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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Transportation Electrification Impact Study (TEIS)

Recent U.S. Environmental Protection Agency (EPA) notices of proposed rulemakings for GHG emissions standards for light-, medium-, and heavy-duty on-road vehicles would accelerate ongoing advancements already happening in the industry because of private investment, consumer demand, state-level policies, and federal incentives. As the EPA finalizes these regulations, questions persist regarding the cost of the requisite charging infrastructure and associated upgrades to the nation's electric grid. With support from the U.S. Department of Energy, U.S. Joint Office of Energy and Transportation, and the EPA, a multidisciplinary team conducted a Multi-State Transportation Electrification Impact Study that quantitatively assesses the incremental investment necessary to enable the levels of vehicle electrification expected to be induced by pending EPA regulations and to estimate the potential value of deferred investments in electric distribution infrastructure stemming from proactive vehicle-grid integration planning and deployment. This study finds the simulated incremental capital cost of charging infrastructure (including grid upgrades) to be at least 2.5 times smaller than the lifetime net benefits of vehicle electrification (including fuel savings but excluding the value of avoided emissions). Additionally, the incremental distribution grid upgrade cost of the EPA Action-Unmanaged scenario was found to be approximately 3% of existing utility distribution system investments (on an annual basis). Finally, the potential for managed charging to defer distribution grid upgrades was found to be significant with costs found to decrease from $2.3 billion to an incremental cost of $1 billion across five states in the Action-Managed scenario (relative to the No Action-Unmanaged scenario).

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗
NASA NTRS2010

Trajectory Optimization: OTIS 4

The latest release of the Optimal Trajectories by Implicit Simulation (OTIS4) allows users to simulate and optimize aerospace vehicle trajectories. With OTIS4, one can seamlessly generate optimal trajectories and parametric vehicle designs simultaneously. New features also allow OTIS4 to solve non-aerospace continuous time optimal control problems. The inputs and outputs of OTIS4 have been updated extensively from previous versions. Inputs now make use of objectoriented constructs, including one called a metastring. Metastrings use a greatly improved calculator and common nomenclature to reduce the user s workload. They allow for more flexibility in specifying vehicle physical models, boundary conditions, and path constraints. The OTIS4 calculator supports common mathematical functions, Boolean operations, and conditional statements. This allows users to define their own variables for use as outputs, constraints, or objective functions. The user-defined outputs can directly interface with other programs, such as spreadsheets, plotting packages, and visualization programs. Internally, OTIS4 has more explicit and implicit integration procedures, including high-order collocation methods, the pseudo-spectral method, and several variations of multiple shooting. Users may switch easily between the various methods. Several unique numerical techniques such as automated variable scaling and implicit integration grid refinement, support the integration methods. OTIS4 is also significantly more user friendly than previous versions. The installation process is nearly identical on various platforms, including Microsoft Windows, Apple OS X, and Linux operating systems. Cross-platform scripts also help make the execution of OTIS and post-processing of data easier. OTIS4 is supplied free by NASA and is subject to ITAR (International Traffic in Arms Regulations) restrictions. Users must have a Fortran compiler, and a Python interpreter is highly recommended.

