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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 OSTI2018

Behind-the-meter Transctive Control Approach for Home Energy Management System

Energy efficiency serves as an essential part of demand-side solutions to address the challenges of energy security and carbon emission, and ensure a reliable, affordable and sustainable energy system. In this paper, a behind-the-meter transactive market is proposed for the home energy management system to achieve energy reduction by coordinating home appliances through market bidding and clearing. The proposed approach can achieve the optimal coordination by taking into account the home owner's preferences of energy reduction over different appliances. Thermostatically controlled loads (TCLs) including air conditioner and water heater are considered as the example to illustrate the controller design. The proposed controllers for TCLs can translate the trade-off between energy saving and temperature discomfort into the bidding information. The simulation results demonstrate the effectiveness of the proposed behind-the-meter transactive design for energy efficiency.

Lian, Jianming↗
DOE OSTI2016

Superoxide (Electro)Chemistry on Well-Defined Surfaces in Organic Environments

Efficient chemical transformations in energy conversion and storage systems depend on understanding superoxide anion (O 2 – ) electrochemistry at atomic and molecular levels. Here, in this work, a combination of experimental and theoretical techniques are used for rationalizing, and ultimately understanding, the complexity of superoxide anion (electro)chemistry in organic environments. By exploring the O 2 + e – ↔ O 2 – reaction on well-characterized metal single crystals (Au, Pt, Ir), Pt single crystal modified with a single layer of graphene (Graphene@Pt(111)), and glassy carbon (GC) in 1,2 dimethoxyethane (DME) electrolytes, we demonstrate that (i) the reaction is an outer-sphere process; (ii) the reaction product O 2 – can “attack” any part of the DME molecule, i.e., the C–O bond via nucleophilic reaction and the C–H bond via radical hydrogen abstraction; (iii) the adsorption of carbon-based decomposition products and the extent of formation of a “solid electrolyte interface” (“SEI”) increases in the same order as the reactivity of the substrate, i.e., Pt(hkl)/Ir(hkl) » Au(hkl)/GC > Gaphene@Pt(111); and (iv) the formation of the “SEI” layer leads to irreversible superoxide electrochemistry on Pt(hkl) and Ir(hkl) surfaces. In conclusion, we believe this fundamental insight provides a pathway for the rational design of stable organic solvents that are urgently needed for the development of a new generation of reliable and affordable battery systems.

25 ENERGY STORAGE↗
DOE OSTI2026

Different Damp-Heat-Induced Series Resistance Degradation Behaviors in Fielded Crystalline Silicon Photovoltaic Modules Due to Difference in Bill of Materials

This case study investigates mono-crystalline silicon modules from underperforming portions of a utility-scale photovoltaic power plant. Field-collected I-V curves and electroluminescence imaging suggested that increased series resistance was a primary factor driving module degradation. Selected modules were removed from the field for further analysis, including incremental damp heat accelerated testing, which confirmed a progression in series resistance degradation. Two distinct cell degradation behaviors became apparent during the investigation. Cross-sectional scanning electron microscopy (with elemental analysis) and scanning spreading resistance microscopy identified key differences between the two degradation mechanisms, primarily grid finger width and contact resistance. Additionally, the study highlights the reliability implications of retest requirements in International Electrotechnical Commission 61215 for material changes and how they may have mitigated the degradation observed at this site.

14 SOLAR ENERGY↗
DOE OSTI2013

Uncertainty Quantification Techniques for Sensor Calibration Monitoring in Nuclear Power Plants

This report describes the status of ongoing research towards the development of advanced algorithms for online calibration monitoring. The objective of this research is to develop the next generation of online monitoring technologies for sensor calibration interval extension and signal validation in operating and new reactors. These advances are expected to improve the safety and reliability of current and planned nuclear power systems as a result of higher accuracies and increased reliability of sensors used to monitor key parameters. The focus of this report is on documenting the outcomes of the first phase of R&D under this project, which addressed approaches to uncertainty quantification (UQ) in online monitoring that are data-driven, and can therefore adjust estimates of uncertainty as measurement conditions change. Such data-driven approaches to UQ are necessary to address changing plant conditions, for example, as nuclear power plants experience transients, or as next-generation small modular reactors (SMR) operate in load-following conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Uncertainty Quantification Techniques for Sensor Calibration Monitoring in Nuclear Power Plants

