Realistic Wind Conditions Research Articles

Enhancement of PV Panel Power Production by Passive Cooling Using Heat Sinks with Perforated Fins

This paper presents a numerical model regarding the passive cooling of PV panels through perforated and non-perforated heat sinks. A typical PV panel was studied in a fixed position, tilted at 45 degrees from the horizontal with the wind direction towards its backside. A challenging approach was used in order to calibrate the base case of the numerical model according to the NOCT conditions. Further validation of the accuracy of the numerical simulation consisted of a comparison between the results obtained for the base case, or heat sink, with horizontal non-perforated fins and the experiments presented in the literature. Six types of heat sink attached to the backside of the PV panel were numerically studied. The analyzed configurations focused on heat sinks with both perforated and non-perforated fins that were distributed horizontally and vertically. The CFD simulation was also conducted by modeling the air volume around the PV panel in real wind conditions. The main output parameters were the average temperature and the convective heat transfer coefficient on the front and back of the PV panel. The most important effect of cooling was achieved in low wind conditions and high levels of solar radiation. For vair = 1 m/s, G = 1000 W/m2 and ambient temperature tair = 35 °C, the percentage of maximum power production achieved 83.33% for the base case, while in the best cooling scenario it reached 88.74%, assuring a rise in the power production of 6.49%.

Seasonal effects in the long-term correction of short-term wind measurements using reanalysis data

Abstract. Measure–correlate–predict (MCP) approaches are often used to correct wind measurements to the long-term wind conditions on-site. This paper investigates systematic errors in MCP-based long-term corrections which occur if the measurement on-site covers only a few months (seasonal biases). In this context, two common linear MCP methods are tested and compared with regard to accuracy in mean, variance, and turbine energy production – namely, variance ratio (VR) and linear regression with residuals (LR). Wind measurement data from 18 sites with different terrain complexity in Germany are used (measurement heights between 100 and 140 m). Six different reanalysis data sets serve as the reference (long-term) wind data in the MCP calculations. All these reanalysis data sets showed an overpronounced annual course of wind speed (i.e., wind speeds too high in winter and too low in summer). However, despite the mathematical similarity of the two MCP methods, these errors in the data resulted in very different seasonal biases when either the VR or LR methods were used for the MCP calculations. In general, the VR method produced overestimations of the mean wind speed when measuring in summer and underestimations in the case of winter measurements. The LR method, in contrast, predominantly led to opposite results. An analysis of the bias in variance did not show such a clear seasonal variation. Overall, the variance error plays only a minor role for the accuracy in energy compared to the error in mean wind speed. Besides the experimental analysis, a theoretical framework is presented which explains these phenomena. This framework enables us to trace the seasonal biases to the mechanics of the methods and the properties of the reanalysis data sets. In summary, three aspects are identified as the main influential factors for the seasonal biases in mean wind speed: (1) the (dis-)similarity of the real wind conditions on-site in correlation and correction period (representativeness of the measurement period), (2) the capability of the reference data to reproduce the seasonal course of wind speed, and (3) the regression parameter β1 (slope) of the linear MCP method. This theoretical framework can also be considered valid for different measurement durations, other reference data sets, and other regions of the world.

Full-scale monitoring of wind effects on a supertall structure during six tropical cyclones

Full-scale measurements under real wind conditions are viewed as the most reliable approach to investigating the wind effects on supertall structures. However, long-term monitoring on wind characteristics at the maximum atmospheric boundary layer height and the corresponding wind-induced responses of structures are very limited, especially under strong tropical cyclones. In this study, field monitoring of wind effects on a 600 m high supertall structure is obtained during 6 tropical cyclones by means of a sophisticated long-term structural health monitoring (SHM) system deployed on the structure. Wind characteristics (wind speed, direction, turbulence intensity, gust factor, power spectral density) of these tropical cyclones above 450 m height are presented and analyzed. The dynamic properties of the supertall structure are determined from the field measurements and compared with those stipulated in design. The damping ratios of the supertall structure are estimated by the virtual dynamic shaker (VDS) and the enhanced virtual dynamic shaker (EVDS) methods. In addition, the response amplitude-dependence of the structural natural frequencies and damping ratios is investigated. Finally, the comfort performance of the supertall structure during different tropical cyclones is assessed against four comfort criteria. The findings of this study would be beneficial to professionals and researchers engaged in wind-resistant design and practice of skyscrapers.

