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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

tell: a Python package to model future total electricity loads in the United States

The purpose of the Total ELectricity Load (tell) model is to generate 21st century profiles of hourly electricity load (demand) across the Conterminous United States (CONUS). tell loads reflect the impact of climate and socioeconomic change at a spatial and temporal resolution adequate for input to an electricity grid operations model. tell uses machine learning to develop profiles that are driven by projections of climate/meteorology and population. tell also harmonizes its results with United States (U.S.) state-level, annual projections from a national- to global-scale energy-economy model. This model accounts for a wide range of other factors affecting electricity demand, including technology change in the building sector, energy prices, and demand elasticities, which stems from model coupling with the U.S. version of the Global Change Analysis Model (GCAM-USA). tell was developed as part of the Integrated Multisector Multiscale Modeling (IM3) project. IM3 explores the vulnerability and resilience of interacting energy, water, land, and urban systems in response to compound stressors, such as climate trends, extreme events, population, urbanization, energy system transitions, and technology change

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Building Energy Codes and Grid-Interactive Efficient Buildings: How building energy codes can enable a more dynamic and energy-efficient built environment

This report considers the role of national model codes to promote grid-interactive efficient buildings (GEBs) as part of the modernization of the U.S. electricity grid. It introduces GEBs, describes their ability to support a clean, resilient grid, and considers challenges and approaches for incorporating GEB measures into national model energy codes and standards. Desirable traits of GEB include being low energy, low peaking, and responsive to grid needs, and minimizing the curtailment of renewable energy resources. In addition, the future grid incurs a time and locational value on these types of building services. Accounting for these considerations in future code development requires a continuation and expansion of code-minimum energy efficiency requirements and inclusion of demand responsive and load flexibility measures while ensuring annual use and cost reductions. Also, efforts to include GEB measures in codes will be limited until they are fully developed into an American National Standards Institute (ANSI)-approved standard. Then it would be straightforward to address GEB measures through points or packages and/or scoring requirements. Otherwise, the building code would have to describe each specific grid responsive strategy. This document reviews topics pertinent to considering codes in this context. Specifically, the study presents the status and direction of current building energy codes, the future smart grid, low-energy buildings, and grid-integrated buildings. The report concludes with recommendations for future code development activities to support low-energy, grid-interactive buildings in order to provide added value to building owners, the grid, and society.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

A neural-network-enhanced parameter-varying framework for multi-objective model predictive control applied to buildings

Management of the electrical grid is becoming more complex due to the increased penetration of alternative energy generation technologies and a broadening diversity of electric loads. This complexity creates challenges in balancing demand and generation that can increase the potential for grid instabilities. One effective way to address this issue is to leverage previously unexploited demand flexibility through advanced control strategies. In this work, we propose an advanced control method, called adaptive neural parameter-varying model predictive control (ANPV-MPC), to control the temperature and energy consumption of a building via its Heating, Ventilation, and Air Conditioning system. ANPV-MPC combines key ideas in parameter-varying control, adaptive control, and online learning strategies to bridge the gap between computationally efficient linear model predictive control and more accurate nonlinear model predictive control. The novelty in ANPV-MPC is the use of a physics-inspired Bayesian neural network to estimate the coefficients of the parameter-varying linear control model. The Bayesian neural network additionally provides uncertainty estimates, triggering online training to capture evolving building system conditions. We show that ANPV-MPC can approximate the building system dynamics with a 28.39% higher accuracy than traditional linear model predictive control, resulting in 36.23% better control performance without increasing complexity of the optimal control problem. ANPV-MPC also adapts in real time to previously unseen conditions using online learning, further improving its performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

End-Use Savings Shapes Measure Documentation: Heat Pump Rooftop Units with Original Fuel Backup

This documentation focuses on a single end-use savings shape measure—heat pump rooftop units with supplemental heat that matches the original fuel type of the replaced system; if the existing system used electric resistance heating, the supplemental heating source is electric resistance. If it was a natural gas furnace, the supplemental system is modeled as natural gas. This is a modification to the heat pump rooftop unit with electric supplemental heat measure from the Commercial EUSS 2023 Release 1 dataset. This document will primarily discuss the supplemental heating change for the heat pump RTU measure. For a comprehensive overview of the fundamental modeling methodology and background of the heat pump RTU measure, including performance curves and other key assumptions, please review the documentation for the original heat pump rooftop unit with electric supplemental heat.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

A digital twin platform for building performance monitoring and optimization: Performance simulation and case studies

