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At least 1,279 records · Page 71

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DOE OSTI2021

Performance of a Hybrid HVAC-Integrated Thermal Storage Device

Thermal equipment in buildings is a primary contributor to peak loads on the electrical grid. Thermal energy storage is a cost-effective strategy to decouple electric use from thermal loads, thus reducing grid peak costs for building owners. One method for storing thermal energy in a building is to integrate a phase change material (PCM) directly into the heating, ventilation, and air conditioning system. These systems often require additional glycol loops, pumps, valves, and heat exchangers to couple the storage to the cooling system and building space, which increases the complexity and cost. This work will discuss an alternate approach where the storage is added directly into the heat pump evaporator. A detailed two-dimensional finite difference heat transfer model of a PCM-refrigerant-glycol heat exchanger was developed to simulate the performance of this component. The fluid stream was discretized along the flow direction to capture changes in the fluid properties and local heat transfer rates, and the phase change material was discretized in both the x and y directions to capture the movement of the melt front. The model was used to understand the impact of different material and geometric properties on the charge and discharge characteristics of the device. Finally, a Ragone framework analogous to that used for electrochemical batteries was used to maximize the energy density and round-trip efficiency of the device while supplying loads appropriate for space cooling in buildings.

buildings↗

DOE OSTI2022

Field Measurement of Central CO2 Heat Pump Water Heater for Multifamily Retrofit

Domestic hot water heating of multifamily buildings accounts for a substantial portion of the energy load of existing buildings. This load is made up of both the energy required to produce hot water and the energy needed to maintain the temperature of the heated water within a building’s distribution piping so that heat can be promptly delivered to building occupants as needed. Properly designed heat pump water heater (HPWH) systems have the ability to improve efficiency in both water heating and temperature control operations. Further, CO2 heat pump technology reflects a shift away from traditional refrigerants and toward refrigerants with low global warming potential (GWP). In this paper’s case study, a design consisting of multiple CO2 heat pump water heaters (commonly used in single-family homes) with a novel “swing tank” was proposed to meet the demand for domestic hot water heating and recirculation loop temperature maintenance. The proposed design was applied to the retrofit of a 60-unit, low-rise, multi-family building located in the Pacific Northwest of the United States. The purpose of this paper is to verify the performance of the system including the proposed “swing tank” in a centralized SHW system using CO2 HPWH. It also provides practical information and lessons learned from the retrofit project. Long-term monitoring data showed that the system had a coefficient of performance (COP) of three or greater and provided an average of 20 gallons of hot water per day per apartment. The results of this work indicate that residential-scale CO2 HPWH equipment and a “swing tank” design can efficiently provide domestic hot water heating and temperature maintenance for mid-sized multifamily buildings.

Banks, Adria↗

DOE OSTI2026

Physics vs structure: A systematic benchmark of learning strategies for multi-zone building thermal dynamics

Recent advances in physics-informed and data-driven machine learning promise improved thermal models for advanced building control, yet there is limited quantitative evidence on when added physics structure and architectural complexity are beneficial. Here, this work presents a systematic benchmark of five representative system identification methods for modeling multi-zone building thermal dynamics: linear state-space models, multi-layer perceptrons, neural state-space models, neural ordinary differential equations, and physically-consistent neural networks. The methods are evaluated across multiple data regimes and zone coupling strategies. Using a high-fidelity multi-zone commercial building emulator, we examine short-term and long-term prediction accuracy, computational efficiency, and ease of development. Our results reveal critical trade-offs between prediction performance, model complexity, and physical consistency. We demonstrate that decoupled, nonlinear black-box models consistently outperform coupled physics-constrained architectures in both predictive accuracy and out-of-distribution robustness in majority of the test cases for the building type considered in the study. Our findings quantify the cost of complexity in building thermal modeling and provide concrete, actionable, scenario-based guidelines for selecting model classes for control-oriented applications.

