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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Thermal and Mechanical Energy Performance Analysis of Closed-loop Systems in Hot-Dry-Rock and Hot-Wet-Rock Reservoirs

To understand the potential and limitations for recovering thermal and mechanical energy from closed-loop geothermal systems a collaborative study is underway that will investigate an array of system configurations, working fluids, geothermal reservoir characteristics, operational periods, and heat transfer enhancements. Closed-loop geothermal systems are distinguished from hydrothermal or enhanced geothermal systems (EGS) in that the working fluid only circulates through drilled boreholes. Principal objectives of this study are to determine upper limits for thermal and mechanical energy recovery and optimal operational and configuration parameters for each scenario. Teams of scientists and engineers are applying a suite of numerical simulation and analytical tools to model the heat recovery from closed-loop geothermal systems, and then optimizing operational and configuration parameters to maximize the thermal and mechanical energy recovery. Results from the suite of numerical simulators and analytical tools, such as outlet and inlet states and temperature profiles in the geothermal reservoir over time are intercompared to increase confidence in the analysis. This paper documents the study findings for closed-loop systems in hot-dry-rock and hot-wet-rock reservoirs, where water is the working fluid. The characteristics of the hot-dry-rock reservoir were based on the U.S. Department of Energy’s Utah Frontier Observatory for Research in Geothermal Energy (FORGE) site, near Milford Utah. Two objective functions are defined to optimize the operational and configuration parameters of the system, one each for the recovery of mechanical and thermal energy over the period of operation. For both objective functions, a surface plant thermal to mechanical energy conversion factor and an energy drilling cost is required. In keeping with the study objectives the surface plant conversion factor is determined from a second-law of thermodynamics analysis of a generic binary plant, and drilling costs are based on those from the Utah FORGE site and current national electrical costs.

Closed-loop geothermal systems, hot-dry-rock, hot-↗
DOE OSTI2020

Method of evaluating change in energy consumption due to Volt VAR optimization

A method of evaluating an optimization system is disclosed. The system is transitioned from an on state to an off state. Data is collected at time intervals for a time period before and after the system is transitioned from the on state to the off state. The transitioning occurs while a load of a particular type is active. In one embodiment, the optimization system is a Volt/VAR Optimization (VVO) system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Optimal Power Management for Large-Scale Battery Energy Storage Systems via Bayesian Inference

Large-scale battery energy storage systems (BESS) have found ever-increasing use across industry and society to accelerate clean energy transition and improve energy supply reliability and resilience. However, their optimal power management poses significant challenges: the underlying high-dimensional nonlinear nonconvex optimization lacks computational tractability in real-world implementation, and the uncertainty of the exogenous power demand makes exact optimization difficult. This paper presents a new solution framework to address these bottlenecks. The solution pivots on introducing power-sharing ratios to specify each cell’s power quota from the output power demand. To find the optimal power-sharing ratios, we formulate a nonlinear model predictive control (NMPC) problem to achieve power-loss-minimizing BESS operation while complying with safety, cell balancing, and power supply-demand constraints. We then propose a parameterized control policy for the power-sharing ratios, which utilizes only three parameters, to reduce the computational demand in solving the NMPC problem. This policy parameterization allows us to translate the NMPC problem into a Bayesian inference problem for the sake of 1) computational tractability, and 2) overcoming the nonconvexity of the optimization problem. We leverage the ensemble Kalman inversion technique to solve the parameter estimation problem. Concurrently, a low-level control loop is developed to seamlessly integrate our proposed approach with the BESS to ensure practical implementation. This low-level controller receives the optimal power-sharing ratios, generates output power references for the cells, and maintains a balance between power supply and demand despite uncertainty in output power. We conduct extensive simulations and experiments on a 20-cell prototype to validate the proposed approach.