Advancements in sensor technology, data analytics, affordable compute, and communication infrastructure have paved the way for Digital Twin technology in optimizing building operations and controls. This study presents the development of an open and interoperable web-based Digital Twin platform for integrating diverse data streams and facilitating effective user interactions. The platform utilizes modern technologies for the web framework and time-series data management, ensuring scalability and responsiveness. The backend supports seamless integration of diverse data sources and emulators, incorporating data from building sensors and meters, external weather Application Programming Interfaces, and advanced EnergyPlus simulation models of the building and its energy systems including the Distributed Energy Resources that are formulated in Functional Mockup Units. A simulation case study was conducted with FlexLab, a test facility on Lawrence Berkeley National Laboratory campus. The case study includes normal operations, Distributed Energy Resource integration, and power outage scenarios, to illustrate the Digital Twin’s ability to provide critical insights into energy performance and thermal resilience. The results demonstrated the platform’s potential as a decision-support tool for optimizing building energy performance and enhancing resilience against extreme weather events. Future work will focus on deploying the Digital Twin platform to a real building for field validation, extending its capabilities to cover more scenarios such as bidirectional Electric Vehicle interactions, and enhancing user engagement.

EnergyPlus↗
DOE OSTI2020

Moving Zero Energy Office Buildings to the Mainstream: Establishing Design Guidelines and Energy Targets: Preprint

Office buildings represent a significant portion of the commercial sector and are ideal candidates to lead the market towards achieving zero energy or zero energy ready buildings. The variety of sizes and uses for office buildings make them challenging to determine set design guidance that can be deployed across the market. A project committee for ASHRAE’s Zero Energy - Advanced Energy Design Guide (ZE-AEDG) for small and medium office buildings , comprised of members from five major national associations with market-pull in commercial buildings, created design guidance for achieving zero energy office buildings for new construction and major retrofit. This design guidance focuses on the process, providing a pathway for both office owners and design teams to achieve zero energy status. Energy use intensity targets range from 16 kBtu/ft²·yr to 36 kBtu/ft²·yr for the different climate zones were established such that office buildings can be “zero-ready,” that is, having low energy consumption that can easily be offset with renewables, preferably on-site. The design guidance was rooted in extensive energy modeling, as well as case studies of actual office buildings that have achieved high levels of energy performance and met zero energy or zero energy ready status. A unique aspect of the zero-energy guide is that it is not compared against a baseline but focuses on achieving an absolute target. The paper presents process of creating the targets, the selection of strategies to achieve the targets, and sample case studies that show how the cost-sensitive solutions are achievable for the design community. It also presents outreach strategies to deploy market achievable zero energy measures.

buildings↗
NASA NTRS1986

HVAC modifications and computerized energy analysis for the Operations Support Building at the Mars Deep Space Station at Goldstone

The key heating, ventilation, and air-conditioning (HVAC) modifications implemented at the Mars Deep Space Station's Operation Support Building at Jet Propulsion Laboratories (JPL) in order to reduce energy consumption and decrease operating costs are described. An energy analysis comparison between the computer simulated model for the building and the actual meter data was presented. The measurement performance data showed that the cumulative energy savings was about 21% for the period 1979 to 1981. The deviation from simulated data to measurement performance data was only about 3%.

Halperin, A.↗
DOE OSTI2021

Whole-building life-cycle analysis with a new GREET® tool: Embodied greenhouse gas emissions and payback period of a LEED-Certified library

Embodied greenhouse gas (GHG) emissions of building components and buildings operations need to be quantified to holistically address building sustainability. To evaluate embodied GHG emissions of buildings and to provide insights on building materials and building design decisions toward decarbonization, we have recently created a building life-cycle assessment (LCA) module in the widely used Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET (R)) LCA model. We applied the GREET building LCA module to examine embodied GHG impacts and the payback period of a LEED (Leadership in Energy and Environmental Design) certified public library in Chicago, USA. We developed localized, detailed life-cycle inventories to address individual building materials used in the library. We expanded the LCA system boundary to include the mechanical, electrical, and plumbing system, as well as refrigerant impacts, which are often ignored in previous studies. Results show that the total embodied GHG emissions are approximately 817 metric tons, or approximately 538 kg/m 2 . Sensitivity analysis highlights the positive role of increasing the use of recycled materials for reducing embodied GHG emissions. Sensitivity analysis on embodied GHG emissions payback periods shows the need to benchmark the embodied and operational carbon performance of buildings for comparison to alternative building designs and sustainability practices. Furthermore, this analysis demonstrates that building LCA models, such as the GREET building LCA module, which addresses embodied and operational GHG emission impacts of whole buildings holistically, could empower building architects, technology developers, manufacturers, and general contractors to address embodied and operational impacts holistically for building sustainability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Integration of a grey-box refrigerated case model in EnergyPlus via Python plugin

