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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Sustainable Wind–Biogas Hybrid System for Remote Areas in Jordan: A Case Study of Mobile Hospital for a Zaatari Syrian Refugee Camp

Access to reliable and sustainable energy in remote areas remains a pressing global challenge, significantly affecting economic development and the quality of life. This study focuses on the implementation of fully off-grid wind–biogas hybrid power systems to address this issue, with a focus on remote healthcare camp facilities. This paper investigates the performance of a hybrid renewable energy system within the context of one of Jordan’s northern remote areas, the Zaatari Syrian Refugee Camp, assessing its efficiency and environmental impact by taking the Zaatari hospital as the case study. Simulations were conducted to evaluate system components, including wind turbines, biogas generators, and diesel generators. A comprehensive evaluation was conducted, encompassing both the operational efficiency of the system and its impact on the environment. This study also considered various scenarios (SC#), including grid availability and autonomy levels, to optimize system configurations. The techno-economic assessment employed the levelized cost of energy (LCOE) as a key performance indicator, and sensitivity analyses explored the impact of diesel costs and wind power fluctuations on the system. Additionally, environmental assessment was conducted to evaluate the environmental effects of hybrid systems, with a specific focus on reducing greenhouse gas emissions. This investigation involved an examination of emissions in three different scenarios. The results indicate that the lowest LCOE that could be achieved was 0.0734 USD/kWh in SC#1 with 72.42% autonomy, whereas achieving 100% autonomy increased the LCOE to 0.1756 USD/kWh. Additionally, the results reveal that in scenarios SC#2 and SC#3, which have a higher proportion of diesel generator usage, there were elevated levels of NO x and CO 2 emissions. Conversely, in SC#1, which lacks diesel generators, emissions were notably lower. The proposed hybrid system demonstrates its potential to provide a reliable energy supply to healthcare facilities in remote regions, emphasizing both economic feasibility and environmental benefits. These findings contribute to informed decision making for sustainable energy solutions in similar contexts, promoting healthcare accessibility and environmental sustainability.

09 BIOMASS FUELS↗
DOE OSTI2020

How many offshore wind turbines does New England need?

The proliferation of countries and regions with 100% clean or renewable energy targets necessitates an analysis to determine the number of generating units and storage needed to meet real-time electricity demand on the electric grid. The coastal areas of New England have the capacity to produce a large percentage of the region's energy needs with offshore wind turbines. Here we model offshore wind turbine power production data using MERRA-2 reanalysis and lidar wind speed data sets. We compare this power production to the New England hourly grid demand over the course of one year. 2,000 10 MW offshore wind turbines could satisfy New England's grid demand for about 37% of the year. When combined with 55 GWh of storage, 2,000 turbines could satisfy grid demand for about 72% of the year.

17 WIND ENERGY↗
NASA NTRS1994

Generation of slow-mode waves in front of the dayside magnetopause

Slow-mode waves have been observed to appear frequently in front of the dayside magnetopause. It is found based on two-dimensional global magnetohydrodynamic (MHD) simulations that slow-mode waves are generated through the interaction between the bow shock and various MHD waves (fast-mode, Alfven-mode, or slow-mode waves) in the upstream solar wind. The generated slow-mode waves stay in front of the magnetopause for a long time (over 15 minutes) before the wave energy is convected away tailward. Since various waves are often present in the solar wind, this mechanism may lead to the frequent appearance of slow-mode waves in front of the magnetopause.

Yan, M.↗
DOE OSTI2021

Data-Driven Reliability Assessment for Marine Renewable Energy Enabled Island Power Systems

Marine renewable energy (MRE) resources are highly predictable and persistent sources of energy, when compared to other renewable sources like wind and solar. These lend them favorably for potential grid applications, particularly for coastal/island power systems where their generation potential is high. Island power systems, on the other hand, are either supported by onsite generation or by transported energy from the mainland grid. Therefore, robustness of grid operations depend heavily on the diversity of onsite generation resources and the reliability of the power transportation medium. Issues relating to either of these two factors may lead to impediments in smooth and reliable operation of the power system. Analyzing and quantifying operational risks for such island power systems with diverse non-conventional generation portfolios through conventional techniques can also prove to be cumbersome, often requiring multiple different inputs. Therefore, in this paper, we firstly present a novel, purely data-driven formulation which quantifies the operational reliability of such island power systems through minimal input data. Specifically, our proposed methodology only relies on historical knowledge of typical hourly load and generation profiles to quantify associated operational risks. Subsequently, we use our proposed formulation to evaluate the effectiveness of MRE resources (over other renewable resources like wind and solar) in providing resilience benefits to island power systems. The proposed formulation is demonstrated with a case study for an island power system in Nantucket, MA.