Building thermal modeling↗

DOE OSTI2024

An Open-Source Decarbonization Analytics Framework: Designing for Low-Carbon Emission Districts and Communities: Preprint

This paper introduces an open-source analytics framework designed to assist in creating low or net-zero carbon buildings and urban districts. Integrated within URBANopt, an open-source platform for energy analysis in districts and communities, this framework equips researchers, architects, engineers, and other stakeholders with tools to evaluate the carbon footprint implications of their design choices. The framework enables the analysis of various scenarios, incorporating both historical and future emission factors, and can span across different climate zones, each with distinct grid and emissions characteristics. The results showcase the framework's capability to evaluate the impact of design upgrades and control strategies on carbon emissions in districts and communities. An illustrative analysis using a hypothetical district in Denver, Colorado, shows reduced emissions from energy efficiency upgrades and control strategies, highlighting the sensitivity in their effects on emissions and energy use.

buildings energy efficiency↗

DOE OSTI2025

Alaska's Rural Building Stock: a Validation Study Using ResStock and Field Data

The availability of accurate national data on demographics, building stock, and energy use is vital for modeling residential buildings and evaluating decarbonization strategies. However, rural and Indigenous populations, including those in rural Alaska, are typically underrepresented in these datasets. These communities face unique challenges due to their remote locations, severe weather conditions, and limited access to resources, resulting in high energy burden. This report examines how rural Alaskan communities are underrepresented in the ResStock housing model and highlights the need for improved data to address their unique housing and energy challenges. Thus, this report examines the representation of rural Alaskan communities within the national housing stock model, ResStock. A validation study was conducted, considering ResStock, Field Data and Aerial and 3D-view data collection (A3DDC) datasets. The validation process started by using the down selecting approach on the ResStock building stock dataset. For the purpose of this study, only the rural Alaska Boroughs and Census areas located in ASHRAE IECC Climate Zone 8 were considered to ensure a more accurate and fair comparison with the field data, which was collected in rural areas located in climate zone 8, specifically within the Nome Census area. While ResStock may accurately represent several characteristics of the building stock for rural Alaska, some differences between modeled, field data, and aerial and 3D-view data collection datasets were identified. The following building characteristics have a high impact on modeled energy consumption and demonstrated large differences: Revisit heating setpoints and consider a substantially higher setpoint distribution, it could potentially address "missing loads" if this is the case. Develop and include Toyo heating in future modeling for ResStock and EnergyPlus. Remove natural gas as a water heater fuel type outside of North Slope County. Foundation type updated to have more crawlspaces rather than basements. Infiltration rates need reexamination for a larger distribution toward higher infiltration rates. Include more vinyl and less brick in exterior wall type and revise wall color for greater proportion of light rather than dark color. Roof material revised from majority shingles to majority metal. Update number of occupants to higher number of occupant count. Building orientation represents a higher proportion of south facing buildings rather than relatively equal. The findings suggest that updating ResStock's probability logic could better represent rural Alaskan buildings. ResStock can be utilized to identify the best upgrades or energy efficiency and energy efficiency improvements, helping community leaders in making more informed decisions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

2024 Stor4Build Annual Meeting: Exploring Challenges and Opportunities in Thermal Energy Storage for Buildings

In late August 2024, Stor4Build brought nearly 80 stakeholders from the thermal energy storage industry to Oak Ridge National Laboratory (ORNL), including researchers, startups, electric utilities, nonprofits, implementers, state energy efficiency offices, and original equipment manufacturers. During the two-day Stor4Build Annual Meeting, participants engaged in vital discussions about the current challenges and opportunities for scaling thermal energy storage solutions in buildings. The event featured panel discussions led by leading technology experts and industry practitioners, as well as updates on Stor4Build–funded projects from national laboratories, highlighting advancements in the thermal energy storage field crucial to achieving the consortium’s mission.

25 ENERGY STORAGE↗

DOE OSTI2026

ComStock Measure Documentation: Fan Static Pressure Reset for Multizone Variable Air Volume Systems

This report assesses the potential for nationwide adoption of a duct static pressure reset in MZ VAV systems in appropriate applications. Building on the 3-year End-Use Load Profiles project to calibrate and validate the U.S. Department of Energy’s ResStock™ and ComStock™ models, this work produces national datasets that enable cities, states, utilities, and other stakeholders to answer a broad range of questions regarding their commercial building stock. ComStock is a highly granular, bottom-up model that uses various data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual sub-hourly energy consumption of the commercial building stock across the United States. The “baseline” model intends to represent the U.S. commercial building stock as it existed in 2018. The methodology of the baseline model is discussed in the ComStock Reference Documentation. The goal of this work is to develop energy efficiency and demand flexibility measures that cover market-ready technologies and study their mass-adoption impact on the baseline building stock. “Measures” refers to various “what-if” scenarios that can be applied to buildings. The results for the baseline and measure scenario simulations are published in public datasets that provide insights into building stock characteristics, operational behaviors, utility bill impacts, and annual and sub-hourly energy usage by fuel type and end use. This report describes the modeling methodology for a single ComStock measure scenario—Fan Static Pressure Reset for Multizone Variable Air Volume (VAV) Systems—and briefly introduces key results. The full public dataset can be accessed on the ComStock data lake or via the Data Viewer at comstock.nrel.gov. The public dataset enables users to create custom aggregations of results for their use case (e.g., filter to a specific county or building type).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

