Utility Savings Estimation

1. Utility Savings Estimation Webinar 1: Methodology and Assumptions Olga Livingston, Rosemarie Bartlett, Doug Elliott Pacific Northwest National Laboratory PNNL-SA-95757

2. Utility Savings Estimator The objective is to develop a generic tool that • estimates potential energy savings from increased compliance with energy codes • utilizes well-understood definitions of compliance • provides easily understood results that can be compared across several utilities or several segments within utility coverage area or aggregated to the national level

3. Utility Savings Estimator • Generic tool will contain defaults for code-to-code savings, commercial and residential floor space forecasts and projected code adoption • Utilities can overwrite defaults in the generic computational algorithm with their own utility-specific assumptions, where applicable (for example, floor space growth in a particular segment of the utility coverage area) • Estimation for commercial and residential buildings follows one methodology, but the computation is implemented in separate files

4. Webinar Objectives • Webinar 1 objectives: • Introduce computational methodology. • Introduce definitions of compliance used in the tool. • Introduce and discuss adoption and compliance assumptions, including implicit adoption and effects of learning on compliance. • Obtain feedback on methodology and assumptions from participants. • Webinar 2: Introduce and discuss the proposed interface • Webinar 3: Present the review version of the Utility Savings Estimator.

5. Methodology Overview The basic methodology is the same as that used for the U.S. Department of Energy Building Energy Codes Program (BECP) to assess national benefits.1 • Estimate nominal energy savings: • Select base (or reference) year • Apply savings estimates for code-to-code changes • Determine applicable floor space subject to code • Adjust nominal energy savings by: • code adoption status • code compliance levels • Analyze multiple code compliance scenarios • Aggregate residential and commercial savings 1. Belzer DB, SC McDonald, and MA Halverson.  2010.  A Retrospective Analysis of Commercial Building Energy Codes: 1990 – 2008. PNNL-19887. Pacific Northwest National Laboratory, Richland, WA. 

6. Methodology Overview (cont.) Reference Year Energy Savings from Code to Code Alternative Scenario Applicable Floor Space Increased Compliance Accelerated Adoption Projected Savings Nominal Savings Baseline Compliance Baseline Adoption Base Case Savings Base Case Impact from Increased Compliance

7. Default Inputs • 2010 is suggested as the reference year • Code-to-code savingsare grouped by end use and fuel • Pacific Northwest National Laboratory conducted extensive simulations to compare code-to-code savings for various versions of residential and commercial energy codes • Simulation results are the same set as utilized in the U.S. DOE determination process, as well as in state-by-state cost-effectiveness analysis • Savings for future code editions will be developed as part of the U.S. DOE Building Energy Codes Program effort Reference Year Energy Savings from Code to Code

8. Default Inputs: Floor Space • The estimator is pre-populated with residential and commercial construction projections by state. • Residential construction permit data by county and place is available from the United States Census Bureau. • Lagged permit data to convert permits to completions for historical, state-level data. • Applied AEO (Annual Energy Outlook from EIA) growth forecast to state-level Census data to obtain projections of households by state. • Used time series of AEO and RECS-based average floor space per household to convert households to floor space. • Scaled up for additions.

9. Default Inputs: Floor Space (cont.) • Commercial construction information is available from McGraw-Hill Construction Dodge data • Lagged construction data to obtain historical, state-level time series • Applied AEO growth forecast to state-level data to obtain projections of floor space by state(new construction and additions) • State shares based on multi-year average to avoid short-term distortions due to economic downturn • Alterations incorporated via a state-level scalar, based on multi-year ratio of new construction and additions to alterations

10. Code Adoption • Tracked historical code adoption and effective code data by state • Performed analysis of jurisdictional adoption for home-rule states, which included contacting code officials at the municipal and county levels to verify the energy code versions in effect • Divided the states into five adoption categories based on historical adoption patterns, their respective regulatory review cycles and recent legislative activity related to energy codes

11. Code Adoption (cont.) • Code adoption scenarios also consider implicit adoption when states do not explicitly adopt an energy code, but building practices are nevertheless changing under influence from within the state or surrounding states • utilities and regional energy efficiency organizations (REEOs) running programs across states • construction contractors and architect firms with operations in multiple states • Implicit code adoption is assumed to occur within 10 years of the code version year • Future code adoption* is projected based on observed differences in • historical adoption lags across different code versions • current code cycles across various states * If interested in analyzing only a particular code version, overwrite future adoption for the rest of the code versions with a year outside of analysis period (>2045)

