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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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The architecture presentation discusses the requirement grid architecture design to integrate AES capabilities. Three NREL projects that cover control, communication, and operation architectures are discussed as reference AES implementations. Testing platforms and capabilities such as ADMS test bed are introduced to validate AES solutions and developed architectures.
Distributed energy resources are an increasingly important part of the electric grid. We examine the problem of partitioning a distributed energy resource among many users while providing privacy to them. In this model, clients can send requests to a server, the server can verify that the requests are valid and aggregate them, but it cannot see the actual values in the requests. Without privacy, each user is forced to reveal their daily schedule or energy use. Energy resources add a novel challenge that prior systems do not address: they require verifying limits on private power (a rate over time) and energy (a sum) values. Furthermore, the cryptographic mechanisms must run on embedded energy control systems. We describe Weft, a novel cryptographic system that verifies both power (rate) and energy (integral) constraints on private client values and aggregates them. The key insight behind the approach is to rely on additively homomorphic secret shares, which allows servers to compute sums from rates. We present 3 cryptographic proof systems with different system trade-off for embedded systems: bit-splitting proofs minimize memory use, sorting proofs minimize computation, and commitment proofs minimize network communication. Using bit-splitting proofs, it takes an IoT client using a CortexM microcontroller 4 minutes of compute time to privately control its share of an energy resource for a day at 20s granularity.
Europe and North America account for 32 % of current carbon emissions. Due to distinct legacy systems, energy infrastructure, socioeconomic development, and energy resource endowment, both regions have different policy and technological pathways to reach net zero by the mid-century. Against this background, our paper examines the results from the net zero emission scenarios for Europe and North America that emerged from the collaboration of the European and American Energy Modeling Forums. Here, in our analysis, we perform an inter-comparison of various integrated assessments and bottom-up energy system models. A clear qualitative consensus emerges on five main points. First, Europe and the United States reach net zero targets with electrification, demand-side reductions, and carbon capture and sequestration technologies. Second, the use of carbon capture and sequestration is more predominant in the United States due to a steeper decarbonization schedule. Third, the buildings sector is the easiest to electrify in both regions. Fourth, the industrial sector is the hardest to electrify in the United States and transportation in Europe. Fifth, in both regions, the transition in the energy mix is driven by the substitution of coal and natural gas with solar and wind, but to a different extent.
The increasing global population and the challenges faced by the food production sector, including urbanization, reduction of arable land, and climatic extremes, necessitate innovative solutions for sustainable agriculture. This comprehensive review examines advancements in improving the energy performance of agricultural greenhouses, highlighting innovations in thermal and energy efficiency, particularly in heating and cooling systems. The methods include a systematic analysis of current technologies and their applications in optimizing greenhouse design and functionality. Key findings reveal significant progress in materials and techniques that enhance energy efficiency and operational sustainability. The review identifies gaps in the current knowledge, such as the need for more research on the economic viability of new materials and the development of predictive models for various climatic conditions. The conclusions emphasize the importance of integrating renewable energy technologies and advanced control systems to achieve energy-efficient and sustainable agricultural practices
The High Energy Astrophysics Costing Tool (HEACT) is a combined Expert System/Numerical Simulation to evaluate sensors and experiments proposed for space platforms in order to determine their expected performance and to assess the amount and quality of scientific information likely to be gathered by such experiments. The end product of this tool will be both a cost estimate for the experiment package as deployed and also an estimate of the amount of new scientific knowledge (both new data and reductions in the uncertainties of previous measurements) which would result from the actual deployment and operation of that experiment package. The numerical simulation part of HEACT will contain components to: (1) calculate the high energy signatures of both actual and proposed classes of astrophysical objects, and (2) model the response and resolution of the candidate sensors for observing those objects. The rule based part of the HEACT will be based on knowledge in the areas of experiment design, instrument selection, and system integration developed from experience with existing high energy astrophysics observatories, both orbiting and lofted by rockets or balloons. This paper presents mainly results from the design of the rule-based part of HEACT. It focuses on the structure of the rules and the structures used to represent the knowledge related to the design and integration of such experiments. Methods for integrating the results from numerical simulations into the expert system will also be discussed.