Battery energy storage systems (BESSs)↗
DOE OSTI2020

Phased: Phase-Aware Submodularity-Based Energy Disaggregation

Energy disaggregation is the task of discerning the energy consumption of individual appliances from aggregated measurements, which holds promise for understanding and reducing energy usage. In this paper, we propose PHASED, an optimization approach for energy disaggregation that has two key features: PHASED (i) exploits the structure of power distribution systems to make use of readily available measurements that are neglected by existing methods, and (ii) poses the problem as a minimization of a difference of sub-modular functions. We leverage this form by applying a discrete optimization variant of the majorization-minimization algorithm to iteratively minimize a sequence of global upper bounds of the cost function to obtain high-quality approximate solutions. PHASED improves the disaggregation accuracy of state-of-the-art models by up to 61% and achieves better prediction on heavy load appliances.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2021

Optimal Sizing of an Electric Vehicle Charging Station with Integration of PV and Energy Storage

This paper proposes an optimization model for the optimal configuration of an grid-connected electric vehicle (EV) extreme fast charging station considering integration of photovoltaic (PV) and energy storage. The proposed model minimizes the annualized net cost (i.e., maximizes the annualized net profit) of the extreme fast charging station, including investment and maintenance cost of charging ports, PV and energy storage, net cost of purchasing energy from utility and selling energy to EV customers, degradation cost of energy storage and demand charge. The decision variables are number of charging ports, capacity of invested PV and the power and energy ratings of invested energy storage. The Erlang-loss system is adopted to model the EV mobility. Results of numerical simulations indicate that investment of PV and energy storage could increase the annualized profit of the extreme fast charging station. In addition, the impacts of various parameters on the optimal solution are investigated by sensitivity analysis.

Liu, Guodong↗
DOE OSTI2022

Designing for Zero Energy and Zero Carbon on a Multi-Building Scale Using URBANopt: Preprint

Groundbreaking efforts are necessary to mitigate contributors increasing impacts of climate change. In parallel to inventing pioneering clean energy technologies it is even more fundamental to rethink designing energy systems within a singular facility and collectively to function as a district. Facilities should not be continuously passive by just consuming; there is a need to shift to perform more dynamically. Designing for zero energy and zero carbon on a multi-building scale can uncover opportunities for building energy efficiency, decarbonization, demand flexibility, and resiliency that are not accessible at an individual building scale. This approach can be challenging without innovative tools to evaluate the multitude of possibilities. As an investigated result, we highlight the use of a campus-scale energy modeling platform - URBANopt™ - for the expansion of the National Renewable Energy Laboratory's (NREL's) South Table Mountain campus in Golden, Colorado. Programmatic growth included the design of three new all-electric, zero-energy, and zero-carbon, mixed used buildings (a combination of research laboratories and office space). This investigation is critical to NREL reaching net-zero emissions for its operational footprint, which will occur in phases over the next decade. Leveraging URBANopt's capabilities, we evaluate 1) high-performance building energy efficiency and decarbonization measures, 2) 4th generation district heating and cooling (4th GDHC) systems, 3) optimized onsite generation and energy storage assets that meet zero-energy and zero-carbon targets at minimum life-cycle costs, and 4) cost-optimal distributed energy technology mixes, dispatch strategies, and associated capacities that increase resiliency to grid outages. This work demonstrates the use and capabilities of URBANopt through a real-world case study on a multi-building scale.

community energy model↗
DOE OSTI2026

Role of electron correlation on the adenine dimer interaction for non-equilibrium geometries: a benchmark Quantum Monte Carlo study

The accurate description of non-covalent interactions is critical for understanding the structure, dynamics, and eventual function of biomolecules. The adenine dimer serves as a benchmark system for computational methods due to its role in nucleic acid structures and its rich conformational landscape. In this study, we employ benchmark diffusion quantum Monte Carlo (DMC) methods to investigate the relative energies and role of electron correlation on a set of adenine dimer conformations generated via a search of the potential energy landscape using the global optimizer algorithm. Relative DMC energies are compared against a wide range of density functional theory (DFT) approximation results. We find that although most of the DFT functionals perform well for low-energy structures, their accuracy varies significantly for higher-energy conformations, including stacked and T-shaped structures. A large fraction of the variation is due to the treatment of the van der Waals interaction. BLYP, B3LYP, and PBE0 significantly improve with added D4 dispersion, while the recent r2SCAN-D4 and ωB97M-V functionals show the least scatter and closest agreement with the DMC. These findings highlight the delicate nature of these interactions in biomolecular systems and provide guidance for simulations of their structure and dynamics and for the development of machine learned interatomic potentials.