This report describes research towards the development of advanced algorithms for online calibration monitoring. The objective of this research is to develop the next generation of online monitoring technologies for sensor calibration interval extension and signal validation in operating and new reactors. These advances are expected to improve the safety and reliability of current and planned nuclear power systems as a result of higher accuracies and increased reliability of sensors used to monitor key parameters. The focus of this report is on documenting the outcomes of the first phase of R&D under this project, which addressed approaches to uncertainty quantification (UQ) in online monitoring that are data-driven, and can therefore adjust estimates of uncertainty as measurement conditions change. Such data-driven approaches to UQ are necessary to address changing plant conditions, for example, as nuclear power plants experience transients, or as next-generation small modular reactors (SMR) operate in load-following conditions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Blockchain: Next Generation Supply Chain Security for Energy Infrastructure and NERC Critical Infrastructure Protection (CIP) Compliance

The U.S. power grid is a complex system of systems that requires a secure, reliable and trustworthy global supply chain. This is especially true for the grid’s increasing number of networked energy delivery system (EDS) and industrial control systems (ICS) and associated vendors, distributers, integrators and end users. Grid modernization has increased the use of “smart” energy devices that network, digitize, automate and increasingly converge the cyber-physical energy supply chain. In this Energy Internet of Things (EIoT) environment there is an increasing number of both critical cyber assets as well as data speed and size requirements, creating new cyber supply chain security and North American Electric Reliability Corporation (NERC) CIP compliance challenges for utilities, regulators and vendors. In realization of these goals, improvements are needed in the process and technology to better monitor, audit and realize cyber security and compliance goals in complex EIoT environments. This paper explores how blockchain technology may present a disruptive solution to facilitate NERC CIP compliance and increase the security of the electricity infrastructure supply chain through a cryptographically signed distributed ledger that provides increased data provenance, attribution and auditability.

Blockchain, Cyber security, grid cyber, NERC CIP, ↗
DOE OSTI2019

Grid-Friendly Renewable Energy: Solar and Wind Participation in Automatic Generation Control Systems

This paper focuses on emerging technological and regulatory considerations of using solar and wind generators to provide essential reliability services through participation in area-wide automatic generation control (AGC) systems. AGC systems enable a grid operator to centrally and automatically manage the output of interconnected generators, storage devices, and controllable loads to maintain reliable and safe system operations. The paper highlights recent experiences of solar and wind on AGC, as well as recent developments that may enable VRE to participate in AGC in the near future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Exploring the Potential Competitiveness of Utility-Scale Photovoltaics plus Batteries with Concentrating Solar Power, 2015–2030

Declining costs of both solar photovoltaics (PV) and battery storage have raised interest in the creation of “solar-plus-storage” systems to provide dispatchable energy and reliable capacity. There has been limited deployment of PV-plus-energy storage systems (PV+ESS), and the actual configuration and performance of these systems for dispatchable energy are in the early stages of being defined. In contrast, concentrating solar power with thermal energy storage (CSP+TES) has been deployed at scale with the proven capability of providing a dispatchable, reliable source of renewable generation. A key question moving forward is how to compare the relative costs and benefits of PV+ESS and CSP+TES. While both technologies collect solar radiation and produce electricity, they do so through very different mechanisms, which creates challenges for direct comparison. Nonetheless, it is important to establish a framework for comparison and to identify cost and performance targets to aid meeting the nation’s goals for clean energy deployment. In this paper, we provide a preliminary assessment comparing the cost of energy from CSP+TES and PV+ESS that focuses on a single metric: levelized cost of energy (LCOE). We begin by defining the configuration of each system, which is particularly important for PV+ESS systems. We then examine a range of projected cost declines for PV, batteries, and CSP. Finally, we summarize the estimated LCOE over a range of configuration and cost estimates. We conclude by acknowledging that differences in these technologies present challenges for comparison using a single performance metric. We define systems with similar configurations in some respects. In reality, because of inherent differences in CSP+TES and PV+ESS systems, they will provide different grid services and different value. For example, depending on its configuration, a PV+ESS system may provide additional value over CSP+TES by providing more flexible operation, including certain ancillary services and the ability to store off-peak grid energy. Alternatively, direct thermal energy storage allows a greater capture of solar energy, reducing the potential for curtailments in very high solar scenarios. So while this analysis evaluates a key performance metric (cost per unit of generation) under a range of cost projections, additional analysis of the value per unit of generation will be needed to comprehensively assess the relative competitiveness of solar energy systems deployed with energy storage.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Guest Editorial Electric Machines in Renewable Energy Applications

