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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

ComStock Measure Documentation: Variable-Speed Pumps

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 data sets 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 subhourly 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 data sets 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 - variable speed pumps - and briefly introduces key results. The full public data set can be accessed on the ComStock data lake or via the Data Viewer at comstock.nlr.gov. The public data set 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

Optimizing Heat Recovery with Storage: Control Validation and Sensitivity Analysis of the Time-Independent Energy Recovery Plant Using Modelica

Heat recovery in large building central plants saves energy but traditionally requires simultaneous heating and cooling. The Time-Independent Energy Recovery (TIER) plant shifts this paradigm by integrating thermal energy storage (TES) to enable heat recovery regardless of concurrent demand, offering a highly efficient, space-saving solution to achieve California’s energy goals. However, its integration of heat recovery chillers, cooling-only chillers, cooling towers, and trim air-source heat pumps (ASHPs) creates growing control and sizing complexity. To overcome this, this study employs high-fidelity Modelica dynamic simulation to validate TIER control sequences and optimize equipment sizing. We translated the written Sequences of Operation into executable Control Description Language (CDL) to test logic against sub-hourly loads. This verification workflow successfully identified and resolved critical vulnerabilities, such as thermal storage freezing and equipment short-cycling, in a virtual environment prior to physical deployment. Then, the study analyzes TIER plant performance across three simulated building types in three locations, and a real building load profile, ensuring variety in heating and cooling loads, and simultaneity factors and explores sizing rules for the TES and ASHP capacity. The analysis shows that the TIER plant operates equipment efficiently leading to a plant SCOP of around 7.5 across all scenarios, higher than a traditional ASHP plant, and a viable pathway to de-risk complex system design and control through simulation to identify optimal designs that maximize energy efficiency, minimize operational costs, and ensure robust operation in varied environmental conditions, thereby facilitating the broader adoption of such a solution for large buildings.

Zanetti, Ettore↗
DOE OSTI2021

High-resolution hourly surrogate modeling framework for physics-based large-scale building stock modeling

Surrogate modeling can play a key role in reducing high computational burdens for large-scale physics-based modeling and uncertainty quantification. With the rapid development of large-scale building stock energy modeling, surrogate modeling has also begun to be widely applied in this field; however, most existing surrogate models lack hourly time resolution for regional-scale modeling, which is essential for understanding building demand profiles and grid impacts. Further, there is generally a lack of necessary data and feature engineering frameworks specific to building modeling for efficiently managing large datasets and complex computations. Furthermore, this paper proposes a modeling framework for large-scale (city-/region-scale), high-resolution, high-fidelity surrogate building stock energy models. Our developed framework consists of six modules: (1) building stock energy modeling (ComStock TM and ResStock TM ), (2) data engineering for large simulation data, (3) high performance computing workflow, (4) feature engineering, (5) machine learning model development, and (6) model performance evaluation. Two case studies apply the developed framework in both residential and commercial building stock analysis to demonstrate its computational efficiency and surrogate modeling accuracies. Results show that surrogate models, when efficiently trained using the HPC workflow module, reach a high level of modeling accuracy for two case studies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Spillway preheating

In traditional models only an order one fraction of energy is transferred from the inflaton to radiation through nonperturbative resonance production in preheating immediately after inflation, due to backreaction effects. We propose a particle production mechanism that could improve the depletion of the inflaton energy density by up to four orders of magnitude. The improvement comes from the fast perturbative decays of resonantly produced daughter particles. They act as a “spillway” to drain these daughter particles, reducing their backreaction on the inflaton and keeping the resonant production effective for a longer period. Thus we dub the scenario “spillway preheating”. We also show that the fraction of energy density remaining in the inflaton has a simple inverse power-law scaling in the scenario. In general, spillway preheating is a much more efficient energy dissipation mechanism, which may have other applications in model building for particle physics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A methodology for selection of solid desiccants in energy recovery ventilators