Washburn, Laurel [ORNL] (ORCID:0000000324179335)↗
DOE OSTI2020

Optimizing PCM-integrated walls for potential energy savings in U.S. Buildings

Buildings in the United States account for nearly half of total U.S. energy use. The energy used for space conditioning can be reduced by utilizing thermal energy storage, such as phase change materials (PCMs), into building envelopes; however, the energy savings of PCM-integrated building envelopes reported in the literature vary widely. In the absence of established guidelines, thermophysical requirements of an optimal PCM, its method of application into the building envelope, and the corresponding energy savings under various climates remain unknown. Here, we perform an extensive numerical investigation on the integration of PCM into building walls to establish the key conditions required for effective utilization of PCM in reducing heat gains in the cooling season and heat losses in the heating season. We also determine the optimal transition temperature, optimal PCM location in the wall, and the energy-saving potential of the PCM-integrated building walls in five U.S. cities located in different International Energy Conservation Code climate zones. Results show that employing PCMs in building walls does not always lead to an improvement; in fact, incorrect applications of PCMs can substantially increase energy use in the buildings. In the climates we studied, PCMs were found effective in reducing heat gains during the cooling season while mostly ineffective in managing heat losses during heating season. Depending on the climate, optimized PCMs in U.S. building walls can provide reduction in the annual heat gain in the range of 3.5% to 47.2% and the annual heat loss in the range of -2.8% to 8.3%. Future consideration of buildings with substantial solar gains in winter may lead to more reduction in heat losses by PCMs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

GIS Supported Optimal Site Selection for Coastal Structure Integrated Wave Energy Converters: Preprint

There is an urgent need for adaptative engineering towards more resilient coastal communities, and Coastal Structure Integrated Wave Energy Converters (CSI-WECs) are a promising solution. CSI-WECs are wave energy converters (WECs) that are built into coastal protection structures, such as breakwaters. These devices provide the dual benefits of coastal protection and local energy production, and unlike other WECs, maximizing energy production is not always the main objective. CSI-WECs are located near the shore, where the wave resource is lower, thus site selection for these devices differs from the typical offshore WECs. Other attributes of a site that may be more important than wave power include existing coastal structures, port proximity, electric transmission line proximity, and location of disadvantaged communities. Geospatial information systems (GIS) interfaces can be used to easily visualize geospatial data that represents these difference kinds of criteria important for the determination of optimal marine energy sites. Multi-Criteria Decision Analysis (MCDA) is a geospatial analysis method that allows for the evaluation of multiple, usually overlapping, criteria. This project applies GIS-based MCDA methods to two distinct case studies in Puerto Rico and California for CSI-WEC site selection. The two study sites contrast in terms of wave resource, coastal hazards, and local energy needs. This research demonstrates the utility of applying an MCDA framework within GIS to facilitate efficient site selection for devices with unique characteristics in different use cases.

coastal protection↗
DOE OSTI2021

Urban cells: Extending the energy hub concept to facilitate sector and spatial coupling

The rapid growth of urban areas and concerns over climate change make it vital to improve the energy sustainability of cities. Understanding the complex interactions within different sectors (sectoral) and localities (spatial) of cities plays a crucial role in improving efficiency and sustainability, which is extremely challenging due to the complex urban morphology. State-of-the-art energy concepts do not facilitate a detailed consideration of both sectoral and spatial coupling that energy infrastructure maintains at the urban scale. This has become a significant challenge when designing interconnected urban energy infrastructure. The Urban Cell concept is introduced to address this bottleneck. A novel computational model using a modular approach is introduced to create an interconnected urban infrastructure, including the energy, building, and transportation sectors. Optimal sizing of the distributed energy system (including renewables, energy storage, and dispatchable sources) and optimal urban morphology is determined within a modular unit. A game-theoretic approach is used to model the interactions between urban cells (modular units). The study revealed that the urban cell concept can reduce the net present value of the interconnected energy infrastructure by 37% while increasing the installed renewable energy capacity by 25%. This demonstrates the benefit potential of urban cells and the importance of considering interactions between different sectors and different parts within a city. The Urban Cell concept can be used to present the complex interactions maintained within a city.

