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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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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Physics-Based DNI Model for Advancing Solar Resource Assessment and Forecasting: Preprint

Direct Normal Irradiance (DNI) is one of the most used quantities to quantify the magnitude of solar energy resource. The concept of DNI is often interpreted differently for ground measurements and solar forecasting by numerical weather prediction (NWP) models, leading to substantial bias during evaluation of DNI forecasts especially under cloudy-sky conditions. To eliminate the bias, we use the Fast All-sky Radiation Model for Solar applications with DNI (FARMS-DNI) to provide a physics-based solution of solar radiation in the circumsolar region. The FARMS-DNI is implemented in the Weather Research and Forecasting model with solar extensions (WRF-Solar) to forecast day-ahead DNI in the north America. By comparing with conventional predictions from WRF-Solar and satellite observations from the National Solar Radiation Data Base (NSRDB), we found significant improvements in our prediction of DNI.

DNI↗
DOE OSTI2024

Advanced co-simulation framework for assessing the interplay between occupant behaviors and demand flexibility in commercial buildings

With buildings contributing significantly to electricity usage, enabling demand flexibility becomes a challenge, especially when accounting for occupant comfort. This study introduces an innovative co-simulation framework integrating multiple models: heating, ventilation, and air conditioning (HVAC) system, building zone load, indoor airflow, supervisory control, and occupant comfort and behavior. Uniquely, this framework allows for a comprehensive and dynamic analysis of building systems and occupant interactions in demand response events. Using this framework, we conducted a case study using a typical small office building model. Specifically, we focused on three areas: (1) the impact of indoor airflow modeling on energy use, occupant comfort, and behaviors forecasting, (2) the impact of occupant behaviors on demand flexibility, and (3) occupant comfort and behaviors under demand response events. Key performance indicators such as energy use, flexibility factor, durations of occupant discomfort and occupant behaviors were analyzed. Our findings indicated variations in energy usage and occupant comfort within demand flexibility events, marked by uncertainty boundaries, with variability in demand shedding up to 57.9%. Here, we concluded that this framework is suitable for analyzing typical commercial buildings and their HVAC systems in terms of demand flexibility potential under the impact of occupant behaviors.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Improving commercial truck fleet composition in emission modeling using 2021 US VIUS data

Commercial trucks are essential elements of the nation's supply chain system. Meanwhile, intensive truck movements contribute significantly to system externalities, such as energy use and air pollution. However, collecting detailed fleet composition and distribution of operational patterns remains a barrier to accurately accounting for these impacts. The recently released 2021 US Vehicle Inventory and Use Survey (US VIUS) fills a critical gap in understanding commercial truck fleet distributions, their operations, and business constraints at the national scale. This study aims to understand the latest US commercial vehicle fleet composition and operational characteristics using 2021 US VIUS data and calibrate the fleet inputs in regulatory emission models to assess the potential emission implications of the VIUS-derived fleet composition. The emission rates for commercial trucks and default fleet composition are collected from the U.S. EPA's MOtor Vehicle Emission Simulator (MOVES4). The 2021 US VIUS data is applied to improve fleet characteristics such as the long-haul fraction and the vehicle mileage accumulation rate. The study also investigates potential emission reduction benefits under various forecasted fleet electrification scenarios. The energy consumption and critical air pollutant rates by vehicle types are compared between MOVES4 and US VIUS fleets for both current and future scenarios to provide insights into the latest U.S. commercial vehicle fleet characteristics and their implications on energy and emissions. This study helps policymakers and practitioners advance the commercial fleet generation for emission models. It also deepens the understanding of the emission reduction potential of the commercial fleet under various fleet projections.

2021 US VIUS↗
DOE OSTI2023

Privacy-preserving federated learning: Application to behind-the-meter solar photovoltaic generation forecasting

Here, the growing usage of decentralized renewable energy sources has made accurate estimation of their aggregated generation crucial for maintaining grid flexibility and reliability. However, the majority of distributed photovoltaic (PV) systems are behind-the-meter (BTM) and invisible to utilities, leading to three challenges in obtaining an accurate forecast of their aggregated output. Firstly, traditional centralized prediction algorithms used in previous studies may not be appropriate due to privacy concerns. There is therefore a need for decentralized forecasting methods, such as federated learning (FL), to protect privacy. Secondly, there has been no comparison between localized, centralized, and decentralized forecasting methods for BTM PV production, and the trade-off between prediction accuracy and privacy has not been explored. Lastly, the computational time of data-driven prediction algorithms has not been examined. This article presents a FL power forecasting method for PVs, which uses federated learning as a decentralized collaborative modeling approach to train a single model on data from multiple BTM sites. The machine learning network used to design this FL-based BTM PV forecasting model is a multi-layered perceptron, which ensures privacy and security of the data. Comparing the suggested FL forecasting model to non-private centralized and entirely private localized models revealed that it has a high level of accuracy, with an RMSE that is 18.17% lower than localized models and 9.9% higher than centralized models.