Riehl, John P.↗
DOE OSTI2026

Application of Ibuprofen Sodium Dihydrate for Thermochemical Energy Storage

Thermochemical energy storage (TCES) offers a transformative approach to address grid instability by harnessing reversible chemical reactions for efficient heat storage and release. Here, we introduce pharmaceutical organic salt hydrates as a class of materials with exceptional performance for low-grade waste heat recovery. We demonstrate ibuprofen sodium dihydrate (ISD) as an example organic hydrate exhibiting a dehydration temperature range of 60-110 °C and a remarkable dehydration enthalpy of up to 59.5 kJ/mol of water, ideally suited for capturing industrial and residential waste heat. Using rigorous multimodal characterization, including thermogravimetric analysis, differential scanning calorimetry, in-situ FTIR, in-situ PXRD, and NMR, we demonstrate ISD's superior thermal, chemical, and structural stability over 150 hydration-dehydration cycles, achieving an unprecedented cycling efficiency of ~99.9%. Compared to conventional inorganic salt hydrates like strontium chloride hexahydrate and calcium oxalate monohydrate, ISD showcases enhanced durability without deliquescence or pulverization, even under high-humidity conditions. In-situ analyses confirm the transition from ISD to ibuprofen sodium anhydrous (ISA) proceeds with structural reorganization, thereby combining the dehydration mechanism with phase transitions, resulting in higher energy storage capacity. Microstructural analyses reveal that repeated water intercalation and structural transitions aid in creating significant porosity that enhances water transport kinetics, further improving the hydration/dehydration performance. By combining the phase change and chemical dehydration mechanisms, ISD paves the way for designing a new class of organic salt hydrates, offering tunable properties to meet diverse thermal energy storage demands and supporting sustainable grid resilience.

Thangaraj, Kavin C.↗
DOE OSTI2026

Calibration of urban building energy model using smart meter data for district peak load prediction

Urban building energy modeling (UBEM) is a powerful approach to assessing baseline building energy performance and retrofits with new technologies across building stocks in cities. However, the accuracy of UBEM is often constrained by the limited availability of reliable data about building characteristics and operations, such as envelope efficiency levels, HVAC system performance, and end-use load patterns. Existing research has performed UBEM calibration using annual or monthly energy consumption data, which falls short when higher-resolution time series applications are needed, such as peak load prediction for utility operation planning. This study presents a new framework for calibrating building energy models at urban scale using smart meter data, targeting the accurate prediction of summer peak electricity loads to support robust grid planning. The framework first integrates various data sources to enhance baseline input assumptions for building models, and then calibrates the baseline models through a pattern-matching approach. A case study using CityBES and two years of AMI data from over 9000 residential customers in Portland, Oregon, demonstrated the workflow and its effectiveness. The calibrated models achieved a daily peak load mean absolute percentage error of 2.6 % during the heatwave in the calibration year, and 2.0 % in the validation year using another year of AMI data. Using the calibrated models, we analyzed the demand flexibility potential of the district building stock as an application of UBEM calibration. The findings affirm the appropriate use of UBEM for peak electric load forecasting and demand side management at the utility distribution system level.

AMI data↗
DOE OSTI2026

Experimental study of a thermal energy storage-integrated heat pump system for load shifting in space cooling and heating

This study experimentally investigates an all-season thermal energy storage-integrated heat pump (TES-HP) system developed to enhance building energy efficiency and support grid-interactive operation through load shifting in both cooling and heating. A 4-ton commercial rooftop air-source heat pump was modified by integrating a hydronic thermal energy storage (TES) unit containing a phase change material (PCM) with a melting temperature of 22.0 °C. The system employs two reversing valves and three electronic expansion valves to enable six operating modes, including normal, TES charging, and TES discharging in both cooling and heating seasons. A subcooling-controlled electronic expansion valve was implemented to mitigate refrigerant maldistribution caused by unequal internal volumes among the heat exchangers. Compared with a baseline heat pump, the TES-HP reduced power consumption by 30–50% during cooling at an ambient temperature of 40.6 °C, and by up to 60% during heating at −15.0 °C, while maintaining high performance under cold-climate conditions. Additionaly to experimental evaluation, a simplified annualized on-peak analysis was conducted to compare the TES-HP with the baseline system, indicating an on-peak electricity reduction of approximately 876 kWhₑ per unit per year and associated on-peak cost savings under time-of-use pricing. These results demonstrate that the TES-HP effectively decouples HP operation from adverse ambient conditions, improving flexibility, resilience, and energy efficiency. This work advances prior research by experimentally proving the integration of PCM-based TES for a year-round, load-flexible HVAC operation.