As demand for digital services accelerates, the energy and environmental footprint of data centers faces increasing scrutiny. While hyperscale cloud facilities have driven efficiency gains, small and midsize U.S. data centers remain a critical yet underexamined segment with significant untapped potential for energy savings. This study leverages data from the Commercial Buildings Energy Consumption Survey (CBECS) to analyze trends in server stocks, computing customers, cooling system adoption and efficiency, and geospatial distribution from 2012 to 2018. Findings reveal a sharp decline in small and midsize data centers, from 1.764 million to 1.398 million, with server counts dropping from 5.177 million to 4.262 million—aligning with the broader shift toward cloud computing. More than 40 % of servers in small data centers and 55 % in midsize data centers are housed in office buildings, and over half of all servers are concentrated in climate zones 5A (cold), 3A (mixed-humid), and 4A (mixed-humid), with the highest densities in metropolitan hubs. While direct expansion units remain the dominant cooling system, a clear transition toward more energy-efficient solutions, particularly air economizers, is evident. By integrating server and cooling system distributions, we estimate Power Usage Effectiveness (PUE) and Water Usage Effectiveness (WUE) for U.S. data centers by size and year. Results show that midsize data centers are more energy-efficient but more water-intensive due to the widespread use of water-cooled chillers. These findings highlight the trade-offs in cooling system selection and provide a critical foundation for policies aimed at enhancing efficiency in an evolving data center landscape.
Neutron fluences were measured from 435 MeV/nucleon Nb ions stopping in a Nb target and 272 MeV/nucleon Nb ions stopping in targets of Nb and Al for neutrons above 20 MeV and at laboratory angles between 3 degrees and 80 degrees. The resultant spectra were integrated over angles to produce neutron energy distributions and over energy to produce neutron angular distributions. The total neutron yields for each system were obtained by integrating over the angular distributions. The angular distributions from all three systems are peaked forward, and the energy distributions from all three systems show an appreciable yield of neutrons with velocities greater than the beam velocity. Comparison of the total neutron yields from the two Nb + Nb systems suggests that the average neutron multiplicity decreases with decreasing projectile energy. Comparison of the total yields from the two 272 MeV/nucleon systems suggests that the total yields show the same dependence on projectile and target mass number as do total inclusive neutron cross sections. The data are compared with Boltzmann-Uehling-Uhlenbeck model calculations.
Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.
Multiport autonomous reconfigurable solar power plant (MARS) has been proposed for integrated development of photovoltaic (PV) and energy storage system (ESS) that can connect to high-voltage direct current (HVdc) and alternating current (ac) transmission grid. To de-risk the development of this complex integrated system that consists of hundreds to thousands of power electronics modules, a controller hardware-in-the-loop (cHIL) test setup will be extremely beneficial. The cHIL testing can be used for evaluation of modules as well as the hierarchical control system in MARS. With the unique configuration of power electronics modules in MARS, it becomes necessary to develop custom-designed real-time simulation models in the cHIL setup in absence of off-the-shelf models. In this paper, high-fidelity dynamic model of MARS, control algorithms at the lower level, and required communication algorithms are developed and optimized for real-time performance in the cHIL setup. Real-time experimental results from the cHIL are provided.
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This report provides an overview of test results for four energy storage systems funded under the Washington Clean Energy Fund deployed at three utilities in Washington State. Integration of energy storage into the U.S. grid has been gathering momentum across the industry, especially as penetration of power generated by renewable resources increases. Several states have storage procurement targets to deal with a variety of issues, such as afternoon total system load ramping requirements, frequency regulation/control, and integration power generated from by renewable resources. This report presents the performance test results for battery energy storage systems (BESS) funded by the Washington Clean Energy Fund (CEF) 1 Program ($\$$14.3 million in state funding supporting a total investment of $\$$43 million). For each project, the technical attributes of the BESS were tested, defined, and evaluated in detail. These projects were funded jointly by Avista, the Snohomish Public Utility District (SnoPUD), Puget Sound Energy (PSE), the Washington CEF, and the U.S. Department of Energy Office of Electricity Delivery and Energy Reliability (DOE-OE).