ComStock Measure Documentation: Thermostat Setbacks During Unoccupied Periods

This report assesses the potential for nationwide adoption of thermostat setbacks in appropriate applications. Building on the 3-year End-Use Load Profiles project to calibrate and validate the U.S. Department of Energy’s ResStock™ and ComStock™ models, this work produces national datasets that enable cities, states, utilities, and other stakeholders to answer a broad range of questions regarding their commercial building stock. ComStock is a highly granular, bottom-up model that uses various data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual sub-hourly energy consumption of the commercial building stock across the United States. The “baseline” model intends to represent the U.S. commercial building stock as it existed in 2018. The methodology of the baseline model is discussed in the ComStock Reference Documentation. The goal of this work is to develop energy efficiency and demand flexibility measures that cover market-ready technologies and study their mass-adoption impact on the baseline building stock. “Measures” refers to various “what-if” scenarios that can be applied to buildings. The results for the baseline and measure scenario simulations are published in public datasets that provide insights into building stock characteristics, operational behaviors, utility bill impacts, and annual and sub-hourly energy usage by fuel type and end use. This report describes the modeling methodology for a single ComStock measure scenario— Thermostat Setbacks During Unoccupied Periods—and briefly introduces key results. The full public dataset can be accessed on the ComStock data lake or via the Data Viewer at comstock.nrel.gov. The public dataset enables users to create custom aggregations of results for their use cases (e.g., filter to a specific county or building type).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Financing Options for Onsite Generation, Energy Storage, and Energy Efficiency Projects

Across sectors, commercial and industrial facilities are benefiting from the implementation of renewable energy generation, storage, and energy efficiency projects. Despite the potential for these projects to reduce onsite energy consumption, build resiliency, and lower operational costs in the long term, the initial expenses are often high. However, there are a growing number of financing mechanisms that can be leveraged. When deployed strategically, these mechanisms can give organizations the financial tools to install projects that accomplish their energy goals. In 6 steps, this resource introduces organizations to a general process to contextualize the many different financing options, ultimately facilitating an informed selection of financing mechanisms. Step 1 discusses the importance of establishing clear organizational preferences. Step 2 briefly introduces common financing options and Steps 3 and 4 provide guidance for selecting mechanisms based on locational availability and organizational preferences. Finally, Steps 5 and 6 show how mechanisms can be combined with incentives and provide preliminary guidance for selecting and engaging with external partners. While this document provides a general approach to selecting a financing mechanism for renewable energy generation, storage, and/or energy efficiency, it does not contain tax and/or legal advice. A tax advisor should be consulted before taking any action.

25 ENERGY STORAGE↗

DOE OSTI2020

Energy Intensity Baselining & Tracking Summary Guide: Better Buildings, Better Plants

The Department of Energy (DOE) Better Plants (BP) program is a voluntary energy efficiency leadership initiative for U.S. manufacturers that encourages companies to reduce their energy intensity, typically by 25% within a ten-year period. BP partners are required to report their progress to the DOE annually by establishing an energy intensity baseline and tracking their energy consumption. BP partners receive access to a Technical Account Manager (TAM), DOE resources including software tools and trainings, and recognition when they achieve their goal. This summary guide provides the basics of baselining and tracking your energy intensity. For a more information and special considerations, please see the Energy Intensity Baselining and Tracking Guidance 2020.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1982

Power efficient optical communications for space applications

Optical communications technology promises substantial size, weight and power consumption savings for space to space high data rate communications over presently used microwave technology. These benefits are further increased by making the most efficient use of the available optical signal energy. This presentation will describe the progress to date on a project to design, build and demonstrate in the laboratory an optical communication system capable of conveying 2.5 bits of information per effective received photon. Such high power efficiencies will reduce the need for photon collection at the receiver and will greatly reduce the requirements for optical pointing accuracy, both at the transmitter as well as the receiver. A longer range program to demonstrate even higher photon efficiencies will also be described.

