BCAP Code Savings Estimator Primer 2012
Content
BCAP Code Savings Estimator Primer
April 2012 – Nils Petermann Purpose of the Savings Estimator
The purpose of the BCAP code savings estimator can vary a little depending on our task, e.g.: a) b) c) d) show the potential difference that codes legislation could make on national or state energy use analyze what role codes could play as part of a portfolio of energy efficiency policies show the potential benefits for a state adopting stronger codes estimate state energy code savings in conjunction with BCAP’s 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 isn’t 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.) don’t improve beyond their 2010efficiency levels. Other factors that aren’t 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. 1
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 of different 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 don’t 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 new construction, 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 of the 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. 2
What about state-specific estimates?
AEO projects national energy use. For state-specific estimates, we don’t 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-specific energy 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 doesn’t 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? Improvement by end-use Share among end-uses Share of improvement End use relative to overall in 2010 from code improvement from code Heating 34% 120% 40% Cooling 30% 120% 36% Water heating 25% 50% 13% Lighting 11% 100% 11%
3
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? Improvement by end-use Share among end-uses Share of improvement End use relative to overall in 2010 from code improvement from code Heating 10% 110% 11% Cooling 30% 110% 33% Ventilation 17% 50% 9% Water heating 8% 75% 6% Lighting 34% 110% 38%
4
April 2012 – Nils Petermann Purpose of the Savings Estimator
The purpose of the BCAP code savings estimator can vary a little depending on our task, e.g.: a) b) c) d) show the potential difference that codes legislation could make on national or state energy use analyze what role codes could play as part of a portfolio of energy efficiency policies show the potential benefits for a state adopting stronger codes estimate state energy code savings in conjunction with BCAP’s 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 isn’t 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.) don’t improve beyond their 2010efficiency levels. Other factors that aren’t 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. 1
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 of different 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 don’t 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 new construction, 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 of the 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. 2
What about state-specific estimates?
AEO projects national energy use. For state-specific estimates, we don’t 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-specific energy 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 doesn’t 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? Improvement by end-use Share among end-uses Share of improvement End use relative to overall in 2010 from code improvement from code Heating 34% 120% 40% Cooling 30% 120% 36% Water heating 25% 50% 13% Lighting 11% 100% 11%
3
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? Improvement by end-use Share among end-uses Share of improvement End use relative to overall in 2010 from code improvement from code Heating 10% 110% 11% Cooling 30% 110% 33% Ventilation 17% 50% 9% Water heating 8% 75% 6% Lighting 34% 110% 38%
4