42 ENGINEERING↗
DOE OSTI2025

Commercial building HVAC demand flexibility with model predictive control: Field demonstration and literature insights

Model Predictive Control (MPC) for building Heating Ventilation and Air Conditioning (HVAC) systems is beginning to gain traction in the market, with a few controls companies incorporating it into their product offerings. However, it remains difficult to assess whether the energy cost savings are enough to justify the cost of MPC implementation for a particular building, given the limited number of reported demonstrations. For small commercial and residential buildings with relatively uniform systems, standardized approaches can help lower implementation costs. In contrast, for large buildings or district systems, the potential magnitude of cost savings could justify more customized solutions. Estimating the cost-effectiveness of MPC becomes more challenging for medium and large commercial buildings, where a one-size-fits-all solution may not be suitable, and the potential energy cost savings may be insufficient to justify a customized solution. To make MPC technology more appealing, incorporating additional value streams beyond energy efficiency alone can significantly increase its attractiveness. One such revenue stream is demand flexibility, in response to dynamic electricity prices, where MPC can leverage the thermal mass of the building to shift the load and support the grid. Building on an extensive literature review of MPC field studies focused on cost savings and demand flexibility, this paper presents the results of implementing MPC control in a large office building HVAC system in Berkeley, CA. Four different dynamic electricity price profiles were integrated into the MPC objective function to shift building demand while maintaining comfort, and field testing was performed with each price profile across four seasons. The results show potential for 40–65 % demand decrease percentage and up to 61 % annual cost savings compared to the existing rule-based control strategy, under the tested dynamic price scenarios. This paper also presents a sensitivity analysis on the cost savings with respect to the price profile variability, discusses the implementation effort for the price-responsive MPC, and compares the cost savings found in this study to those found in literature on the basis of dynamic price variability, or so-called Electricity Price Relative Standard Deviation.

Zanetti, Ettore↗
DOE OSTI2025

A New Design Consideration for Bidirectional Resonant Converters

This paper introduces innovative design considerations for a bidirectional resonant converter, optimized for Electric Vehicle (EV) charging and vehicle-togrid (V2G) applications. By eliminating the need for complex voltage or current gain functions, the proposed design greatly simplifies the development process, making it more accessible for manufacturers and system integrators. This approach not only reduces engineering time and resource investment but also accelerates time-to-market, giving stakeholders a competitive edge in rapidly expanding EV infrastructure markets. In addition, the streamlined design ensures soft switching at maximum output power, leading to higher efficiency and improved durability, which translates to lower operating costs and a longer service life for EV charging equipment. These benefits provide a clear pathway to more cost-effective, scalable, and sustainable EV charging and V2G solutions, enhancing value for stakeholders by facilitating smoother integration into the grid and supporting energy resilience. To validate the benefits, a 60 kW bidirectional charger with a flexible input range of 700−900VDC and an output range of 400−1250VDC was developed, underscoring the design's adaptability and potential for large-scale implementation.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗
DOE OSTI2025

Online Dynamic Mode Decomposition Based System Identification of Multi-Zone Building HVAC Systems

Many works have recently been conducted to reduce the electricity consumption of smart buildings and allow them to support various grid services. Most of these works require accurate system models for the various appliances in the building including heating, ventilation, and air conditioning (HVAC) units. In this paper, we investigate a recursive data-driven system identification strategy to construct the thermal model for a time-varying building with a multi-zone HVAC unit. The online dynamic mode decomposition (DMD)-based strategy is employed to identify the multi-zone thermal building dynamics, where a simple information update (rank-1) is selected to avoid computational complexity. The DMD-based identification strategy is validated using a real gymnasium building equipped with a 4-zone HVAC unit, and its performance is compared with that of the traditional nuclear-norm subspace identification (N2SID) strategy.