Lesh, J. R.↗

DOE OSTI2022

Paintable Heat-Reflective Coatings for Low-Cost Energy Efficient Windows

The major objective of this effort is to manufacture a paintable coating to inexpensively retrofit energy-inefficient windows with a heat-reflective, visibly transparent film. This coating will drastically reduce cooling costs for millions of homes and buildings and lower the Nation’s greenhouse gas emissions. Widespread implementation could reduce the national consumption of electricity for cooling by billions of kWh, saving billions of dollars per year. This improved energy efficiency would decrease CO2 emissions by billions kg per year, the equivalent to removing millions of cars from the road. Although near-IR reflective adhesive films are commercially available products and have demonstrated significant energy efficiency enhancement, high upfront costs largely deter potential consumers across all sectors. The technology developed under this award was proposed to disrupt the building envelope market, by providing an inexpensive coating that can be directly applied by consumers to improve the energy efficiency of virtually all window types. The proof of concept for a paintable, DIY applicable, visibly transparent, and infrared reflective coating was achieved, laying the foundation for future technology development in this area.

14 SOLAR ENERGY↗

DOE OSTI2021

A Scoping Study to Develop a Computational Fluid Dynamics Based Model to Predict Radiological Materials Packaging Temperatures within a Generic Staging Building

The objective of this work is to perform computational fluid dynamics simulations of a ventilated radiological-material-package staging building to determine the effect of including or excluding a variety of physical effects and computational methods on both the predicted package temperatures and required computational resources. The generic building contains 640 drum-packages containing heat-generating, radiological material supported on four racks that are eight levels tall. Additionally, there is a forced ventilation system, lighting, and insulated walls. Computational models were constructed that included or excluded (a) shelving, (b) effects of unsteadiness, and (c) radiation heat transfer. Simulations with each drum modeled separately were compared to simpler simulations with sets of four drums represented by an equivalent box-package. These models employed between 106 to 107 elements. Steady state simulations predicted package temperatures that were within 0.1°C of simulations that included transient effects and required only one-eighth the computational resources. Calculations that excluded shelving predicted temperatures within 0.6°C of simulations that included shelving and required one-fourth the computational resources. Excluding radiation heat transfer systematically increased temperatures by around 1.5°C but reduced computational resources by a factor of four. The box-package model reduced the computational resources by a factor of 3, but systematically predicted higher temperatures by around 1.1°C. These results will be used to develop an efficient computational fluid dynamics model to assess the ability of different staging building designs to prevent the temperature of package components from exceeding specified limits.

42 ENGINEERING↗

DOE OSTI2026

Opportunity Assessment for U.S. Industry: Energy-Efficient Cooling Technologies in Mexico

Mexico's rapidly expanding room air conditioner (AC) market presents a strategic opportunity for U.S. manufacturers to strengthen North American supply chains while addressing critical energy infrastructure challenges. With demand for room AC units in residential and commercial buildings projected to drive a 26 GW increase in Mexico’s peak electrical load by 2050, high-efficiency air conditioning systems offer both substantial market opportunities and essential grid stability benefits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Performance analysis of hybrid power configurations: Impact on primary energy intensity, carbon dioxide emissions, and life cycle costs

In this work, utilization of Natural gas and Hydrogen to support current and future building energy needs to offset the total electric demand while improving the grid resiliency and energy efficiency was investigated. Demand side energy management will play an important role in efficiently managing the available energy resources. Performance assessment of different power generation and energy management configurations is presented in this paper. Development of solutions in addressing grid resiliency by providing the ability to design suitable configurations for meeting individual building energy needs is discussed. Primary movers (PM) such as internal combustion engines (ICE) and fuel cells (FC) along with small scale auxiliary renewable energy source such as photovoltaics (PV) were considered. Key attributes of total carbon foot-print, life cycle costs including capital and operational expenditure, electric grid offset or peak shaving capability, thermal energy availability and its further potential to offset total electric demand, and primary energy intensity are analyzed and discussed in detail.

