BCAP Code Savings Estimator Primer 2012

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    BCAP Code Savings Estimator Primer

    April 2012 Nils Petermann

    Purpose of the Savings EstimatorThe purpose of the BCAP code savings estimator can vary a little depending on our task, e.g.:

    a) show the potential difference that codes legislation could make on national or state energy useb) analyze what role codes could play as part of a portfolio of energy efficiency policiesc) show the potential benefits for a state adopting stronger codesd) estimate state energy code savings in conjunction with BCAPs cost-benefit analyses

    In cases a) and b), it might be most useful to estimate the savings by comparing the codes scenario with

    the EIA Annual Energy Outlook (AEO) reference case. This reference case includes assumptions about

    energy efficiency improvements independent of codes progress, so if AEO is used as the baseline, the

    estimates show the expected savings in addition to business-as-usual efficiency progress. This is useful

    for seeing what difference a codes policy can be expected to make.In cases c) and d), it might be most useful to compare the codes scenario with current practice. While

    current practice isnt likely to continue unchanged even in the absence of stronger codes, this

    comparison allows us to see what benefits can be reaped from codes that might increase construction

    cost. In cases where the estimated cost of stronger codes is based on comparisons to current practice, it

    makes sense to also estimate the benefits of codes compared to current practice.

    The code savings estimator allows you to either use the AEO reference case or current practice as the

    baseline, and estimates the energy, cost and emissions savings from a codes scenario relative to the

    chosen baseline. What the codes scenario looks like is up to you. You can choose which version of the

    IECC/ASHRAE 90.1 or any code that goes beyond the IECC/ASHRAE 90.1 gets adopted in which year and

    what the rate of compliance is in any given year. The estimator estimates the annual savings out to

    2035.

    Baseline and Code Scenarios

    We estimate savings by comparing code scenarios to one of two baselines (Annual Energy Outlook

    reference case or current practice). The different baselines and code scenarios assume different

    efficiency levels for building shell, lighting and equipment, and the code savings estimator calculates

    savings based on these differences.

    Annual Energy Outlook reference case

    We currently use the reference case of the 2010 version of AEO as the baseline. AEO includes

    projections of the efficiency of equipment, lighting, building shell, etc. and how these efficiencies change

    over time.

    Current practice

    Our current practice baseline assumes that those aspects that are impacted by codes (shell, lighting,

    etc.) dont improve beyond their 2010efficiency levels. Other factors that arent impacted by codes

    residential HVAC, water-consuming appliances, etc. do change as projected by AEO, so current

    practice refers only to those components where codes make a difference.

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    Code scenarios

    In a code scenario, we assume the implementation of codes that improve energy efficiency relative to

    current practice by a percentage depending on the code.

    By what percentage do codes improve energy efficiency? Depends. For example, we assume

    that a state without a residential energy code can improve energy efficiency by 6% if with the

    2006 IECC or by 18% with the 2009 IECC. Nationwide, current practice consists of a mix ofdifferent codes. For the code savings estimator, we assume that the 2009 IECC, if fully complied

    with, would improve efficiency by 12% over the national mix of current practice.

    What does X% improvement over current practice mean? If a code offers X% improvement

    over current practice, the end uses covered by code are X% lower than with 2010 practice. In

    residential construction, this means that the efficiencies of the building shell, lighting and water

    heating are each X% better than their respective 2010 efficiencies in the AEO. In the commercial

    sector, where the code impacts heating and cooling through HVAC as well as shell requirements,

    a code scenario improves the combined efficiency of HVAC and shell by X% compared to their

    2010 efficiencies in the AEO (i.e. shell and HVAC dont improve by X% each on their own).

    Code scenarios vs. baseline

    So an X% better code means X% better efficiencies for shell, lighting, etc. compared to 2010 practice. To

    calculate savings from this, we must calculate energy use based on these code-improved efficiency

    levels and compare the results to the baseline (AEO reference case or current practice). If current

    practice is the baseline, code-improved efficiencies of X% over current practice remain X% better than

    baseline over the years. If the AEO reference case is the baseline, baseline efficiencies improve over

    time and may catch up with the code-improved efficiencies unless the code keeps improving.

    How do we calculate energy use and savings based on code efficiency levels?