Perera, ATD↗
DOE OSTI2021

A Technical and Economic Assessment of LWR Flexible Operation for Generation and Demand Balancing to Optimize Plant Revenue

With increased penetration of subsidized variable renewable energy (VRE) resources and competition from low natural gas prices, existing light water reactor (LWR) nuclear power plants (NPPs) are struggling to remain economically competitive. This work examines the potential economic competitiveness of various thermal energy storage (TES) technologies when coupled directly or indirectly with a NPP. To highlight their relative economic competitiveness, we contrast several energy storage solutions in stochastic dispatch optimization. We leverage data from recent work analyzing a range of TES technologies with varying capital costs, performance, and technology readiness level (TRL) to establish our case. We explore inserting these technologies into an electricity market with existing nuclear generation and large projected variable renewable energy (VRE) penetration. Although these technologies' projected capital costs may make them unlikely candidates in their current state, this analysis demonstrates a high-fidelity techno-economic analysis of energy storage. Furthermore, as the projected cost of energy storage technologies evolves, this analysis sets a precedent for similar future investigations. One region with projected trends that may be unfavorable for existing nuclear capacity is the New York Independent System Operator (NYISO) market. New York state’s baseload generation has been historically provided by fossil-fired and nuclear assets. However, amid economic pressures from subsidized VREs and low natural gas prices, the state has recently deactivated Indian Point nuclear power plant units 2 and 3. Furthermore, the state plans to meet its zero-emission generation target by 2040 by replacing fossil-fired capacity with significant investments in VRE resources like wind and solar photovoltaic (PV) and battery storage. Increased intermittent resource penetration lowers the baseload power requirement, adding further economic pressure to the state’s three remaining NPPs still in operation. With three NPPs still in operation in New York, this work analyzes potential economic benefits to NPPs on the New York grid when directly or indirectly coupled with various TES technologies. This work requires two modeling steps to analyze the potential economic benefits of various system configurations of the TES directly or indirectly coupled with nuclear. First, this analysis leverages capacity expansion modeling by experts at the Electric Power Research Institute (EPRI). Using their deterministic capacity expansion model, U.S. Regional Economy, Greenhouse Gas, and Energy (US-REGEN), EPRI analysts evaluated the capacity and generation evolution of the New York state energy market under four projection scenarios. These four projection scenarios were developed to represent the potential evolution of the capacity and generation in NYISO from 2015 to 2050 under various economic, technology, and policy constraints. The results from these capacity expansion models are then used as boundary conditions in the second modeling step. The second modeling step uses the Holistic Energy Resource Optimization Network (HERON) for a set of stochastic techno-economic analyses (STEAs) to investigate the potential increase in the economic viability of various configurations of the TES. With no current capacity expansion capabilities, HERON takes the data generated from US-REGEN for 2050 to generate synthetic load, solar, and wind data. Then HERON economically optimizes the capacity and dispatch of the various TES configurations. The potential economic benefit is the differential net present value (NPV) of the TES configurations from the no-TES baseline. As a stochastic techno-economic analysis package, HERON introduces uncertainty into the economic metrics, while US-REGEN trades resolution for reduced computational complexity. Using HERON also allows the modeling of direct thermal coupling, a feature not common in capacity and dispatch models. As expected, with high capital costs, the costs of introducing energy storage for all the technologies considered outweighed the potential economic benefit of this strategy for flexible plant operation. The benefit of this analysis is primarily in demonstrating a workflow that examines innovative solutions to increase NPP revenue via TES coupling. HERON’s stochastic capacity and dispatch optimization process used in this work has proven an effective tool in observing and evaluating the impact of introducing storage technologies in a grid energy system.