Wu, Tumin [University of Tennessee, Knoxville (UTK↗
DOE OSTI2024

Peer-to-peer communication control for resilient operations of networked cyberphysical systems

This report includes two main accomplishments of the peer-to-peer communication control for resilient operation of networked microgrids project in FY24, which include a scheme for cyberattack-aware coordination of networked microgrids for supporting voltages of bulk power systems and a scheme for price signal-based operations of EV-rich networked microgrids with mixed ownership. First, the cyberattack-aware scheme enables networked microgrids to distributedly determine the amount of reactive power injection to support the voltage of bulk power system (BPS) in a fair manner. In this scheme, a risk-informed algorithm is presented to generate the peer-to- peer (P2P) communication graph with minimal risk of attack on communication links. To deal with cyberattacks on MG controllers, the resilient consensus algorithm (CA) is utilized for MG controllers to robustly estimate the total reactive power headroom, from which the MGs can accurately provide the needed amount of reactive power injection for supporting the voltage of BPS. The CA implementation and performance within the P2P communication framework are demonstrated on the IEEE 39-bus system with 6 microgrids contained in the distribution feeder under different cyberattack scenarios. Second, the price-based scheme enables the usage of the real-time price signal for the operations of electric vehicle (EV)-rich networked-microgrids with mixed ownership, in which not all the microgrids can communicate with the distribution system operator (DSO). In this scheme, a max consensus is introduced to enable the real-time price signal to be propagated from the DSO to all the microgrids, from which each microgrid controller will manage the DERs to balance the load demand and the power injection from the EV charging stations within its microgrid. Numerical results over one day with 288 slots of 5-minute intervals on the modified 123-node test feeder including 3 microgrids with high penetration of EV are presented to evaluate how the price signal affects the operations of networked microgrids under different charging strategies of the EV charging stations. The result indicates that our proposed EVCS (dis)charging strategy, which leverages the flexibility of EVs to support the grid through discharging during peak demand, proves to be a cost-effective solution that reduces operational costs while improving the social welfare of EV charging.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Pumped Thermal Energy Storage Using Low-Cost Particles and a Fluid Bed Heat Exchanger for Maximum Power Efficiency

Robust, efficient, cost-effective long-duration electricity storage (LDES) solutions can enhance grid resiliency, support existing transmission and distribution infrastructure, and enable a greater share of low-cost, variable alternative energy sources to penetrate the market. To meet this need, the project team at the National Renewable Energy Laboratory developed a transformative LDES system based on pumped thermal energy storage (TES) using low-cost particles and a fluid bed heat exchanger for maximum power efficiency (PUMP). The PUMP system is composed of high-temperature, low-cost particle TES coupled with an advanced pressurized fluid bed heat exchanger (PFB HX) that supports a high-efficiency pumped thermal energy storage (PTES) system integrated with concentrating solar thermal power (CSP). The PUMP project developed and de-risked a PFB HX and particle CSP system intended to be integrated with reversible turbomachinery and a modeling tool to assess PTES cost and performance.

14 SOLAR ENERGY↗
DOE OSTI2025

Unlocking America's Abundant Marine Energy Resources

NREL Marine Energy One-Pager: A resource designed for use during NREL campus visits - especially with high-profile guests - as well as at events in Washington, D.C., when engaging with the new administration, and for displays at WPTO or lab booths. The U.S. holds vast untapped marine energy resources - wave, tidal, river, and ocean currents - that can strengthen grid resilience, support coastal communities, and advance energy independence. NREL leads innovation in this space through advanced modeling tools, patented technologies, and world-class testing facilities. NREL's simulation platforms, like OpenFAST and SAM, help reduce development time and risk. Patented devices such as PKelp and FlexWEC demonstrate flexible, resilient approaches to energy capture. At Flatirons Campus, NREL offers motion simulation, structural testing, wave tanks, and megawatt-scale microgrid emulation via the ARIES platform. These capabilities help developers refine and validate devices before in-water trials. With upcoming open-water testing at PacWave and strong partnerships, NREL is accelerating the path to commercialization - positioning the U.S. as a global leader in marine energy innovation.

