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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 OSTI2024

Grid Integration of Renewable Energy and Energy Storage

Grid integration of renewable energy and energy storage requires forward-looking planning process, and increased emphasizes on reliability, resilience, and equity. Power-electronics based energy generation including solar, wind, distributed energy resources (DERs), and various types of grid-tied energy storage and emerging loads, are reshaping grid operator's understanding on interconnection level performance and responses. This paper will present the ongoing work at PNNL related to power electronics R&D, energy modeling and analysis, and a wide spectrum of grid stability studies and technologies in support of grid integration of renewable energy and energy storage.

Power Electronics, grid integration of renewable e↗
DOE OSTI2022

Electrifying High-Efficiency Future Communities: Impact on Energy, Emissions, and Grid

To combat climate change and meet decarbonization goals, the building sector is improving energy efficiency and electrifying end uses to reduce carbon emissions from fossil fuels. All-electric buildings are becoming a trend among new constructions, introducing opportunities for decarbonization but also technical challenges and research gaps. For instance, further investigation is needed to understand how the adoption of energy efficiency measures (EEMs) and distributed energy resources (DERs) in all-electric communities would affect energy consumption, carbon emissions, and grid planning. This paper presents a case study of a mixed-use, all-electric community located in Denver, Colorado. We use URBANopt TM , a physics-based urban energy modeling platform to model the community and then evaluate the impact of EEMs and DERs (i.e., photovoltaics [PV], electric vehicles [EVs], and batteries) on the community's energy usage, carbon emissions, and peak demand. The results show that adding EEMs and PV led to both energy consumption and carbon emissions reductions across all building types. However, we saw fairly limited impact of EEMs and PV on buildings' peak demand in our case. Additionally, due to overnight EV charging activities and higher grid carbon intensity at night, the carbon emissions in multifamily buildings have a noticeable increase compared to scenarios without vehicles. Finally, the addition of batteries helped reduce peak demand by 11%-29%. The modeling workflow and evaluation methods can be applied to similar communities to evaluate their performance and the effect of integrating EEMs and DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Perspective on Integrative Simulations of Bioenergetic Domains

Bioenergetic processes in cells, such as photosynthesis or respiration, integrate many time and length scales, which makes the simulation of energy conversion with a mere single level of theory impossible. Just like the myriad of experimental techniques required to examine each level of organization, an array of overlapping computational techniques is necessary to model energy conversion. Here, in this work, a perspective is presented on recent efforts for modeling bioenergetic phenomena with a focus on molecular dynamics simulations and its variants as a primary method. An overview of the various classical, quantum mechanical, enhanced sampling, coarse-grained, Brownian dynamics, and Monte Carlo methods is presented. Example applications discussed include multiscale simulations of membrane-wide electron transport, rate kinetics of ATP turnover from electrochemical gradients, and finally, integrative modeling of the chromatophore, a photosynthetic pseudo-organelle.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Long-lived oscillations of metastable states in neutral atom systems

Metastable states arise in a range of quantum systems and can be observed in various dynamical scenarios, including decay, bubble nucleation, and long-lived oscillations. The phenomenology of metastable states has been examined in quantum many-body systems, notably in one-dimensional (1D) ferromagnetic Ising spin systems and superfluids. Here, in this paper, we study long-lived oscillations of metastable and ground states in 1D antiferromagnetic neutral atom chains with long-range Rydberg interactions. We use a staggered local detuning field to achieve confinement. Using theoretical and numerical models, we identify novel spectral signatures of quasiparticle oscillations distinct to antiferromagnetic neutral atom systems and interpret them using a classical energy model of short-range meson repulsion. Finally, we evaluate the experimental accessibility of our proposed setup on current neutral-Atom platforms and discuss experimental feasibility and constraints.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Convex Relaxation of Grid-Connected Energy Storage System Models With Complementarity Constraints in DC OPF