The main objective of this special issue is to collect and disseminate publications that highlight recent advances and breakthroughs in the area of renewable energy resources. The use of these resources for production of electricity is increasing rapidly worldwide. As of 2015, a majority of countries have set renewable electricity targets in the 10%-40% range to be achieved by 2020-2030, with a few notable exceptions aiming for 100% generation by renewables. We are experiencing a truly unprecedented transition away from fossil fuels, driven by environmental, energy security, and socio-economic factors.Electric machines can be found in a wide range of renewable energy applications, such as wind turbines, hydropower and hydrokinetic systems, flywheel energy storage devices, and low-power energy harvesting systems. Hence, the design of reliable, efficient, cost-effective, and controllable electric machines is crucial in enabling even higher penetrations of renewable energy systems in the smart grid of the future. In addition, power electronic converter design and control is critical, as they provide essential controllability, flexibility, grid interface, and integration functions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

The Novel Hybrid Ab Initio Model of High-Performance Structural Alloys Design for Fossil Energy Power Plants

The current project developed a novel HT-CALPHAD/DFT approach, which can quickly design new high-performance structural alloys for the application of FE power plants. The PI will mainly take charge of high-throughput DFT simulations and computational thermodynamics of the selected multicomponent alloy systems for the FE power plant applications. At the end of the project, a novel hybrid model based on high throughput CALPHAD/DFT simulations and computational thermodynamics will be developed to provide guidance on how to identify multi-component new high-performance structural alloys with much less computational effort needed. It will address the extensive computation time needed for DFT on the new alloys design. In addition, it will also address the well-known headache of DFT, i.e. how to make the accurate prediction of the high-temperature equilibria. The novel hybrid model the PI proposed will not only be applied to the design of high-performance structural alloys in FE power plants but in many different applications, such as nuclear reactors. This hybrid modeling approach includes four sections: 1) HT-CALPHAD modeling of Al-Co-Cr-Ni-Fe system with FCC and BCC phase. In this section, 3561 non-equiatomic compositions were randomly generated in order to investigate the phase stability of single FCC and BCC phases. Meanwhile, we proposed a data screening procedure to screen out the good candidates within these compositions, considering the temperature range, average density, and melting temperature, etc. 2) Investigation of FCC-Cr lattice stability in Fe-Cr system. We systematically assessed the reliability of FCC-Cr lattice stability derived by DFT and CALPHAD approaches. Meanwhile, the Fe-Cr binary system was chosen as a case study to verify the Cr lattice stability obtained by both approaches. 3) High-throughput DFT modeling on elastic properties of Al-Co-Cr-Ni-Fe systems. We predicted and established the FCC quinary elastic constant database of the Al-Co-Cr-Fe-Ni systems at 0K by using special quasi-random structure (SQS) approach. The predictions will start with pure elements of Al-Co-Cr-Fe-Ni system and will be continued with binaries, ternaries, quaternaries, and finally the quinary compositions. 3) Modeling of temperature-dependent elastic properties in Al-Co-Cr-Ni-Fe systems. In this part, we predict the thermal expansion coefficient and elastic stiffness coefficient as a function of temperature by applying quasiharmonic approximation. With this approach, the elastic properties of HEAs at elevate temperature can be estimated.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