14 SOLAR ENERGY↗
DOE OSTI2022

A Global Building Occupant Behavior Database

This paper introduces a database of 34 field-measured building occupant behavior datasets collected from 15 countries and 39 institutions across 10 climatic zones covering various building types in both commercial and residential sectors. This is a comprehensive global database about building occupant behavior. The database includes occupancy patterns (i.e., presence and people count) and occupant behaviors (i.e., interactions with devices, equipment, and technical systems in buildings). Brick schema models were developed to represent sensor and room metadata information. The database is publicly available, and a website was created for the public to access, query, and download specific datasets or the whole database interactively. The database can help to advance the knowledge and understanding of realistic occupancy patterns and human-building interactions with building systems (e.g., light switching, set-point changes on thermostats, fans on/off, etc.) and envelopes (e.g., window opening/closing). With these more realistic inputs of occupants’ schedules and their interactions with buildings and systems, building designers, energy modelers, and consultants can improve the accuracy of building energy simulation and building load forecasting.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

AquaPV: Regulatory and Environmental Considerations for Floating Photovoltaic Projects Located on Federally Controlled Reservoirs in the United States

To meet the nation's decarbonization goals, the U.S. Department of Energy's Solar Futures study forecasts that installed solar photovoltaic (PV) capacity must increase nearly tenfold, from 80 gigawatts (GW) in 2020 to approximately 760 GW cumulative installed capacity by 2035. Ground-mounted PV is expected to dominate future solar deployment and will require more than 3.5 million acres of land to meet annual demand projections (of nearly 45 GW) by 2030. However, various competing demands for land (e.g., agricultural production, conservation) and high land acquisition costs in specific locations could be challenges to meeting future PV demand solely with ground-mounted PV deployment. Floating photovoltaics (FPV) may be an alternative in locations where ground-mounted PV is not feasible and aid in reaching the nation's PV deployment and decarbonization goals. FPV is a newer siting approach in which a PV array is affixed to a floating apparatus and sited on a water body like a reservoir behind a dam. FPV systems may be stand-alone or co-located at new or existing hydroelectric facilities or pumped storage hydropower (PSH) facility reservoirs. Co-located FPV systems may or may not be operationally paired and work in tandem with the hydroelectric or PSH facility. This report provides novel analysis to understand the opportunities and challenges associated with developing stand-alone and co-located FPV projects on reservoirs in the United States. Specifically, the report explores potential environmental and energy benefits and environmental impacts associated with the siting, construction, and operation of FPV projects. The report also identifies and analyzes U.S. federal- and state-issued permits and authorizations required by federal laws to understand the licensing pathways and regulatory requirements for FPV projects sited on reservoirs licensed by the Federal Energy Regulatory Commission and on powered and non-powered reservoirs owned by the Bureau of Reclamation or U.S. Army Corps of Engineers.

13 HYDRO ENERGY↗
DOE OSTI2024

AquaPV: Regulatory and Environmental Considerations for Floating Photovoltaic Projects Located on Federally Controlled Reservoirs in the United States

To meet the nation's decarbonization goals, the U.S. Department of Energy's Solar Futures study forecasts that installed solar photovoltaic (PV) capacity must increase nearly tenfold, from 80 gigawatts (GW) in 2020 to approximately 760 GW cumulative installed capacity by 2035. Ground-mounted PV is expected to dominate future solar deployment and will require more than 3.5 million acres of land to meet annual demand projections (of nearly 45 GW) by 2030. However, various competing demands for land (e.g., agricultural production, conservation) and high land acquisition costs in specific locations could be challenges to meeting future PV demand solely with ground-mounted PV deployment. Floating photovoltaics (FPV) may be an alternative in locations where ground-mounted PV is not feasible and aid in reaching the nation's PV deployment and decarbonization goals. FPV is a newer siting approach in which a PV array is affixed to a floating apparatus and sited on a water body like a reservoir behind a dam. FPV systems may be stand-alone or co-located at new or existing hydroelectric facilities or pumped storage hydropower (PSH) facility reservoirs. Co-located FPV systems may or may not be operationally paired and work in tandem with the hydroelectric or PSH facility. This report provides novel analysis to understand the opportunities and challenges associated with developing stand-alone and co-located FPV projects on reservoirs in the United States. Specifically, the report explores potential environmental and energy benefits and environmental impacts associated with the siting, construction, and operation of FPV projects. The report also identifies and analyzes U.S. federal- and state-issued permits and authorizations required by federal laws to understand the licensing pathways and regulatory requirements for FPV projects sited on reservoirs licensed by the Federal Energy Regulatory Commission and on powered and non-powered reservoirs owned by the Bureau of Reclamation or U.S. Army Corps of Engineers.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗
DOE OSTI2024