17 WIND ENERGY↗
DOE OSTI2026

HydraGNN_OPF_GFM_2026 - Ensemble of predictive graph foundation models for power grid applications

This dataset supports research on graph foundation models for optimal power flow (OPF) on electric grids using HydraGNN. It contains heterogeneous graph representations of PGLib-OPF cases spanning systems from 14 to 13,659 buses, together with packed HDF5 datasets for pretraining, feasibility classification, and N-1 contingency analysis. The release includes OPF solution data, downstream fine-tuning datasets, pretrained HeteroSAGE and HeteroHEAT model checkpoints, hyperparameter-optimization summaries across multiple heterogeneous GNN architectures, and aggregated fine-tuning results for sample-efficiency studies. The dataset is designed to enable scalable training, evaluation, and transfer-learning studies for OPF surrogate modeling, including node-level AC-OPF solution prediction, graph-level prediction, feasibility classification, operating-condition generalization, and contingency-response tasks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2003

Enhanced Product Generation at NASA Data Centers Through Grid Technology

This paper describes how grid technology can support the ability of NASA data centers to provide customized data products. A combination of grid technology and commodity processors are proposed to provide the bandwidth necessary to perform customized processing of data, with customized data subsetting providing the initial example. This customized subsetting engine can be used to support a new type of subsetting, called phenomena-based subsetting, where data is subsetted based on its association with some phenomena, such as mesoscale convective systems or hurricanes. This concept is expanded to allow the phenomena to be detected in one type of data, with the subsetting requirements transmitted to the subsetting engine to subset a different type of data. The subsetting requirements are generated by a data mining system and transmitted to the subsetter in the form of an XML feature index that describes the spatial and temporal extent of the phenomena. For this work, a grid-based mining system called the Grid Miner is used to identify the phenomena and generate the feature index. This paper discusses the value of grid technology in facilitating the development of a high performance customized product processing and the coupling of a grid mining system to support phenomena-based subsetting.

Barkstrom, Bruce R.↗
DOE OSTI2024

High-Level Assessment of Grid Infrastructure in Southeast Asia to Support Regional Interconnections

The purpose of this slide deck is to provide an overview of the benefits of interregional transmission and to assess the specific transmission landscape of Southeast Asia, with respect to potential interconnections between Singapore and neighboring countries. This analysis also explores the distribution of renewable resources and electricity demand in ASEAN (the Association of Southeast Asian Nations) as well as current and anticipated interregional transmission, in order to inform future interconnection plans.

ASEAN↗
NASA NTRS1999

3D Structured Grid Generation Codes for Turbomachinery

This report describes the research tasks during the past year. The research was mainly in the area of computational grid generation in support of CFD analyses of turbomachinery components. In addition to the grid generation work, a numerical simulation was obtained for the flow through a centrifugal gas compressor using an unstructured Navier-Stokes solver. Other tasks involved many different turbomachinery component analyses. These analyses were performed for NASA projects or for industrial applications. The work includes both centrifugal and axial machines, single and multiple blade rows, and steady and unsteady analyses. Over the past five years, a set of structured grid generation codes were developed that allow grids to be obtained fairly quickly for the large majority of configurations we encounter. These codes do not comprise a generalized grid generation package; they are noninteractive codes specifically designed for turbomachinery blade row geometries. But because of this limited scope, the codes are small, fast, and portable, and they can be run in the batch mode on small workstations. During the past year, these programs were used to generate computational grids were modified for a wide variety of configurations. In particular, the codes or wrote supplementary codes to improve our grid generation capabilities for multiple blade row configurations. This involves generating separate grids for each blade row, and then making them match and overlap by a few grid points at their common interface so that fluid properties are communicated across the interface. Unsteady rotor/stator analyses were performed for an axial turbine, a centrifugal compressor, and a centrifugal pump. Steady-state single-blade-row analyses were made for a study of blade sweep in transonic compressors. There was also cooperation on the application of an unstructured Navier-Stokes solver for turbomachinery flow simulations. In particular, the unstructured solver was used to analyze the flow through a centriftio compressor impeller.