Chalishazar, Vishvas H.↗
NASA NTRS1994

EGRET upper limits to the high-energy gamma-ray emission from the millisecond pulsars in nearby globular clusters

We report upper limits to the high-energy gamma-ray emission from the millisecond pulsars (MSPs) in a number of globular clusters. The observations were done as part of an all-sky survey by the energetic Gamma Ray Experiment Telescope (EGRET) on the Compton Gamma Ray Observatory (CGRO) during Phase I of the CGRO mission (1991 June to 1992 November). Several theoretical models suggest that MSPs may be sources of high-energy gamma radiation emitted either as primary radiation from the pulsar magnetosphere or as secondary radiation generated by conversion into photons of a substantial part of the relativistic e(+/-) pair wind expected to flow from the pulsar. To date, no high-energy emission has been detected from an individual MSP. However, a large number of MSPs are expected in globular cluster cores where the formation rate of accreting binary systems is high. Model predictions of the total number of pulsars range in the hundreds for some clusters. These expectations have been reinforced by recent discoveries of a substantial number of radio MSPs in several clusters; for example, 11 have been found in 47 Tucanae (Manchester et al.). The EGRET observations have been used to obtain upper limits for the efficiency eta of conversion of MSP spin-down power into hard gamma rays. The upper limits are also compared with the gamma-ray fluxes predicted from theoretical models of pulsar wind emission (Tavani). The EGRET limits put significant constraints on either the emission models or the number of pulsars in the globular clusters.

Michelson, P. F.↗
DOE OSTI2024

Powering Data Centers with Clean Energy: A Techno-Economic Case Study of Nuclear and Renewable Energy Dependability

Rising data demands from artificial intelligence (AI) and large language models (LLMs) generating images, videos, and text have prompted increased need for larger and more robust data centers in the United States. Major companies interested in these larger data centers face the choice of linking them to existing regional grids, building stand-alone power supplies onsite, or a combination of both. The request, review, and approval process for new transmission lines to grids in the United States, however, has grown in recent years to times spans rivaling those of new construction for nuclear power plants. Building an islanded power supply for each data center is therefore becoming a prominent option. In this case study, several technologies are modeled in techno-economic simulations for long-term system costs subject to fixed electricity demand from a singular data center. A 250 MWe data center is assumed with additional 50 MWe for resiliency. Techno-economic simulations are conducted using the Holistic Energy Resource Optimization Network (HERON) software, which is a part of the Framework for Optimization of Resources and Economics (FORCE) tool suite. Technologies considered include solar, wind, lithium-ion batteries, and several types of nuclear reactors: large-scale reactors, small modular reactors, and microreactors. A low- and high-cost estimate for each technology is assumed to develop a range of expected economic performance. Low-cost estimates included several clean energy production tax credits. Different combinations of renewable energy generators with nuclear reactors are considered, ranging from a fully renewable-powered data center to a fully nuclear-powered data center. Historic time series of wind and solar availability from the Texas grid are used to train a reduced order model; this model then generates unique time series with similar characteristics of the training dataset. Multiple scenarios of weather and subsequent operations are simulated for each renewable-nuclear combination to determine total costs throughout the project lifetime. Fully renewable-powered configurations required large amounts of installed capacity (GW scale) in the simulations to meet the fixed demand of the data center. This is due to some scenarios in the historical dataset which captured low-wind and low-solar days, requiring over-building of these technologies as well as batteries to compensate for the low amounts of electricity generation. Fully nuclear-powered configurations outperformed the fully renewable and mixed renewable-nuclear configurations in terms of cost, with ranges between $1B and $10B in 2023 USDs compared to $40B+ for fully renewable configurations. Of the nuclear technologies, small modular reactors performed better economically than large-scale nuclear models due to lower projected capital costs, and both performed better than the microreactor models. These results demonstrate the applicability of firm, dispatchable electricity resources from baseload generators like nuclear power plants for operating facilities that run at constant power without daily variability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

California Time-of-Use (TOU) Transition: Effects on Distributed Wind and Solar Economic Potential

