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Preview: Wind Energy

Wind Energy

Wiley Online Library : Wind Energy

Published: 2018-03-01T00:00:00-05:00


Validation of a hybrid modeling approach to floating wind turbine basin testing


Hybrid modeling combining physical tests and numerical simulations in real time opens new opportunities in floating wind turbine research. Wave basin testing is an important validation step for floating support structure design, but current methods are limited by scaling problems in the aerodynamic loadings. Applying wind turbine loads with an actuation system controlled by a simulation that responds to the basin test offers a way to avoid scaling problems and reduce cost barriers for floating wind turbine design validation in realistic coupled conditions. In this work, a cable-based hybrid coupling approach is developed and implemented for 1:50-scale wave basin tests with the DeepCwind semisubmersible floating wind turbine. Tests are run with thrust loads provided by a numerical wind turbine model. Matching tests are run with physical wind loads using an above-basin wind maker. When the numerical submodel is set to match the aerodynamic performance of the physical scaled wind turbine, the results show good agreement with purely physical wind-wave tests, validating the hybrid model approach. Further hybrid model tests with simulated true-to-scale dynamic thrust loads and wind turbulence show noticeable differences and demonstrate the value of a hybrid model approach for improving the true-to-scale realism of floating wind turbine basin tests.

A wind field downscaling strategy based on domain segmentation and transfer functions


This paper presents a novel methodology for mesoscale-to-microscale downscaling of near-surface wind fields. The model chain consists on the Weather Research and Forecast mesoscale model and the Alya-CFDWind microscale model (assuming neutral stability). The downscaling methodology combines precomputed microscale simulations with a mesoscale forecast using a domain segmentation technique and transfer functions. As a result, the downscaled wind field preserves the mesoscale pattern but, at the same time, incorporates local mesoscale subgrid terrain effects, particularly at valleys and channelling zones. The methodology has been validated over a 9-month period on a very complex terrain site instrumented with a dense observational network of meteorological masts. With respect to mesoscale results, the global skills of the downscaled wind at masts improve for wind direction and remain similar for wind velocity. However, a substantial improvement occurs under stable and neutral conditions and for high wind velocity regimes.

Experimental identification of modal parameters of an industrial 2-MW wind turbine


This contribution presents modal testing of a 2-MW wind turbine on a 100-m tubular tower with a 93-m rotor developed by W2E Wind to Energy GmbH. This research is part of the DYNAWIND project of the University of Rostock and W2E. Beside classical modal analysis schemes, this contribution mainly focusses on the application of operational modal analysis techniques to a wind turbine. Specific problems are addressed, and hints for modal testing on wind turbines are given. Furthermore, an effective measurement setup is proposed for identification of the modal parameters of a wind turbine. The measurement campaign is divided in two parts. First, a measurement campaign using 8 sensor positions on a rotor blade was done while the rotor is lying on ground. Second, a detailed measurement campaign was done on the entire wind turbine with the rotor locked in Y position using 61 sensor positions on the tower, the mainframe, the gearbox, the generator, and the low-voltage unit. While the rotor blade was tested by classical and operational modal analysis techniques, the entire wind turbine was tested by operational modal analysis techniques only. The mode shapes and eigenfrequencies of the wind turbine identified within the measurement campaigns are within the expected range of the design values of the wind turbine. But in contrast, the damping ratios differ strongly from those given in guidelines and literature. Furthermore, a strong influence of aerodynamic damping compared to structural damping is observed for the first tower mode even for a parked wind turbine.

