Inflow Wind Speed Research Articles

Reliability aware multi-objective predictive control for wind farm based on machine learning and heuristic optimizations

In this paper, a reliability aware multi-objective predictive control strategy for wind farm based on machine learning and heuristic optimizations is proposed. A wind farm model with wake interactions and the actuator health informed wind farm reliability model are constructed. The wind farm model is then represented by training a relevance vector machine (RVM), with lower computational cost and higher efficiency. Then, based on the RVM model, a reliability aware multi-objective predictive control approach for the wind farm is readily designed and implemented by using five typical state of the art meta-heuristic evolutionary algorithms including the third evolution step of generalized differential evolution (GDE3), the multi-objective evolutionary algorithm based on decomposition (MOEA/D), the multi-objective particle swarm optimization (MOPSO), the multi-objective grasshopper optimization algorithm (MOGOA), and the non-dominated sorting genetic algorithm III (NSGA-III). The computational experimental results using the FLOw Redirection and Induction in Steady-state (FLORIS) and under different inflow wind speeds and directions demonstrate that the relative accuracy of the RVM model is more than 97%, and that the proposed control algorithm can largely reduce thrust loads (by around 20% on average) and improve the wind farm reliability while maintaining similar level of power production in comparison with a conventional predictive control approach. In addition, the proposed control method allows a trade-off between these objectives and its computational load can be properly reduced.

Unsteady dynamic load and output performance of the rotor using the dynamic wake theory

ABSTRACT To accurately calculate the unsteady dynamic load and output performance of the rotor in the stand-alone large-scale wind turbine, a novel added mass force expression m A = 128 / 75 ρ R 3 is derived and corresponding dynamic wake model is established using the acceleration potential flow theory and the blade element momentum in the present study. Moreover, induced velocity delay, wind shear, and yaw are considered in the proposed model. Referring to IEC61400-1 standard of the wind turbine, numerical models of turbulence, gust and wind direction change are established to investigate the output performance of the rotor under the combined effect of aerodynamic force, gravity, and centrifugal force. The obtained results show that the axial load and flapwise bending moment of the blade root are mainly determined by the axial aerodynamic component, while the tangential load and edgewise bending moment are mainly determined by the gravity component of the blade. It is found that the wind shear has a significant impact on the axial load and flapwise bending moment. Meanwhile, the axial thrust and rotor power are mainly affected by the inflow wind speed. It is observed that when the yaw angle exceeds 9.25°, the axial thrust and power of the rotor decrease obviously. The research results are compared with the experimental data from the NREL, it is found that the proposed model provides a new choose for the calculation of added mass force, and it has more calculation accuracy compared with classical BEM method in the prediction of unsteady dynamic load and output performance of the rotor.

Uncertainty identification of blade-mounted lidar-based inflow wind speed measurements for robust feedback–feedforward control synthesis

Abstract. The current trend toward larger wind turbine rotors leads to high periodic loads across the components due to the non-uniformity of inflow across the rotor. To address this, we introduce a blade-mounted lidar on each blade to provide a preview of inflow wind speed that can be used as a feedforward control input for the mitigation of such periodic blade loads. We present a method to easily determine blade-mounted lidar parameters, such as focus distance, telescope position, and orientation on the blade. However, such a method is accompanied by uncertainties in the inflow wind speed measurement, which may also be due to the induction zone, wind evolution, “cyclops dilemma”, unidentified misalignment in the telescope orientation, and the blade segment orientation sensor. Identification of these uncertainties allows their inclusion in the feedback–feedforward controller development for load mitigation. We perform large-eddy simulations, in which we simulate the blade-mounted lidar including the dynamic behaviour and the induction zone of one reference wind turbine for one above-rated inflow wind speed. Our calculation approach provides a good trade-off between a fast and simple determination of the telescope parameters and an accurate inflow wind speed measurement. We identify and model the uncertainties, which can then be directly included in the feedback–feedforward controller design and analysis. The rotor induction effect increases the preview time, which needs to be considered in the controller development and implementation.