Time-of-use (TOU) retail energy rates price electricity differently by the time of day, communicating to consumers the costs of supplying electricity diurnally. This study evaluates the impact of Decision D.15.07-001, which mandates a transition in 2020 to default TOU rates for residential ratepayers in California, on the economic viability of behind-the-meter distributed wind and solar systems. Previous studies have demonstrated that increasing wind and solar generation will materially affect the diurnal cost of wholesale electricity. As retail and wholesale prices become more aligned, this could affect the inter-technology economic viability of distributed generation. We assess economic viability through 'economic potential,' or the amount of generation capacity that exceeds a rate of return of 5.4%. In addition, we identify sensitivities of economic potential to capital costs and other techno-economic factors as well as the specific counties and sectors with substantial economic potential. We find that TOU implementation is projected to moderately increase economic potential of distributed wind and marginally decrease that of distributed solar. Over the long-term as variable renewable energy penetration increases in California, particularly utility-scale solar, net peak load and thus peak prices will shift later in the evening. To the extent that retail rates continue to evolve with wholesale prices, we find the changes could positively affect the value of wind generation more than that of solar generation. Over the scenarios considered, model results indicate realistic pathways to reaching a robust distributed wind market in California though solar economic potential was found to be substantially larger than that of wind.

17 WIND ENERGY↗
NASA NTRS1985

A rotating superconducting solenoid for 100 kWh energy storage

Two concentric superconducting solenoids, one rotating, the other stationary are analyzed for energy storage in space. Energy is transferred from the rotating mass through a shaft coupled to a motor-generator. The inner windings interact with the magnetic field of the outer solenoid to cancel the centrifugal and self-field forces of the flywheel rim. Current is induced in the inner solenoid thus requiring no separate power supply, while the current in the outer solenoid must vary with the angular velocity of the flywheel. The effect of the gap and scaling laws are developed. The efficiency in energy per unit mass is marginally attractive.

Waynert, J.↗
DOE OSTI2022

WPGNN and PLayGen (Wind Plant Graph Neural Network and Plant Layout Generator) [SWR-21-90]

WPGNN is the graph neural network machine learning based surrogate model and software that provides a streamlined approximation of wind plant wake models. It can rapidly estimate the energy production of the plant and turbines for any arbitrarily sized wind plant and layout under any inflow condition. Associated tools include graphing and visualization capabilities as well as a wind plant generator capable of creating randomized realizations of canonical wind plant layouts. The WPGNN architecture and application is extendable to multiple wake models, turbine technologies and features, and supports downstream optimizations of wind plant layouts and control strategies. In addition to the WPGNN, we include the code for the plant layout generator (PLayGen) playgen.py. This generator can produce random realizations of realistic wind plant layouts from one of the four canonical styles: cluster, single string, multiple string, or parallel string. The PLayGen_demo.ipynb notebook provides a demonstration of how to use the generator tool.

Harrison-Atlas, Dylan↗
DOE OSTI2023

Synthesis of Platinum Nanoparticles Supported on Fused Nanosized Carbon Spheres Derived from Sustainable Source for Application in a Hydrogen Generation Reaction

The dwindling supply of fossil fuels has prompted the search for an alternative energy source that could effectively replace them. Potential renewable energy sources such as solar, wind, tidal, and geothermal are all promising but each has its own drawbacks. Hydrogen gas on the other hand can be combusted to produce energy with only water as a byproduct and can be steadily generated via the aqueous media hydrolysis reaction of Sodium Borohydride (NaBH 4 ). This study successfully synthesized fused carbon spheres derived from sugar and decorated them with platinum nanoparticles to form a novel composite material (PtFCS) for catalyzing this reaction. The platinum nanoparticles were produced by reducing chloroplatinic acid in a solution with sodium borohydride and using sodium citrate as a capping agent for the nanoparticles. Transmission electron microscopy (TEM), Energy-dispersive X-ray spectroscopy (EDS), Fourier-transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD) were used to characterize and determine the size and shape of the Pt nanoparticles (PtNPs) and fused carbon spheres. TEM was able to determine the average size of the fused carbon spheres to be 200 nm and the average size for the PtNPs to be 2–3 nm. The PtFCS composite was tested for its ability to catalyze the hydrolysis of NaBH 4 under various reaction conditions including various solution pH, various temperatures, and various dosages of sodium borohydride. The catalyst was found to perform the best under acidic solution conditions (pH 6), producing hydrogen at a rate of 0.0438 mL/mg cat ·min. The catalyst was determined to have an activation energy of 53.0 kJ/mol and could be used multiple times in succession with no loss in the volume of hydrogen produced. This sugar-derived composite catalyst shows promise and could be implemented as a sustainable catalyst for the generation of hydrogen fuel.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Scalable Risk Assessment of Rare Events in Power Systems With Uncertain Wind Generation and Loads