Including complementarity constraints in energy storage system (ESS) models in optimization problems ensure an optimal solution will not produce a physically unrealizable control strategy where there is simultaneous charging and discharging. However, the current approaches to impose complementarity constraints require the use of non-convex optimization methods. Here, we propose a convex relaxation for a common ESS model that has terms for both charging and discharging based on a penalty reformulation for use in a model predictive control (MPC) based optimal power flow (DC OPF) problem. In this approach, the complementarity constraints are omitted and a penalty term is added to the optimization objective function. For the DC OPF problem, we provide analysis for the conditions under which the convex relaxation of the complementarity constraint ensures that a solution with simultaneous ESS charging and discharging operation is suboptimal. Simulation results demonstrating ESS behavior with and without the penalty reformulation are provided for an MPC-based DC OPF problem on multiple IEEE test systems.

25 ENERGY STORAGE↗
DOE OSTI2020

Implications of climate change mitigation strategies on international bioenergy trade

Most climate change mitigation scenarios rely on increased use of bioenergy to decarbonize the energy system. Here we use results from the 33rd Energy Modeling Forum study (EMF-33) to investigate projected international bioenergy trade for different integrated assessment models across several climate change mitigation scenarios. Results show that in scenarios with no climate policy, international bioenergy trade is likely to increase over time, and becomes even more important when climate targets are set. More stringent climate targets, however, do not necessarily imply greater bioenergy trade compared to weaker targets, as final energy demand may be reduced. However, the scaling up of bioenergy trade happens sooner and at a faster rate with increasing climate target stringency. Across models, for a scenario likely to achieve a 2 °C target, 10–45 EJ/year out of a total global bioenergy consumption of 72–214 EJ/year are expected to be traded across nine world regions by 2050. While this projection is greater than the present trade volumes of coal or natural gas, it remains below the present trade of crude oil. This growth in bioenergy trade largely replaces the trade in fossil fuels (especially oil) which is projected to decrease significantly over the twenty-first century. As climate change mitigation scenarios often show diversified energy systems, in which numerous world regions can act as bioenergy suppliers, the projections do not necessarily lead to energy security concerns. Nonetheless, rapid growth in the trade of bioenergy is projected in strict climate mitigation scenarios, raising questions about infrastructure, logistics, financing options, and global standards for bioenergy production and trade.

09 BIOMASS FUELS↗
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 OSTI2024

Model Formulations: Integrating Distributed Energy Resources (DER) using Advanced Unit Commitment Models and DER Aggregation Methodologies

A distribution energy resource aggregator (DERA) constitutes a group of distribution energy resources with small generation capacities which meet the threshold to participate in the electricity wholesale market. This document provides the proposed DERA model formulation that will be implemented in the SCUC simulation’s architecture for the SCUC-DER project. Different economical assessment methodologies have been developed to incorporated bids for individual distributed resources, which include solar cost dispatch and cost model, BESS opportunity cost offer algorithm, and price sensitive demand response model. Detailed methods are proposed to aggregate individual cost offers to a DERA cost curve to bid in SCUC market while three methods are proposed to simulate DER actual dispatch. Based on the DERA models in this document, the SCUC-DER project will be able to assess the impacts of DERA on the distribution system’s operation and reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Evaluating the energy impact potential of energy efficiency measures for retrofit applications: A case study with U.S. medium office buildings