25 ENERGY STORAGE↗
DOE OSTI2024

Thermochemical Data for Furan-based Monomer Candidates for Frontal Ring-Opening Metathesis Polymerization (FROMP)

This dataset includes 471 furan-based monomer candidates for frontal ring-opening metathesis polymerization (FROMP) and relevant thermochemistry as calculated with density functional theory (DFT). The monomer candidates were combinatorically enumerated using Diels-Alder reactions of furan derivatives as dienes and four types of dienophiles (alkenes, alkynes, allenes, and benzynes). Common substituents were enumerated for the dienophile classes, and methyl substitution on the diene was explored. We used the SMILES arbitrary target specification (SMARTS) language to produce monomers and ring-opened structures from diene and dienophile precursor SMILES, and we studied the ring-opening reaction using a homodesmotic equation with ethene. RDKit conformers were initially generated from SMILES, then optimized with GFN2-xTB. The two conformers lowest in energy were then optimized with DFT using the wb97x-D3 functional, def2-TZVP basis set, and def2/J auxiliary basis set. Gibbs free energy corrections were obtained through frequency calculations. Structures with imaginary frequencies below -50 cm^{-1} were excluded from this work, and smaller imaginary modes were flipped to be positive for free energy calculations. Modes below 50 cm^{-1} were treated with the modified rigid rotor approximation, and all thermochemical values were calculated at T=200C. The CSV file contains the monomer SMILES, the free energy of reaction for Diels-Alder addition (G_DA_200), and the enthalpy of the ring-opening reaction (H_RO_200). All energies are given in kcal/mol. An interactive HTML is also included to visualize the monomers in this dataset.

Chua, Lauren↗
NASA NTRS2005

Small Body GN&C Research Report: A Guidance and Control Technique for Small-Body Proximity Operations with Guaranteed Guidance Resolvability and Required Thruster Silent Time

The guidance and control (G&C) algorithms for enabling small-body proximity operations are developed by using a model predictive control approach along with a convexification of the governing dynamics, control constraints, and trajectory/state constraints. The open-loop guidance is solved ahead of time or in a resolvable, real-time manner through the use of PWG (Pseudo Way-point Generation), a technique developed in this research. The PWG scheme ensures required thruster silent times during trajectory maneuvers. The feedback control is implemented to track the PWG trajectories in a manner that guarantees the resolvability for the open-loop problem, enabling the ability to update the G&C in a model-predictive manner. The schemes incorporate gravity models and thruster ring times into discrete dynamics that are solved as a optimal control problem to minimize fuel consumption or thruster energy expenditure. The optimal control problem is cast as an LMI (Linear Matrix Inequality) and then solved through Semi-Definite Programming techniques in a computationally efficient manner that provides convergence and constraint guarantees.

guidance and control (G&C)↗
DOE OSTI2024

Autonomous Energy Systems: Building Reliable, Resilient, and Secure Electrified Communities

Technological changes across energy systems are forcing utilities and operators to reconsider their methods for managing power delivery, but few operators have adopted advanced controls and operational software. Their challenge is that every system has peculiar requirements, and the available solutions are relatively new, untested, and difficult to integrate into an operational environment. Through extensive collaboration with utilities and cooperatives, the National Renewable Energy Laboratory has realized the need for autonomous and optimized management of energy resources, leading to the development of Autonomous Energy Systems, a packaged set of controls that is ready to be integrated into existing control rooms.

automation↗
NASA NTRSDate not supplied

Wind-Optimal Cruise Airspeed for a Multirotor Aircraft in Urban Air Mobility

This paper first investigates the effect of wind on the wind-optimal (minimum-energy) cruise airspeed for a NASA-proposed conceptual multirotor aircraft for the urban air mobility environment. Next, energy consumption and flight duration results are compared for flying at the wind-optimal airspeed and best-range airspeed on a great-circle cruise segment under different wind conditions. Finally, the difference in energy consumption when flying to meet the assigned required time of arrival based on actual wind conditions vs. predicted wind conditions are examined and compared for the two airspeed modes (wind-optimal and best-range) for different values of wind magnitude uncertainty. The results show operational benefits of flying at the wind-optimal cruise airspeed compared to the best-range airspeed, especially understrong headwind conditions from both an energy consumption and flight duration perspective.The results also show that flying at wind-optimal airspeed under wind magnitude uncertainty has lower variability and higher predictability of energy consumption than flying at best-range airspeed.

