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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2018

Prototype Courthouse Building Energy Model: Building and System Characteristics

As part of the Department of Energy’s support of ANSI/ASHRAE/IES Standard 90.1 and the International Energy Conservation Code, researchers at Pacific Northwest National Laboratory apply a suite of prototype buildings covering 80% of the commercial building floor area in the United States for new construction. Efforts have begun to cover 90% of the commercial building floor area in the United States by developing prototype models for additional building types that include supermarket, laboratory, place of worship, public order and safety, and public assembly. “Courthouse” is a subcategory under the “Public Order and Safety” building type category defined by the Commercial Buildings Energy Consumption Survey (CBECS); other subcategories include police station, fire station, and detention and correctional facilities (i.e., jail, reformatory, or penitentiary). Oak Ridge National Laboratory used building design guides, databases, and documented courthouse projects, supplemented by personal communication with courthouse facility planning and design experts, to systematically conduct research on the courthouse building and system characteristics. This report documents this research and reports the building and system characteristics necessary for developing a Courthouse prototype building energy model to be included in the Commercial Building Prototype Model suite.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

DEEP: A Database of Energy Efficiency Performance to Accelerate Energy Retrofitting of Commercial Buildings

The paper presents a method and process to establish a database of energy efficiency performance (DEEP) to enable quick and accurate assessment of energy retrofit of commercial buildings. DEEP was compiled from results of about 35 million EnergyPlus simulations. DEEP provides energy savings for screening and evaluation of retrofit measures targeting the small and medium-sized office and retail buildings in California. The prototype building models are developed for a comprehensive assessment of building energy performance based on DOE commercial reference buildings and the California DEER prototype buildings. The prototype buildings represent seven building types across six vintages of constructions and 16 California climate zones. DEEP uses these prototypes to evaluate energy performance of about 100 energy conservation measures covering envelope, lighting, heating, ventilation, air-conditioning, plug-loads, and domestic hot water. DEEP consists the energy simulation results for individual retrofit measures as well as packages of measures to consider interactive effects between multiple measures. The large scale EnergyPlus simulations are being conducted on the super computers at the National Energy Research Scientific Computing Center of Lawrence Berkeley National Laboratory. The pre-simulation database is a part of an on-going project to develop a web-based retrofit toolkit for small and medium-sized commercial buildings in California, which provides real-time energy retrofit feedback by querying DEEP with recommended measures, estimated energy savings and financial payback period based on users’ decision criteria of maximizing energy savings, energy cost savings, carbon reduction, or payback of investment. The pre-simulated database and associated comprehensive measure analysis enhances the ability to performance assessments of retrofits to reduce energy use for small and medium buildings and business owners who typically do not have resources to conduct costly building energy audit. DEEP will be migrated into the DEnCity - DOE’s Energy City, which integrates large-scale energy data for multi-purpose, open, and dynamic database leveraging diverse source of existing simulation data.

Hoon Lee, Sang↗
DOE OSTI2015

DEEP: Database of Energy Efficiency Performance

A database of energy efficiency performance (DEEP) is a presimulated database to enable quick and accurate assessment of energy retrofit of commercial buildings. DEEP was compiled from results of about 10 million EnergyPlus simulations. DEEP provides energy savings for screening and evaluation of retrofit measures targeting the small and medium-sized office and retail buildings in California. The prototype building models are developed for a comprehensive assessment of building energy performance based on DOE commercial reference buildings and the California DEER [sic] prototype buildings. The prototype buildings represent seven building types across six vintages of constructions and 16 California climate zones. DEEP uses these prototypes to evaluate energy performance of about 100 energy conservation measures covering envelope, lighting, heating, ventilation, air conditioning, plug loads, and domestic hot war. DEEP consists the energy simulation results for individual retrofit measures as well as packages of measures to consider interactive effects between multiple measures. The large scale EnergyPlus simulations are being conducted on the super computers at the National Energy Research Scientific Computing Center (NERSC) of Lawrence Berkeley National Laboratory. The pre-simulation database is a part of the CEC PIER project to develop a web-based retrofit toolkit for small and medium-sized commercial buildings in California, which provides real-time energy retrofit feedback by querying DEEP with recommended measures, estimated energy savings and financial payback period based on users' decision criteria of maximizing energy savings, energy cost savings, carbon reduction, or payback of investment. The pre-simulated database and associated comprehensive measure analysis enhances the ability to performance assessments of retrofits to reduce energy use for small and medium buildings and business owners who typically do not have resources to conduct costly building energy audit.