The WRF-Solar Ensemble Prediction System: Development, Test, and Validation

Providing reliable probabilistic solar radiation information is needed to improve management of the uncertainty and variability of solar generation. Thus, guidance on how to develop skillful and accurate ensemble forecasts is essential and it will ultimately contribute to integration of high amounts of solar energy on the grid. A team from the National Renewable Energy Laboratory and the National Center for Atmospheric Research had been collaborating to develop the WRF-Solar ensemble prediction system (WRF-Solar EPS) in the past three years to produce probabilistic solar irradiance forecasts and better predict solar energy by quantifying forecast uncertainty. The WRF-Solar EPS basically generates ensemble members for solar irradiance based on stochastic perturbations to provide intraday and day-ahead probabilistic forecasts. This study will present main research steps in developing the WRF-Solar EPS including: (a) tangent linear analysis for identifying key input variables of six WRF-Solar modules significantly related to predicting of cloud and solar irradiance, (b) combining stochastic perturbation technique with the WRF-Solar model, and (c) ensemble calibration method to decrease error and uncertainty of ensemble-based solar forecasts. The capability of WRF-Solar EPS is now updated to the most recent version of standard WRF model. This presentation will summarize comprehensive results from the evaluation of forecasts against the National Solar Radiation Data Base as well as ground-measured observations. Moreover, we will introduce the user's guide for WRF-Solar EPS (e.g., parameters to configure stochastic perturbations) and future extension of this research.

day-ahead forecast↗
DOE OSTI2015

Comparison of Integral Parameter Estimated Uncertainties in Fast Neutron Systems with COMMARA-2.1 and COMMARA-2.0 Covariance Data

This paper shows the main differences between the COMMARA-2.0 and COMMARA-2.1 evaluated covariance data in the uncertainty estimation of integral parameters of interest for a large number of typical innovative fast neutron systems. The study provides some guidelines to the nuclear data evaluators on which materials and which reaction types need to be evaluated most accurately to achieve reliable results in computational analyses of similar systems. The assessment of the quality and reliability of the covariance data is outside the scope of the study.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Data-Driven Digital Twin for Reliability Assessment of DC/DC Buck Converter

In commercial applications, the operation of DC/DC converters significantly impacts overall system performance and long-term reliability. This study introduces a data-driven digital twin (DT) approach for estimating critical degradation parameters of DC/DC BUCK converter under steady-state condition. Initially, a circuit-level MATLAB/Simulink digital model (DM C ) is refined against a hardware prototype’s switching model dataset using offline particle swarm optimization. The optimized digital model’s steady-state response is then verified with its average model response while varying the duty and load. Subsequently, degradation profiles are imposed on the inductor, capacitor, MOSFET in the DMC. A large dataset is generated from this model, allowing training, validation, and testing of machine learning (ML) models for component health regression tasks. The proposed method employs random forest ML models, achieving impressive regression results with a squared R value as high as 0.99978 and a root mean square error of 4.2× 10 –6 . The method is further validated on a medium power level DC/DC BUCK prototype with varying load conditions, and includes the analysis of MOSFET’s on-resistance under degradation conditions. This data-driven DT method shows promise for identifying parasitic degradation and ohmic loss parameters, enhancing converter reliability assessments in a non-invasive, generalized, and computationally efficient manner.

14 SOLAR ENERGY↗
DOE OSTI2017

Application of a bayesian belief network model to reliability assessment of nuclear safety-related software - 207

As the instrumentation and control (I and C) systems in nuclear power plants (NPPs) have been replaced with digital-based systems, the need to incorporate software failures into NPP probabilistic risk assessments has arisen. In order to assess the probability of software failure on demand, a Bayesian belief network (BBN) model was developed which estimates the number of defects and the resulting probability of software failure on demand in nuclear safety-related software. To assess the feasibility of the BBN framework, the BBN model was applied to the prototype Integrated Digital Protection System-Reactor Protection System (IDiPS-RPS) to estimate the number of remaining faults and the software failure probability of a target software. The developmental- and V and V-activities carried out during the IDiPS-RPS development process were evaluated based on the well-defined checklist derived by the V and V team and were estimated based on expert elicitation. In addition, the attribute evaluations and the number of FPs of the target software is provided as the inputs for the BBN model. The application results showed the feasibility of using BBNs for quantifying software failure probabilities and several insights were gained from the applications of the BBN model. The proposed BBN framework can be applied to estimate the software failure probability for other safety-related NPP software and provide an insight on modeling the software development process that involves iterations between different development phases. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Residential PV-Energy Storage Testing Collaboration with SunPower: Cooperative Research and Development Final Report, CRADA Number CRD-14-569

