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At least 271 records · Page 15

Large-Eddy Simulation of Wind-Plant Aerodynamics

In this work, we present results of a large-eddy simulation of the 48 multi-megawatt turbines composing the Lillgrund wind plant. Turbulent inflow wind is created by performing an atmospheric boundary layer precursor simulation, and turbines are modeled using a rotating, variable-speed actuator line representation. The motivation for this work is that few others have done large-eddy simulations of wind plants with a substantial number of turbines, and the methods for carrying out the simulations are varied. We wish to draw upon the strengths of the existing simulations and our growing atmospheric large-eddy simulation capability to create a sound methodology for performing this type of simulation. We used the OpenFOAM CFD toolbox to create our solver. The simulated time-averaged power production of the turbines in the plant agrees well with field observations, except with the sixth turbine and beyond in each wind-aligned. The power produced by each of those turbines is overpredicted by 25-40%. A direct comparison between simulated and field data is difficult because we simulate one wind direction with a speed and turbulence intensity characteristic of Lillgrund, but the field observations were taken over a year of varying conditions. The simulation shows the significant 60-70% decrease in the performance of the turbines behind the front row in this plant that has a spacing of 4.3 rotor diameters in this direction. The overall plant efficiency is well predicted. This work shows the importance of using local grid refinement to simultaneously capture the meter-scale details of the turbine wake and the kilometer-scale turbulent atmospheric structures. Although this work illustrates the power of large-eddy simulation in producing a time-accurate solution, it required about one million processor-hours, showing the significant cost of large-eddy simulation.

17 WIND ENERGY↗

Studying Wind Loading on CSP Collectors to Improve Performance and Reliability

Electricity generation through Concentrating Solar-thermal Power (CSP) adds the advantage of thermal energy storage and heat production. CSP collector costs constitute nearly one-third of total plant costs. Managing wind loading, especially dynamic wind loading caused by the turbulent wind flow, is a significant design challenge. Traditional collector designs rely on wind tunnel experiments and numerical simulations, which do not fully capture dynamic effects. Here, we provide an overview of NREL's activities on wind loading on CSP collectors, aiming to improve their reliability and cost-efficiency. We present insights from field measurements at operational parabolic trough and power-tower CSP plants. Over two years, we measured turbulent wind fields and resulting structural loads in a parabolic trough plant, revealing wind, turbulence, and collector field interactions. Similar measurements are ongoing at the Crescent Dunes heliostat field. These campaigns show how atmospheric turbulence, wind direction, and collector orientation affect dynamic wind loading. Upwind collector structures can generate turbulent structures, causing fluctuating loads at downstream collectors, impacting fatigue lifetime and optical efficiency. Preliminary results indicate that interior collectors experience higher turning moments than those at the edges, suggesting higher drive wear. At Crescent Dunes, we use instrumented heliostats at the field's edge and interior to study the translation of turbulent wind to dynamic structural loads. The campaign is still ongoing, and we will present first findings. Another focus of our work is tying the experimental wind loading findings to optical performance of the collectors, using simulation tools. For example, we derive torsional errors of the parabolic troughs - the angular offset from the sun position along a collector row. This error is impacted by wind-induced mirror deformations. Future work will focus on continuing the measurement efforts and combining them with computational fluid dynamic simulations. By providing detailed field measurements and validated models, our efforts aim to enhance understanding of wind loading on CSP collectors, improving their structural integrity and optical performance.

CSP↗

Wind energy developments in the 20th century

Wind turbine systems of the past are reviewed and wind energy is reexamined as a future source of power. Various phases and objectives of the Wind Energy Program are discussed. Conclusions indicate that wind generated energy must be considered economically competitive with other power production methods.

Vargo, D. J.↗

Impact of Distributed Wind on Bulk Power System Operations in ISO-NE

The work presented in this paper aims to study the impact of a range of penetration levels of distributed wind on the operation of the electric power system at the transmission level. This paper presents a case study on the power system in Independent System Operator New England. It is analyzed using PLEXOS, a commercial power system simulation tool. The results show that increasing the integration of distributed wind reduces total variable electricity generation costs, coal- and gas-fired electricity generation, electricity imports, and CO2 emissions, and increases wind curtailment. The variability and uncertainty of wind power also increases the start-up and shutdown costs and ramping of most conventional power plants.