Hong, Tianzhen↗
DOE OSTI2022

Prototype Courthouse Building Energy Model: Building Characteristics and Energy Simulation Results

To coordinate commercial building energy research activities, the US Department of Energy uses a suite of commercial prototype building models, which includes 16 building types and covers 80% of US commercial floorspace. Efforts are underway to expand this suite by developing prototype models for additional building types, including a courthouse. Informed by building design guides, databases, documented projects, and personal communication with courthouse design experts, a 3-story, 4-courtroom, 69,324 ft 2 building was considered as the prototype courthouse to represent an average-sized courthouse in the United States. This report documents the building and system characteristics of the prototype courthouse model combined with climate-specific and construction vintage–specific requirements for the building envelope and systems from ASHRAE Standard 90.1. The energy simulation results are presented for 4 construction vintages (2004, 2007, 2010, and 2013) and 15 ASHRAE climate zones. To verify the energy simulation results, energy use statistics of existing courthouses from different building database are also presented. Based on the simulated energy use, the site energy use intensity of the prototype courthouse ranged from 45 to 159 kBtu/ft 2 compared with the average energy use intensity of 94.7 kBtu/ft 2 for the courthouse building type in the 2012 Commercial Building Energy Consumption Survey (CBECS) Data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Occupancy schedule development and its effect on OpenStudio prototype college building model

College buildings have unique characteristics compared with school buildings. Therefore, defining the realistic occupancy schedule in a prototype college building has significant research opportunities. In this study, the actual operating schedules of each space type were collected and generated based on the class reservation schedule and compared with the previous reference schedule (primary/secondary school). Here, the schedules were analyzed for their effect on the OpenStudio prototype college building model. The findings highlight that the use of a typical school building schedule in a college building impairs the granularity of information. The analysis shows significant differences between the previous occupancy schedule and the updated occupancy schedule of the college building, leading to a considerable decrease in occupancy density. Furthermore, the effect of these occupancy pattern changes on the prototype building model is examined. The variations were observed in minimum ventilation requirements, the average mechanical ventilation rate, and energy consumption attributed to changes in occupancy density.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Developing a landscape of urban building energy use with improved spatiotemporal representations in a cool-humid climate

Urban buildings account for up to 75% of total energy use in the United States (U.S.). Understanding urban building energy use is important for developing feasible options to mitigate energy use and greenhouse gas emissions. In this study, an improved bottom-up building energy use model, named City Building Energy Use Model (City-BEUM), was developed to estimate building energy use for all buildings in Polk County, Iowa. First, 28 commercial and 6 residential building prototypes were designed by combing Assessor's parcel data and building footprint data. Then, the EnergyPlus in the CityBEUM was calibrated for all building prototypes using the U.S. Energy Information Administration's survey data, monthly utility meter data, and actual weather data. Finally, spatial and temporal variations of building energy use in the study area were estimated using the CityBEUM. Results indicate that the spatial variation of building energy use in the study area can be captured using the CityBEUM. With the monthly-calibrated model, the temporal pattern of urban building energy use can be well represented. The comparison of building energy use using the Typical Meteorological Year and actual weather data demonstrates the importance of using actual weather data in building energy modeling for an improved temporal representation.

