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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Reduced order modelling for dynamic simulations: LDRD feasibility study final report

This feasibility study (12-FS-007) investigated the current state-of-the-art for the construction of reduced order models (ROMs) from dynamic PDE-based simulations. One novel result of was the demonstration of a time-partitioned ROM for the advection-diffusion equation that achieved high accuracy with a small ROM size. The time-domain of a model PDE was partitioned and a fixed-size ROM was tuned to each subdomain resulting in an effective method for achieving an efficient and accurate ROM for a dynamic problem. This LDRD also investigated the construction ROMs for simulations that utilize overlapping grids. In this case, it was found that weighting the discrete inner product in a manner that approximates the continuous inner product yields a significantly more accurate ROM. This project demonstrated the feasibility of applying reduced order models to complex PDE-based simulation tools and explored the benefits of adaptive ROM techniques. The results of the work led to an Exploratory Research LDRD, funded for FY13, that will focus on the development of composite adaptive reduced order models suitable for use with a number of LLNL applications.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1998

Effect of Configuration Pitching Motion on Twin Tail Buffet Response

The effect of dynamic pitch-up motion of delta wing on twin-tail buffet response is investigated. The computational model consists of a delta wing-twin tail configuration. The computations are carried out on a dynamic multi-block grid structure. This multidisciplinary problem is solved using three sets of equations which consists of the unsteady Navier-Stokes equations, the aeroelastic equations, and the grid displacement equations. The configuration is pitched-up from zero up to 60 deg. angle of attack, and the freestream Mach number and Reynolds number are 0.3 and 1.25 million, respectively. With the twin tail fixed as rigid surfaces and with no-forced pitch-up motion, the problem is solved for the initial flow conditions. Next, the problem is solved for the twin-tail response for uncoupled bending and torsional vibrations due to the unsteady loads on the twin tail and due to the forced pitch-up motion. The dynamic pitch-up problem is also solved for the flow response with the twin tail kept rigid. The configuration is investigated for inboard position of the twin tail which corresponds to a separation distance between the twin tail of 33% wing chord. The computed results are compared with the available experimental data.

Sheta, Essam 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↗
NASA NTRS1987

Initial turbulence effect on jet evolution with and without tonal excitation

The effect of initial turbulence level on the development of a jet and on the susceptability of the jet to discrete tone excitation was experimentally investigated. Turbulence intensity was varied, over the range 0.15 to 5 percent, by using screens and grids placed upstream of an 8.8 cm diameter nozzle. Top-hat mean velocity profiles with approximately identical initial boundary layer states were ensured in all cases; the turbulence spectra were broadband. It was found, contrary to earlier reports, that the natural jet decay remained essentially unchanged for varying initial turbulence. For a fixed amplitude of the tonal excitation, increasing the initial turbulence damped out the growth of the instability wave; as a result, the excitability, assessed from the mean velocity decay on the axis, was found to diminish. However, the degree of damping in the amplification of the instability wave was only slight compared to the large increase in the initial turbulence. The jet with 5 percent turbulence could be measurably altered by excitation with a velocity perturbation amplitude as little as 0.25 percent of the jet velocity. The amplitude effect data indicate an upper bound of the extent to which a jet could be excited, and thus its plume shortened, by the plane wave, single frequency excitation. An additional data set with no grid or trip, yielding a nominally laminar boundary layer, re-emphasizes the profound effect of initial boundary layer state on jet evolution as well as on its excitability. This jet decayed the fastest naturally, and consequently, it was the least excitable in spite of its turbulence being the least.