Commercial buildings, in particular grocery stores (due mainly to their large refrigeration load), provide opportunities for energy cost reductions. Grocery stores could offer substantial load flexibility to the power grid through participation in demand response programs because of their usage patterns and relatively high energy intensity. This load flexibility could come from modifying the control of heating, ventilation, and air conditioning (HVAC) systems, refrigeration systems, or both. Although estimation of the HVAC system’s load flexibility potential is relatively targeted in the literature, estimating load flexibility of refrigeration systems is nascent and has been a challenge, in part because of the lack of proper simulation tools that capture the dynamics in the refrigeration cases. The existing refrigerated case model within EnergyPlus, a whole building energy simulation program, assumes a constant case temperature throughout the simulation period and does not explicitly model the cycling of the compressor serving the refrigerated case. In addition, it does not encompass modeling of temperatures of the product inside the refrigerated case. This difference between modeled and actual operation can be a barrier to the development of demand control algorithm and accurate analysis of load flexibility potential. In this paper, we present a grey-box model for modeling refrigerated cases in grocery stores, which include medium temperature and low temperature. Four cases are modeled; two are low-temperature closed cases and two are medium-temperature cases with one closed and one open. Data from an experimental facility are used to train and test the models. Results demonstrate the efficacy of the grey-box models in predicting the temperatures. This model is integrated into EnergyPlus to capture the dynamic effects of case temperature on the environment and enhance the calculation of sensible and latent heat exchange with the environment (case credits). These enhancements can be leveraged more broadly to model advanced refrigeration controls such as defrost, develop and test unique algorithms that could affect refrigeration interactions with HVAC, and refine store design for any commercial building with refrigeration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2005

National Aeronautics and Space Administration (NASA) Earth Science Research for Energy Management: Overview of Energy Issues and an Assessment of the Potential for Application of NASA Earth Science Research - Part 1

Effective management of energy resources is critical for the U.S. economy, the environment, and, more broadly, for sustainable development and alleviating poverty worldwide. The scope of energy management is broad, ranging from energy production and end use to emissions monitoring and mitigation and long-term planning. Given the extensive NASA Earth science research on energy and related weather and climate-related parameters, and rapidly advancing energy technologies and applications, there is great potential for increased application of NASA Earth science research to selected energy management issues and decision support tools. The NASA Energy Management Program Element is already involved in a number of projects applying NASA Earth science research to energy management issues, with a focus on solar and wind renewable energy and developing interests in energy modeling, short-term load forecasting, energy efficient building design, and biomass production.

Atmospheric models↗
DOE OSTI2022

Potential Heating Energy and Cost Savings of Dual Fuel Heat Pump Controls as a Residential Building Equipment Retrofit in the U.S.

This study investigated the energy and cost savings potential by modeling a dual fuel heat pump system with its control for a residential building in (5A) cold climate in U.S. The simulation analysis showed that the application of the DFHP system and its control to the target building can save the heating energy by 42% over a gas furnace system (baseline system). Although the HP-only system can save more heating energy (i.e., 53%) over the baseline system than DFHP system does, the DFHP with its control demonstrated the higher cost savings when a time of use electricity rate was considered.

Yoon, Yeobeom↗
DOE OSTI2021

Reactor rate modulation oscillation analysis with two detectors in Double Chooz

A θ 13 oscillation analysis based on the observed antineutrino rates at the Double Chooz far and near detectors for different reactor power conditions is presented. This approach provides a so far unique simultaneous determination of θ 13 and the total background rates without relying on any assumptions on the specific background contributions. The analysis comprises 865 days of data collected in both detectors with at least one reactor in operation. The oscillation results are enhanced by the use of 24.06 days (12.74 days) of reactor-off data in the far (near) detector. The analysis considers the ${\overline{\nu}}_e$ interactions up to a visible energy of 8.5 MeV, using the events at higher energies to build a cosmogenic background model considering fast-neutrons interactions and 9 Li decays. The background-model-independent determination of the mixing angle yields sin 2 (2 θ 13 ) = 0.094 ± 0.017, being the best-fit total background rates fully consistent with the cosmogenic background model. A second oscillation analysis is also performed constraining the total background rates to the cosmogenic background estimates. While the central value is not significantly modified due to the consistency between the reactor-off data and the background estimates, the addition of the background model reduces the uncertainty on θ 13 to 0.015. Along with the oscillation results, the normalization of the anti-neutrino rate is measured with a precision of 0.86%, reducing the 1.43% uncertainty associated to the expectation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

State-Level Employment Projections for Four Clean Energy Technologies in 2025 and 2030