17 WIND ENERGY↗

Optimizing investments in coupled offshore wind-electrolytic hydrogen storage systems in Denmark

In response to electricity markets with growing levels of wind energy production and varying electricity prices, this research examines incentives for investments in integrated renewable energy power systems. A strategy for using optimization methods for a power system consisting of wind turbines, electrolyzers, and hydrogen fuel cells is explored. This research reveals the investment potential of coupling offshore wind farms with different hydrogen systems. The benefits in terms of a return on investment are demonstrated with data from the Danish electricity markets. This research also investigates the tradeoffs between selling the hydrogen directly to customers or using it as a storage medium to re-generate electricity at a time when it is more valuable. Finally, this research finds that the most beneficial configuration is to produce hydrogen at a time that complements the wind farm and sell the hydrogen directly to end users.

25 ENERGY STORAGE↗

Optimizing the physical design and layout of a resilient wind, solar, and storage hybrid power plant

We report as wind and solar technologies improve and their costs decrease, the share of power produced by these sources will increase. As the market penetration increases, these power sources will need to provide grid services, such as dispatchability, in addition to providing energy. One way to reduce variability, provide higher quality power to the grid, and address local grid stability issues is through colocating wind and solar power plants. In addition to operating reliably during normal operating conditions, in scenarios with high penetrations of renewable generation, it is important that these hybrid plants can withstand production disruptions and continue to supply power despite prolonged resource reduction, extreme weather events, or other disruptions. In this paper, we present a methodology to optimize a wind-solar-battery hybrid power plant down to the component level that is resilient against production disruptions and that can continually produce some minimum required power. We introduce the models and assumptions we used to simulate a hybrid power plant as well as the design variable parameterization and specific methods we used to optimize the plant. We demonstrate the performance of our method by comparing a plant optimized for different objectives, generation outage durations, minimum power requirements, and power purchase agreements. Although the plant design is sensitive to model parameters and various other assumptions, our results demonstrate some of the optimal designs that occur in different scenarios and what one should expect when designing a hybrid wind-solar-storage power plant.

14 SOLAR ENERGY↗

A code-independent generalized actuator line model for wind farm aerodynamics over simple and complex terrain

Actuator line model representations of wind turbines reduce the simulation cost of wind farm aerodynamics relative to blade geometry resolving simulations. However, most implementations are code specific and may not have proper load balancing when run in parallel. Here, a generalized actuator line model (GALM) is developed to overcome this implementation drawback of existing approaches. The GALM can be coupled to any existing microscale solver with minimal or no modifications. The coupling of our GALM model with the open-source microscale code CgWind is used to demonstrate both its ease of use and fidelity. The results obtained from the coupled-model simulations are validated for both isolated turbine in wind tunnel experiments and measurements in offshore wind farm. Finally, an operational wind farm over complex terrain is demonstrated. The simulations show that wake meandering and power production are strongly influenced by terrain impacts. Access information for obtaining the code is provided.

17 WIND ENERGY↗

2016 Wind Technologies Market Report

Wind power capacity in the United States experienced strong growth in 2016. Recent and projected near-term growth is supported by the industry’s primary federal incentive—the production tax credit (PTC)—as well as a myriad of state-level policies. Wind additions have also been driven by improvements in the cost and performance of wind power technologies, yielding low power sales prices for utility, corporate, and other purchasers.