Controlling indoor humidity levels is essential for maintaining acceptable indoor air quality in buildings. The use of energy recovery ventilators (ERVs) is an energy-efficient way to regulate indoor air humidity. Fixed-bed regenerators and rotary wheels are widely used ERVs because of their high sensible and latent effectiveness. These ERVs are made of desiccant-coated substrates, which enable them to transfer moisture between the supply and exhaust air streams. However, the moisture transfer ability of ERVs depends on the physiochemical and sorption properties of desiccants. Extensive, full-scale experiments are required to determine the best desiccant material for these systems. This paper presents a simplified method of selecting suitable desiccant materials for ERVs. The methodology involves important characterization methods, literature correlations for performance prediction, and cost-effective testing methods prior to full-scale testing, and full-scale test methods are discussed in detail. Furthermore, the performance of a few newly derived materials is evaluated and compared with that of conventional desiccants such as silica gel and molecular sieves. The highest latent effectiveness was obtained for composite of super absorbent polymer (SAP) with potassium formate (SAP-HCO2K-50 %), all-polymer porous solid desiccant (APPSD) and metal organic framework (MOF)–MIL–101 (Cr), followed by activated carbon fibre felt (ACFF) Silica sol-LiCl30, SAP, silica gel, MOF–303, and molecular sieve. Researchers and manufacturers would benefit from the proposed methodology and presented data in developing new desiccant materials for ERV applications.

Energy recovery↗
DOE OSTI2022

Predicting industrial building energy consumption with statistical and machine-learning models informed by physical system parameters

The industrial sector consumes about one-third of global energy, making them a frequent target for energy use reduction. Variation in energy usage is observed with weather conditions, as space conditioning needs to change seasonally, and with production, energy-using equipment is directly tied to production rate. Previous models were based on engineering analyses of equipment and relied on site-specific details. Others consisted of single-variable regressors that did not capture all contributions to energy consumption. Further, new modeling techniques could be applied to rectify these weaknesses. Applying data from 45 different manufacturing plants obtained from industrial energy audits, a supervised machine-learning model is developed to create a general predictor for industrial building energy consumption. The model uses features of air enthalpy, solar radiation, and wind speed to predict weather-dependency; motor, steam, and compressed air system parameters to capture support equipment contributions; and operating schedule, production rate, number of employees, and floor area to determine production-dependency. Results showed that a model that used a linear regressor over a transformed feature space could outperform a support vector machine and utilize features more representative of physical systems. Using informed parameters to build a reliable predictor will more accurately characterize a manufacturing facility's energy savings opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

A global comparison of building decarbonization scenarios by 2050 towards 1.5–2 °C targets

Buildings play a key role in the transition to a low-carbon-energy system and in achieving Paris Agreement climate targets. Analyzing potential scenarios for building decarbonization in different socioeconomic contexts is a crucial step to develop national and transnational roadmaps to achieve global emission reduction targets. This study integrates building stock energy models for 32 countries across four continents to create carbon emission mitigation reference scenarios and decarbonization scenarios by 2050, covering 60% of today’s global building emissions. These decarbonization pathways are compared to those from global models. Results demonstrate that reference scenarios are in all countries insufficient to achieve substantial decarbonization and lead, in some regions, to significant increases, i.e., China and South America. Decarbonization scenarios lead to substantial carbon reductions within the range projected in the 2 °C scenario but are still insufficient to achieve the decarbonization goals under the 1.5 °C scenario.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Analyzing the Impact of Future Weather Data on Energy Consumption in Weatherization Assistant

This study supports the mission of the U.S. Department of Energy’s Weatherization Assistance Program (WAP), which aims to increase the energy efficiency of dwellings and reduce their total residential expenditures. Specifically, we examine how projected future climate conditions may affect residential building energy performance by integrating future weather data into the National Energy Audit Tool (NEAT). Since WAP evaluates the cost-effectiveness of retrofit measures over lifespans of up to 30 years, accounting for evolving climate conditions is increasingly important. To reflect future household energy demands, this study replaces historically based Typical Meteorological Year (TMY3) weather inputs with Future Typical Meteorological Year (fTMY) datasets derived from global climate model (GCM) projections. A simulation-based framework was established to enable NEAT analysis under future weather conditions. This workflow involves converting EPW-format weather files into JSON inputs compatible with NEAT and generating degree-hour metrics needed for load calculations. The fTMY dataset used in this study was developed by Oak Ridge National Laboratory through downscaling of six GCMs under different emission scenarios and covers the period from 2020 to 2100. In contrast, the TMY3 dataset is based on historical weather data from 1961 to 1990. Simulations were conducted for benchmark single-family prototype buildings across ASHRAE climate zones 1–7, which cover all regions of the U.S. except the subarctic Zone 8 in northern Alaska, evaluating both heating and cooling loads under TMY3 and fTMY conditions. Four foundation types were tested, while heating systems were standardized, as NEAT does not differentiate thermal energy load by HVAC system type in its load calculations. Results show that fTMY weather input consistently yield lower heating loads and higher cooling loads across most locations, aligning with expected climate warming trends. Notably, colder regions such as zones 6A, 6B, and 7 experience marked reductions in heating load, while warmer and transitional zones, such as 2A (Lufkin, TX) and 3C (San Francisco, CA), have substantial increases in cooling loads. Although this study does not directly assess the performance of retrofit measures under future climate conditions, it provides a critical foundation for doing so. By quantifying shifts in baseline (i.e., pre-retrofit case) energy loads between historical and future weather files, the study highlights the importance of integrating climate-responsive data into audit tools. These findings will inform future efforts to evaluate the long-term effectiveness and cost-effectiveness of weatherization measures under changing climate conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Advanced Building Construction Collaborative (Final Technical Report)