Residential scale energy storage devices have shown great promise to add value and improve the ability to integrate distributed and variable generation into the distribution grid. Battery energy storage systems combined with PV and advanced inverters can provide many services. These include extended backup power in case of grid failure, reductions in feeder and system level peak load, system level net load ramp reduction, grid management services both locally (e.g., voltage management) and bulk system (e.g., reserves) level, and improved grid reliability through grid voltage and frequency support. Even though the cost of the energy storage systems are decreasing, one of the main challenges related to the widespread deployment of energy storage, as found by the U.S. Department of Energy (DOE), is utility acceptance of storage technologies. Various interconnection challenges exist when connecting distributed PV-energy storage into the electrical distribution grid in terms of safety, reliability and stability of the electric power systems. Some of the urgent challenges, as seen by the manufacturers and installers are: safety of the battery cells and the packs, performance of the power conversion systems, effect of bidirectional power flow on existing utility equipment and qualification of solutions such as volt-ampere reactive (VAR) support and frequency regulation. Under this project, National Renewable Energy Laboratory (NREL) researchers will work with SunPower to address these challenges by research, testing and analysis at Energy System Integration Facility (ESIF) and energy storage testing laboratory at NREL. NREL's unique power hardware-in-the-loop (PHIL) capability will be utilized to evaluate system-level issues such as reverse power flow and VAR support (if available) for these PV-energy storage systems. Through the analysis of test results, the proposed project will demonstrate use of ESIF capabilities in a way that advances both the DOE and SunPower's goals of moving clean, renewable energy technologies onto the electrical grid.

14 SOLAR ENERGY↗
DOE OSTI2018

Under canopy light detection and ranging–based autonomous navigation

This study describes a light detection and ranging (LiDAR)–based autonomous navigation system for an ultralightweight ground robot in agricultural fields. The system is designed for reliable navigation under cluttered canopies using only a 2D Hokuyo UTM–30LX LiDAR sensor as the single source for perception. Its purpose is to ensure that the robot can navigate through rows of crops without damaging the plants in narrow row–based and high–leaf–cover semistructured crop plantations, such as corn ( Zea mays ) and sorghum ( Sorghum bicolor ). The key contribution of our work is a LiDAR–based navigation algorithm capable of rejecting outlying measurements in the point cloud due to plants in adjacent rows, low–hanging leaf cover or weeds. The algorithm addresses this challenge using a set of heuristics that are designed to filter out outlying measurements in a computationally efficient manner, and linear least squares are applied to estimate within–row distance using the filtered data. Moreover, a crucial step is the estimate validation, which is achieved through a heuristic that grades and validates the fitted row–lines based on current and previous information. The proposed LiDAR–based perception subsystem has been extensively tested in production/breeding corn and sorghum fields. In such variety of highly cluttered real field environments, the robot logged more than 6 km of autonomous run in straight rows. These results demonstrate highly promising advances to LiDAR–based navigation in realistic field environments for small under–canopy robots.

42 ENGINEERING↗
DOE OSTI2018

Energy of Motion of Internal and Surface Waves in a Two-Layer Hydrodynamic System

We study the energy of wave motion in a two-layer “layer with solid bottom–layer with free surface” hydrodynamic system. The dependences of the energies of motion of internal and surface waves on the geometric and physical parameters of the system are analyzed. The contribution of the second approximation to the total energy of the system is estimated. The reliability of the obtained results is verified. The results are graphically illustrated.

42 ENGINEERING↗
DOE OSTI2020

Tensor network investigation of the double layer Kagome compound Ca 10 Cr 7 O 28

Quantum spin liquids are exotic quantum phases of matter that do not order even at zero temperature. While there are several toy models and simple Hamiltonians that could host a quantum spin liquid as their ground state, it is very rare to find actual, realistic materials that exhibit their properties. At the same time, the classical simulation of such instances of strongly correlated systems is intricate and reliable methods are scarce. Here, in this work, we investigate the quantum magnet Ca 10 Cr 7 O 28 that has recently been discovered to exhibit properties of a quantum spin liquid in inelastic neutron scattering experiments. This compound has a distorted bilayer Kagome lattice crystal structure consisting of Cr 5+ ions with spin- moments. Coincidentally, the lattice structure renders a tensor network algorithm in 2D applicable that can be seen as a new variant of a projected entangled simplex state algorithm in the thermodynamic limit. In this first numerical investigation of this material that takes into account genuine quantum correlations, good agreement with the experimental findings is found. Our study contributes to uplifting tensor networks from conceptual tools to methods to describe real two-dimensional quantum materials.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