ANSI/ASHRAE/IES Standard 90.1-2013 Preliminary Determination: Quantitative Analysis

Halverson, Mark A.; Rosenberg, Michael; Wang, Weimin; Zhang, Jian; Mendon, Vrushali V.; Athalye, Rahul A.; Xie, Yuan; Hart, Reid; Goel, Supriya

doi:10.2172/1131376

Cited by 6 publications

(15 citation statements)

References 6 publications

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“…The technical analysis process, model descriptions and results were presented in PNNL's technical report titled Achieving the 30% Goal: Energy and Cost Savings Analysis of ASHRAE Standard 90.1-2010, referred to in this report as Energy and Cost Savings Analysis of ASHRAE Standard 90.1-2010(Thornton et al 2011. The prototype models used in the analysis, their development, and the climate locations were described in detail in the quantitative determination and are available for download 1 (Halverson et al 2014;DOE 2014b).…”

Section: Contents Of the Reportmentioning

confidence: 99%

“…The analysis used 16 prototype building models which were simulated in 15 climate locations, and developed in collaboration with SSPC 90.1. These prototype models, their development, and the climate locations were described in detail in the quantitative determination and are available for download (Halverson et al 2014;DOE 2014b). PNNL selected six of the prototype buildings and developed cost estimates for them in five climate locations.…”

Section: Building Prototypes and Climate Locationsmentioning

confidence: 99%

“…The other addenda do not have quantifiable savings, had no savings, do not directly affect building energy usage, or they could not be quantified during the determination quantitative analysis. The addenda are described in more detail in the report documenting the determination quantitative analysis (Halverson et al 2014).…”

Section: Cost Estimate Items From 901-2010 Addendamentioning

confidence: 99%

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National Cost-Effectiveness of ANSI/ASHRAE/IES Standard 90.1-2013

Hart

Loper

Richman

et al. 2015

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The U.S. Department of Energy (DOE) Building Energy Codes Program supports the upgrade and implementation of building energy codes and standards, which set minimum requirements for energyefficient design and construction for new and renovated buildings, and impact energy use and greenhouse gas emissions for the life of buildings. Continuous improvement of building energy efficiency is achieved by periodically updating model energy codes for commercial and residential buildings. Through consensus-based code development processes, DOE recommends revisions and amendments, supporting technologically feasible and economically justified energy efficiency measures. Ensuring that model code changes impacting the cost of building construction, maintenance, and energy services are cost-effective also encourages their adoption and implementation at the state and local levels. Pacific Northwest National Laboratory (PNNL) prepared this analysis to support DOE in evaluating the energy and economic impacts associated with updated codes in commercial buildings. The purpose of this analysis is to examine the cost-effectiveness of the 2013 edition of ANSI/ASHRAE/IES 1 Standard 90.1 (ANSI/ASHRAE/IES 2013). Standard 90.1 is developed by the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Standard Standing Project Committee (SSPC) 90.1. It is the model energy standard for commercial and multifamily residential buildings over three floors (42 USC 6833). PNNL analyzed the cost-effectiveness of changes in Standard 90.1 from 90.1-2010 to 90.1-2013, as applied in commercial buildings across the United States. During the development of new editions of Standard 90.1, the cost-effectiveness of individual changes (addenda) is often calculated to support the deliberations of ASHRAE Standard Standing Project Committee (SSPC) 90.1. The ASHRAE process, however, does not include analysis of the cost-effectiveness of the entire package of addenda from one edition of the standard to the next, which is of particular interest to adopting State and local governments. Providing States with an analysis of costeffectiveness may encourage more rapid adoption of newer editions of energy codes based on Standard 90.1. This information may also inform the development of future editions of Standard 90.1.To establish the cost-effectiveness of Standard 90.1-2013, three main tasks were addressed:• Identification of building elements impacted by the updated standard • Allocation of associated installation, maintenance, and replacement costs • Cost-effectiveness analysis of required changes In addition to installation, maintenance, and replacement costs, energy cost differences were needed to determine cost-effectiveness. The energy costs for each edition of Standard 90.1 were determined previously under the development of Standard 90.1-2013, as described below.The current analysis builds on the previous PNNL analysis (as outlined in Section 5.2) of the energy use and energy cost saving impacts of Standard 90.1-2013 compared to pre...