Numerical Simulation of Unsteady Aerodynamic Performance of Novel Adaptive Airfoil for Vertical Axis Wind Turbine

The aerodynamic performance of the blade determines the power and load characteristics of a wind turbine. In this paper, numerical research of the active deformation of an airfoil with equal thickness camber line was carried out, which shows the great potential of this active flow control method to improve the flow field. The NACA0012 is taken as the reference airfoil, and the inflow wind speed is 9 m/s, the chord length of the airfoil is 0.4 m, and the Reynolds number is 2.5 × 105. The influence factors, such as deformation amplitude and deformation frequency on the aerodynamic performance, were studied at different attack angles before and after stall. Studies have shown that: firstly, at different angles of attack, different deformation amplitudes and frequencies have great influence on the aerodynamic performance of the active deformed airfoil. The active deformation can improve the aerodynamic performance of the airfoil in different degrees in deep stall and light stall regions. Secondly, a suitable deformation amplitude and deformation frequency can improve the aerodynamic performance of airfoil stably and effectively in light stall, which occurs when the deformation amplitude equals to 0.02c and the deformation frequency is lower than 2 Hz, and the maximum lift-drag ratio can be increased by about 25%. Before stall, when the deformation frequency is 2 Hz and amplitude is 0.10c, the airfoil will have a negative drag coefficient in the process of deformation, and the airfoil will produce a thrust which is similar to the energy capture of the flapping foil. This is an unexpected discovery in our research.

Wake modeling of wind turbines using machine learning

In the paper, a novel framework that employs the machine learning and CFD (computational fluid dynamics) simulation to develop new wake velocity and turbulence models with high accuracy and good efficiency is proposed to improve the turbine wake predictions. An ANN (artificial neural network) model based on the back-propagation (BP) algorithm is designed to build the underlying spatial relationship between the inflow conditions and the three-dimensional wake flows. To save the computational cost, a reduced-order turbine model ADM-R (actuator disk model with rotation), is incorporated into RANS (Reynolds-averaged Navier-Stokes equations) simulations coupled with a modified k-ε turbulence model to provide big datasets of wake flow for training, testing, and validation of the ANN model. The numerical framework of RANS/ADM-R simulations is validated by a standalone Vestas V80 2 MW wind turbine and NTNU wind tunnel test of double aligned turbines. In the ANN-based wake model, the inflow wind speed and turbulence intensity at hub height are selected as input variables, while the spatial velocity deficit and added turbulence kinetic energy (TKE) in wake field are taken as output variables. The ANN-based wake model is first deployed to a standalone turbine, and then the spatial wake characteristics and power generation of an aligned 8-turbine row as representation of Horns Rev wind farm are also validated against Large Eddy Simulations (LES) and field measurement. The results of ANN-based wake model show good agreement with the numerical simulations and measurement data, indicating that the ANN is capable of establishing the complex spatial relationship between inflow conditions and the wake flows. The machine learning techniques can remarkably improve the accuracy and efficiency of wake predictions.

Automated wind turbine wake characterization in complex terrain

Abstract. An automated wind turbine wake characterization algorithm has been developed and applied to a data set of over 19 000 scans measured by a ground-based scanning Doppler lidar at Perdigão, Portugal, over the period January to June 2017. Potential wake cases are identified by wind speed, direction and availability of a retrieved free-stream wind speed. The algorithm correctly identifies the wake centre position in 62 % of possible wake cases, with 46 % having a clear and well-defined wake centre surrounded by a coherent area of lower wind speeds while 16 % have split centres or multiple lobes where the lower wind speed volumes are no longer in coherent areas but present as two or more distinct areas or lobes. Only 5 % of cases are not detected; the remaining 33 % could not be categorized either by the algorithm or subjectively, mainly due to the complexity of the background flow. Average wake centre heights categorized by inflow wind speeds are shown to be initially lofted (to two rotor diameters, D, downstream) except when the inflow wind speeds exceed 12 ms−1. Even under low wind speeds, by 3.5 D downstream of the wind turbine, the mean wake centre position is below the initial wind turbine hub height and descends broadly following the terrain slope. However, this behaviour is strongly linked to the hour of the day and atmospheric stability. Overnight and in stable conditions, the average height of the wake centre is 10 m higher than in unstable conditions at 2 D downstream from the wind turbine and 17 m higher at 4.5 D downstream.