Risk assessment of rare events has become increasingly important in power system planning and operation with the increasing integration of renewable energy and the presence of system uncertainties. However, quantifying the risk posed by rare events via the traditional method, i.e., Monte Carlo sampling (MCS), incurs substantial computational expense stemming from the vast ensemble of power flow simulations. To accelerate the assessment, this paper proposes a Deep Neural Network (DNN)-kernelized vector-valued Gaussian Process (VVGP) approach with excellent computational efficiency while maintaining high accuracy. Consequently, serving as a surrogate model for the power flow solver, the DNN-kernelized VVGP enables significantly faster but accurate risk assessment compared to the power flow solver. The developed surrogate model evaluates low-order N - k events that contain more than 90% instances by adeptly capturing the topological features while the high-order N - k events are assessed via a power flow solver, thereby striking a balance between computational efficiency and uncertainty quantification accuracy. Moreover, the model incorporates a Support Vector Machine (SVM) classifier to resample concerning low-probability tail events to counteract the biases potentially introduced during the DNN-kernelized VVGP evaluations. Simulations conducted on the modified IEEE 24-bus, 118-bus, and European 1354-bus systems demonstrate that the proposed method maintains the accuracy benchmark set by MCS while significantly reducing computational demands in large-scale power systems as compared to other state-of-the-art methods.

17 WIND ENERGY↗
DOE OSTI2023

Measurements and Model Improvement: Insight into NWP Model Error Using Doppler Lidar and Other WFIP2 Measurement Systems

Abstract Doppler-lidar wind-profile measurements at three sites were used to evaluate NWP model errors from two versions of NOAA’s 3-km-grid HRRR model, to see whether updates in the latest version 4 reduced errors when compared against the original version 1. Nested (750-m grid) versions of each were also tested to see how grid spacing affected forecast skill. The measurements were part of the field phase of the Second Wind Forecasting Improvement Project (WFIP2), an 18-month deployment into central Oregon–Washington, a major wind-energy-producing region. This study focuses on errors in simulating marine intrusions, a summertime, 600–800-m-deep, regional sea-breeze flow found to generate large errors. HRRR errors proved to be complex and site dependent. The most prominent error resulted from a premature drop in modeled marine-intrusion wind speeds after local midnight, when lidar-measured winds of greater than 8 m s −1 persisted through the next morning. These large negative errors were offset at low levels by positive errors due to excessive mixing, complicating the interpretation of model “improvement,” such that the updates to the full-scale versions produced mixed results, sometimes enhancing but sometimes degrading model skill. Nesting consistently improved model performance, with version 1’s nest producing the smallest errors overall. HRRR’s ability to represent the stages of sea-breeze forcing was evaluated using radiation budget, surface-energy balance, and near-surface temperature measurements available during WFIP2. The significant site-to-site differences in model error and the complex nature of these errors mean that field-measurement campaigns having dense arrays of profiling sensors are necessary to properly diagnose and characterize model errors, as part of a systematic approach to NWP model improvement. Significance Statement Dramatic increases in NWP model skill will be required over the coming decades. This paper describes the role of major deployments of accurate profiling sensors in achieving that goal and presents an example from the Second Wind Forecast Improvement Program (WFIP2). Wind-profile data from scanning Doppler lidars were used to evaluate two versions of HRRR, the original and an updated version, and nested versions of each. This study focuses on the ability of updated HRRR versions to improve upon predicting a regional sea-breeze flow, which was found to generate large errors by the original HRRR. Updates to the full-scale HRRR versions produced mixed results, but the finer-mesh versions consistently reduced model errors.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

Results from the FOCAL Experiment Campaign 1: Turbine Control Co-Design

This paper summarizes the scaling approach and results from the first experimental campaign of the Floating Offshore-wind and Controls Advanced Laboratory (FOCAL) Experimental Program, which is focused on developing public data sets to support the validation of numerical models for floating wind control co-design. A 1:70 Froude-scale performance-matched model of the IEA Wind 15-MW reference turbine was designed, built, and characterized on a fixed base. The National Renewable Energy Laboratory's Reference Open-Source COntroller (ROSCO) was integrated into the scale testing to examine the impact advanced turbine and generator control strategies have on turbine performance and loads, enabling validation of control strategies for floating wind design optimization.

17 WIND ENERGY↗
DOE OSTI2025

Advancements on Multi-Fidelity Random Fourier Neural Networks: Application to Hurricane Modeling for Wind Energy

Multi-fidelity approaches are emerging as effective strategies in computational science to handle otherwise intractable tasks like Uncertainty Quantification (UQ), training of Machine Learning (ML) models, and optimization, for expensive high-fidelity applications in which the amount of available simulations or data is limited. The main idea is simple: large datasets generated for low-fidelity approximations of the problem at hand are fused with a much sparser dataset for the target (high-fidelity) system. In this paper, we build on our recent success in designing random Fourier Neural Networks (rFNNs) [1] to target problems arising in wind energy applications and in particular problems of interest for hurricane modeling. In this context, data for the high-fidelity models are limited and lower fidelity alternatives are needed. In this work, we introduce a novel multi-fidelity training approach for our rFNNs and demonstrate its use on a simple verification problem and on a hurricane modeling problem in which high-fidelity data are generated via Large-Eddy Simulations (LES), while low-fidelity data are given by a mesoscale model. Initial results demonstrate how the multi-fidelity training approach can improve the quality of the resulting surrogate.