A generalized framework for reduced-order modeling of a wind turbine wake


A reduced-order model for a wind turbine wake is sought from large eddy simulation data. Fluctuating velocity fields are combined in the correlation tensor to form the kernel of the proper orthogonal decomposition (POD). Proper orthogonal decomposition modes resulting from the decomposition represent the spatially coherent turbulence structures in the wind turbine wake; eigenvalues delineate the relative amount of turbulent kinetic energy associated with each mode. Back-projecting the POD modes onto the velocity snapshots produces dynamic coefficients that express the amplitude of each mode in time. A reduced-order model of the wind turbine wake (wakeROM) is defined through a series of polynomial parameters that quantify mode interaction and the evolution of each POD mode coefficients. The resulting system of ordinary differential equations models the wind turbine wake composed only of the large-scale turbulent dynamics identified by the POD. Tikhonov regularization is used to recalibrate the dynamical system by adding additional constraints to the minimization seeking polynomial parameters, reducing error in the modeled mode coefficients. The wakeROM is periodically reinitialized with new initial conditions found by relating the incoming turbulent velocity to the POD mode coefficients through a series of open-loop transfer functions. The wakeROM reproduces mode coefficients to within 25.2%, quantified through the normalized root-mean-square error.  A high-level view of the modeling approach is provided as a platform to discuss promising research directions, alternate processes that could benefit stability and efficiency, and desired extensions of the wakeROM.

A market-oriented wind power dispatch strategy using adaptive price thresholds and battery energy storage


In this paper, an adaptive dispatch strategy is presented to maximize the revenue for grid-tied wind power plant coupled with a battery energy storage system (BESS). The proposed idea is mainly based on time-varying market-price thresholds, which are varied according to the proposed algorithm in an adaptive manner. The variable nature of wind power and market price signals leads to the idea of storing energy at low price periods and consequently selling it at high prices. In fact, the wind farm operators can take advantage of the price variability to earn additional income and to maximize the operational profit based on the choice of best price thresholds at each instant of time. This research study proposes an efficient strategy for intermittent power dispatch along with the optimal operation of a BESS in the presence of physical limits and constraints. The strategy is tested and validated with different BESSs, and the percentage improvement of income is calculated. The simulation results, based on actual wind farm and market-price data, depict the proficiency of the proposed methodology over standard linear programming methods.

Machine learning methods for short-term bid forecasting in the renewable energy market: A case study in Italy


In liberalized markets, there usually exists a day-ahead session where energy is sold and acquired for the following production day. Owing to the high uncertainty of its production, renewable energy (wind in particular) can significantly influence the network imbalance of the following day. In this work, we consider the problem of predicting the sum of the bid volumes for wind energy of all the producers inside the day-ahead energy market. This is a valuable tool to be used by an energy provider in order to determine the imbalance of a market zone and, thus, properly size its bids. In particular, we focus on the estimation of the possible relationship between the meteorological forecasts and the wind power offered on the market by the companies for a market zone. We propose a machine learning model which is used to compute a 1-day-ahead forecast. The input-output mapping is obtained by support vector regression. The input feature vector is defined by a suitable feature extraction technique since the meteorological forecasts are given on a lattice of thousands of geographical points. The computational experiments are performed considering the Italian market as a case study (years 2012-2016). The results show that the proposed feature extraction technique, selecting only some geographical zones, manages to reduce the error attained using all the features. Moreover, classical statistical methods are shown to be outperformed by machine learning models. The analysis reveals also some weaknesses of the model, which may be due to other nonmeteorological factors at play.

A new class of actuator surface models for wind turbines


Actuator line model has been widely used in wind turbine simulations. However, the standard actuator line model does not include a model for the turbine nacelle which can significantly impact turbine wake characteristics. Another disadvantage of the standard actuator line model is that more geometrical features of turbine blades cannot be resolved on a finer mesh. To alleviate these disadvantages of the standard model, we develop a new class of actuator surface models for turbine blades and nacelle to take into account more geometrical details of turbine blades and include the effect of turbine nacelle. The actuator surface model for nacelle is evaluated by simulating the flow over periodically placed nacelles. Both the actuator surface simulation and the wall-resolved large-eddy simulation are conducted. The comparison shows that the actuator surface model is able to give acceptable results especially at far wake locations on a very coarse mesh. It is noted that although this model is used for the turbine nacelle in this work, it is also applicable to other bluff bodies. The capability of the actuator surface model in predicting turbine wakes is assessed by simulating the flow over the MEXICO (Model experiments in Controlled Conditions) turbine and the hydrokinetic turbine of Kang, Yang, and Sotiropoulos (Journal of Fluid Mechanics 744 (2014): 376-403). Comparisons of the computed results with measurements show that the proposed actuator surface model is able to predict the tip vortices, turbulence statistics, and meandering of turbine wake with good accuracy.