CityBEUM, Urban building energy use, High spatiote↗
DOE OSTI2022

Defining the Prototype Convenience Store Building Characteristics

The US Department of Energy supports the development of commercial building energy codes and standards. To support commercial building energy research activities and the development of commercial building energy codes and standards, continuous efforts have been made to convert 30 prototype building models (20 different building types), which cover 80% of US commercial building floor space, to OpenStudio prototype buildings. Additionally, the suite of prototype building models was expanded to include the addition of new building prototype models (e.g., courthouse, college building). This report documents the building and system characteristics of the prototype convenience store building model. Multiple sources, including databases, documented projects, and personal communications, were used to define the prototype convenience store building characteristics, and a one-story, 3,000 ft 2 building was considered as the prototype convenience store to represent an average-sized convenience store in the United States. The Oak Ridge National Laboratory team defined the operational hours of the convenience store as 17 hours per day. The types of exterior walls, roof, and floor were defined as brick wall, metal surfacing roof, and slab-on-grade floor, respectively. Double glazing was selected, and the window-towall ratio was set as 15% on the front side. For the system part, packaged system and centralized water heater were selected for the space heating and cooling system and water heater system, respectively. In terms of the refrigerator system, the number of refrigerators and freezers were determined as eight closed cases and two walk-in units.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Understanding the U.S. Commercial Building Stock: Building Envelope and HVAC Systems Characteristics Using 2012 CBECS Data Analysis

The U.S. Department of Energy (DOE) and its national labs developed a series of commercial reference building models in 2007. Over the past decade, the Pacific Northwest National Laboratory, in support of DOE’s Building Energy Codes Program, expanded these prototype building models to comply with multiple editions of national model codes and standards, including both ASHRAE Standard 90.1 and International Energy Conservation Code. The prototype building models established a credible foundation to develop new requirements in building codes and standards, track progress of codes and standards, and evaluate the energy saving potential of new technologies or systems in the commercial building sector. The 2003 Commercial Building Energy Consumption Survey (CBECS) was the primary data source used to develop the original models. Given the recent release of 2012 CBECS data, this paper characterizes the most representative design choices for building envelope and HVAC systems in recently-constructed commercial buildings. The results from this analysis provide actionable insight for future commercial building research in reflection of recent construction practices.

energy efficiency, building energy codes, CBECS, b↗
DOE OSTI2023

Establishing a versatile toolkit of flux enhanced strains and cell extracts for pathway prototyping

Building and optimizing biosynthetic pathways in engineered cells holds promise to address societal needs in energy, materials, and medicine, but it is often time-consuming. Cell-free synthetic biology has emerged as a powerful tool to accelerate design-build-test-learn cycles for pathway engineering with increased tolerance to toxic compounds. However, most cell-free pathway prototyping to date has been performed in extracts from wildtype cells which often do not have sufficient flux towards the pathways of interest, which can be enhanced by engineering. Here, in this study, to address this gap, we create a set of engineered Escherichia coli and Saccharomyces cerevisiae strains rewired via CRISPR-dCas9 to achieve high-flux toward key metabolic precursors; namely, acetyl-CoA, shikimate, triose-phosphate, oxaloacetate, α-ketoglutarate, and glucose-6-phosphate. Cell-free extracts generated from these strains are used for targeted enzyme screening in vitro. As model systems, we assess in vivo and in vitro production of triacetic acid lactone from acetyl-CoA and muconic acid from the shikimate pathway. The need for these platforms is exemplified by the fact that muconic acid cannot be detected in wildtype extracts provided with the same biosynthetic enzymes. We also perform metabolomic comparison to understand biochemical differences between the cellular and cell-free muconic acid synthesis systems (E. coli and S. cerevisiae cells and cell extracts with and without metabolic rewiring). While any given pathway has different interfaces with metabolism, we anticipate that this set of pre-optimized, flux enhanced cell extracts will enable prototyping efforts for new biosynthetic pathways and the discovery of biochemical functions of enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Analysis for Building Envelopes and Mechanical Systems Using 2012 CBECS Data

