Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “variable energy generation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

A kinetic energy analysis of the meso beta-scale severe storm environment

Analyses are performed of the meso beta-scale (20-200 km wavelengths and several hours to one-day periods) severe storm kinetic energy balance on the fifth day of the AVE SESAME campaign of May 1979. A 24-hr interval covering the antecedent, active and post-convective outbreak activity over Oklahoma are considered. Use is made of the kinetic energy budget equation (KEBE) for a finite volume in an isobaric coordinate system. Rawindsonde data with 75 km resolution were treated. The KEBE model covered changes in kinetic energy due to the cross contour flows, horizontal and vertical components of flux divergence, and volumic mass changes on synoptic and subsynoptic scales. The greatest variability was concentrated above 400 mb height and over the most intense storm activity. Energy was generated at the highest rates in divergence and decreased the most in convection. The meso beta-scale lacked sufficient resolution for analyzing mesoscale activity.

Fuelberg, H. E.↗
NASA NTRS2019

Radiative Heating Rates Computed With Clouds Derived From Satellite‐Based Passive and Active Sensors and their Effects on Generation of Available Potential Energy

Radiative heating rates computed with cloud properties derived from passive and active sensors are investigated. Zonal monthly radiative heating rate anomalies computed using both active and passive sensors show that larger variability in longwave cooling exists near the tropical tropopause and near the top of the boundary layer between ~50°N to ~50°S. Aerosol variability contributes to increases in shortwave heating rate variability. When zonal monthly mean cloud effects on the radiative heating rate computed with both active and passive sensors and those computed with passive sensor only are compared, the latter shows cooling and heating peaks corresponding to cloud top and base height ranges used for separating cloud types. The difference of these two sets of cloud radiative effect on heating rates in the middle to upper troposphere is larger than the radiative heating rate uncertainty estimated based on the difference of two active sensor radiative heating rate profile data products. In addition, radiative heating rate contribution to generation of eddy available potential energy is also investigated. Although radiation contribution to generation of eddy available potential energy averaged over a year and the entire globe is small, radiation increases the eddy available potential energy in the northern hemisphere during summer. Two key elements that longwave radiation contribute to the generation of eddy potential energy are (1) longitudinal temperature gradient in the atmosphere associated with land and ocean surface temperatures contrasts and absorption of longwave radiation emitted by the surface and (2) cooling near the cloud top of stratocumulus clouds.

Kato, Seiji↗
DOE OSTI2026

Development of a 95-Year Solar Dataset for Resource Adequacy Studies

Long-term high-resolution solar data provides enhanced understanding of variability of solar generation and enhances our ability to develop strategies for a resilient and reliable electric grid under high deployment of solar energy. Therefore, it is important to develop long-term synthetic datasets that can provide multiple occurrences of various severe weather scenarios that are expected to test the limits of resource adequacy under scenarios contain various energy generation sources. Examples of such scenarios could be long periods of high temperatures when demand for electricity is high or periods where high winds could lead to a shut-down of transmission lines for long periods of time to ensure fire safety. NREL has developed the first version of such a dataset covering a 95-year period covering 2006-2100 at a 4km hourly resolution. This dataset contains all variables necessary to calculate solar generation. During development of this dataset, we focused on creating unbiased, high-resolution solar irradiance through statistical downscaling methods, using Regional Climate Model (RCM) simulations from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) as input. The National Solar Radiation Database (NSRDB) containing over 25 years of observations was used to calibrate the statistical downscaling models. This presentation will outline the primary steps in developing this dataset, including (1) regridding RCM data to a common grid at 20-km resolution, (2) correcting RCM biases with NSRDB, (3) applying temporal and spatial downscaling methods to generate high-resolution (4-km, hourly) solar and ancillary data. Additionally, we will present an evaluation of the downscaled data against the NSRDB across various zones in the CONUS. Lastly, we will present a user guide for accessing the datasets.