Simulation of urban boundary and canopy layer flows in port areas induced by different marine boundary layer inflow conditions

Computational fluid dynamics (CFD) simulations and wind-tunnel (WT) tests can be considered as boundary-value problems, where the inlet boundary condition, which is usually obtained inferring inlet mean wind profiles from on-site measurements or other type of experimental data, represents the large-scale atmospheric forcing exerted at the outer limit of the urban model. It is not clear, however, to which extent the choice of different inflow wind speed profiles may affect WT and CFD results in the urban environment. In the present study, this aspect is investigated through the comparison of the wind flow fields simulated numerically and tested experimentally in an atmospheric boundary layer wind tunnel (ABLWT) within a district of Livorno city, Italy, called “Quartiere La Venezia”. Three different shapes of inflow profiles were tested using the CFD technique and the results were compared with each other: one is based on the approach-flow profiles measured upstream of the urban model in the WT test section (WT profile) and two are based on anemometric data corresponding to the approach-flow profile measured by means of a LiDAR wind profiler (LiDAR profile 1 and 2). The analysis showed that using different wind speed profiles does not affect significantly the results in the urban canopy layer (UCL), where correlations of 95% and 98% were found between the LiDAR profile 1 and 2 data and the WT profile data (at z = 0.02 m above the bottom), respectively. Conversely, the different inflow profiles strongly affected the results above the UCL. This means that the local-scale effects induced on the wind field in the UCL by the urban texture are dominated mainly by the larger-scale forcing, as within the canopy the flow remains topologically invariant despite the different inflow conditions.

Effects of Heat Intensity and Inflow Wind on the Reactive Pollution Dispersion in Urban Street Canyon

This paper investigates the impacts of heating intensity and inflow wind speed on the characteristics of reactive pollutant dispersion in street canyons using the computational fluid dynamic (CFD) model that includes the transportation of NO, NO2, and O3 coupled with NO-NO2-O3 photochemistry. The results indicated that the heat intensity and inflow wind speed have a significant influence on the flow field, temperature field and the characteristics of reactive pollutant dispersion in and above the street canyon. With the street canyon bottom heating intensity increasing, NO, NO2 and O3 concentrations in street canyon are decreased. The O3 concentration reductions are even more than the NO and NO2 concentrations. Improving the inflow wind speed can significantly reduce the NO and NO2 concentrations within street canyons. But the O3 concentrations have a slight rise with wind speed increasing. The results would be useful for understanding the interrelation among reactive vehicle emissions, and provide references for urban planners.

High-solidity straight-bladed vertical axis wind turbine: Aerodynamic force measurements

Vertical axis wind turbines (VAWTs) have many advantages over horizontal axis wind turbines (HAWTs), but due to the lack of knowledge of complicated aerodynamic mechanisms, the power generation of VAWTs is lower per equivalent area. The detailed experimental investigations are therefore highly recommended to understand the aerodynamic mechanisms of blades of a VAWT. This study performs direct measurements of aerodynamic forces on the blades of a high-solidity straight-bladed VAWT in a wind tunnel. The wind turbine and measurement system are presented in detail. A series of wind tunnel tests were carried out to investigate the effects of azimuth angle, tip speed ratio, inflow wind speed and blade chord width on the aerodynamic (both tangential and normal) forces of the blades. The wind tunnel test results demonstrate that the measurement system developed in this study is capable of providing aerodynamic forces with adequate accuracy. The measurement results show that the high-solidity straight-bladed VAWT has better self-starting performance and can achieve higher power coefficient at lower tip speed ratios, which enable them to work at low rotational speed conditions. Nevertheless, high-solidity adds the complexity to the flow field around blades at lower tip speed ratios.

Performance evaluation of a blade-mounted LiDAR with dynamic versus fixed parameters through feedback-feedforward individual pitch and trailing edge flap control

This paper investigates combined feedback-feedforward control of a wind turbine using a blade-mounted telescope LiDAR sensor to measure the inflow wind speed. The objective of this paper is to evaluate the controller performance with fixed telescope parameters compared to the wind speed dependent dynamically changing telescope parameters. First the telescope parameters for both cases are determined, then the robust feedback controllers are extended with an inverse-based feedforward individual pitch and trailing edge flap controller to alleviate the 1P and 2P loads of the flapwise blade root bending moments. A minor performance degradation is observed with the fixed telescope parameters in comparison to the dynamic telescope parameters.