Raman, G.↗
NASA NTRS1987

Initial turbulence effect on jet evolution with and without tonal excitation

The effect of initial turbulence level on the development of a jet and on the susceptibility of the jet to discrete tone excitation was experimentally investigated. Turbulence intensity was varied, over the range 0.15 to 5 percent, by using screens and grids placed upstream of an 8.8 cm diameter nozzle. Top-hat mean velocity profiles with approximately identical initial boundary layer states were ensured in all cases; the turbulence spectra were broadband. It was found, contrary to earlier reports, that the natural jet decay remained essentially unchanged for varying initial turbulence. For a fixed amplitude of the tonal excitation, increasing the initial turbulence damped out the growth of the instability wave; as a result, the excitability, assessed from the mean velocity decay on the axis, was found to diminish. However, the degree of damping in the amplification of the instability wave was only slight compared to the large increase in the initial turbulence. The jet with 5 percent turbulence could be measurably altered by excitation with a velocity perturbation amplitude as little as 0.25 percent of the jet velocity. The amplitude effect data indicate an upper bound of the extent to which a jet could be excited, and thus its plume shortened, by the plane wave, single frequency excitation. An additional data set with no grid or trip, yielding a nominally laminar boundary layer, re-emphasizes the profound effect of initial boundary layer state on jet evolution as well as on its excitability. This jet decayed the fastest naturally, and consequently, it was the least excitable in spite of its turbulence being the least.

Raman, G.↗
DOE OSTI2021

Probabilistic Resilience of DER Systems - A Simulation Assisted Optimization Approach

Energy systems resilience is becoming increasingly important as the frequency of major grid outages increases. In this work, we present a methodology to optimize a behind-tlie-meter distributed energy resource system to sustain a site's critical loads during a pre-defined outage period. With the fixed system design, we then propose an outage simulation approach to estimate the resilience potential of the DER system to sustain loads beyond the fixed outage period - a yearlong resilience performance analysis. We apply statistical analysis to assess the system's resilience performance over a broader parametric problem space on an hourly, monthly, and yearly basis. We demonstrate the impact of the pre-defined outage period on the resilience performance through a case study. Results show that the probability of surviving a random outage of a given duration changes from 20% to 95% when the outage is modeled for a weekday instead of a weekend for the given load-profile.

28 EE - Advanced Manufacturing Office (EE-5A)↗
DOE OSTI2020

System Studies for Global Nuclear Assurance and Security (GNAS): 3S Risk Analysis for Portable Nuclear Reactors (Volume II) -- Conclusions and Implications

Growing interest in compact, easily transportable sources of baseload electricity has manifested in the proposal and early deployment of portable nuclear reactors (PNRs). PNRs are sought because they are scalable, efficient, and cost-effective for meeting energy demands in unique, remote, or contested areas. For example, Russia's KLT-40S Akademik Lomonosov is a floating nuclear power plant (FNPP) that successfully reached the Arctic coastal city of Pevek. It began providing power to the local grid in December 2019. While providing such key advantages as having a highly flexible power generation mechanism, FNPPs appear to directly challenge international norms and conventions for nuclear safety, safeguards, and security. FNPPs are neither a purely fixed nuclear fuel cycle activity nor a purely transportation-based nuclear fuel cycle activity. In response, Sandia's Mitigating International Nuclear Enogy Risks (MINER) research perspective frames this discussion in terms of risk complexity and the interdependencies between safety, safeguards, and security in FNPPs, and PNRs more generally. This systems study is a technically rigorous analysis of the safety, safeguards, and security risks of FNPP technologies. This research's aims are three-fold. The first aim is to provide analytical evidence to support safety, safeguards, and security claims related to PNRs and FNPPs (Study Report Volume I). Second, this study aims to introduce a systems- theoretic approach for exploring interdependencies between the technical evaluations (Study Report Volume II). The third aim is to show Sandia's ability for prompt, rigorous, and technical analysis to support emerging complex MINER mission objectives.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Probabilistic Resilience of DER Systems - A Simulation Assisted Optimization Approach

