report- Tool to track implemented retrofits and performance over time- Case Studies- Ask the Expert

Filling Out the Data Inventory

Initially, house-level inventory records provide actual data for actual homes

For homes without inventory records, statistical methods using assessor and utility data are used to impute most probable “default values” to fill out the inventory

Users can update data fields via the platform

Over time, more user engagement and collection of “actual data” will make the imputation and the data inventory become more accurate

Building the Retrofit Model

Initially, [building analysis] is used to produce a “savings table” yielding a range of potential savings for a given retrofit

Figures are calibrated, and tested against actual usage data and historical retrofit data

Over time, as more data is collected, models can be refined and calibrated to make more accurate estimates and to include additional types of retrofits

Frame CottageBungalow Colonial Georgian

Newer Luxury Raised Ranch Ranch

Townhome Tudor VictorianSplit level

Architectural Style Segmentation a Basis for Analysis

Each architectural style has distinct energy use characteristics

The Long Term Vision

Accurate, actionable retrofit recommendations with less effort on homeowners’ part

Data collection and model development to enable accurate ratings for homes and sub-ratings by type of energy system that can be incorporated into the value of the home

Part of a spectrum of tools complementing existing tools and building labeling initiatives

Current Status

The energy performance of 1.2 MM single family homes in Cook County, IL: 119 municipalities Nearly 2 million households ~ 1,000 square miles

Performance being refined by architectural housing type (Bungalows, Victorians, Tudors, etc).

Begun “beta testing” the accuracy of savings values of 145 Bungalows that have undergone retrofits

IV. Next Steps

From Product to Business

Data Development Collect additional retrofit data and individual “audit” data

Model Refinement Further testing with bungalows database (N=10,000) Testing the accuracy of the imputation model

Business Planning Identify and engage business partners Focus Groups with stakeholder groups to refine design &

content: Homeowners; Contractors, Auditors; Real estate professionals (agents, appraisers, mortgage); Potential funders

Rollout

“Discussion to Work Together”

How much do we want this on a slide? [Ask: Data Development] [Ask: “models”? – savings tables, retrofit

analysis impact?] [Ask: partnering] [Ask: resources] [Potential Role for DOE/HUD?]

Discussion

Could add slide with issues/discussion E.g. measures/display (slide at end)

EnergyScore

Contact info:

Context: Challenges

Challenges of existing tools in the market Are still too expensive on a per unit basis Take too much time and are difficult for homeowners

to use without assistance Have not been able to achieve widespread market

acceptance (only hundreds of units) Accuracy and QA/QC Data and models are not validated by actual energy

consumption

Over 80% of Cook County Single Family Homes fall into 5 Assessor Classes

Detail if needed. RS to update text if time

ExampleBungalow 1428 S. ClintonBerwyn, IL 1,250 sf - built 1927

= median EUI value

= 25th percentile EUI value

= 75th percentile EUI value

Conclusion: Energy Scores need context. Local context.

Potential: Links to Existing Real Estate Information Resources