Urban Air Mobility↗
DOE OSTI2022

FORCE-DISPATCHES Integration - Initial Demonstration

Integrated energy systems (IES) combine, in mutually beneficial ways, power from variable renewable energy sources and nuclear power plants (NPP) to improve economic viability under uncertain market and weather conditions. The open-source Framework for Optimization of Resources and Economics (FORCE) tool suite, developed at Idaho National Laboratory (INL), has enabled comprehensive modeling and simulation of IES. The capabilities within FORCE include grid portfolio optimization through the Holistic Energy Resource Optimization Network (HERON) and the transient process model analysis library HYBRID, among others. Continuous efforts and investments from the IES programs have been made to expand and improve the versatility of the FORCE toolset in fiscal year 2022. Code-coupling and cross-tool communication have been important methods for improving this versatility. This report focuses on an additional workflow in the HERON tool for capacity and dispatch stochastic optimization through integration with the external tool Design Integration and Synthesis Platform to Advance Tightly Coupled Hybrid Energy Systems (DISPATCHES). DISPATCHES was primarily developed by the National Energy Technology Laboratory, in collaboration with other national laboratories, which included INL, universities, and industry partners. It is coupled to a library of algebraic models for specific plant components, and to a framework for stochastic optimization different from that provided in the current Risk Analysis Virtual Environment (RAVEN)-running-RAVEN algorithm in HERON. HERON currently conducts stochastic optimization via an outer-inner loop: it optimizes over variable capacity on the outer loop, and at each step within the capacity parameter space, conducts an inner optimization over scenarios (of market signals, demand, and/or weather patterns) and hourly dispatch throughout a user-specified number of years. On the other hand, DISPATCHES conducts stochastic optimization via an “all-at-once” strategy in which capacity variables are optimized at the same level as dispatch variables, as all scenarios are considered at once. The latter method works especially well for projects of limited size and project length, as the necessary computational power and memory increases with the number of variables and scenarios. The new capability to use the DISPATCHES workflow in HERON enhances standalone simulations by leveraging FORCE tools—namely, the economic metrics from the Tool for Economic Analysis (TEAL) and reduced-order model (ROM) sampling from RAVEN. The initial demonstration of the DISPATCHES workflow simulates an existing nuclear-case flowsheet within the DISPATCHES repository—this models a NPP with a secondary revenue stream for hydrogen production. Electrical output from the plant is converted to hydrogen via a proton-exchange membrane (PEM) electrolyzer, hydrogen tanks are used for storage, and an additional turbine is added for hydrogen combustion. Continued work regarding this FORCE-DISPATCHES integration will include automatic generation of DISPATCHES models from HERON inputs, offering analysts the option of using either the RAVEN-runsRAVEN or DISPATCHES workflow to solve technoeconomic optimization problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Roadmap on advanced and / real-time characterisation of solid state materials and devices for energy applications

A strong societal and political drive is motivating the development and optimization of novel energy conversion and storage systems for decarbonization. The successful implementation of solid state devices such as fuel cells and secondary batteries depends, however, on achieving ambitious targets in terms of performance, reliability and cost competitiveness. Research and technology are addressing these needs through a holistic approach including exploration of new materials and nanoarchitectures, as well as system engineering. These significant efforts require the support of appropriate characterization tools capable of assessing nanometer-scale phenomena such as concentration profiles of ionic and electronic charges, local chemical compositions and their evolution over time across interfaces. This roadmap provides an overview of selected advanced characterization techniques for energy materials and devices. Specific focus is put on in situ/operando methods for probing electrochemical phenomena in real-time under realistic working conditions. Experts in the field provide an extensive review of the current state of the art in 2025 and the current and future challenges for the characterization of local chemistry and kinetics in the bulk of the material, in nanoarchitectures (e.g. thin films) and at the interfaces (e.g. grain boundaries, phase contacts, solid/liquid and solid/gas interfaces) . The aim is to provide a detailed guide to the techniques, describing opportunities and bottlenecks for their practical deployment and examples of successful applications.

25 ENERGY STORAGE↗