Energy systems resilience is becoming increasingly important as the frequency of major grid outages increases. In this work, we present a methodology to optimize a behind-the-meter distributed energy resource system to sustain a site's critical loads during a pre-defined outage period. With the fixed system design, we then propose an outage simulation approach to estimate the resilience potential of the DER system to sustain loads beyond the fixed outage period - a yearlong resilience performance analysis. We apply statistical analysis to assess the system's resilience performance over a broader parametric problem space on an hourly, monthly, and yearly basis. We demonstrate the impact of the pre-defined outage period on the resilience performance through a case study. Results show that the probability of surviving a random outage of a given duration changes from 20% to 95% when the outage is modeled for a weekday instead of a weekend for the given load-profile.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Power System Feature-Based Event Classification by Means of Multiple PMU Data

Abstract—Phasor Measurement Units (PMUs) provide time synchronized measurements across the power grid, enabling data driven event detection and classification for enhanced system monitoring and situational awareness. However, variations in event duration, spatial extent, and severity, along with coincident events, pose challenges for conventional classification models that require fixed-size inputs. This paper presents a feature-based framework that aggregates diverse attributes from all available PMUs for each event into a fixed-length vector, facilitating the application of standard machine learning classifiers, including Random Forest, XGBoost, and Multilayer Perceptron. A probabilistic post-processing scheme is further introduced to enable multi-label classification in the presence of overlapping events. Experiments using real-world PMU data demonstrate that the Random Forest model achieves 95% accuracy, while the proposed post-processing method yields an additional 3% improvement.

Nematirad, Reza↗
DOE OSTI2022

Optimal Energy Storage System and Smart Switch Placement in Dynamic Microgrids With Applications to Marine Energy Integration

Here this paper studies a dynamic microgrid (DMG) planning problem that places energy storage systems (ESSs) and smart switches (SSWs) optimally in the system. We apply the proposed methodology to applications concerning marine renewable energy (MRE). MRE is an emerging clean energy resource with enormous capacity but volatile and intermittent energy output profiles. Innovative grid-integration technologies designed to enhance the reliability of an MRE-integrated system are needed. However, there are still limited studies in this regard. Existing works have shown the promising prospect of using a dynamic microgrid (DMG) operational concept to accommodate renewable resources in distribution systems, but they usually assume fixed ESS and SSW installations. To further improve the operational flexibility of DMGs, we propose a DMG planning methodology that optimally places ESSs and SSWs so that a DMG with MRE is warranted with proper resource adequacy and topological flexibility in both the contingency and normal operations. We use realistic case studies based on a real-world distribution network and the U.S. Department of Energy's MRE dataset to verify the value and validity of the proposed work.

25 ENERGY STORAGE↗
DOE OSTI2021

Lagrangian–Eulerian multidensity topology optimization with the material point method

Abstract In this paper, a hybrid Lagrangian–Eulerian topology optimization (LETO) method is proposed to solve the elastic force equilibrium with the Material Point Method (MPM). LETO transfers density information from freely movable Lagrangian carrier particles to a fixed set of Eulerian quadrature points. This transfer is based on a smooth radial kernel involved in the compliance objective to avoid the artificial checkerboard pattern. The quadrature points act as MPM particles embedded in a lower‐resolution grid and enable a subcell multidensity resolution of intricate structures with a reduced computational cost. A quadrature‐level connectivity graph‐based method is adopted to avoid the artificial checkerboard issues commonly existing in multiresolution topology optimization methods. Numerical experiments are provided to demonstrate the efficacy of the proposed approach.