Numerical Studies on a NACA0018 Airfoil Blade HAWT with Trailing Edge Jet Flow

This study analyzed an airfoil blade for a horizontal-axis wind turbine (HAWT) with a trailing-edge jet flow design. This design was realized by drilling a hole in the trailing edge of an NACA0018 blade of a conventional HAWT to serve as a pressure injection nozzle. Five inflow wind speeds and three trailing-edge jet flow conditions were examined in the test. The results revealed the efficiency differences between a HAWT with the new jet flow design and conventional HAWTs. The experimental methods employed involved a wind tunnel experiment and a computational fluid dynamics (CFD) simulation. The results revealed that when the inflow wind speed was low, the trailing-edge jet flow accelerated the initiation phase and increased the rotating speed of the HAWT; however, when the inflow wind speed was high, damping occurred and the rotating speed of the turbine blades decreased.

Analysis of wind turbine blades aeroelastic performance under yaw conditions

The aeroelastic modeling of Tjæreborg wind turbine blades was performed based on the unsteady Reynolds Averaged Navier-Stokes equations (URANS) combined with Finite Element Method (FEM) in a loosely coupled manner. This method was verified by comparing numerical and experiment results at four axial inflow wind speeds. Furthermore, the aeroelastic performance of Tjæreborg wind turbine under yaw angle of 10°, 30° and 60°were computed and analyzed. The results showed that the average power and thrust of the wind turbine decreased with increasing yaw angle, along with the increasing oscillation amplitude under large yaw angle. The aerodynamic load showed periodic change within one revolution of rotor, resulting in the blade deflection and the strain present considerably asymmetric distributions. The maximum deflection and strain occurred at azimuth angle of about90° and their minimum values occurred at azimuth angle of about 270°. Besides, both the maximum deflection and strain under yaw conditions became larger than those in axial inflow condition do. For Tjæreborg wind turbine, the coupled solver gave a higher average power and thrust than the CFD solver alone. The aerodynamic performances showed more asymmetrical characters under the combined effect of yaw and fluid structure interaction (FSI).

Experimental investigation of aerodynamic effect–induced dynamic characteristics of an OC4 semi-submersible floating wind turbine

Compared to onshore wind turbines, aerodynamics-induced dynamic characteristics of a floating wind turbine are more complicated due to its coupled aero-hydro-servo-elastic behaviours. The study investigates these aerodynamics-induced dynamic characteristics using an OC4 semi-submersible floating wind turbine. In this research, a high-fidelity wind field and a 1/50th scale model were tested. The dynamic characteristics induced by the aerodynamic effects were investigated in detail via the experimental results, including aerodynamic damping effects, gyroscopic effects, dynamic responses of the Rotor-Nacelle-Assembly and dynamic responses of the mooring system. It is found that aerodynamic damping is active in reducing surge and pitch resonant responses and probably increases with the inflow wind speed and the rotating-blades–induced induction coefficient; the gyroscopic effect intensifies the yaw motion and increases with the rotational speed of a rotor; the significant responses from the Rotor-Nacelle-Asse...

도시 지역 대상의 CFD 모델 영역에서 유입류 풍속 추정에 관한 연구

도시 지역 대상의 CFD 모델 영역에서 유입류 풍속 추정에 관한 연구

Verification of Convection-Allowing Model Ensemble Analyses of Near-Storm Environments Using MPEX Upsonde Observations

The Mesoscale Predictability Experiment (MPEX) conducted during the spring of 2013 included frequent coordinated sampling of near-storm environments via upsondes. These unique observations were taken to better understand the upscale effects of deep convection on the environment, and are used to validate the accuracy of convection-allowing (Δ x = 3 km) model ensemble analyses. A 36-member ensemble was created with physics diversity using the Weather Research and Forecasting Model, and observations were assimilated via the Data Assimilation Research Testbed using an ensemble adjustment Kalman filter. A 4-day sequence of convective events from 28 to 31 May 2013 in the south-central United States was analyzed by assimilating Doppler radar and conventional observations. No MPEX upsonde observations were assimilated. Since the ensemble mean analyses produce an accurate depiction of the storms, the MPEX observations are used to verify the accuracy of the analyses of the near-storm environment. A total of 81 upsondes were released over the 4-day period, sampling different regions of near-storm environments including storm inflow, outflow, and anvil. The MPEX observations reveal modest analysis errors overall when considering all samples, although specific environmental regions reveal larger errors in some state fields. The ensemble analyses underestimate cold pool depth, and storm inflow meridional winds have a pronounced northerly bias that results from an underprediction of inflow wind speed magnitude. Most bias distributions are Gaussian-like, with a few being bimodal owing to systematic biases of certain state fields and environmental regions.