Overall design optimization of dedicated outboard airfoils for horizontal axis wind turbine blades


Designing the primary airfoils for the outboard part of wind turbine blades is a complicated problem of balancing structural, aerodynamic, and acoustic requirements. This paper presents an optimization method for the overall performance of outboard wind turbine airfoils. Based on the complex flow characteristics of the rotor blades and the varying requirements along the span of a blade, the design principles of outboard airfoils were investigated. The requirements for improving the structural performance and reducing the aerodynamic noise were combined with the following aerodynamic design considerations: high efficiency, low extreme loads, stability, and a wide operating region. Thus, this paper proposes a new mathematical model for overall airfoil optimization using the airfoil performance evaluation indicators. Then, an integrated optimization design platform is established for outboard airfoils. Through 2 design cases, new airfoils with desirable aerodynamic characteristics and improved overall performance were obtained. Comparisons between the new airfoils and reference airfoils based on numerical predictions indicate that the proposed method with the newly established mathematical model can effectively balance the complex requirements of the airfoil and improve its overall performance. More notably, the design cases also indicate that the established optimization design method can be used to address special designs of outboard airfoils for different blade requirements.

Wind turbine sensor array for monitoring avian and bat collisions


Assessment of avian and bat collisions with wind turbines is necessary to ensure that the benefits of renewable wind power generation are not outweighed by mortality of protected species. An onboard, integrated multisensor system capable of providing detection of turbine collision events, including taxonomic information, was developed. The conceptual design of a multisensor system including a vibration sensing node, an optics node, and an bioacoustic node with an event-driven trigger architecture was field-tested on utility-scale wind turbines. A pixel density computational model was built to estimate the spatial coverage and target resolution to the optimized configuration for camera placement. Field test results of the vibration node showed that nearly half of the recorded impact events were successfully identified by visual inspection and running short-time Fourier transform on recorded vibration signals. The remaining undetected impact events were masked under background noise due to low impact energy and high background noise of the operating turbine, which result in subsequent low signal-to-noise ratio. Our results demonstrate the feasibility of triggering the system through single impact event sensed by vibration sensors.

Dynamic behavior of wind turbines influenced by aerodynamic damping and earthquake intensity


In the present paper the effects of aerodynamic damping and earthquake loads on the dynamic response of flexible-based wind turbines are studied. A numerical analysis framework (NAF) is developed and applied. NAF is based on a user-compiled module that is developed for the purposes of the present paper and is fully coupled with an open source tool. The accuracy of the developed NAF is validated through comparisons with predictions that are calculated with the use of different numerical analysis methods and tools. The results indicate that the presence of the aerodynamic loads due to the reduction of the maximum displacement of the tower attributed to the dissipation of earthquake excitation energy in fore-aft direction. Emergency shutdown triggered by strong earthquakes results to a rapid change of aerodynamic damping, resulting to short-term instability of the wind turbine. After shutdown of the wind turbine, enhanced dynamic response is observed. For the case where the wind turbine is parked, the maxima displacement and acceleration of tower-top increase linearly with the peak ground acceleration. With the use of the least-square method a dimensionless slope of tower-top displacements is presented representing the seismic response coefficient of tower that can be used to estimate the tower-top acceleration demand. Moreover, on the basis of the seismic response coefficient, an improved model for the evaluation of load design demand is proposed. This model can provide accurate predictions.

Offshore wind speed estimates from a high-resolution rapidly updating numerical weather prediction model forecast dataset


In association with the Department of Energy–funded Position of Offshore Wind Energy Resources (POWER) project, we present results from compositing a 3-year dataset of 80-m (above ground level) wind forecasts from the 3-km High-Resolution Rapid Refresh (HRRR) model over offshore regions for the contiguous United States. The HRRR numerical weather prediction system runs once an hour and features hourly data assimilation, providing a key advantage over previous model-based offshore wind datasets. On the basis of 1-hour forecasts from the HRRR model, we highlight the different climatological regimes of the nearshore environment, characterizing the mean 80-m wind speed as well as the frequency of exceeding 4, 12, and 25 m s−1 for east and west coast, Gulf of Mexico, and Great Lake locations. Preliminary verification against buoy measurements demonstrates good agreement with observations. This dataset can inform the placement of targeted measurement systems in support of improving resource assessments and wind forecasts to advance offshore wind energy goals both in New England and other coastal regions of the United States.