This report summarizes the outcomes of RMI’s five-year U.S. Department of Energy–funded Advanced Building Construction Collaborative (ABC-C), which accelerated adoption of high-performance construction through industry collaboration, market research, technology commercialization, and demand aggregation. It highlights the Collaborative’s achievements—including engagement of more than 130 organizations, support for over $637 million in funding for ABC companies, and recommendations to scale advanced building construction through coordinated market, policy, and investment strategies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2021

Spillway Preheating

In traditional models only an order one fraction of energy is transferred from the inflaton to radiation through nonperturbative resonance production in preheating immediately after inflation, due to backreaction effects. We propose a particle production mechanism that could improve the depletion of the inflaton energy density by up to four orders of magnitude. The improvement comes from the fast perturbative decays of resonantly produced daughter particles. They act as a “spillway” to drain these daughter particles, reducing their backreaction on the inflaton and keeping the resonant production effective for a longer period. Thus we dub the scenario “spillway preheating”. We also show that the fraction of energy density remaining in the inflaton has a simple inverse power-law scaling in the scenario. In general, spillway preheating is a much more efficient energy dissipation mechanism, which may have other applications in model building for particle physics.

Cosmology of Theories beyond the SM↗
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 OSTI2025

Scaling Up: Demonstrating Risk Reduction and Cost Compression for Commercial Heat Pump Water Heaters (CRADA 625) (Final Report)

This report is a final deliverable for project 81966: Scaling Up: Demonstrating Risk Reduction and Cost Compression for Commercial Heat Pump Water Heaters (CRADA 625) Commercial heat pump water heater (CHPWH) systems can significantly improve the energy efficiency of service water heating (SWH), aka domestic hot water (DHW), in commercial and multifamily buildings but have not yet achieved widespread adoption due to pricing, complexity, and perceived risk factors. The goal of this project – Scaling Up: Demonstrating Risk Reduction and Cost Compression for Commercial HPWHs (Scaling Up) – was to demonstrate and validate a holistic systems approach for CHPWHs that de-risks the technology, creating a reliable, cost-effective, and repeatable approach to CHPWH deployment.

