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

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Presentation on theme: "EnergyScore U.S. Department of Energy U.S. Department of Housing and Urban Development April 19, 2010."— Presentation transcript:

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

2 Agenda I. Overview II. EnergyScore Demo III. Platform Backend IV. Next Steps

3 I. Overview

4 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.

5 EnergyScore: A Tool for Homeowners and the Real Estate Market Calculates and displays a homes 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

6 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.

7 Context: EnergyScore Alongside Existing and Developing Tools [Add graphic representing spectrum of tools]

8 Comparison of Single Family Housing Datasets 2005 RECS EnergyScore CharacteristicStatisticNational East North Central Sample Queried for Yardstick Number of Homes in Sample (unweighted)3, ,359 (Note: remaining statistics below are all weighted) Electric Usage, KWHMedian11,0039,6749,197 Natural Gas Usage, KBTUMedian67,62492,713130,400 Building Square FootageMedian1,6761,8451,268 Number of BedroomsMean

9 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).

10 II. EnergyScore Demo

11 Site Tree Design






17 Your Energy Score RS add screenshot

18 Go To Live Demo

19 III. Platform Backend

20 Platform Backend Core DatasetsData InventoryRetrofit ModelCore Outputs Obtained via - House-level inventory records - User input on platform - Statistical imputation Tax Assessor Data House structure Utility Data Electric and natural gas usage Historical Retrofit Data Date, Type, and Cost of Retrofit Home Inventory House Structure Systems Appliances Household Savings Table Potential savings for a given retrofit, segmented by: House Architecture Energy Use Quartile Initial energy characteristic EUI Score Retrofit Recommend 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

21 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

22 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

23 Frame CottageBungalowColonialGeorgian Newer LuxuryRaised Ranch Ranch Townhome Tudor Victorian Split level Architectural Style Segmentation a Basis for Analysis Each architectural style has distinct energy use characteristics

24 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

25 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

26 IV. Next Steps

27 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

28 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?]

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

30 EnergyScore Contact info:


32 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

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

34 Detail if needed. RS to update text if time

35 Example Bungalow 1428 S. Clinton Berwyn, IL 1,250 sf - built 1927 = median EUI value = 25 th percentile EUI value = 75th percentile EUI value Conclusion: Energy Scores need context. Local context.

36 Potential: Links to Existing Real Estate Information Resources


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