AquaPV: Regulatory and Environmental Considerations for Floating Photovoltaic Projects Located on Federally Controlled Reservoirs in the United States

To meet the nation's decarbonization goals, the U.S. Department of Energy's Solar Futures study forecasts that installed solar photovoltaic (PV) capacity must increase nearly tenfold, from 80 gigawatts (GW) in 2020 to approximately 760 GW cumulative installed capacity by 2035. Ground-mounted PV is expected to dominate future solar deployment and will require more than 3.5 million acres of land to meet annual demand projections (of nearly 45 GW) by 2030. However, various competing demands for land (e.g., agricultural production, conservation) and high land acquisition costs in specific locations could be challenges to meeting future PV demand solely with ground-mounted PV deployment. Floating photovoltaics (FPV) may be an alternative in locations where ground-mounted PV is not feasible and aid in reaching the nation's PV deployment and decarbonization goals. FPV is a newer siting approach in which a PV array is affixed to a floating apparatus and sited on a water body like a reservoir behind a dam. FPV systems may be stand-alone or co-located at new or existing hydroelectric facilities or pumped storage hydropower (PSH) facility reservoirs. Co-located FPV systems may or may not be operationally paired and work in tandem with the hydroelectric or PSH facility. This report provides novel analysis to understand the opportunities and challenges associated with developing stand-alone and co-located FPV projects on reservoirs in the United States. Specifically, the report explores potential environmental and energy benefits and environmental impacts associated with the siting, construction, and operation of FPV projects. The report also identifies and analyzes U.S. federal- and state-issued permits and authorizations required by federal laws to understand the licensing pathways and regulatory requirements for FPV projects sited on reservoirs licensed by the Federal Energy Regulatory Commission and on powered and non-powered reservoirs owned by the Bureau of Reclamation or U.S. Army Corps of Engineers.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗
DOE OSTI2023

DESI and DECaLS (D&D): galaxy–galaxy lensing measurements with 1 per cent survey and its forecast

The shear measurement from the Dark Energy Camera Legacy Survey (DECaLS) provides an excellent opportunity for galaxy–galaxy lensing study with the Dark Energy Spectroscopic Instrument (DESI) galaxies, given the large (~9000 deg 2 ) sky overlap. We explore this potential by combining the DESI 1 per cent survey and DECaLS Data Release 8 (DR8). With ~106 deg 2 sky overlap, we achieve significant detection of galaxy–galaxy lensing for Bright Galaxy Survey (BGS) and luminous red galaxy (LRG) as lenses. Scaled to the full BGS sample, we expect the statistical errors to improve from 18(12)per cent to a promising level of 2(1.3)per cent at θ > 8arcmin(< 8 arcmin) ⁠. This brings stronger requirements for future systematics control. To fully realize such potential, we need to control the residual multiplicative shear bias |m| < 0.006 and the bias in the mean redshift |Δz| < 0.008, requiring the introduced bias in the measurement is <0.31σ. We also expect significant detection of galaxy–galaxy lensing with DESI LRG/emission line galaxy (ELG) full samples as lenses, and cosmic magnification of ELG through cross-correlation with low-redshift DECaLS shear. If such systematical error control can be achieved, we find the advantages of DECaLS, comparing with the Kilo Degree Survey (KiDS) and the Hyper Suprime-Cam (HSC), are at low redshift, large scale, and in measuring the shear ratio (to σ R ~ 0.04) and cosmic magnification.