Aeroelastic analysis of a wind turbine blade using the harmonic balance method


An aeroelastic model for wind turbine blades derived from the unsteady Navier-Stokes equations and a mode shape–based structural dynamics model are presented. For turbulent flows, the system is closed with the Spalart-Allmaras turbulence model. The computation times for the aerodynamic solution are significantly reduced using the harmonic balance method compared to a time-accurate solution. This model is significantly more robust than standard aeroelastic codes that rely on blade element momentum theory to determine the aerodynamic forces. Comparisons with published results for the Caradonna-Tung rotor in hover and the classical AGARD 445.6 flutter case are provided to validate the aerodynamic model and aeroelastic model, respectively. For wind turbines, flutter of the 1.5 MW WindPACT blade is considered. The results predict that the first flapwise and edgewise modes dominate flutter at the rotor speeds considered.

Analysis and suppression measures of lightning transient overvoltage in the signal cable of wind turbines


Lightning strikes are a major threat to the secure operation of wind turbines. When lightning strikes a wind turbine, the lightning current flows through the blade and the tower and then the induced overvoltage will damage sensors and signal cables. In this study, a comprehensive transient surge impedance model of a wind turbine was built to analyze the causes of the overvoltage in the signal cable. The model that studies the overvoltage caused by both capacitive coupling and electromagnetic induction included the blade, nacelle, tower, signal cable, power cable, and grounding system using π networks. The influences of the cable shielding layer, soil resistivity, and lightning current waveform on the overvoltage were also analyzed. Then, 2 overvoltage suppression measures, ie, grounding at 2 ends of the outer shielding layer and installation of a surge protective device, were tested. Results show that a signal cable with double shielding layers reduced the overvoltage in the signal cable, and higher soil resistivity resulted in increased voltage on the tower base. In addition, the peak and the front time of the lightning current significantly influenced the overvoltage on the tower and the cable. The effectiveness of the 2 suppression measures was also verified. The calculation results will provide guidance for a reasonable lightning protection design.

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An input-output linearization–based control strategy for wind energy conversion system to enhance stability


This paper proposes a novel control strategy for doubly fed induction generator (DFIG)-based wind energy conversion system to investigate the potential of enhancing the stability of wind energy transmission system, a synchronous generator weakly integrated to a power system with a DFIG-based wind farm. The proposed approach uses state feedback to exactly linearize the nonlinear wind energy transmission system from control actions (active power and reactive power control order of DFIG) to selected outputs (power angle and voltage behind transient resistance of synchronous generator) at first. Then, on account of the linearized subsystem, the stability enhancement controller is designed based on linear quadratic regulator algorithm to contribute adequate damping characteristics to oscillations of the synchronous generator system under various operation points. The proposed control strategy successfully deals with the nonlinear behaviors exist from the inputs to outputs and improve the robustness with respect to the variation of system operation points. Furthermore, not only the rotor angle stability but also the voltage stability is enhanced by using the proposed control strategy. The simulation results carried on the studied system verify the effectiveness of the proposed control strategy of wind energy conversion system for system stability enhancement and the robustness against various system operation points.