Quantifying the energy savings of various energy efficiency measures (EEMs) for an energy retrofit project often necessitates an energy audit and detailed whole building energy modeling to evaluate the EEMs; however, this is often cost-prohibitive for small and medium buildings. In order to provide a defined guideline for projects with assumed common baseline characteristics, this paper applies a sensitivity analysis method to evaluate the impact of individual EEMs and groups these into packages to produce deep energy savings for a sample prototype medium office building across 15 climate zones in the United States. We start with one baseline model for each climate zone and nine candidate EEMs with a range of efficiency levels for each EEM. Three energy performance indicators (EPIs) are defined, which are annual electricity use intensity, annual natural gas use intensity, and annual energy cost. Then, a Standard Regression Coefficient (SRC) sensitivity analysis method is applied to determine the sensitivity of each EEM with respect to the three EPIs, and the relative sensitivity of all EEMs are calculated to evaluate their energy impacts. For the selected range of efficiency levels, the results indicate that the EEMs with higher energy impacts (i.e., higher sensitivity) in most climate zones are high-performance windows, reduced interior lighting power, and reduced interior plug and process loads. However, the sensitivity of the EEMs also vary by climate zone and EPI; for example, improved opaque envelope insulation and efficiency of cooling and heating systems are found to have a high energy impact in cold and hot climates.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Theory and Implementation of the Spectacular Nonlinear Viscoelastic Constitutive Model

This report is a comprehensive guide to the nonlinear viscoelastic Spectacular model, which is an isotropic, thermo-rheologically simple constitutive model for glass-forming materials, such as amorphous polymers. Spectacular is intermediate in complexity to the previous PEC and SPEC models (Potential Energy Clock and Simplified Potential Energy Clock models, respectively). The model form consists of two parts: a Helmholtz free energy functional and a nonlinear material clock that controls the rate of viscoelastic relaxation. The Helmholtz free energy is derived from a series expansion about a reference state. Expressions for the stress and entropy functionals are derived from the Helmholtz free energy following the Rational Mechanics approach. The material clock depends on a simplified expression for the potential energy, which itself is a functional of the temperature and strain histories. This report describes the thermo-mechanical theory of Spectacular, the numerical methods for time-integrating the model, model verification for its implementation in LAMÉ, a user guide for its implementation in LAMÉ, and ideas for future work. A number of appendices provide supplementary mathematical details and a description of the procedure used to derive the simplified potential energy from the full expression for the potential energy. The goal of this report is create a convenient point-of-entry for engineers who wish to learn more about Spectacular, but also to serve as a reference manual for advanced users of the model.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A framework to evaluate machine learning crystal stability predictions

The rapid adoption of machine learning in various scientific domains calls for the development of best practices and community agreed-upon benchmarking tasks and metrics. We present Matbench Discovery as an example evaluation framework for machine learning energy models, here applied as pre-filters to first-principles computed data in a high-throughput search for stable inorganic crystals. We address the disconnect between (1) thermodynamic stability and formation energy and (2) retrospective and prospective benchmarking for materials discovery. Alongside this paper, we publish a Python package to aid with future model submissions and a growing online leaderboard with adaptive user-defined weighting of various performance metrics allowing researchers to prioritize the metrics they value most. To answer the question of which machine learning methodology performs best at materials discovery, our initial release includes random forests, graph neural networks, one-shot predictors, iterative Bayesian optimizers and universal interatomic potentials. We highlight a misalignment between commonly used regression metrics and more task-relevant classification metrics for materials discovery. Accurate regressors are susceptible to unexpectedly high false-positive rates if those accurate predictions lie close to the decision boundary at 0 eV per atom above the convex hull. The benchmark results demonstrate that universal interatomic potentials have advanced sufficiently to effectively and cheaply pre-screen thermodynamic stable hypothetical materials in future expansions of high-throughput materials databases.