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

Analysis of Space-Conditioning Loads in Commercial Buildings

Space conditioning end-uses, which include heating, cooling, and ventilation, represent a significant fraction of commercial building energy use, with a wide variety of heating and cooling technology options available in the market. In the interest of improving the overall efficiency of heating, ventilation and air-conditioning (HVAC) technologies, governments, utilities and private sector entities have implemented a variety of market transformation policies that aim to influence consumer purchase decisions. To evaluate the costs and benefits of such programs, analysts typically postulate a hypothetical default equipment choice, and compare it to one that provides comparable service with lower energy and/or power use. The corresponding reduced operating cost provides a benefit that offsets the potential higher cost of improved efficiency. Typically, life-cycle cost or cash-flow analyses are used to quantify the net economic benefit. These analyses require the capability to assess how a given equipment design would perform across a broad range of characteristics, both of the building and of the local weather. While these assessments can be performed using customized building simulations, it is generally not practical to develop and validate detailed building simulation code to cover all the potential variations of equipment design and installation. An alternative, and somewhat simpler, approach is to solely use detailed building simulations to generate time series of heating and cooling loads in commercial buildings. These loads can then be used as input to more detailed, stand-alone engineering models that simulate HVAC system performance under different equipment designs. This approach was used to evaluate a range of high-efficiency commercial packaged air conditioner design options for the Department of Energy’s Appliance and Equipment Standards Program (DOE-EERE 2015). While there may be some loss of precision relative to full simulation, the accuracy of this approach is sufficient for practical applications of cost-benefit analysis. This report describes the development of a database of commercial building heating and cooling loads, generated using the EnergyPlus software package, a whole building energy use model supported by the Department of Energy (DOE-EERE 2020a). EnergyPlus takes as input a set of configuration files that describe the building itself (size, zoning, envelope characteristics, etc.) and the various systems within it (HVAC, lighting, water heating, etc.). This analysis uses a publicly available collection of commercial reference buildings (CRB), comprised of sixteen building types and three vintages (DOE-EERE 2020b; Deru et al 2011). Each building is simulated in eighteen different locations, covering a wide range of climatic conditions. The prototype building description files assign the type of HVAC equipment used, and capacities across climate zones.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Bio-Based Phase Change Materials (PCMs) for Thermal Energy Storage (Final Scientific/Technical Report)

The goal of this project is to develop a novel bio-based phase change material (PCM) derived from squid ring teeth (SRT) proteins, and design a prototype heat exchanger based on these bio-based PCMs for energy storage and dynamic heat exchange for building thermal energy storage systems. The PCMs, derived from SRT proteins, will demonstrate room temperature energy storage capacities and switchable thermal conductivities that redefine the current state-of-the-art (SOA) for building thermal energy storage. Further, in a single material and with a single manufacturing processes, our proposed thermal battery will be developed with “on demand” thermal conductivity for rapid charging/discharging but superior insulation during energy storage periods. More specifically, our bio-based PCMs have demonstrated: 1) the potential for increased energy storage capacity (i.e., greater than paraffines at room temperature); 2) tunability in thermal conductivity with the largest thermal conductivity switching ratios for an intrinsic material reported to date, and 3) a 100% recyclable and biodegradable PCM with low volatility and toxicity and scalability in its manufacture for both residential and commercial applications. The already established ability for roll-to-roll processing of these non-toxic, non-flammable SRT composites along with their carbon-neutral manufacturing processes that has been pioneered by our team make this solution a disruptive and impactful technology to redefine the current SOA of energy storage technologies. The outcomes of this effort have been: 1) the identification of new bio-based PCM that establishes a new SOA for thermal conductivity and energy storage density at room temperature and 2) the development of a new experimental technique to measure the energy storage density via latent heat measurements during melting of thin films. This new technique can be applied to thin films (as thin as < 1 micrometer), and represents a novel approach for thin film energy storage density measurements. Dynamic thermal energy storage is the missing technology that will enable a grid- interactive efficient building (GEB). For a “smart” building capable of connecting with the power grid, the media must be inexpensive and possess thermal switching capabilities to control the time-dependent heat flow into (and out of) the PCM on demand. Unique to the material system in this program, programmable SRT-based PCM show improvements as compared to traditionally used PCMs, and thus its technical performance will represent a leap forward for the future GEB concept.

25 ENERGY STORAGE↗
DOE OSTI2021

Integration of Storage in the DC Link of a Full Converter-Based Distributed Wind Turbine

Energy storage is known to support the dispatchability of variable renewable resources. In this paper, we model a battery energy storage system (BESS) integrated with the DC link of a Type IV full converter-based wind turbine and the necessary controls to achieve efficient dispatch. To support the validation of control methodologies, we build a detailed model of a Type IV research wind turbine at the National Renewable Energy Laboratory (NREL), the Controls Advanced Research Turbine (CART 3), and we integrated a lithium-ion BESS model in grid-following mode into the model. The simulation results illustrate the sizing and control of the DC link-integrated BESS for a given variable wind resource and varying dispatch strategies (i.e., under constant, uncertain, and ramping wind scenarios). The integrated storage can smooth variabilities in distributed wind output, hedge against uncertainties, provide the ramping capability, as well as support stability under voltage and frequency transients. All of these have been illustrated in MATLAB/Simulink.

DC-link voltage↗