Li, Yue↗
NASA NTRS2002

Aeroelastic Calculations of Quiet High- Speed Fan Performed

An advanced high-speed fan was recently designed under a cooperative effort between the NASA Glenn Research Center and Honeywell Engines & Systems. The principal design goals were to improve performance and to reduce fan noise at takeoff. Scale models of the Quiet High-Speed Fan were tested for operability, performance, and acoustics. During testing, the fan showed significantly improved noise characteristics, but a self-excited aeroelastic vibration known as flutter was encountered in the operating range. Flutter calculations were carried out for the Quiet High-Speed Fan using a three-dimensional, unsteady aerodynamic, Reynolds-averaged Navier-Stokes turbomachinery code named "TURBO." The TURBO code can accurately model the viscous flow effects that can play an important role in various aeroelastic problems such as flutter with flow separation, flutter at high loading conditions near the stall line (stall flutter), and flutter in the presence of shock and boundary-layer interaction. Initially, calculations were performed with no blade vibrations. These calculations were at a constant rotational speed and a varying mass flow rate. The mass flow rate was varied by changing the backpressure at the exit boundary of the computational domain. These initial steady calculations were followed by aeroelastic calculations in which the blades were prescribed to vibrate harmonically in a natural mode, at a natural frequency, and with a fixed interblade phase angle between adjacent blades. The AE-prep preprocessor was used to interpolate the in-vacuum mode shapes from the structural dynamics mesh onto the computational fluid dynamics mesh and to smoothly propagate the grid deformations from the blade surface to the interior points of the grid. The aeroelastic calculations provided the unsteady aerodynamic forces on the blade surface due to blade vibrations. These forces were vector multiplied with the structural dynamic mode shape to calculate the work done on the blade during one vibration period, then this result was converted to an aerodynamic damping. Flutter occurs when the aerodynamic damping becomes negative, if structural damping is ignored. The results of these aeroelastic calculations are summarized in this plot of aerodynamic damping versus mass flow rate at a constant rotational speed. As the backpressure is increased, the mass flow rate through the fan decreases and the fan operating point moves towards the stall line. The aeroelastic calculations showed that the aerodynamic damping decreases as the stall line is approached, as observed during testing. In addition, the aeroelastic calculations with the TURBO code correctly predicted the aeroelastic parameters: the most unstable vibration mode and interblade phase angle, as observed during testing. The Quiet High-Speed Fan demonstrated significant noise reductions during testing, but flutter imposed limits on its operating range. The accurate calculation of the aeroelastic characteristics using the TURBO code is a significant step toward eliminating flutter from the operating range and toward realizing the benefits of reduced fan noise. The aeroelastic calculations described here were performed under a grant by University of Toledo researchers in collaboration with Glenn's researchers.

Bakhle, Milind A.↗
NASA NTRS2007

Comparison of Water Vapor Measurements by Airborne Sun Photometer and Near-Coincident in Situ and Satellite Sensors during INTEX/ITCT 2004

We have retrieved columnar water vapor (CWV) from measurements acquired by the 14-channel NASA Ames Airborne Tracking Sun photometer (AATS-14) during 19 Jetstream 31 (J31) flights over the Gulf of Maine in summer 2004 in support of the Intercontinental Chemical Transport Experiment (INTEX)/Intercontinental Transport and Chemical Transformation (ITCT) experiments. In this paper we compare AATS-14 water vapor retrievals during aircraft vertical profiles with measurements by an onboard Vaisala HMP243 humidity sensor and by ship radiosondes and with water vapor profiles retrieved from AIRS measurements during eight Aqua overpasses. We also compare AATS CWV and MODIS infrared CWV retrievals during five Aqua and five Terra overpasses. For 35 J31 vertical profiles, mean (bias) and RMS AATS-minus-Vaisala layer-integrated water vapor (LWV) differences are -7.1 percent and 8.8 percent, respectively. For 22 aircraft profiles within 1 hour and 130 km of radiosonde soundings, AATS-minus-sonde bias and RMS LWV differences are -5.4 percent and 10.7 percent, respectively, and corresponding J31 Vaisala-minus-sonde differences are 2.3 percent and 8.4 percent, respectively. AIRS LWV retrievals within 80 lan of J31 profiles yield lower bias and RMS differences compared to AATS or Vaisala retrievals than do AIRS retrievals within 150 km of the J31. In particular, for AIRS-minus-AATS LWV differences, the bias decreases from 8.8 percent to 5.8 percent, and the RMS difference decreases from 2 1.5 percent to 16.4 percent. Comparison of vertically resolved AIRS water vapor retrievals (LWVA) to AATS values in fixed pressure layers yields biases of -2 percent to +6 percent and RMS differences of -20 percent below 700 hPa. Variability and magnitude of these differences increase significantly above 700 hPa. MODIS IR retrievals of CWV in 205 grid cells (5 x 5 km at nadir) are biased wet by 10.4 percent compared to AATS over-ocean near-surface retrievals. The MODIS-Aqua subset (79 grid cells) exhibits a wet bias of 5.1 percent, and the MODIS-Terra subset (126 grid cells) yields a wet bias of 13.2 percent.