Days to visit an offshore island: effect of weather conditions on arrival fuel load and potential flight range for common blackbirds Turdus merula migrating over the North Sea

BackgroundCrossing open water instead of following the coast(line) is one way for landbirds to continue migration. However, depending on prevailing weather and the birds’ physiological conditions, it is also a risky choice. To date, the question remains as to which interplay between environmental and physiological conditions force landbirds to stop on remote islands. We hypothesise that unfavourable winds affect lean birds with low energy resources, while poor visibility affects all birds regardless of their fuel loads.MethodsTo test this hypothesis, we caught 1312 common blackbirds Turdus merula stopping over on Helgoland during autumn and spring migration. Arrival fuel load was measured using quantitative magnetic resonance technology. Weather parameters (wind and relative humidity as a proxy for visibility) were interpolated for the night before arrival. Further, we calculated whether caught individuals would have successfully crossed the North Sea instead of landing on Helgoland, depending on wind conditions.ResultsBoth wind and relative humidity the night before arrival were correlated with arrival fuel load. After nights with strong headwinds, birds caught the following day were mostly lean, most of which would not have managed to cross the sea if they had not stopped on Helgoland. In contrast, fat birds that could have successfully travelled on were caught mainly after nights with high relative humidity (≥ 80%). Furthermore, the rate of presumably successful flights was lower due to wind: although only 9% of all blackbirds captured on Helgoland had insufficient fuel loads to allow safe onward migration in still air, real wind conditions would have prevented 30% of birds from successfully crossing the sea during autumn and 21% during spring migration.ConclusionsWe were able to decipher how physiological condition, wind and relative humidity partially force blackbirds to stop on a remote island. Adverse winds tend to affect lean birds with low energy resources, while poor visibility can affect blackbirds, regardless of whether the arrival fuel load was sufficient for onward flight. Our findings will help to understand different migratory strategies and explain further questions like migration timing.

Biohybrid generators based on living plants and artificial leaves: influence of leaf motion and real wind outdoor energy harvesting

Plants translate wind energy into leaf fluttering and branch motion by reversible tissue deformation. Simultaneously, the outermost structure of the plant, i.e. the dielectric cuticula, and the inner ion-conductive tissue can be used to convert mechanical vibration energy, such as that produced during fluttering in the wind, into electricity by surface contact electrification and electrostatic induction. Constraining a tailored artificial leaf to a plant leaf can enhance oscillations and transient mechanical contacts and thereby increase the electricity outcome. We have studied the effects of wind-induced mechanical interactions between the leaf of a plant (Rhododendron) and a flexible silicone elastomer-based artificial leaf fixed at the petiole on power output and whether performance can be further tuned by altering the vibrational behavior of the artificial leaf. The latter is achieved by modifying a concentrated mass at the tip of the artificial leaf and observing plant-generated current and voltage signals under air flow. In this configuration, the plant-hybrid wind-energy converters can directly power light-emitting diodes and a temperature sensor. Detailed output analysis has revealed that, under all conditions, an increase in wind speed leads to nearly linearly increased voltages and currents. Accordingly, the cumulative sum energy reaches its highest values at the highest wind speed and resulting oscillations of the plant-artificial leaf system. The mass at the tip can, in most cases, be used to increase the voltage amplitude and frequency. Nevertheless, this behavior was found to depend on the individual configuration of the system, such as the leaf morphology. Analysis of these factors under controlled conditions is crucial for optimizing systems meant to operate in unstructured outdoor scenarios. We have established, in a first approach, that the artificial leaf-plant hybrid generator is capable of autonomously generating electricity outdoors under real outdoor wind conditions, even at a low average wind speed of only 1.9 m s−1.

Analysis of Mineral Aerosol in the Surface Layer over the Caspian Lowland Desert by the Data of 12 Summer Field Campaigns in 2002–2020

In-situ knowledge on characteristics of mineral aerosols is important for weather and climate prediction models, particularly for modeling such processes as the entrainment, transport and deposition of aerosols. However, field measurements of the dust emission flux, dust size distribution and its chemical composition under realistic wind conditions remain rare. In this study, we present experimental data over annual expeditions in the arid and semi-arid zones of the Caspian Lowland Desert (Kalmykia, south of Russia); we evaluate characteristics of mineral aerosol concentration and fluxes, estimate its chemical composition and calculate its long-distance transport characteristics. The mass concentration in different years ranges from several tens to several hundred of μg m−3. The significant influence of wind velocity on the value of mass and counting concentration and on the proposed entrainment mechanisms is confirmed. An increased content of anthropogenic elements (S, Sn, Pb, Bi, Mo, Ag, Cd, Hg, etc.), which is characteristic for all observation points in the south of the European Russia, is found. The trajectory analysis show that long-range air particles transport from the Caspian Lowland Desert to the central regions of European Russia tends to increase in the recent decades.