Loellbach, James↗
DOE OSTI2025

Grid Resiliency with a 100% Renewable Microgrid

San Diego Gas & Electric Company (SDG&E) installed America’s first and largest utility-scale microgrid in Borrego Springs in 2013. The first generation Borrego Springs Microgrid utilized diesel generators to form and stabilize the microgrid island, with support from grid-scale batteries and local solar photovoltaic (PV) generation. In this project, SDG&E in partnership with National Renewable Energy Laboratory (NREL) demonstrated through modeling, simulation and utility field testing that blackstart and islanding of the microgrid can be led with 100% renewable, inverter based resources (IBRs), to help reduce community reliance on conventional generation resources. Through equipment upgrades, grid-forming island leader capability was transitioned to a battery IBR instead of the Borrego Springs Microgrid diesel generators. A new microgrid controller was integrated to the microgrid and programmed to control and manage multiple energy storage systems. Synchrophasor and other power quality data verified autonomous, high-speed response of the IBRs through blackstart, islanding, and load step testing. Results of project field evaluations provide distribution systems operators (DSO) with increased confidence that renewable, IBR can replace traditional generators to blackstart and island microgrids and rapidly establish stable island frequency with rapid changes in peak power demand. Importantly, the project validated the integration feasibility of a distributed energy resource management system (DERMS) controller that manages multiple grid-forming and grid-following IBRs, establishing a standard design interface to reduce the complexity of integrating new DERs in the future and supporting replication by the industry. As a result of learnings in this project, SDG&E has implemented the microgrid controller strategy at multiple other microgrid sites, thereby validating the replicability of the solution. Hardware-in-the-loop (HIL) simulations including power and controller HIL hardware — along with electromagnetic transient (EMT) simulations of Borrego Springs Microgrid —informed adjustments to inverter parameters and were important to characterize the performance of the IBRs in relevant operating conditions before deployment. The EMT and HIL simulations of islanding the entire community are important contributions in providing confidence in IBR performance prior to future islanding of the community in the field. High-fidelity EMT and/or HIL simulation of IBRs can de-risk field operations, and its relevance and importance as a tool is increasing as distribution grids and microgrids become more complex and dynamic with an increasing proportion of renewable generation, distributed energy storage, and two-way power and energy flows.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Sensor Data Analytics and Data Quality Assessment Software

The proposed framework derives a set of quality metrics to provide critical insights into and tracking of grid operations, sensor performance, sensor longevity, and event statistics. Power grid engineers can utilize this information to identify problems with existing sensor locations and problematic power grid assets including generators, transmission lines, load centers, and substations. This information can also be used to identify unexpected/abnormal behavior of power grid components, improve power grid observability, and operational monitoring, and thus enhance real-time decision-making support system. Power grid planners can utilize this information to augment existing sensing architecture with new sensors and improve the observability of the network.

Mahapatra, Kaveri↗
NASA NTRS2003

Accelerating the Design of Space Vehicles

One of NASA's key goals is to increase the safety and reduce the cost of space transportation. Thus, a key element of NASA's new Integrated Space Transportation Plan is to develop new propulsion, structures, and operations for future generations of reusable launch vehicles (RLVs). As part of this effort to develop the next RLV, the ClCT Program's Computing, Networking, and Information Systems (CNIS) Project is developing and demonstrating collaborative software technologies that use the collective power of the NASA Grid to accelerate spacecraft design. One of these technologies, called AeroDB, automates the execution and monitoring of computational fluid dynamics (CFD) parameter studies on the NASA Grid. About the NASA Grid The NASA Grid, or Information Power Grid,. is being developed to leverage the distributed resources of NASA's many computers. instruments, simulators, and data storage systems. The goal is to use these combined resources to sdve difficult NASA challenges, such as iimulating the entire flight of a space vehicle from ascent to descent.To realize the vision of the NASA Grid, the CNIS Project is developing the software framework and protocols for building domain-specific environments and interfaces, new Grid services based on emerging industry standards, and advanced networking and computing testbeds to support new Grid-based applications such as AeroDB.

Laufenberg, Larry↗