17 WIND ENERGY↗

Efficient Loads Surrogates for Waked Turbines in an Array

Accurately and efficiently predicting wind turbine structural loading is a crucial step in wind farm design. Without considering structural loading, wind farm optimization could negatively impact turbine fatigue and ultimate loads, especially for waked and partially waked turbines, which could result in higher maintenance costs and reduced turbine lifetime. However, predicting turbine loads throughout an array is a costly step, as these quantities require time-accurate results across long time histories, which is often intractable for large array optimization. Therefore, surrogate models that link array spacing to load outputs are often used, but the surrogates are then unique to the inflow conditions and array configurations in the training library. This work develops surrogate models for many wind turbine load outputs based solely on rotor plane velocity measurements, with no required input about array configuration or freestream inflow parameters. Surrogate models were constructed for many turbine quantities of interest (QoI), considering mean, standard deviation, ultimate, and fatigue loads. In general, most QoI statistics were accurately captured, as measured by predicted vs. actual correlation coefficient, confirming the suitability of the approach. Temporal mean values of the QoI required only temporal mean measurements of the rotor plane inflow velocity. However, accurate prediction of temporal standard deviation, ultimate, and fatigue values of QoI also required temporal standard deviations of the rotor plane velocity field. Poor surrogate performance was observed when too many correlated inputs were used, such as multiple velocity components. If the fewest inflow parameters are used to construct the surrogates, the average correlation coefficient value for all output QoI statistics is 0.89. Surrogates for standard deviations and damage equivalent loads (DELs) of turbine QoIs generally had lower accuracy and tower-base and shaft load channels posed the most difficult to capture accurately. The results suggest that these surrogates could be easily paired with analytic wake models, which are frequently used for pre-construction wind farm array optimization, to account for turbine loading in addition to power production. By including the optimal inflow conditions, the surrogate accuracy can improve to an average correlation coefficient value for all output QoI statistics of 0.92. This work has established the ability to build accurate surrogates for mean, standard deviation, ultimate load, and DEL turbine QoI values based on the rotor plane inflow velocity, and identified which inflow conditions lead to greater surrogate accuracy.

17 WIND ENERGY↗

Optimal Wind Turbine Design for H2 Production

The Optimal Wind Turbine Design for Hydrogen Production work seeks to address the H2@Scale program's goal to "advance affordable hydrogen production" by optimizing the wind turbine design specifically for hydrogen (H2) production. The project identifies optimal wind turbine designs made specifically for hydrogen production to advance affordable green hydrogen production. The project also couples wind turbine, wind plant, solar plant, and electrolyzer models to predict hydrogen production from variable, renewable power sources.

electrolyzer↗

Measurement-driven large-eddy simulations of a diurnal cycle during a wake-steering field campaign

Abstract. High-fidelity flow modeling with data assimilation enables accurate representation of the wind farm operating environment under realistic, nonstationary atmospheric conditions. Capturing the temporal evolution of the turbulent atmospheric boundary layer is critical to understanding the behavior of wind turbines under operating conditions with simultaneously varying inflow and control inputs. This paper has three parts: the identification of a case study during a field evaluation of wake steering; the development of a tailored mesoscale-to-microscale coupling strategy that resolved local flow conditions within a large-eddy simulation (LES), using observations that did not completely capture the wind and temperature fields throughout the simulation domain; and the application of this coupling strategy to validate high-fidelity aeroelastic predictions of turbine performance and wake interactions with and without wake steering. The case study spans 4.5 h after midnight local time, during which wake steering was toggled on and off five times, achieving yaw offset angles ranging from 0 to 17°. To resolve nonstationary nighttime conditions that exhibited shear instabilities, the turbulence field was evolved starting from the diurnal cycle of the previous day. These background conditions were then used to drive wind farm simulations with two different models: an LES with actuator disk turbines and a steady-state engineering wake model. Subsequent analysis identified two representative periods during which the up- and downstream turbines were most nearly aligned with the mean wind direction and had observed yaw offsets of 0 and 15°. Both periods corresponded to partial waking on the downstream turbine, which had errors in the LES-predicted power of 4 % and 6 %, with and without wake steering. The LES was also able to capture conditions during which an upstream turbine wake induced a speedup at a downstream turbine and increased power production by up to 13 %.