This report describes the aggregation and mapping of certain building characteristics data available in the most recent Commercial Building Energy Consumption Survey (CBECS) (DOE EIA 2012) to describe most typical building construction practices. This report provides summary data for potential use in the support of modifications to the Pacific Northwest National Laboratory’s commercial building prototypes used for building energy code analysis. Specifically, this report outlines findings and most typical design choices for certain building envelope and heating, ventilating, and air-conditioning (HVAC) system choices.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

A Retrofit Tool for Improving Energy Efficiency of Commercial Buildings

Existing buildings will dominate energy use in commercial buildings in the United States for three decades or longer and even in China for the about two decades. Retrofitting these buildings to improve energy efficiency and reduce energy use is thus critical to achieving the target of reducing energy use in the buildings sector. However there are few evaluation tools that can quickly identify and evaluate energy savings and cost effectiveness of energy conservation measures (ECMs) for retrofits, especially for buildings in China. This paper discusses methods used to develop such a tool and demonstrates an application of the tool for a retrofit analysis. The tool builds on a building performance database with pre-calculated energy consumption of ECMs for selected commercial prototype buildings using the EnergyPlus program. The tool allows users to evaluate individual ECMs or a package of ECMs. It covers building envelope, lighting and daylighting, HVAC, plug loads, service hot water, and renewable energy. The prototype building can be customized to represent an actual building with some limitations. Energy consumption from utility bills can be entered into the tool to compare and calibrate the energy use of the prototype building. The tool currently can evaluate energy savings and payback of ECMs for shopping malls in China. We have used the tool to assess energy and cost savings for retrofit of the prototype shopping mall in Shanghai. Future work on the tool will simplify its use and expand it to cover other commercial building types and other countries.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

The Building ENergy Demand (BEND) Model: A Comprehensive Composite Building Energy Modeling Framework

The Building ENergy Demand (BEND) model was developed at Pacific Northwest National Laboratory (PNNL) to simulate climate-dependent hourly building energy demand with the ability to disaggregate down to or aggregate up to any geographic area of interest, including counties, states, electric utility service territories, and census regions. The BEND modeling framework is designed to study the effects of climate change, economics, technology advancement, and various mitigation policies on aggregate building energy demand. To make the process computationally feasible, BEND reduces granularity in building characteristics and weather forcing while maintaining enough detail to minimize systematic differences (biases) between BEND results and data from the Energy Information Administration (EIA). Based on the Commercial Building Energy Consumption Survey (CBECS) and Residential Energy Consumption Survey (RECS) databases, BEND establishes a set of representative buildings with predefined sets of building types, sizes, and vintages. These representative buildings are defined for each of the four U.S. census regions and the five climate zones used by the EIA for building surveys (hereafter “EIA climate zones”). BEND’s representative buildings are based on a statistical analysis of the CBECS and RECS databases that infers detailed parameters such as construction type, thermal properties, internal loads, equipment and mechanical systems, and operation schedules from the high-level descriptors in those databases (building type, vintage, size, and location). The representative buildings are simplified and consolidated into a set of prototype buildings for the purpose of simulating building energy demand. Combining the prototype buildings with weather files from selected locations and years, BEND creates a set of simulation-ready building models to be run using the EnergyPlus simulation engine (EnergyPlus). The base spatial unit of each BEND simulation is a subregion that is the intersection of an International Energy Conservation Code climate zone, a census region, and an EIA climate zone; analysis for each spatial unit is influenced by the weather file BEND selects to represent the climate-similar area. The major simulation outputs of interest to BEND are hourly energy consumption values for each simulated year, possibly for multiple fuel types. Based on building-stock weights derived from the CBECS/RECS data, the hourly output streams are aggregated to a single, 8760-hour load profile for each of the major building categories—residential and commercial—with the possibility of segregating by fuel types. To correct for biases inherent in the use of a limited suite of representative buildings, BEND is calibrated against observational targets of total annual building energy consumption and hourly load profiles (including peak demand) obtained for the decision-relevant geographic scales of interest (e.g., total electric load data for individual balancing authorities available from EIA). Based on available data such as population distribution, BEND is able to aggregate both up and down scales, allowing the study of building energy demand over a range of spatial scales (e.g., states or counties within the Western Electricity Coordinating Council, Eastern Interconnection, or the entire U.S.) and/or subsets of building types (e.g., office buildings with particular size ranges).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2011