14 SOLAR ENERGY↗
DOE OSTI2025

Toward 100% Renewable Power Grids: A Review

The transition to a 100% renewable power grid remains beset by significant technical challenges. This paper critically examines the obstacles arising from the variability and unpredictability of renewable energy sources (RES), which complicate the real-time balancing of power generation and load demand. In addition to traditional stability concerns (e.g., rotor angle, voltage, and frequency stability), the increasing penetration of inverter-based resources (IBRs) introduces novel challenges, including resonance stability issues and converter-driven dynamics. Moreover, the dynamic behavior and fault response of IBRs diverge markedly from those of conventional synchronous generators, rendering traditional protection schemes increasingly inadequate. This paper reviews state-of-the-art solutions in power balancing, grid flexibility, stability enhancement, and advanced protection strategies, discussing their implications for future grid design. The analysis provides a comprehensive assessment of recent technological advancements, thereby outlining critical research directions essential for achieving a resilient, 100% renewable power grid.

100% renewable power grid↗
NASA NTRS1987

Controller for a High-Power, Brushless dc Motor

Driving and braking torques controllable. Control circuit operates 7-kW, 45-lb-ft (61-N-m), three-phase, brushless dc motor in both motor and generator modes. In motor modes, energy from power source is pulse-width modulated to motor through modified "H-bridge" circuit, in generator mode, energy from motor is pulse-width modulated into bank of load resistors to provide variable braking torques. Circuit provides high-resolution torque control in both directions over wide range of speeds and torques. Tested successfully at bus voltages up to 200 Vdc and currents up to 45 A.

Fleming, David J.↗
NASA NTRS2002

Vibration Reduction of Helicopter Blade Using Variable Dampers: A Feasibility Study

In the report, the investigation of controlling helicopter-blade lead-lag vibration is described. Current practice of adding passive damping may be improved to handle large dynamic range of the blade with several peaks of vibration resonance. To minimize extra-large damping forces that may damage the control system of blade, passive dampers should have relatively small damping coefficients, which in turn limit the effectiveness. By providing variable damping, a much larger damping coefficient to suppress the vibration can be realized. If the damping force reaches the maximum allowed threshold, the damper will be automatically switched into the mode with smaller damping coefficient to maintain near-constant damping force. Furthermore, the proposed control system will also have a fail-safe feature to guarantee the basic performation of a typical passive damper. The proposed control strategy to avoid resonant regions in the frequency domain is to generate variable damping force in combination with the supporting stiffness to manipulate the restoring force and conservative energy of the controlled blade system. Two control algorithms are developed and verified by a prototype variable damper, a digital controller and corresponding algorithms. Primary experiments show good potentials for the proposed variable damper: about 66% and 82% reductions in displacement at 1/3 length and the root of the blade respectively.

Lee, George C.↗
DOE OSTI2023

Projecting Future Energy Production from Operating Wind Farms in North America. Part III: Variability

Abstract Daily expected wind power production from operating wind farms across North America are used to evaluate capacity factors (CF) computed using simulation output from the Weather Research and Forecasting (WRF) Model and to condition statistical models linking atmospheric conditions to electricity production. In Parts I and II of this work, we focus on making projections of annual energy production and the occurrence of electrical production drought. Here, we extend evaluation of the CF projections for sites in the Northeast, Midwest, southern Great Plains (SGP), and southwest U.S. coast (SWC) using statewide wind-generated electricity supply to the grid. We then quantify changes in the time scales of CF variability and the seasonality. Currently, wind-generated electricity is lowest in summer in each region except SWC, which causes a substantial mismatch with electricity demand. While electricity of residential heating may shift demand, research presented here suggests that summertime CF are likely to decline, potentially exacerbating the offset between seasonal peak power production and current load. The reduction in summertime CF is manifest for all regions except the SGP and appears to be linked to a reduction in synoptic-scale variability. Using fulfillment of 50% and 90% of annual energy production to quantify interannual variability, it is shown that wind power production exhibits higher (earlier fulfillment) or lower (later fulfillment) production for periods of over 10–30 years as a result of the action of internal climate modes. Significance Statement Electrical power system reassessment and redesign may be needed to aid efficient increased use of variable renewables in the generation of electricity. Currently wind-generated electricity in many regions of North America exhibits a minimum in summertime and hence is not well synchronized with electricity demand, which tends to be maximized in summer. Future projections indicate evidence of reductions in wind power during summer that would amplify this offset. However, electrification of heating may lead to increased wintertime demand, which would lead to greater synchronization.