地窓を利用した夜間自然換気による潜熱蓄熱材の蓄冷効果に関する研究

1. Introduction In this paper, we focused on introduction of phase change material(PCM) into a house to secure a cold storage with night natural ventilation. We conducted measurement in order to understand indoor thermal characteristics in a room with night natural ventilation for introducing PCM on the floor of a house to maximize cooling effect. Measurement was mainly conducted for on a room of the full-scale house where it has two openings at floor level. We measured vertical air temperature distribution and inflow wind speed to understand indoor thermal characteristics. And heat flow was also measured on the floor and under the floor to reveal cold storage mechanism. 2. Categorization We categorized measurement results according to weather condition on each day as follows. 1) Day of large air temperature difference between indoor and outdoor(ΔT) with high inflow wind speed, 2) Day of large ΔT with low inflow wind speed, and 3) Day of small ΔT with high inflow wind speed. 3. Measurement summary on indoor thermal characteristics Vertical air temperature distribution of indoor was influenced by inflow wind speed and ΔT. In case that inflow wind speed was lower than 0.1m/s, cold air accumulated along the floor was not mixed with the air at upper area of indoor. In case that inflow wind speed was over 0.1m/s and under 0.3m/s, inlet air mixed with indoor air. At this time, mixing height was determined by ΔT and inflow wind speed. In case that inflow wind speed was over 0.3m/s, indoor air was entirely mixed with outdoor air, thus vertical air temperature distribution tended to be disappeared. 4. Measurement summary on cold storage Cold storage tended to be proportional to ΔT. Cold storage accelerated as the condition of large ΔT and low inflow wind speed because cold air accumulated along the floor was not mixed with upper air of indoor. In case that air temperature near the floor was 2°C lower than phase change temperature of PCM for solidification, latent cold storage begun to progress. Cold storage ratio of latent heat was averagely 70%, and total cold storage tended to change approximate 1.5 times depending on outdoor air temperature. 5. Conclusion Indoor thermal characteristics and cold storage rate were changed by ΔT and inflow wind speed. In some cases, latent cold storage efficiency of PCM on the floor with night natural ventilation was confirmed. In the future, considering the daily life activity of residents, we are going to research passive cooling effect of PCM including the day time. Also, in order to develop a numerical simulation tool for designing a passive cooling house with PCM including a calculation model of vertical air temperature distribution, we will determine the parameter of turbulence diffusion coefficient by CFD simulation.

Maximization of the annual energy production of wind power plants by optimization of layout and yaw-based wake control

This paper presents a wind plant modeling and optimization tool that enables the maximization of wind plant annual energy production (AEP) using yaw-based wake steering control and layout changes. The tool is an extension of a wake engineering model describing the steady-state effects of yaw on wake velocity profiles and power productions of wind turbines in a wind plant. To make predictions of a wind plant's AEP, necessary extensions of the original wake model include coupling it with a detailed rotor model and a control policy for turbine blade pitch and rotor speed. This enables the prediction of power production with wake effects throughout a range of wind speeds. We use the tool to perform an example optimization study on a wind plant based on the Princess Amalia Wind Park. In this case study, combined optimization of layout and wake steering control increases AEP by 5%. The power gains from wake steering control are highest for region 1.5 inflow wind speeds, and they continue to be present to some extent for the above-rated inflow wind speeds. The results show that layout optimization and wake steering are complementary because significant AEP improvements can be achieved with wake steering in a wind plant layout that is already optimized to reduce wake losses. Copyright © 2016 John Wiley & Sons, Ltd.