08 HYDROGEN↗

DOE OSTI2020

P-model v1.0: an optimality-based light use efficiency model for simulating ecosystem gross primary production

Terrestrial photosynthesis is the basis for vegetation growth and drives the land carbon cycle. Accurately simulating gross primary production (GPP, ecosystem-level apparent photosynthesis) is key for satellite monitoring and Earth system model predictions under climate change. While robust models exist for describing leaf-level photosynthesis, predictions diverge due to uncertain photosynthetic traits and parameters which vary on multiple spatial and temporal scales. Here, we describe and evaluate a GPP (photosynthesis per unit ground area) model, the P-model, that combines the Farquhar–von Caemmerer–Berry model for C 3 photosynthesis with an optimality principle for the carbon assimilation–transpiration trade-off, and predicts a multi-day average light use efficiency (LUE) for any climate and C 3 vegetation type. The model builds on the theory developed in Prentice et al. (2014) and Wang et al. (2017a) and is extended to include low temperature effects on the intrinsic quantum yield and an empirical soil moisture stress factor. The model is forced with site-level data of the fraction of absorbed photosynthetically active radiation (fAPAR) and meteorological data and is evaluated against GPP estimates from a globally distributed network of ecosystem flux measurements. Although the P-model requires relatively few inputs, the R 2 for predicted versus observed GPP based on the full model setup is 0.75 (8 d mean, 126 sites) – similar to comparable satellite-data-driven GPP models but without predefined vegetation-type-specific parameters. The R 2 is reduced to 0.70 when not accounting for the reduction in quantum yield at low temperatures and effects of low soil moisture on LUE. The R 2 for the P-model-predicted LUE is 0.32 (means by site) and 0.48 (means by vegetation type). Applying this model for global-scale simulations yields a total global GPP of 106–122 Pg C yr –1 (mean of 2001–2011), depending on the fAPAR forcing data. The P-model provides a simple but powerful method for predicting – rather than prescribing – light use efficiency and simulating terrestrial photosynthesis across a wide range of conditions. The model is available as an R package (rpmodel).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Powering Post-COVID-19 Resilient Recovery with Green Stimulus

As the coronavirus disease (COVID-19) pandemic spread globally in early 2020, many governments enacted lockdown measures as an initial containment response. These lockdowns, while effective in slowing infection rates, have also had substantial economic consequences. A series of supply and demand shocks, workforce and supply chain disruptions, and other impacts of the pandemic and ensuing lockdowns have upended the livelihoods for much of the world's population. This quick read spotlights how green stimulus plans and other recovery measures can support near-term recovery and enable longer-term power system resilience against future threats. The term “green stimulus” encompasses fiscal measures (i.e., governmental tax and spending actions) that support short-term economic activity that enhances environmental and natural resource quality over a longer term. The deployment of energy efficiency (EE) and renewable energy (RE) technologies, as well as associated initiatives (e.g., grid modernization, electrification of transport, and so on) have been demonstrably effective in providing this kind of short-run economic boost while simultaneously strengthening the resilience of the power sector. Along with green stimulus packages, concurrent action on the regulatory side—for example, the development of green building codes, updating grid interconnection standards, creating programs and marketplaces for demand-side efficiency, and others—can be a force multiplier in ensuring that public spending achieves maximum impact in near-term recovery and long-term power sector transformation

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Developing Equivalent Surface Heat Transfer Input Parameters for Updated Standard 140/BESTEST Thermal Fabric Test Cases

ANSI/ASHRAE Standard 140, Standard Method of Test for the Evaluation of Building Energy Analysis Computer Programs, is widely cited for evaluating software for use with performance-path energy efficiency analysis in conjunction with well-known energy-efficiency standards, including: ASHRAE Standard 90.1, the International Energy Conservation Code, and other international standards. This paper summarizes recent work to develop improved equivalent surface heat transfer input parameters for the building thermal fabric comparative test cases that comprise a portion of Standard 140. The software-to-software comparative test method allows comparison of simulation results from a wide variety of building energy simulation programs to each other. In this type of test method, it is of great importance to specify inputs that are as well-equivalenced as possible to accommodate a wide variety of input schemes for the tested programs, and thereby reduce the potential for disagreements among them in the tests. Results include new alternative constant surface coefficients that are appropriate to the test cases and demonstrate their ability to approximate the more detailed surface heat transfer models from which they are derived.

BESTEST↗