Coburn, Jacob↗
DOE OSTI2023

SDOM (Storage Deployment Optimization Model) [SWR-21-73]

SDOM is designed to accurately represent the operation of energy storage across different timescales, including long-duration and seasonal applications, and the spatiotemporal diversity and complementarity among VRE sources. SDOM uses an hourly temporal resolution, a fine spatial resolution for VRE sources, and a 1-year optimization window. SDOM assumes that all builds of VRE are accompanied by sufficient additional transmission capacity to allow full utilization of these additional resources. Nuclear, hydropower, and other renewable generation (e.g., biomass and geothermal energy sources) are fixed based on operational data (time series) for a given year; thus, SDOM minimizes total system cost using conventional generators as balancing units and using VRE and storage technologies to achieve a user-defined carbon-free or renewable energy target. The total system cost includes capital costs, fixed operation-and-maintenance (FO&M) costs, variable operation-and-maintenance (VO&M) costs, and fuel cost for power generation and storage technologies.

Guerra Fernandez, Omar Jose↗
DOE OSTI2021

IDAES Enterprise: Generation Expansion Planning with Enhanced Requirements for Capacity Adequacy Under Renewable Intermittency

Achieving net zero carbon emissions likely requires future power systems to integrate new, flexible energy technologies to accommodate higher levels of capacity from variable renewable energy sources. To determine the optimal deployment of new electricity capacity and to study the likelihood of deployments of new energy technologies, an expansion planning model has been developed as part of the IDAES-Enterprise suite of grid models. The Generation Expansion Planning (GEP) model is a multi-period model in which investment decisions occur yearly, and a Unit Commitment (UC) problem is examined on an hourly timescale. To reduce computational complexity of the GEP model, the UC problem is solved for average “representative days” which leaves out extreme, but relatively common, scenarios in which low renewable generation occurs, leaving the system with inadequacy in capacity. The IDAES-Enterprise GEP model has been modified to include these extreme scenarios while keeping the model reasonably tractable. Specifically, a lazy constraint technique was implemented to check for capacity adequacy on an hourly basis over a large data set of aligned load-wind-solar profiles. As a vast majority of the capacity constraints will not be violated, the technique lowers computational expense by searching for violated capacity constraints over an “iterative manner,” adding those infeasible constraints back into the model. Results on a test case of the Southwest Power Pool shows that the lazy constraint technique significantly reduces retirements and increases installments of natural gas combined cycles and flexible natural gas units. It also reduces some retirements of coal units. These modifications provide a more reasonable estimation of required dispatchable power generation capacity to ensure feasibility during peak net load.

Liu, Peng↗
DOE OSTI2021

Spectral characterization of flash and high flux x-ray radiographic sources with a magnetic Compton spectrometer

In this article, we present a new analysis method applied to revitalize permanent magnet Compton spectrometers used to measure photon energy spectra in the MeV range. The inversion of the measured electron distribution to determine the original photon distribution is achieved via a method of consistent coupled radiation transport and magnetic field mapping of the input photon spectra to the measured electron distribution. The method of linear least squares was used to perform the unfolding of the electron distribution to the initial photon spectra, without any assumptions made regarding the electron distribution. We present an application of this method to data from a nominal 19.4 MeV flash radiographic source (the first axis of the Dual Axis Radiographic Hydro-Test Facility) capable of generating 500 R @ 1 m in ~60 ns and a medical therapy source (a Scanditronix M22, Microtron) capable of variable energies with nominal endpoints of 6, 10, 15, and 20 MeV and an output of ~1000–2000 R/min @ 1 m. The results provide agreement between the modeled and unfolded experimentally measured photon spectra as quantified by statistical tests, from 1.5 to 20 MeV. Experimental results are presented as well as a discussion of the novel MCNP6-based simulations and methods for reconstruction of the spectra.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Generative deep-learning reveals collective variables of Fermionic systems