Fourier Neural Networks↗
DOE OSTI2022

Advances in Energy Hybridization for Resilient Supply: A Sustainable Approach to the Growing World Demand

Energy poverty, defined as a lack of access to reliable electricity and reliance on traditional biomass resources for cooking, affects over a billion people daily. The World Health Organization estimates that household air pollution from inefficient stoves causes more premature deaths than malaria, tuberculosis, and HIV/AIDS. Increasing demand for energy has led to dramatic increases in emissions. The need for reliable electricity and limiting emissions drives research on Resilient Hybrid Energy Systems (RHESs), which provide cleaner energy through combining wind, solar, and biomass energy with traditional fossil energy, increasing production efficiency and reliability and reducing generating costs and emissions. Microgrids have been shown as an efficient means of implementing RHESs, with some focused mainly on reducing the environmental impact of electric power generation. The technical challenges of designing, implementing, and applying microgrids involve conducting a cradle-to-grave Life Cycle Analysis (LCA) to evaluate these systems’ environmental and economic performance under diverse operating conditions to evaluate resiliency. A sample RHES was developed and used to demonstrate the implementation in rural applications, where the system can provide reliable electricity for heating, cooling, lighting, and pumping clean water. The model and findings can be utilized by other regions around the globe facing similar challenges.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1977

Structure of radio sources with remarkably flat spectra - PKS 0735+178

Three incoherent synchrotron models are used to account for the very flat radio spectrum of the BL Lac object PKS 0735+178. The first interpretation is that the spectrum results from optically-thin synchrotron emission from relativistic electrons with a particular energy distribution. The second posits a single nonuniform, self-absorbed source generated by a wind flowing from a central object. The third suggests that sources with flat spectra are caused by the presence of multiple (three or more) discrete uniform components, and that the magnetic field and relativistic electron distribution for each source is correlated with the size of the individual components. It is proposed that the last model is the most tenable explanation of the phenomenon, and multi-frequency VLBI observations are suggested for the evaluation of the detailed structure of compact radio sources.

Marscher, A. P.↗
NASA NTRS1979

A broad look at solar physics adapted from the solar physics study of August 1975

The current status of our knowledge of the basic mechanisms involved in fundamental solar phenomena is reviewed. These include mechanisms responsible for heating the corona, the generation of the solar wind, the particle acceleration in flares, and the dissipation of magnetic energy in field reversal regions, known as current sheets. The discussion covers solar flares and high-energy phenomena, solar active regions; solar interior, convection, and activity; the structure and energetics of the quiet solar atmosphere; the structure of the corona; the solar composition; and solar terrestrial interactions. It also covers a program of solar research, including the special observational requirements for spectral and angular resolution, sensitivity, time resolution, and duration of the techniques employed.

Parker, E.↗
DOE OSTI2024

Optimum Operation of Microgrid Systems that Employ PV Solar and Battery Systems

On a global scale, over 1.3 billion lack access to electricity (85% in rural areas), and approximately 2.8 billion people rely on traditional biomass for cooking. The World Health Organization estimates that household air pollution from inefficient stoves causes more premature deaths than malaria, tuberculosis, and HIV/AIDS. Increasing demand for energy has led to dramatic increases in emissions. The need for reliable electricity and limiting emissions drives research on Resilient Hybrid Energy Systems (RHESs), which provide cleaner energy by combining wind, solar, and biomass energy with traditional fossil energy, increasing production efficiency and reliability and reducing generating costs and emissions. Microgrids have been shown as an efficient means of implementing RHESs, with some focused mainly on reducing the environmental impact of electric power generation. The technical challenges of designing, implementing, and applying microgrids involve conducting a cradle-to-grave Life Cycle Analysis (LCA) to evaluate these systems’ environmental and economic performance under diverse operating conditions to evaluate resiliency. A sample RHES was developed and used to demonstrate the implementation in rural applications, where the system can provide reliable electricity for heating, cooling, lighting, and pumping clean water. The model and findings can be utilized by other regions around the globe facing similar challenges.

Nagapurkar, Prashant↗