17 WIND ENERGY↗

Automated Quantification of Wind Turbine Blade Leading Edge Erosion from Field Images

Wind turbine blade leading edge erosion is a major source of power production loss and early detection benefits optimization of repair strategies. Two machine learning (ML) models are developed and evaluated for automated quantification of the areal extent, morphology and nature (deep, shallow) of damage from field images. The supervised ML model employs convolutional neural networks (CNN) and learns features (specific types of damage) present in an annotated set of training images. The unsupervised approach aggregates pixel intensity thresholding with calculation of pixel-by-pixel shadow ratio (PTS) to independently identify features within images. The models are developed and tested using a dataset of 140 field images. The images sample across a range of blade orientation, aspect ratio, lighting and resolution. Each model (CNN v PTS) is applied to quantify the percent area of the visible blade that is damaged and classifies the damage into deep or shallow using only the images as input. Both models successfully identify approximately 65% of total damage area in the independent images, and both perform better at quantifying deep damage. The CNN is more successful at identifying shallow damage and exhibits better performance when applied to the images after they are preprocessed to a common blade orientation.

Aird, Jeanie A.↗

Idealized simulations of wind farm interactions with intermittent turbulence in stable boundary layer conditions

Stable atmospheric boundary layer conditions typically correspond to weak turbulence levels, but intermittent periods of elevated turbulence can occur during otherwise quiescent conditions. The interaction between intermittent turbulence and wind turbines is not well understood because of sparse observations, as well as the difficulty in realistically resolving small-scale turbulence during strongly stable conditions with numerical simulations. In this study, an explicit filtering and reconstruction approach for large-eddy simulation (LES) is used to simulate weakly and strongly stable conditions, with surface cooling rates of −0.2 and −2.0 K h −1 , respectively. This approach can sustain resolved background turbulence at relatively coarse grid spacing and stronger stratification compared to conventional closures, permitting more realistic intermittent stable boundary layer (SBL) turbulence. The idealized LES capability of the Weather Research and Forecasting model is employed with turbine rotors parameterized using generalized actuator disks to examine (1) how the presence of turbine wakes affects SBL evolution and (2) the effect of intermittent turbulence on power production and wake recovery. Wakes increase mixing and deepen the SBL, with a stronger effect under strongly stable conditions, primarily because the SBL is shallower and closer to the top of the wind turbine rotor layer. Intermittent turbulence does not have a significant impact on mean power generation and wake recovery because the relevant intermittent turbulent structures in this study only affect the bottom half of the rotor disk. Power production is, however, more variable during periods of elevated turbulence, demonstrating the impact of SBL intermittency. This study uses an idealized configuration, focusing on LES model performance and physical understanding, with the goal of informing future simulations of the conditions observed during the American Wake Experiment.

Energy - Wind↗

Wind Turbine Modeling for Computational Fluid Dynamics

With the shortage of fossil fuel and the increasing environmental awareness, wind energy is becoming more and more important. As the market for wind energy grows, wind turbines and wind farms are becoming larger. Current utility-scale turbines extend a significant distance into the atmospheric boundary layer. Therefore, the interaction between the atmospheric boundary layer and the turbines and their wakes needs to be better understood. The turbulent wakes of upstream turbines affect the flow field of the turbines behind them, decreasing power production and increasing mechanical loading. With a better understanding of this type of flow, wind farm developers could plan better-performing, less maintenance-intensive wind farms. Simulating this flow using computational fluid dynamics is one important way to gain a better understanding of wind farm flows. In this study, we compare the performance of actuator disc and actuator line models in producing wind turbine wakes and the wake-turbine interaction between multiple turbines. We also examine parameters that affect the performance of these models, such as grid resolution, the use of a tip-loss correction, and the way in which the turbine force is projected onto the flow field.

17 WIND ENERGY↗

Retrofit Winglets for Wind Turbines

The benefits of using winglets on wind turbines has been well documented. However, adding winglets to wind turbine blades leads to significant increases in blade root bending moments, requiring expensive structural reinforcement with cost and weight drawbacks. A unique design philosophy for retrofitting winglets on existing wind turbines is presented. These retrofit winglets offer an increase in power produced without the need for structural reinforcement. Predicted performance and cost benefits are illustrated via a study using the NREL 5MW reference wind turbine. The addition of winglets resulted in a 2.45% increase in Coefficient of Power (Cp) and 1.69% increase in Annual Energy Production (AEP).

17 WIND ENERGY↗