National Cost-Effectiveness Analysis of the Residential Provisions of the 2015 IECC

Mendon, Vrushali V.; Selvacanabady, Abinesh; Zhao, Mingjie; Taylor, Zachary T.

doi:10.2172/1209867

“…The Pacific Northwest National Laboratory used the DOE EnergyPlus building energy simulation tool to model the energy use reductions of incremental changes between "vintages" (the year in which the code was released) of the International Energy Conservation Code (IECC) (Mendon, Lucas, and Goel 2013;Zhang et al 2013;Mendon et al 2015;Zhang et al 2015). Tables A-1 and A-2 summarize the findings of these and other studies of the building energy reduction effects of updated building code vintages.…”

Section: Appendix B For Methodologies For Implementation Cost Assumptmentioning

confidence: 99%

Estimating the National Carbon Abatement Potential of City Policies: A Data-Driven Approach

O’Shaughnessy¹,

Heeter²,

Keyser³

et al. 2016

1

0

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The Office of Strategic Programs within the U.S. Department of Energy's (DOE's) Office of Energy Efficiency and Renewable Energy initiated a multi-year project called Cities Leading through Energy Analysis and Planning (Cities-LEAP). The project aims to enable cities to lead clean energy innovation and integrate strategic energy analysis into decisions by providing standardized, localized energy data and analysis. Cities-LEAP informs the implementation of city-sponsored, data-driven energy policies, programs, and projects that have the potential to impact the national energy landscape. Through Cities-LEAP, cities will be able to: Set data-informed climate or energy goals Prioritize and implement energy strategies Understand the potential impacts of climate or energy action plans Learn from peers about city energy planning best practices Get access to credible data and transparent, usable analytic methodologies Make data-driven energy decisions. The initial Cities-LEAP technical report, "City-Level Energy Decision Making: Data Use in Energy Planning, Implementation, and Evaluation in U.S. Cities" (Aznar et al. 2015), explores how a sample of cities incorporates data into making energy-related decisions. Building on the needs identified in the initial Cities-LEAP report, the DOE and the National Renewable Energy Laboratory developed the City Energy Profile tool. 1 The profiles in the tool provide estimates and actual data on city-level energy use metrics, including electricity use, natural gas use, vehicle fuel use, and vehicle miles traveled. These data allow city decision makers to better understand their energy landscape and make more strategic energy decisions. The following figure illustrates how the current report fits into the broader Cities-LEAP body of work. This report builds on the existing Cities-LEAP work by applying the findings from "City-Level Energy Decision Making" and data from the City Energy Profile tool to estimate the carbon abatement potential of city-led actions identified in "City-Level Energy Decision Making." 2.

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“…Energy use reductions for residential buildings exhibit far more variability than commercial buildings. DOE (2012) reported that the 2012 IECC made a significant (24%) reduction in energy use relative to the 2009 IECC, while Mendon et al (2015) found that the 2015 IECC made little impact relative to the 2012 IECC. In Section 2, the following equation is used to model the energy realization rate:…”

Section: Next Steps: Using City Energy Data To Prioritize City Actionsmentioning

confidence: 99%

Estimating the National Carbon Abatement Potential of City Policies: A Data- Driven Approach

O’Shaughnessy

¹

,

Heeter

²

,

Keyser

³

et al. 2016

1

0

View full text Add to dashboard Cite

The Office of Strategic Programs within the U.S. Department of Energy's (DOE's) Office of Energy Efficiency and Renewable Energy initiated a multi-year project called Cities Leading through Energy Analysis and Planning (Cities-LEAP). The project aims to enable cities to lead clean energy innovation and integrate strategic energy analysis into decisions by providing standardized, localized energy data and analysis. Cities-LEAP informs the implementation of city-sponsored, data-driven energy policies, programs, and projects that have the potential to impact the national energy landscape. Through Cities-LEAP, cities will be able to: Set data-informed climate or energy goals Prioritize and implement energy strategies Understand the potential impacts of climate or energy action plans Learn from peers about city energy planning best practices Get access to credible data and transparent, usable analytic methodologies Make data-driven energy decisions. The initial Cities-LEAP technical report, "City-Level Energy Decision Making: Data Use in Energy Planning, Implementation, and Evaluation in U.S. Cities" (Aznar et al. 2015), explores how a sample of cities incorporates data into making energy-related decisions. Building on the needs identified in the initial Cities-LEAP report, the DOE and the National Renewable Energy Laboratory developed the City Energy Profile tool. 1 The profiles in the tool provide estimates and actual data on city-level energy use metrics, including electricity use, natural gas use, vehicle fuel use, and vehicle miles traveled. These data allow city decision makers to better understand their energy landscape and make more strategic energy decisions. The following figure illustrates how the current report fits into the broader Cities-LEAP body of work. This report builds on the existing Cities-LEAP work by applying the findings from "City-Level Energy Decision Making" and data from the City Energy Profile tool to estimate the carbon abatement potential of city-led actions identified in "City-Level Energy Decision Making." 2.

show abstract

“…According to simulation studies by the National Association of Home Builders, the 2009 and 2012 IECC codes decrease the site energy consumption of the 2006 code-built home by 10.7% and 33.7%, respectively. According to Pacific Northwest National Laboratory, the 2015 IECC code decreases the site energy consumption of a 2015 code-built home by 1% more than the 2012 code (Mendon et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Comparing Retrofit Wall Performance Predicted from Hygrothermal Simulations to Measurements

Boudreaux¹,

Salonvaara²,

Desjarlais³

2021

0

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National Cost-Effectiveness Analysis of the Residential Provisions of the 2015 IECC

Cited by 3 publications

References 0 publications

Estimating the National Carbon Abatement Potential of City Policies: A Data-Driven Approach

Estimating the National Carbon Abatement Potential of City Policies: A Data-Driven Approach

Estimating the National Carbon Abatement Potential of City Policies: A Data- Driven Approach

Comparing Retrofit Wall Performance Predicted from Hygrothermal Simulations to Measurements

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