Riebesell, Janosh↗
DOE OSTI2026

Mauka Energy FEVER Tool Dataset

Mauka Energy’s dataset, developed under the Forestry Electric Vehicle Energy Routing (FEVER) project and funded by the U.S. Department of Energy’s Small Business Innovation Research program, is a high-resolution geospatial resource designed to support energy modeling for electric log trucks in complex forestry environments. The dataset integrates detailed spatial and road network data to enable accurate simulation of vehicle performance across varied terrain. At its core, the dataset incorporates lidar-derived elevation models, road alignments, and surface classifications from Oregon State University’s McDonald-Dunn Research Forest. These data capture fine-scale variations in slope, curvature, and surface conditions across forest road systems, allowing for vehicle-level analysis of energy consumption and recovery. The dataset also includes data collected on the surrounding public and private road networks in Benton County, Oregon, used in real-world haul routes. These connecting segments provide critical context for modeling transitions between forest operations and regional transportation infrastructure, incorporating attributes such as grade profiles, elevation change, and speed constraints. This combined dataset underpins the development of Mauka Energy’s rolldown tool, which quantifies energy use and regenerative braking potential on downhill and variable-grade segments. By leveraging high-resolution terrain and road data, the FEVER project enables more accurate assessment of electric vehicle feasibility and performance in forestry applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
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 OSTI2020

The good, the bad, and the ugly: Data-driven load profile discord identification in a large building portfolio

Reducing the overall energy consumption and associated greenhouse gas emissions in the building sector is essential for meeting our future sustainability goals. Recently, smart energy metering facilities have been deployed to enable monitoring of energy consumption data with hourly or subhourly temporal resolution. This unprecedented data collection has created various opportunities for advanced data analytics involving load profiles (e.g., building energy benchmarking programs, building-to-grid integration, and calibration of urban-scale energy models). These applications often need preprocessing steps to detect daily load profile discords, such as: 1) outliers due to system malfunctions (the bad) and 2) irregular energy consumption patterns, such as those resulting from holidays (the ugly) compared to normal consumption patterns (the good). However, current preprocessing methods predominantly focus on filtering using statistical threshold values, which fail to capture the contextual discords of daily profiles. In addition, discord detection algorithms in building research are often aimed at finding individual building-level discords, which are not suitable at a large scale. Thus, here, we develop a method for automated load profile discord identification (ALDI) in a large portfolio of buildings (more than 100 buildings). Specifically, ALDI 1) uses the matrix profile (MP) method to quantify the similarities of daily subsequences in time series meter data, 2) compares daily MP values with typical-day MP distributions using the Kolmogorov-Smirnov test, and 3) identifies daily load profile discords in a large building portfolio. We evaluate ALDI using the metering data of both an academic campus and a residential neighborhood. Our results demonstrate that ALDI efficiently discovers measurement errors by system malfunctions and low energy consumption days in the academic campus portfolio, and it detects unique load shape patterns likely driven by occupant behavior and extreme weather conditions in the residential neighborhood.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Free energy and specific heat near a quantum critical point of a metal

We analyze the free energy and the specific heat for fermions interacting with a gapless boson at a quantum-critical point (QCP) in a metal. We use the Luttinger-Ward-Eliashberg formula for the free energy in the normal state, which includes contributions from bosons, fermions, and their interaction, all expressed via fully dressed fermionic and bosonic propagators. The sum of the last two contributions is the free energy F γ of an effective low-energy model of fermions with boson-mediated dynamical 4-fermion interaction V(Ω m ) ∝ 1/|Ω m | γ (the γ model). This purely electronic model has been used to analyze the interplay between non-Fermi liquid behavior and pairing near a QCP, which are both independent of the upper energy cutoff Λ. However, the specific heat C γ (T), obtained from F γ , does depend on Λ. We argue that this dependence is spurious and cancels out, once we include the contribution from bosons. We further argue that the full C(T) is the sum of the contribution from free fermions and the one from a critical boson, with the fully dressed propagator, other terms cancel out. We compare the full C(T) with the C γ (T), obtained using recently proposed regularization of F γ . We argue that for γ < 1, the full C(T) and the regularized C γ (T) differ by a γ-dependent prefactor, while for γ > 1, the full C(T) and C γ (T) differ by the positive contribution from free massless fermions (a positive constant for the electron-phonon case γ = 2). For these γ, C γ (T) is negative, but the full C(T) is positive. We argue that only the full C(T) matters as the positive and the negative contributions originate from the term in C(T) which contains the fully dressed bosonic propagator. Here, we then argue that the normal state remains stable until the pairing instability develops.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