(cosmology:) large-scale structure of Universe↗
DOE OSTI2024

Solar, Wind, and Load Forecasting Dataset for MISO, NYISO, and SPP Balancing Areas

The Performance-based Energy Resource Feedback, Optimization, and Risk Management (PERFORM) program is an initiative intended to foster "a fundamental shift in grid management rooted in an understanding of asset risk and system risk" (ARPA-E 2020). Launched by the Advanced Research Projects Agency-Energy (ARPA-E), the program supports efforts to incorporate uncertainty in electric power decision making. In support of PERFORM, the National Renewable Energy Laboratory (NREL) has produced a set of time-coincident forecasts of solar, wind, and load profiles. As part of Phase I of the PERFORM effort, NREL created a dataset that consists of one year of time-coincident load, wind, and solar actuals and probabilistic forecasts based on data from the Electric Reliability Council of Texas (ERCOT) (Bryce et al. 2023). In Phase II, NREL developed similar datasets for three other U.S. Independent System Operators (ISO): the Midcontinent Independent System Operator (MISO), the New York Independent System Operator (NYISO), and the Southwest Power Pool (SPP).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Cluster cosmology without cluster finding

ABSTRACT We propose that observations of supermassive galaxies contain cosmological statistical constraining power similar to conventional cluster cosmology, and we provide promising indications that the associated systematic errors are comparably easier to control. We consider a fiducial spectroscopic and stellar mass complete sample of galaxies drawn from the Dark Energy Spectroscopic Instrument (DESI) and forecast how constraints on Ωm–σ8 from this sample will compare with those from number counts of clusters based on richness λ. At fixed number density, we find that massive galaxies offer similar constraints to galaxy clusters. However, a mass-complete galaxy sample from DESI has the potential to probe lower halo masses than standard optical cluster samples (which are typically limited to λ ≳ 20 and Mhalo ≳ 1013.5 M⊙ h−1); additionally, it is straightforward to cleanly measure projected galaxy clustering wp for such a DESI sample, which we show can substantially improve the constraining power on Ωm. We also compare the constraining power of M*-limited samples to those from larger but mass-incomplete samples [e.g. the DESI Bright Galaxy Survey (BGS) sample]; relative to a lower number density M*-limited samples, we find that a BGS-like sample improves statistical constraints by 60 per cent for Ωm and 40 per cent for σ8, but this uses small-scale information that will be harder to model for BGS. Our initial assessment of the systematics associated with supermassive galaxy cosmology yields promising results. The proposed samples have a ∼10 per cent satellite fraction, but we show that cosmological constraints may be robust to the impact of satellites. These findings motivate future work to realize the potential of supermassive galaxies to probe lower halo masses than richness-based clusters and to potentially avoid persistent systematics associated with optical cluster finding.

(cosmology): large-scale structure of Universe↗
DOE OSTI2021

Fast All-sky Radiation Model for Solar applications (FARMS) [SWR-16-18]

The Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute cloudy irradiance. Radiative transfer (RT) models simulating broadband solar radiation have been widely used by atmospheric scientists to model solar resources for various energy applications such as operational forecasting. Due to the complexity of solving the RT equation, the computation under cloudy conditions can be extremely time consuming though many approximations (e.g. two-stream approach and delta-M truncation scheme) have been utilized. Thus, a more efficient RT model is crucial for model developers as a new option for approximating solar radiation at the land surface with minimal loss of accuracy. We have developed a fast all-sky radiation model for solar applications (FARMS) using the simplified clear-sky RT model, REST2, and simulated cloud transmittances and reflectances from the Rapid Radiation Transfer Model (RRTM) with a sixteen-stream Discrete Ordinates Radiative Transfer (DISORT). Simulated lookup tables (LUTs) of cloud transmittances and reflectances were created by varying cloud optical thicknesses, cloud particle sizes, and solar zenith angles. Equations with optimized parameters were fitted to the cloud transmittances and reflectances to develop the model. Using this model the all-sky solar irradiance at the land surface can be computed rapidly by combining REST2 with the cloud transmittances and reflectances. This new RT model is more than 1000 times faster than those currently utilized in solar resource assessment and forecasting since it does not explicitly solve the RT equation for each individual cloud condition. Our results indicate the accuracy of the fast radiative transfer model is comparable to or better than two-stream approximation in term of computing cloud transmittance and solar radiation.