Livingston, J.↗
NASA NTRS1985

Mean Winds and Tides over Urbana, Illinois During November 16-22, 1981

The Urbana Meteor Radar uses a high power pulse transmitter to achieve high echo rates, and an interferometer to spatially locate the individual echoes. The irregularly spaced observations of range, radial velocity, and direction cosines are reduced to a rectangular grid, evenly spaced in time and height, of estimates of the zonal and meridional wind. This is accomplished using the method of GROVES whereby a constant horizontal wind is fitted, using least squares, to all echoes occurring within a fixed time/height interval. This interpolation region is then stepped in time and height. the size of the interpolation region is 2 hours by 5 km, the time step is approximately 11 minutes, and the height step is 2 km. The filtering of high temporal and spatial frequencies is somewhat reduced by weighting the echoes according to their distance from the center of the interpolation box.

Tetenbaum, D.↗
DOE OSTI2023

Co-Simulation Model for Optimal Wind-Hydro Coordination Using Wind Farm Control Dynamics

The growing share of Variable Renewable Energy sources (VRES) in power systems presents challenges for regula- tors, grid operators and energy producers. The VRES’ operation has limited flexibility in their operations, as they are highly dependent on ambient environments. To address these challenges, decision-makers must consider multiple objectives, among these are revenue, power system services and mechanical load on wind turbines. Coordinated operation of power plants and different wind farm control strategies are examples of measures that can benefit these objectives. This study proposes a Multi-Objective Linear Programming (MOLP) model to simulate the optimum operation of wind and hydropower plants that share limited transmission capacity. Further, wind farm control dynamics are included to obtain realistic output power and accumulated damage. From this, a case study based on a relevant location in Norway is presented to analyze the improved effect of wind- hydro coordination and wind farm control in achieving the objectives of accumulated wind turbine damage and total revenue of the hybrid power system. In addition, the study considers the potential advantages of adding a variable-speed pump to the hydropower plant. The results demonstrate that by considering multiple objectives in the optimization, one may achieve better overall performance of the objectives. By utilizing the flexibility of hydro storage, the decision maker may adjust to obtain the most desired outcome. Moreover, the added flexibility of utilizing a pump for hydro storage shows great improvements for the combined revenue of the power plants and reduced curtailment of the wind farm. However, less impact is observed from using a variable speed pump compared to a fixed speed pump.

13 HYDRO ENERGY↗
DOE OSTI2023

A National Infrastructure for Artificial Intelligence on the Grid (NI4AI) (Final Scientific/Technical Report)