ANSI/ASHRAE/IES Standard 90.1-2010 Final Determination Quantitative Analysis

The U.S. Department of Energy (DOE) conducted a final quantitative analysis to assess whether buildings constructed according to the requirements of the American National Standards Institute (ANSI)/American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE)/Illuminating Engineering Society of North America (IESNA) Standard 90.1-2010 (ASHRAE Standard 90.1-2010, Standard 90.1-2010, or 2010 edition) would result in energy savings compared with buildings constructed to ANSI/ASHRAE/IESNA Standard 90.1-2007(ASHRAE Standard 90.1-2007, Standard 90.1-2007, or 2007 edition). The final analysis considered each of the 109 addenda to ASHRAE Standard 90.1-2007 that were included in ASHRAE Standard 90.1-2010. All 109 addenda processed by ASHRAE in the creation of Standard 90.1-2010 from Standard 90.1-2007 were reviewed by DOE, and their combined impact on a suite of 16 building prototype models in 15 ASHRAE climate zones was considered. Most addenda were deemed to have little quantifiable impact on building efficiency for the purpose of DOE's final determination. However, out of the 109 addenda, 34 were preliminarily determined to have a measureable and quantifiable impact. A suite of 240 computer energy simulations for building prototypes complying with ASHRAE 90.1-2007 was developed. These prototypes were then modified in accordance with these 34 addenda to create a second suite of corresponding building simulations reflecting the same buildings compliant with Standard 90.1-2010. The building simulations were conducted using the DOE EnergyPlus building simulation software. The resulting energy use from the complete suite of 480 simulation runs was then converted to energy use intensity (EUI, or energy use per unit floor area) metrics (Site EUI, Primary EUI, and energy cost intensity [ECI]) results for each simulation. For each edition of the standard, these EUIs were then aggregated to a national basis for each prototype using weighting factors based on construction floor area developed for each of the 15 U.S. climate zones using commercial construction data. When compared, the resulting weighted EUIs indicated that each of the 16 building prototypes used less energy under Standard 90.1-2010 than under Standard 90.1-2007 on a national basis when considering site energy, primary energy, or energy cost. The EUIs were also aggregated across building types to a national commercial building basis using the same weighting data. On a national basis, the final quantitative analysis estimated a floor-space-weighted national average reduction in new building energy consumption of 18.2 percent for source energy and 18.5 percent when considering site energy. An 18.2 percent savings in energy cost, based on national average commercial energy costs for electricity and natural gas, was also estimated.