Xie, Yu↗
DOE OSTI2021

Coal and Carbon Management Guidebook: Coal-to-Hydrogen Opportunities and Challenges

Key elements of this report include coal-to-hydrogen production in the context of the U.S. hydrogen market; the state of various hydrogen production technologies; present and forecasted demand for hydrogen in energy, transportation, and industrial sectors; an overview of environmental, economic, and infrastructure challenges to greater coal-to-hydrogen production; and information on the U.S. Department of Energy (DOE) programs and priorities for coal-to-hydrogen research and development.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Field Study of Grid-connected Heat Pump Water Heaters in the Southeast U.S.: The Next Right Thing

The integration of grid-connected functionality and advanced control algorithms into heat pump water heaters (HPWH) offers the capability to shift load with minimal customer impact. This capability provides a flexible grid resource to utilities, while the increased energy efficiency of HPWHs offers customers a lower electric bill. The combined utility/customer value from grid-connected HPWHs is compelling in the Southeast U.S. where residential electric water heating is prevalent and utility load management is common. This paper presents the results of a HPWH load shifting study conducted in Central Florida using the CTA-2045 standard. Building upon previous research in the Pacific Northwest, this study consisted of approximately 45 occupied homes equipped with HPWHs undergoing load shifting strategies weekly for over a year. Curtailment durations ranged from three to five hours in the morning, and four to five hours in the evening to coincide with high-value periods for utility coincident load for system-wide electric demand reductions. During the morning and afternoon, a one- or two-hour load-up event preceded curtailment. Baseline data were collected across varied Florida weather in which no load shifting events were implemented. Results from traditional load shifting strategies were analyzed across seasons and used to devise unique load shifting approaches to increase renewable energy use during periods of high solar energy generation. Regional impacts are forecasted for large-scale implementation of strategies. Lessons learned and recommendations are also provided for how utilities, manufacturers, and regional planners can maximize load shifting benefits from grid-connected HPWHs.

Heat pump water heaters, residential building, loa↗
DOE OSTI2023

Fast All-sky Radiation Model for Solar applications (FARMS) 2023 [SWR-16-18]

The Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute cloudy irradiance. Radiative transfer (RT) models simulating broadband solar radiation have been widely used by atmospheric scientists to model solar resources for various energy applications such as operational forecasting. Due to the complexity of solving the RT equation, the computation under cloudy conditions can be extremely time consuming though many approximations (e.g. two-stream approach and delta-M truncation scheme) have been utilized. Thus, a more efficient RT model is crucial for model developers as a new option for approximating solar radiation at the land surface with minimal loss of accuracy. We have developed a fast all-sky radiation model for solar applications (FARMS) using the simplified clear-sky RT model, REST2, and simulated cloud transmittances and reflectances from the Rapid Radiation Transfer Model (RRTM) with a sixteen-stream Discrete Ordinates Radiative Transfer (DISORT). Simulated lookup tables (LUTs) of cloud transmittances and reflectances were created by varying cloud optical thicknesses, cloud particle sizes, and solar zenith angles. Equations with optimized parameters were fitted to the cloud transmittances and reflectances to develop the model. Using this model the all-sky solar irradiance at the land surface can be computed rapidly by combining REST2 with the cloud transmittances and reflectances. This new RT model is more than 1000 times faster than those currently utilized in solar resource assessment and forecasting since it does not explicitly solve the RT equation for each individual cloud condition. Our results indicate the accuracy of the fast radiative transfer model is comparable to or better than two-stream approximation in term of computing cloud transmittance and solar radiation.

Xie, Yu↗
DOE OSTI2026

Dynamical Downscaling of Earth System Model Data for Energy System Analysis

Assessing energy resources (e.g., solar, wind, and hydro) under future scenarios requires datasets with sufficient spatial and temporal detail to capture variability and extreme events. While global-scale Earth System Model (ESM) projections are widely used, their coarse resolution limits direct application to regional energy system analyses. Dynamical downscaling offers a robust approach to generate physically consistent, fine-scale datasets that better represent local atmospheric processes impacting energy resources. In this work, we present a two-stage approach for producing high-resolution historical and future projections over the contiguous United States (CONUS). First, we optimize the Weather Research and Forecasting (WRF) model configuration for energy-relevant variables - solar irradiance, wind speed, and precipitation - by conducting ERA5-driven simulations at 8-km and 28-km resolution. Multiple physics schemes and model configurations within the WRF are evaluated against observational datasets including the National Solar Radiation Database (NSRDB), the Parameter-elevation Regressions on Independent Slopes Model (PRISM), and the Stage IV multi-radar/multi-sensor precipitation product for the CONUS domain. Using the best-performing configuration, we dynamically downscale MPI-ESM1-2-HR simulations for 2000-2060 under SSP2-4.5 and SSP5-8.5 scenarios at 4-km spatial and hourly temporal resolution. This presentation will provide a comprehensive analysis of the results from multiple numerical experiments and high-resolution ESM projections. In addition, we will discuss potential applications of our high-resolution datasets within the energy sector and outline future research avenues dedicated to evaluating how extreme weather events influence system performance and resilience.

24 POWER TRANSMISSION AND DISTRIBUTION↗