Large-eddy simulations of wind-farm wake characteristics associated with a low-level jet


In this study, we performed a suite of flow simulations for a 12-wind-turbine array with varying inflow conditions and lateral spacings, and compared the impacts of the flow on velocity deficit and wake recovery. We imposed both laminar inflow and turbulent inflows, which contain turbulence for the Ekman layer and a low-level jet (LLJ) in the stable boundary layer. To solve the flow through the wind turbines and their wakes, we used a large-eddy simulation technique with an actuator-line method. We compared the time series for the velocity deficit at the first and rear columns to observe the temporal change in velocity deficit for the entire wind farm. The velocity deficit at the first column for LLJ inflow was similar to that for laminar inflow. However, the magnitude of velocity deficit at the rear columns for the case with LLJ inflow was 11.9% greater because of strong wake recovery, which was enhanced by the vertical flux of kinetic energy associated with the LLJ. To observe the spatial transition and characteristics of wake recovery, we performed statistical analyses of the velocity at different locations for both the laminar and LLJ inflows. These studies indicated that strong wake recovery was present, and a kurtosis analysis showed that the probability density function for the streamwise velocity followed a Gaussian distribution. In a quadrant analysis of the Reynolds stress, we found that the ejection and sweep motions for the LLJ inflow case were greater than those for the laminar inflow case.

Using wind velocity estimated from a reanalysis to minimize the variability of aggregated wind farm production over Europe


In this work we use the mean-variance portfolio optimization, using as input the power derived from the wind and density results of meteorological model simulations (ERA-Interim reanalysis), to minimize the variability of the wind power produced in a large region. The methodology involves selecting the placement of the wind farms on a high spatial resolution grid. We used the EU-28 region to check the method and perform sensitivity tests. We studied the influence of the ratio between the total installed power of the whole domain (Pt) and the maximum power that can be installed per cell (Pmi) on the variability of wind power yield. The results show that the reliability of the electrical system improves when Pmi grows and worsens when Pt grows. A quadratic fit relates the variability of the system and the aforementioned ratio. The optimization procedure tends to select groups of terrain cells where wind farms should be installed. These groups grow when more energy production is demanded of the system, but they roughly maintain their location. There is some evidence that in a larger region greater system reliability could be achieved. Most of the selected cells have either a high or a low capacity factor and those with the latter are crucial in enhancing system reliability.

Parabolic RANS solver for low-computational-cost simulations of wind turbine wakes


A numerical framework for simulations of wake interactions associated with a wind turbine column is presented. A Reynolds-averaged Navier-Stokes (RANS) solver is developed for axisymmetric wake flows using parabolic and boundary-layer approximations to reduce computational cost while capturing the essential wake physics. Turbulence effects on downstream evolution of the time-averaged wake velocity field are taken into account through Boussinesq hypothesis and a mixing length model, which is only a function of the streamwise location. The calibration of the turbulence closure model is performed through wake turbulence statistics obtained from large-eddy simulations of wind turbine wakes. This strategy ensures capturing the proper wake mixing level for a given incoming turbulence and turbine operating condition and, thus, accurately estimating the wake velocity field. The power capture from turbines is mimicked as a forcing in the RANS equations through the actuator disk model with rotation. The RANS simulations of the wake velocity field associated with an isolated 5-MW NREL wind turbine operating with different tip speed ratios and turbulence intensity of the incoming wind agree well with the analogous velocity data obtained through high-fidelity large-eddy simulations. Furthermore, different cases of columns of wind turbines operating with different tip speed ratios and downstream spacing are also simulated with great accuracy. Therefore, the proposed RANS solver is a powerful tool for simulations of wind turbine wakes tailored for optimization problems, where a good trade-off between accuracy and low-computational cost is desirable.

Reliability assessment for Chinese domestic wind turbines based on data mining techniques


In this work, based on the field operating data of a Chinese domestic wind farm, which came from the supervisory control and data acquisition system, data mining techniques are applied to analyze the reliability characteristics of wind turbines and their components. The reliability indexes including time among failures, failure rate, and downtime are analyzed. On that basis, the key components that influence the wind turbines' reliability most seriously are determined. The internal relation between the failure rate and the environmental temperature is identified with correlation function, and time series approach is used to analyze the seasonal feature of the wind turbines' failure rate. The results show that compared with the wind turbines mentioned in the literatures, the failure rate of the current sample is higher. Among the components, the failure rates of electrical and control systems are the highest, while the corresponding repair time is relatively short; on the contrary, the failure rates of main shaft, gearbox, and generator are relatively low, while the average time for maintenance is comparably long. Furthermore, there is an obvious dependency between the failure rate and environmental temperature, and the failure rate has a clear seasonal feature.