Complex processes of fermionic systems ranging from protein folding to nuclear fission often follow a low-dimensional reaction path parametrized in terms of a few collective variables. In nuclear theory, variables related to the shape of the nuclear density in a mean-field picture are key to describing the large amplitude collective motion of the neutrons and protons. Exploring the adiabatic energy landscape spanned by these degrees of freedom reveals the possible reaction channels while simulating the dynamics in this reduced space yields their respective probabilities. Unfortunately, this theoretical framework breaks down whenever the systems encounters a quantum phase transition with respect to the collective variables. Here, in this study, we introduce a novel generative deep-learning algorithm designed to build reaction paths that ensure that the many-fermion wave function stays differentiable with respect to the collective variables. This approach is applicable to any fermionic system described by a coherent state. We use the case of potential energy curves in the 16 O nucleus within the Hartree-Fock theory to illustrate its main features.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2016

Biological Potential in Serpentinizing Systems

Generation of the microbial substrate hydrogen during serpentinization, the aqueous alteration of ultramafic rocks, has focused interest on the potential of serpentinizing systems to support biological communities or even the origin of life. However the process also generates considerable alkalinity, a challenge to life, and both pH and hydrogen concentrations vary widely across natural systems as a result of different host rock and fluid composition and differing physical and hydrogeologic conditions. Biological potential is expected to vary in concert. We examined the impact of such variability on the bioenergetics of an example metabolism, methanogenesis, using a cell-scale reactive transport model to compare rates of metabolic energy generation as a function of physicochemical environment. Potential rates vary over more than 5 orders of magnitude, including bioenergetically non-viable conditions, across the range of naturally occurring conditions. In parallel, we assayed rates of hydrogen metabolism in wells associated with the actively serpentinizing Coast Range Ophiolite, which includes conditions more alkaline and considerably less reducing than is typical of serpentinizing systems. Hydrogen metabolism is observed at pH approaching 12 but, consistent with the model predictions, biological methanogenesis is not observed.

the potential of serpentinizing systems to support↗
DOE OSTI2021

Methods for Representing Flexible, Energy-Constrained Technologies in Utility Planning Tools

Capacity expansion models are widely used by power system researchers, planners, and policy analysts to evaluate alternative power system investment scenarios. With the increasing deployment of wind and solar in the US, there has been much focus on improving the representations of variable generation (VG) technologies within capacity expansion models. Models that capture the variable net-load profiles and larger reserve requirements associated with high penetration VG systems represent an improvement to classic capacity expansion models, but fall short of capturing the complexities associated with storage technologies, such as battery energy storage (BES) and concentrating solar power with thermal energy storage (CSP with TES). While difficult to model in a capacity expansion setting, these technologies are potentially competitive sources of flexibility with the intriguing characteristics of being able to absorb VG that would otherwise be curtailed and directly contribute to renewable energy goals, respectively. In this paper we present methods for accurately representing these technologies in a large-scale capacity expansion model with high electrical and geospatial resolution. VG modeling techniques, including novel methods for capturing curtailment due to unit commitment and other hourly dispatch phenomena, are also reviewed. Modeling for a region in the southwestern United States demonstrates the economic relevance of being able to explicitly trade off the costs and capabilities of energy-constrained technologies, especially BES, against other resources in the near-term, in time to make plans for the coming decade

24 POWER TRANSMISSION AND DISTRIBUTION↗
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 OSTI2023

Modulation of xanthophyll cycle impacts biomass productivity in the marine microalga Nannochloropsis

Life on earth depends on photosynthetic primary producers that exploit sunlight to fix CO 2 into biomass. Approximately half of global primary production is associated with microalgae living in aquatic environments. Microalgae also represent a promising source of biomass to complement crop cultivation, and they could contribute to the development of a more sustainable bioeconomy. Photosynthetic organisms evolved multiple mechanisms involved in the regulation of photosynthesis to respond to highly variable environmental conditions. While essential to avoid photodamage, regulation of photosynthesis results in dissipation of absorbed light energy, generating a complex trade-off between protection from stress and light-use efficiency. This work investigates the impact of the xanthophyll cycle, the light-induced reversible conversion of violaxanthin into zeaxanthin, on the protection from excess light and on biomass productivity in the marine microalgae of the genus Nannochloropsis. Zeaxanthin is shown to have an essential role in protection from excess light, contributing to the induction of nonphotochemical quenching and scavenging of reactive oxygen species. On the contrary, the overexpression of zeaxanthin epoxidase enables a faster reconversion of zeaxanthin to violaxanthin that is shown to be advantageous for biomass productivity in dense cultures in photobioreactors. These results demonstrate that zeaxanthin accumulation is critical to respond to strong illumination, but it may lead to unnecessary energy losses in light-limiting conditions and accelerating its reconversion to violaxanthin provides an advantage for biomass productivity in microalgae.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