03 NATURAL GAS↗
DOE OSTI2011

ANSI/ASHRAE/IES Standard 90.1-2010 Final Determination Quantitative Analysis

The U.S. Department of Energy (DOE) conducted a final quantitative analysis to assess whether buildings constructed according to the requirements of the American National Standards Institute (ANSI)/American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE)/Illuminating Engineering Society (IES) Standard 90.1-2010 (ASHRAE Standard 90.1-2010, Standard 90.1-2010, or 2010 edition) would result in energy savings compared with buildings constructed to ANSI/ASHRAE/Illuminating Engineering Society of North America (IESNA) Standard 90.1- 2007(ASHRAE Standard 90.1-2007, Standard 90.1-2007, or 2007 edition). The final analysis considered each of the 109 addenda to ASHRAE Standard 90.1-2007 that were included in ASHRAE Standard 90.1- 2010. All 109 addenda processed by ASHRAE in the creation of Standard 90.1-2010 from Standard 90.1-2007 were reviewed by DOE, and their combined impact on a suite of 16 building prototype models in 15 ASHRAE climate zones was considered. Most addenda were deemed to have little quantifiable impact on building efficiency for the purpose of DOE’s final determination. However, out of the 109 addenda, 34 were preliminarily determined to have a measureable and quantifiable impact. A suite of 240 computer energy simulations for building prototypes complying with ASHRAE 90.1- 2007 was developed. These prototypes were then modified in accordance with these 34 addenda to create a second suite of corresponding building simulations reflecting the same buildings compliant with Standard 90.1-2010. The building simulations were conducted using the DOE EnergyPlus building simulation software. The resulting energy use from the complete suite of 480 simulation runs was then converted to energy use intensity (EUI, or energy use per unit floor area) metrics (Site EUI, Primary EUI, and energy cost intensity [ECI]) results for each simulation. For each edition of the standard, these EUIs were then aggregated to a national basis for each prototype using weighting factors based on construction floor area developed for each of the 15 U.S. climate zones using commercial construction data. When compared, the resulting weighted EUIs indicated that each of the 16 building prototypes used less energy under Standard 90.1-2010 than under Standard 90.1-2007 on a national basis when considering site energy, primary energy, or energy cost. The EUIs were also aggregated across building types to a national commercial building basis using the same weighting data. On a national basis, the final quantitative analysis estimated a floor-space-weighted national average reduction in new building energy consumption of 18.2 percent for source energy and 18.5 percent when considering site energy. An 18.2 percent savings in energy cost, based on national average commercial energy costs for electricity and natural gas, was also estimated.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Comparison of effectiveness and energy use of airborne pathogen mitigation measures to meet clean air targets in a prototypical office building

Organizations such as ASHRAE and the Centers for Disease Control and Prevention (CDC) have proposed guidelines for controlling infectious aerosols in buildings, which can be met through measures such as modified operation of the heating, ventilation, and air-conditioning (HVAC) system or incorporating air-cleaning technologies. However, more research is needed to understand the trade-offs between health, energy, and comfort aspects when designing measures for these guidelines. To address this gap, this paper presents an analysis using new models for air-cleaning technologies, including in-duct and in-room germicidal ultraviolet (GUV) systems and portable air cleaners (PACs). These models are incorporated into an existing prototypical office building model and six measures are designed to meet ASHRAE Standard 241 and CDC clean air targets: MERV 13 HVAC filtration, maximum outdoor air supplied to the building, PACs, and in-duct, upper-room, and whole-room GUV. The measures are simulated for an office building in a cool and humid climate compared against a baseline simulation using MERV 8 filtration. The results show that all measures, except for the maximum outdoor air case, can meet the ASHRAE 241 standard without significant impacts on energy or comfort. The HVAC system measures were not able to meet the CDC target with the default system sizing and lead to significant energy increases, while the in-room measures were able to meet the CDC target with small impacts on energy consumption. Finally, this paper consolidates the simulation findings and provides practical guidance for building operators to meet clean air targets while limiting energy and comfort impacts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Assessing overall building energy performance of a large population of residential single-family homes using limited field data