    Energy codes improve the efficiency levels of the shell, lighting, etc. If we ignore other factors for now,

    an X% improvement in efficiency means X% savings in the associated energy use (e.g. a 10%

    improvement in lighting reduces lighting energy use by 10%). This improvement applies only to newconstruction, additions and renovation. To translate this into savings, we need to calculate the baseline

    energy use of new construction and additions (renovations are more tricky).

    The AEO gives us projected baseline energy use for the whole building stock as well as projections for

    construction activity. The energy use intensity of the stock and new construction in the AEO is based on

    RECS and CBECS. So in principle, increasing the floor space of the stock by the amount projected by AEO

    should increase energy use for heating, cooling, etc. by the added floor space times the RECS/CBECS

    energy use intensities minus demolished floor space. If the changing efficiencies of shell, equipment,

    etc. are taken into account, this is roughly the case. The code savings estimator replicates the AEO

    projections in a simplified manner, including some fudge factors so that it allows us to replicate the

    results of the more sophisticated AEO calculations. This is the principle behind the formulas of the code

    savings estimator: if the AEO efficiency levels for shell, lighting etc. are used, the results match those ofthe AEO. With different efficiency levels, we can calculate alternative scenarios. For instance, we can

    freeze the efficiencies at their 2010 levels for the current practice baseline. Or we can ramp up the

    efficiencies by X% beyond their 2010 levels to reflect improved codes.

    Comparing different scenarios based on different efficiency levels is the basic approach for estimating

    savings. A few further considerations somewhat complicate the calculations: taking into account the

    impact of renovations, compliance levels, and the efficiency rebound (higher propensity to use energy

    services due to greater efficiency). Renovations and the rebound are taken into account by AEO.

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    What about state-specific estimates?

    AEO projects national energy use. For state-specific estimates, we dont have as neat a reference case.

    Nonetheless, we can break down the national energy use trends and derive state-specific trends by

    taking into account state-specific construction data (from the U.S. Census), energy use intensity (based

    on recent EIA data), the end-use breakdown by census region in RECS and CBECS, and state-specific

    heating degree days and cooling degree days. The code savings estimator calculates state-specificenergy use based on a combination if this state and census-region data. When added together, the

    state-specific energy use calculations match the national total as provided by AEO.

    Some of the main assumptions used in the code savings estimator

    Assumed efficiency improvements IECC and ASHRAE 90.1

    Residential:

    Improvement 2012 IECC over 2009 IECC 20%

    Improvement 2012 IECC over 2006 IECC 30%

    Improvement 2012 IECC over 2000-03 IECC 31%

    Improvement 2012 IECC over pre-IECC code 34%

    Commercial:

    Improvement 90.1-2010 over 90.1-2007 24%

    Improvement 90.1-2010 over 90.1-2004 28%

    Improvement 90.1-2010 over older or no code 41%

    Residential and commercial:

    Current national average code compliance 50%

    Efficiency rebound

    15% for each 10% energy efficiency improvement in building design or equipment, people increase

    their use of energy services (lighting, cooling, etc.) by 1.5%, so that the resulting energy savings are 8.5%

    instead of 10%.

    Share of different end-uses among code efficiency improvements

    If a given code improves energy efficiency by, say, 30%, this doesnt necessarily mean that all end-uses

    are affected equally (i.e. that heating and lighting energy use are both equally reduced by 30%). For

    instance, residential codes may have a bigger impact on heating and cooling than on water heating

    because a much larger portion of the code deals with the building shell and ducts than with pipe

    insulation. Here is how we assume the improvements are weighed among the different end uses:

    Residential: Which end-use gets improved how much by a given code improvement?

    End use Share among end-usesin 2010

    Improvement by end-use

    relative to overall

    improvement from code

    Share of improvementfrom code

    Heating 34% 120% 40%

    Cooling 30% 120% 36%

    Water heating 25% 50% 13%

    Lighting 11% 100% 11%

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    As an example, if a code improves residential efficiency by 30%, the heating efficiency gets improved by

    30% x 120% = 36% and accounts for 40% of the overall improvement induced by the code.

    Commercial: Which end-use gets improved how much by a given code improvement?

    End useShare among end-uses

    in 2010

    Improvement by end-use

    relative to overall

    improvement from code

    Share of improvement

    from code

    Heating 10% 110% 11%

    Cooling 30% 110% 33%

    Ventilation 17% 50% 9%

    Water heating 8% 75% 6%

    Lighting 34% 110% 38%