H ∞ Control for Energy Dispatch in Autonomous Nanogrid With Communication Delays

This paper proposes an optimal controller and estimator for energy dispatch to balance the power supply and demand considering communication delays. The proposed algorithm involves modeling an autonomous nanogrid (ANG) consisting of distributed energy resources, energy storage systems, loads, an $H$ ∞ controller with a reference power modulation technique, and a state estimator. The ANG was developed to express the dynamic supply-demand energy balance of a nanogird system. Reference power modulation was designed to generate the desired ESS power based on the imbalanced energy. Random communication delays were modeled using a stochastic variable satisfying the Bernoulli random binary distribution. The optimal $H$ ∞ controller and estimator were developed using a linear matrix inequality approach to exponentially stabilize the closed-loop system. Simulations were performed using real daily demand forecasts obtained from the Korea Meteorological Administration to demonstrate the effectiveness of the proposed real-time optimization algorithm.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1978

Background and system description of the Mod 1 wind turbine generator

The Mod-1 wind turbine considered is a large utility-class machine, operating in the high wind regime, which has the potential for generation of utility grade power at costs competitive with other alternative energy sources. A Mod-1 wind turbine generator (WTG) description is presented, taking into account the two variable-pitch steel blades of the rotor, the drive train, power generation/control, the Nacelle structure, and the yaw drive. The major surface elements of the WTG are the ground enclosure, the back-up battery system, the step-up transformer, elements of the data system, cabling, area lighting, and tower foundation. The final system weight (rotor, Nacelle, and tower) is expected to be about 650,000 pounds. The WTG will be capable of delivering 1800 kW to the utility grid in a wind-speed above 25 mph.

Ernst, E. H.↗
NASA NTRS2012

A New and General Formulation of the Parametric HFGMC Micromechanical Method for Three-Dimensional Multi-Phase Composites

The recent two-dimensional (2-D) parametric formulation of the high fidelity generalized method of cells (HFGMC) reported by the authors is generalized for the micromechanical analysis of three-dimensional (3-D) multiphase composites with periodic microstructure. Arbitrary hexahedral subcell geometry is developed to discretize a triply periodic repeating unit-cell (RUC). Linear parametric-geometric mapping is employed to transform the arbitrary hexahedral subcell shapes from the physical space to an auxiliary orthogonal shape, where a complete quadratic displacement expansion is performed. Previously in the 2-D case, additional three equations are needed in the form of average moments of equilibrium as a result of the inclusion of the bilinear terms. However, the present 3-D parametric HFGMC formulation eliminates the need for such additional equations. This is achieved by expressing the coefficients of the full quadratic polynomial expansion of the subcell in terms of the side or face average-displacement vectors. The 2-D parametric and orthogonal HFGMC are special cases of the present 3-D formulation. The continuity of displacements and tractions, as well as the equilibrium equations, are imposed in the average (integral) sense as in the original HFGMC formulation. Each of the six sides (faces) of a subcell has an independent average displacement micro-variable vector which forms an energy-conjugate pair with the transformed average-traction vector. This allows generating symmetric stiffness matrices along with internal resisting vectors for the subcells which enhances the computational efficiency. The established new parametric 3-D HFGMC equations are formulated and solution implementations are addressed. Several applications for triply periodic 3-D composites are presented to demonstrate the general capability and varsity of the present parametric HFGMC method for refined micromechanical analysis by generating the spatial distributions of local stress fields. These applications include triply periodic composites with inclusions in the form of a cavity, spherical inclusion, ellipsoidal inclusion, discontinuous aligned short fiber. A 3-D repeating unit-cell for foam material composite is simulated.

Haj-Ali, Rami↗