The U.S. Department of Energy (DOE), through the Building Energy Codes Program (BECP), supports building energy code development and implementation processes to achieve the maximum practicable, cost-effective improvements in energy efficiency while providing safe, healthy buildings for occupants. Currently, there is a lack of statistically representative data that shows how energy codes are implemented in the field and the energy savings opportunities that exist. To address this gap, DOE initiated a research study targeted at new residential single-family homes in 8 states starting in the fall of 2014. The study comprises of a baseline phase to determine current levels of compliance with the key energy provisions of the residential building energy code, identify issues, and calculate potential energy savings from improved compliance; a second phase implementing education, training and outreach activities designed to increase targeted code compliance; and a post-study phase to measure the impact of the training and outreach activities compared to the baseline phase. Initial analyses determined the code requirements with the largest energy impact and the minimum number of observations required to detect statistically significant differences in energy use. Data was collected in the field during a single site visit to avoid bias from repeat visits. However, the single site visit principle prevented energy simulation of individual homes due to the lack of all required model inputs. To address this, energy simulation was conducted using Pacific Northwest National Laboratory’s prototype building models and employing bootstrap random sampling on the data collected from all homes visited. The modeled energy consumption using the observed field data was evaluated relative to that associated with the minimum code requirements and potential savings associated with improved compliance of select items were assessed. This paper discusses the methodology developed for this field study, and presents the results and findings from the baseline phase.

Xie, YuLong↗
DOE OSTI2015

An Analysis of Representative Heating Load Lines for Residential HSPF Ratings

This report describes an analysis to investigate representative heating loads for single-family detached homes using current EnergyPlus simulations (DOE 2014a). Hourly delivered load results are used to determine binned load lines using US Department of Energy (DOE) residential prototype building models (DOE 2014b) developed by Pacific Northwest National Laboratory (PNNL). The selected residential single-family prototype buildings are based on the 2006 International Energy Conservation Code (IECC 2006) in the DOE climate regions. The resulting load lines are compared with the American National Standards Institute (ANSI)/Air-Conditioning, Heating, and Refrigeration Institute (AHRI) Standard 210/240 (AHRI 2008) minimum and maximum design heating requirement (DHR) load lines of the heating seasonal performance factor (HSPF) ratings procedure for each region. The results indicate that a heating load line closer to the maximum DHR load line, and with a lower zero load ambient temperature, is more representative of heating loads predicted for EnergyPlus prototype residential buildings than the minimum DHR load line presently used to determine HSPF ratings. An alternative heating load line equation was developed and compared to binned load lines obtained from the EnergyPlus simulation results. The effect on HSPF of the alternative heating load line was evaluated for single-speed and two-capacity heat pumps, and an average HSPF reduction of 16% was found. The alternative heating load line relationship is tied to the rated cooling capacity of the heat pump based on EnergyPlus autosizing, which is more representative of the house load characteristics than the rated heating capacity. The alternative heating load line equation was found to be independent of climate for the six DOE climate regions investigated, provided an adjustable zero load ambient temperature is used. For Region IV, the default DOE climate region used for HSPF ratings, the higher load line results in an ~28% increase in delivered heating load and an ~52% increase in the estimated heating operating cost over that given in the AHRI directory (AHRI 2014).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Energy Performance of Awnings in Residential Buildings

Residential buildings consume approximately 20% of the total primary energy in the United States. More than 50% of this energy is spent in heating, cooling, and lighting these buildings. Solar heat gain is one of the largest and most variable sources of cooling load in these buildings, while it can also provide passive heating during the heating season. Shading devices can be used to control the amount of solar heat gain in buildings. Various studies have considered how different shading devices and their applications affect energy and occupant comfort in buildings. However, most of these studies were limited to planar shading devices such as roller shades, cellular shades, and blinds. Although some theoretical studies have been performed for awnings, the energy performance of awnings has rarely been studied via either energy simulation or field measurement. In this study, the authors evaluated the energy performance of typical operable awnings by using field data, aided by simulation. Awnings were installed on a real house, and measurements were performed to evaluate the thermal performance of the awning. The measured data were then used to develop a calibrated energy model and evaluate the awning’s energy performance. The annual simulation of the building model used showed that awnings left in the closed position from April to September can reduce annual HVAC energy consumption by 15% compared with a building without any shades. The validated model was used in US Department of Energy prototype buildings to evaluate awning energy performance in climate zones 1A through 4B via energy simulation. For these prototype buildings, energy savings of up to 1,034 kWh were achieved for a building with a conditioned floor area of 2,377 ft 2 .

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