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Section: Contents Of the Reportmentioning

confidence: 99%

Section: Building Prototypes and Climate Locationsmentioning

confidence: 99%

Section: Cost Estimate Items From 901-2010 Addendamentioning

confidence: 99%

See 1 more Smart Citation

National Cost-Effectiveness of ANSI/ASHRAE/IES Standard 90.1-2013

Hart

Loper

Richman

et al. 2015

View full text Add to dashboard Cite

show abstract

“…Modeling Strategy. The implementation of requirements within addendum ci was very similar to that of addendum 90.1-2010bw and is described by Halverson et al (2014). As was the case with addendum bw, prototypes were examined to see if they first met option (a) in the fenestration orientation requirement, either with their current orientation or if rotated 90 degrees.…”

Section: Quantiative Analysis Resultsmentioning

confidence: 99%

Energy Savings Analysis: ANSI/ASHRAE/IES Standard 90.1-2016

Athalye

Halverson

Rosenberg

et al. 2017

Self Cite

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Title III of the Energy Conservation and Production Act, as amended (ECPA), establishes requirements for building energy conservation standards, administered by the DOE Building Energy Codes Program. (42 U.S.C. 6831 et seq.) Section 304(b), as amended, of ECPA provides that whenever the ANSI/ASHRAE/IESNA Standard 90.1-1989 (Standard 90.1-1989 or 1989 edition), or any successor to that code, is revised, the Secretary of Energy (Secretary) must make a determination, not later than 12 months after such revision, whether the revised code would improve energy efficiency in commercial buildings, and must publish notice of such determination in the Federal Register. (42 U.S.C. 6833(b)(2)(A)) Standard 90.1 is developed under ANSI-approved consensus procedures, and is under continuous maintenance by a Standing Standard Project Committee (commonly referenced as SSPC 90.1). ASHRAE has an established program for regular publication of addenda, or revisions, including procedures for timely, documented, consensus action on requested changes to the Standard. 1 Standard 90.1-2016 was published in October 2016, triggering the statutorily-required DOE review process. To meet the statutory requirement, DOE conducted an analysis to quantify the expected energy savings associated with Standard 90.1-2016. This report documents the methodology used to conduct the analysis below. Based on the analysis, DOE has determined that the 2016 edition of the ANSI/ASHRAE/IES Standard 90.1 would improve overall energy efficiency in buildings subject to the code compared to the 2013 edition of Standard 90.1. Methodology The methodology applied in this analysis is consistent with that utilized for previous DOE building energy codes analysis and determinations, and is based on a combination of qualitative and quantitative assessments:

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“…The collected actual occupancy data were converted to EnergyPlus model inputs with the schedule editing function in OpenStudio. The assumed occupancy schedules, written in fractional schedule format [45,46], were overwritten with actual occupancy data, using 0 and 1 to indicate vacancy and occupancy, respectively. The resulting actual occupancy schedules were then embedded in IDF files generated in OpenStudio, and used in simulations in EnergyPlus.…”

Section: Building Model Calibrationmentioning

confidence: 99%

Why is the reliability of building simulation limited as a tool for evaluating energy conservation measures?

Yang

Becerik-Gerber

et al. 2015

Applied Energy

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Buildings account for approximately 32% of the total energy consumption globally and up to 40% in the developed countries, which makes buildings a prime target for energy conservation. Various energy conservation measures (ECMs) have been proposed to improve the energy efficiency in buildings, and these ECMs are usually designed and assessed using calibrated building energy models. However, there is empirical evidence that reveals noticeable discrepancies between simulated performances of ECMs reported in building energy models and their actual performances measured in buildings. This paper examines two possible causes of such discrepancies. Specifically, this paper tests the following two hypotheses: (1) using assumed occupancy data as opposed to actual occupancy data in building energy simulation reduces the reliability of estimated performance of demand-driven ECMs; and (2) using an energy model built for one ECM to cross estimate energy consumption of another ECM is statistically inaccurate. An educational building was used as a test bed. The results proved both hypotheses true, showing that estimations were more accurate and consistent for models calibrated using actual occupancy compared with those using assumed occupancy, and that cross-ECM estimation resulted in statistical inaccuracy. The findings indicated that current

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ANSI/ASHRAE/IES Standard 90.1-2013 Preliminary Determination: Quantitative Analysis

Cited by 6 publications

References 6 publications

National Cost-Effectiveness of ANSI/ASHRAE/IES Standard 90.1-2013

National Cost-Effectiveness of ANSI/ASHRAE/IES Standard 90.1-2013

Energy Savings Analysis: ANSI/ASHRAE/IES Standard 90.1-2016

Why is the reliability of building simulation limited as a tool for evaluating energy conservation measures?

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