도시 협곡에서 유입류 풍속과 난류 슈미트수에 대한 대기오염물질 확산의 민감도 연구

In this study, sensitivity of inflow wind speed and turbulent Schmidt number to pollutant dispersion in an urban street canyon is investigated, by comparing CFD-simulated results to wind-tunnel results. For this, we changed systematically inflow wind speed at the street-canyon height (<TEX>$1.5{\sim}10.0m\;s^{-1}$</TEX> with the increment of <TEX>$0.5m\;s^{-1}$</TEX>) and turbulent Schmidt number (0.2~1.3 with interval of 0.1). Also, we performed numerical experiments under the conditions that turbulent Schmidt numbers selected with the magnitude of mean kinetic energy at each grid point were assigned in the street canyon. With the increase of the inflow wind speed, the model underestimated (overestimated) pollutant concentration in the upwind (downwind) side of the street canyon because of the increase of pollutant advection. This implies that, for more realistic reproduction of pollutant dispersion in urban street canyons, large (small) turbulent Schmidt number should be assigned for week (strong) inflow condition. In the cases of selectively assigned turbulent Schmidt number, mean bias remarkably decreased (maximum 60%) compared to the cases of constant turbulent Schmidt number assigned. At week (strong) inflow wind speed, root mean square error decreases as the area where turbulent Schmidt number is selectively assigned becomes large (small).

Sizing and control of trailing edge flaps on a smart rotor for maximum power generation in low fatigue wind regimes

In this paper an extension of the spectrum of applicability of rotors with active aerodynamic devices is presented. Besides the classical purpose of load alleviation, a secondary objective is established: power capture optimization. As a first step, wind speed regions that contribute little to fatigue damage have been identified. For these regions the turbine energy output can be increased by deflecting the trailing edge (TE) flap as a function of local, instantaneous speed ratios. For this purpose, sizing of TE flap configuration for maximum power generation is established using blade element momentum theory. The investigation then focuses on operation in non-uniform wind field conditions. Firstly, the deterministic fluctuation in local tip speed ratio due to wind shear was evaluated. The second effect is associated with delays in adapting the rotor speed to time varying inflow. The increase of power generation due to wind shear has been demonstrated with an increase of energy yield of 1%. Finally a control logic based on inflow wind speeds has been devised.

Quantifying error of lidar and sodar Doppler beam swinging measurements of wind turbine wakes using computational fluid dynamics

Abstract. Wind-profiling lidars are now regularly used in boundary-layer meteorology and in applications such as wind energy and air quality. Lidar wind profilers exploit the Doppler shift of laser light backscattered from particulates carried by the wind to measure a line-of-sight (LOS) velocity. The Doppler beam swinging (DBS) technique, used by many commercial systems, considers measurements of this LOS velocity in multiple radial directions in order to estimate horizontal and vertical winds. The method relies on the assumption of homogeneous flow across the region sampled by the beams. Using such a system in inhomogeneous flow, such as wind turbine wakes or complex terrain, will result in errors. To quantify the errors expected from such violation of the assumption of horizontal homogeneity, we simulate inhomogeneous flow in the atmospheric boundary layer, notably stably stratified flow past a wind turbine, with a mean wind speed of 6.5 m s−1 at the turbine hub-height of 80 m. This slightly stable case results in 15° of wind direction change across the turbine rotor disk. The resulting flow field is sampled in the same fashion that a lidar samples the atmosphere with the DBS approach, including the lidar range weighting function, enabling quantification of the error in the DBS observations. The observations from the instruments located upwind have small errors, which are ameliorated with time averaging. However, the downwind observations, particularly within the first two rotor diameters downwind from the wind turbine, suffer from errors due to the heterogeneity of the wind turbine wake. Errors in the stream-wise component of the flow approach 30% of the hub-height inflow wind speed close to the rotor disk. Errors in the cross-stream and vertical velocity components are also significant: cross-stream component errors are on the order of 15% of the hub-height inflow wind speed (1.0 m s−1) and errors in the vertical velocity measurement exceed the actual vertical velocity. By three rotor diameters downwind, DBS-based assessments of wake wind speed deficits based on the stream-wise velocity can be relied on even within the near wake within 1.0 m s−1 (or 15% of the hub-height inflow wind speed), and the cross-stream velocity error is reduced to 8% while vertical velocity estimates are compromised. Measurements of inhomogeneous flow such as wind turbine wakes are susceptible to these errors, and interpretations of field observations should account for this uncertainty.