12. Adoption Categories • States with Criteria Exceeding MEC/IECC. These states have historically developed their own codes, which are generally more advanced than the most recent MEC/IECC standards. • States with Rapid Adoption Rate. Many of the states in this category have regularly reviewed and adopted energy codes. Many of the states have begun to follow a systematic 3-year “review cycle” and some have passed legislation that mandates regular adoption. • States with Medium Adoption Rate. These states have demonstrated a willingness to adopt a state-level energy code, but their review cycle and adoption activities often lag behind the “rapid adopters.” • States with Slower Adoption Rate. These states are judged to have taken little action from 1990 to 2010 to adopt a new or update an existing energy code applying to buildings without substantial DOE support. • States without a Statewide Energy Code. Some states still have not adopted a mandatory state-level code. In terms of the analytical approach, these states reflect no direct, historical impact from the BECP; however, due to additional assistance from the American Recovery and Reinvestment Act of 2009 (ARRA 2009) and assistance from the BECP, most of these states are expected to adopt the IECC or an equivalent model energy code within five years.

13. Adoption Assumptions by State

14. Code Compliance • Two aspects of energy code compliance: • compliance in legal terms, which is defined as meeting all of the provisions of the code • compliance in energy terms, which accounts for energy savings in buildings that only partially meet the requirements of the new energy code Full code-to-code savings Partial code-to-code savings 30% 70%

15. Code Compliance (cont.) • Compliance is modeled as the weighted average: compliance in energy terms is weighted by the compliance in legal terms

16. Code Compliance (cont.) • Time dimension of compliance: Initial compliance vs. compliance after 10 years Interpolate from 44% to 60% over 10 years • Time dimension of compliance captures effects of utility programs targeting compliance, as well as learning by doing

17. Code Compliance (cont.) • Sensitivity study for various aspects of compliance:

18. Code Compliance Levers • Increase the initial legal compliance – fraction of the construction fully compliant with the energy codes • Increase initial compliance in energy terms – fraction of savings in buildings that only partially meet the code requirements • Newer code and initial higher compliance are not the only levers in the model • Model allows accounting for increased compliance with existing code version over time

19. Methodology Summary • Estimate nominal energy savings: • Select base (or reference) year • Apply savings estimates for code-to-code changes • Determine applicable floor space subject to code • Adjust nominal energy savings by: • code adoption status • code compliance levels • Analyze multiple code compliance scenarios • Aggregate residential and commercial savings • Compute code savings scenarios by segment and aggregate to the utility/program coverage area Savings from Increased Compliance = Alternative Scenario – Base Case

20. Results Provided by the Estimator • Energy savings as a result of increased compliance (multiple aspects of compliance are considered), by fuel type, by year and cumulative over the analyzed time frame • Emissions savings, by year and cumulative over the analyzed time frame • Consumer savings, by year and cumulative over the analyzed time frame • The estimator handles multiple code versions. If interested in analyzing compliance with a particular code version only, overwrite future adoption for the rest of the code versions with a year outside of analysis period (>2045).

21. Conclusions • Utility Savings Estimator is a straightforward framework to analyze savings from increased compliance. • Common definitions of compliance and estimation methodology enable comparison across different segments of the utility coverage area. • Common framework and definitions also allow comparison of results across different players and programs targeting energy code compliance. • In turn, utility-level studies based on a common model will provide a more sound foundation for national codes benefits analysis.

22. Contact Information Rosemarie Bartlett – webinar registration and logistics rosemarie.bartlett@pnnl.gov Olga Livingston – overall feedback, assumptions, estimation algorithm, tool interface olga.livingston@pnnl.gov Doug Elliott – floor space projections, tool interface douglas.elliott@pnnl.gov

23. Future Webinars • As a follow-up to today’s webinar, each attendee will be sent a set of assumption tables. • Your feedback is greatly appreciated. • July Webinar 2: Introduce and discuss the proposed interface. • August Webinar 3: Present the review version of the utility savings estimator. All participants in this webinar will be sent invitations to the next webinars.