As states and local governments weigh how to spur economic growth, stimulate job creation, and simultaneously adapt to meet climate goals, modern energy codes, and energy demand, this report provides a simple and transparent method to estimate the size of the workforce needed to support modeled deployments for energy efficiency in buildings, stationary battery energy storage (BES), solar photovoltaics (PV), and land-based wind in 2025 and 2030. In addition to a straightforward estimation method, this report includes state-level job estimates for two different deployment scenarios: a business-as-usual scenario and a more accelerated deployment scenario. The scope of the technologies included in this report is limited to four key energy technologies within the power sector that have strong job growth prospects and widespread geographic deployment potential. Although the included technologies are not all-encompassing, they have generated specific interest from state energy offices across the nation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Raising the Bar in High Performance Laboratory Design

Laboratory facilities are expensive to build and operate, they consume energy at high rates compared to other types of buildings, and modifications are frequently required to accommodate ever-changing research activities. PNNL sought ways to address these issues in the design and construction of a 14,700 sq. ft. new laboratory building. To improve adaptability to change a high roof structure was used that allows raising the ceiling when needed with minimal disruption to installed HVAC and electrical utilities. Also, HVAC equipment was located on a mezzanine above the central corridor rather than above ceilings. This eliminates the need for maintenance personnel to routinely access lab spaces, reducing disruption to research staff and improving maintenance access. To improve the reliability of operations while reducing energy consumption, heat pipe heat recovery with evaporative cooling, zoned heating/cooling coils, high-efficiency condensing boilers, district cooling, VAV fume hoods, DDC controls, energy use monitoring, and implementation of the US Department of Energy’s Guiding Principles for Federal Leadership in Sustainable Buildings were all used. The energy model developed during design projected energy use at 2,840 MBtu/yr, a 13.5% savings over ASHRAE Standard 90.1-2010. The first full year of operation resulted in actual energy use of 2,661 MBtu, a savings of 19% over Standard 90.1. As a result of the project design’s demonstrated success, these strategies will be incorporated into a significantly larger (125,000 sq ft), $65 million lab facility to be constructed on the PNNL campus in 2020.

Scott, Jeffery M.↗
DOE OSTI2026

Enhancing Building Resilience: Maintaining Energy Efficiency and Thermal Comfort During Power Outages in Cold Climates

The increasing frequency and intensity of extreme weather events, such as heatwaves and cold snaps, present significant challenges to building energy performance and occupant comfort. Highly correlated with climate events are widespread long duration power interruptions that may affect thousands of buildings and millions of customers. This study evaluates the impact of building energy performance and occupant thermal comfort in medium-sized office buildings in a cold climate region. Using energy models representing pre-1980 and 2019 vintages, simulations were conducted to assess energy performance under typical weather conditions and occupant thermal comfort during power interrupted extreme cold snap and heatwave climate events under both current 2020s and future 2050s weather conditions. The results show a projected 33% increase in cooling energy demand and a 19% reduction in heating energy by 2050. Findings reveal that older buildings are more susceptible to cold discomfort during cold snaps, while modern airtight buildings are more vulnerable to overheating during heatwaves. Various passive energy efficiency measures, such as improved infiltration control, thermal windows, solar-controlled windows, and cool envelopes, were evaluated for their ability to mitigate thermal discomforts. Solar controlled windows and weatherstripping contribute to reducing cold thermal discomfort by 21% during a power-interrupted cold snap. Solar-controlled windows were found to reduce hot thermal discomfort by 34% during a future power-interrupted heatwave. The study highlights the importance of targeted retrofitting strategies to enhance thermal resilience, especially during power outages, to ensure occupant safety and comfort during extreme climate events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Development of an Advanced Multiphysics Simulation Capability for Radiant's Microreactor Design

Argonne National Laboratory and Idaho National Laboratory, through a Department of Energy Gateway for Accelerated Innovation in Nuclear Voucher, supported key analysis needs of Radiant related to (i) air jacket thermal fluid performance, (ii) evaluation of decay heat source terms defining air jacket technical requirements, and (iii) assessment of modeling methodologies employed for core analysis. All of these activities center on numerical simulation of various aspects of Kaleidos using the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, the Cardinal multiphysics application, the OpenMC Monte Carlo code, and the Nek5000 computational fluid dynamics (CFD) code. This project builds upon an earlier Nuclear Energy Advanced Modeling and Simulation (NEAMS) Thermal-Hydraulic (T/H) Center of Excellence (CoE) project focused on initial demonstration of Cardinal multiphysics simulation of High Temperature Gas Reactors (HTGRs) and now focuses on Radiant’s Kaleidos concept.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