An energy analysis methodology was developed to serve as a rational basis for evaluating alternative regional management/use schemes. Human and natural systems are coupled and can be interpreted, using a common base of energy-flow analysis to evaluate past, present, and future states of regional integrated systems in the coastal zone and to provide the capability for rational selection of alternative patterns of resource use. Energy flows (or flows of dollars or materials converted to energy equivalents) are believed to be the basic factor in the organizations of all types of systems. An analysis example is provided of an estuarine subsystem of the Chesapeake Bay, and tabular listings of regional data needs are given. Current remote sensing capabilities were used to provide some of the necessary information.
With the increasing urgency to decarbonize power systems, while mitigating extreme events, capacity expansion models can play a vital role in reliably planning the expansion of power systems and facilitating the integration of renewable energy sources. Optimizing capacity expansion generally involves selecting surrogate representative days from forecasts of load and the generation profiles of variable renewable energy resources. To properly select those representative days, we propose a novel input-based approach in combination with the k-means clustering algorithm that utilize three unique operational inputs: load shedding, renewable curtailment, and transmission congestion. The proposed method allows for more robust and cost-effective capacity planning. The method is validated using a capacity expansion model and a production cost model based on California Independent System Operator (CAISO)'s decarbonization goals, and results in reduced costs and drastically lower load shedding.
Transitioning from fossil-fuel power generation to renewable energy generation and energy storage in remote locations has the potential to reduce both carbon emissions and cost. Here, this study presents a techno-economic analysis for implementation of a hybrid renewable energy system at the South Pole in Antarctica, which currently hosts several high-energy physics experiments with nontrivial power needs. A tailored model of resource availability and economics for solar photovoltaics, wind turbine generators, lithium-ion energy storage, and long-duration energy storage at this site is explored in different combinations with and without existing diesel energy generation. The Renewable Energy Integration and Optimization (REopt) platform is used to determine the optimal system component sizing and the associated system economics and environmental benefit. We find that the least-cost system includes all three energy generation sources and lithium-ion energy storage. For an example steady-state load of 170 kW, this hybrid system includes 180 kW-DC of photovoltaic panels, 570 kW of wind turbines, and a 3.4 MWh lithium-ion battery energy storage system. This system reduces diesel consumption by 95% compared to an all -diesel configuration, resulting in approximately 1200 metric tons of carbon footprint avoided annually. Over the course of a 15-year analysis period the reduced diesel usage leads to a net savings of 57 million United States dollars, with a time to payback of approximately two years. All the scenarios modeled show that the transition to renewables is highly cost effective under the unique economics and constraints of this extremely remote site.
This guidebook provides power system planners with a brief but comprehensive summary of the strategies, best practices, and terminology associated with conducting a high-impact grid integration study. The objective is to provide practical guidance to teams that are in the initial stages of designing a grid integration study effort. Though this guidance is broadly applicable to most power systems, it emphasizes considerations relevant to developing economies, drawing on experiences from efforts by the United States Agency for International Development (USAID) to support this type of analysis with its partner countries.
This report describes a summary and the final deliverables for the Wind Reference Architecture project funded by the Department of Energy's (DOE) Wind Energy Technology Office (WETO). The project objective was to further refine the reference architecture of the existing wind power plant reference architecture developed by Idaho National Laboratory (INL) and Sandia National Laboratories (SNL) by expanding the wind turbine generator (WTG) into a separate individual wind turbine reference architecture. Additional details regarding the wind turbine system and how it integrates with a wind power plant were researched and reflected in the reference architecture. This addition is important because it allows researchers to understand the components and devices in a wind turbine, how they function and how a wind turbine integrates into a wind power plant to be able to perform cybersecurity evaluations on the system. The communication and control systems were the focus while developing this reference architecture to understand the cybersecurity posture of a wind turbine and power plant. The information technology (IT) and operational technology (OT) systems perspective are integral in helping improve the cybersecurity posture by creating a starting point to study how wind energy can be safely designed and deployed in our power grid from an integrated systems standpoint. A holistic wind power plant and turbine reference architecture and simulation was developed and made open-sourced for further research efforts.