Electric utilities have traditionally taken a very pragmatic yet myopic approach with grid sensors and the resulting collected data. Sensors are purchased and deployed to solve a specific, known problem that has risen to sufficient awareness as to justify the effort of deploying sensors and the needed capital investment. This sensor data flows into proprietary software packages with limited functionality intended only to address the initial problem. This approach aligns with the financial incentives of the utility to deploy capital into fixed hardware assets for which the corporations earn a rate of return. This mentality stands in stark contrast to the big data revolution that started nearly 25 years ago with the rise of Google. In this worldview, data is a fundamental business asset; successful organizations collect, store, explore, merge, and exploit as much data as possible to not only solve problems well understood today but also to tackle new problems that will inevitably rise tomorrow. The ARPA-E Open Innovation 2018 project entitled A National Infrastructure for Artificial Intelligence on the Grid or NI4AI for short was designed to demonstrate this alternative paradigm for using data. To do this, the project was composed of three key thrust areas. The first major component deployed a variety of high-frequency grid sensors and captured terabytes of both wide-scale and localized grid measurements, generating high-value datasets for grid research and algorithm development. The second aspect made available PingThings’ PredictiveGridTM, a horizontally scalable, cloud-based data management and AI platform built for time series data to explore and exploit the collected data. Finally, the project fostered a diverse and open research community composed of experts from numerous fields through focused educational content, code sharing, and data science competitions. Shifting away from “single use” sensors and closed data silos within electric utilities is a major benefit to the public at large. This legacy approach to data is incredibly (1) capital intensive (new sensors must be deployed for each new problem and problems tend to arise continuously) and (2) painfully slow (new problems must be identified first and then new sensors must be deployed to collect data to begin to address the issue). The transition to a carbon neutral grid requires a massive transformation of the existing grid infrastructure and will continue to challenge the legacy grid in unforeseen ways. The only way to make the energy transition cost effective is for utilities to abandon this dated data paradigm and adopt more contemporary approaches. NI4AI has shown that it is technically possible and economically feasible to ingest, explore, and exploit grid data collected from even very high frequency sensing, such as continuous point on wave sensors collecting measurements 10,000 times a second. In fact, the PredictiveGrid platform used is commercially available and deployed at several utilities in the United States. Project accomplishments were numerous and included (1) making available a state of the art time series platform to the community, (2) collecting over 520 streams of time series data from grid sensors totaling over 1 trillion grid measurements, and (3) developing and nurturing a community within the industry focused on the use of data to create value for utilities and, ultimately, end consumers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Adaptive Hierarchical Voltage Control of a DFIG-Based Wind Power Plant for a Grid Fault

This paper proposes an adaptive hierarchical voltage control scheme of a doubly-fed induction generator (DFIG)-based wind power plant (WPP) that can secure more reserve of reactive power (Q) in the WPP against a grid fault. To achieve this, each DFIG controller employs an adaptive reactive power to voltage (Q-V) characteristic. The proposed adaptive Q-V characteristic is temporally modified depending on the available Q capability of a DFIG; it is dependent on the distance from a DFIG to the point of common coupling (PCC). The proposed characteristic secures more Q reserve in the WPP than the fixed one. Furthermore, it allows DFIGs to promptly inject up to the Q limit, thereby improving the PCC voltage support. To avert an overvoltage after the fault clearance, washout filters are implemented in the WPP and DFIG controllers; they can prevent a surplus Q injection after the fault clearance by eliminating the accumulated values in the proportional-integral controllers of both controllers during the fault. Test results demonstrate that the scheme can improve the voltage support capability during the fault and suppress transient overvoltage after the fault clearance under scenarios of various system and fault conditions; therefore, it helps ensure grid resilience by supporting the voltage stability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Impacts of Providing Inertial Response on Dynamic Loads of Wind Turbine Drivetrains

There has been growing demand from the power industry for wind power plants to support power system operations. One such requirement is for wind turbines to provide ancillary services in the form of inertial response. When the grid frequency drops, it is essential for wind turbine generators (WTGs) to inject kinetic energy stored in their inertia into the grid to help arrest the frequency decline. However, the impacts of inertial response on the structural loads of the wind turbine have not been given much attention. To bridge this gap, this paper utilizes a holistic model for both fixed-speed and variable-speed WTGs by integrating the aeroelastic wind turbine model in FAST, developed by the National Renewable Energy Laboratory, with the electromechanical drivetrain model in SimDriveline and SimPowerSystems.

17 WIND ENERGY↗