Wind energy conversion system under asymmetrical voltage failures: Analysis and nonlinear control

AbstractThis work presents the analysis and proposes nonlinear controls of a wind energy conversion system (WECS) to pass through symmetrical and asymmetrical voltage failures. The WECS is equipped with a nonsalient pole permanent magnet synchronous generator (PMSG) and two full converters, synchronous generator side converter (SGSC) and grid side converter (GSC), joined by a direct current (DC) link. As a consequence of the strong disturbances considered, a general strategy based on grid voltage values changes control references at SGSC and GSC. This strategy uses two flags for indicating normal grid voltages, symmetrical faults, or asymmetrical ones. Then, while control laws deal with model uncertainties and fast disturbances due to wind gusts, the strategy changes references to surpass strong, probably unbalanced, grid voltages disturbances. To assure robust properties, controllers are designed via a conjunction of Lyapunov and passivity theories. The proposed controllers and the strategy are tested under realistic wind conditions, uncertain parameters, and strong voltage disturbances.

Numerical model of vertical axis wind turbine performance in realistic gusty wind conditions

The goal of this study is to implement a numerical strategy to estimate the performance of a Vertical Axis Wind Turbine (VAWT) in response to realistic winds typical of an urban/suburban area over a full year of operation, and to predict the Levelized Cost of Energy (LCOE) produced by that VAWT in comparison to the national electricity price. Wind speed data from sensors located in Oklahoma City were used as input. Three numerical models were implemented, including Computational Fluid Dynamics (CFD), Blade Element Momentum (BEM), and a transient response model based on conservation of angular momentum of the VAWT. Here, CFD is utilized to simulate the flow around an isolated turbine blade in order to obtain the dynamic lift and drag coefficients as a function of azimuth angle, wind speed, and rotational speed. In total, 86 CFD simulations were performed over a range of wind speeds from 3 to 15 m/s and tip speed ratios from 2.5 to 4.5. These results are then used as input to the BEM and transient response models. Results show that the LCOE price for the VAWT is equal to or less than the average national electricity price at four locations where annual average wind speed measures ≥4.3 m/s.

Wind Farm Layout Optimization (WindFLO) : An advanced framework for fast wind farm analysis and optimization

A new framework for Wind Farm Layout Optimization (WindFLO) is developed to accelerate the design of wind farms. The framework provides a large set of analytical wake models and wake superposition schemes. It is able to take into account terrain elevation and the ambient wind velocity profile. The schemes in the WindFLO model were validated against experimental data from a wind tunnel to within 1% relative error. A turbine rotor diameter and height dependent cost model was also developed using data from 250 different wind turbines. A land usage model was also developed using the convex hull approach. The framework was used to optimize a wind farm layout for maximum annual energy production using real wind farm terrain and conditions. The nonlinear optimization problem was solved using a robust Single-Objective Hybrid Optimizer. The wind farm layout and wind turbine (rotor diameter and tower height) were optimized and resulted in increased annual energy production, reduced cost and reduced land usage. The WindFLO framework is made publicly available to accelerate and advance the techniques for wind farm optimization.11WindFLO can be downloaded from https://github.com/sohailrreddy/WindFLO.

An Improved Power Control Approach for Wind Turbine Fatigue Balancing in an Offshore Wind Farm

Increasing maintenance costs will hinder the expansion of the wind power industry in the coming decades. Training personnel, field maintenance, and frequent boat or helicopter visits to wind turbines (WTs) is becoming a large cost. One reason for this cost is the routine turbine inspection repair and other stochastic maintenance necessitated by increasingly unbalanced figure loads and unequal turbine fatigue distribution in large-scale offshore wind farms (OWFs). In order to solve the problems of unbalanced fatigue loads and unequal turbine fatigue distribution, thereby cutting the maintenance cost, this study analyzes the disadvantages of conventional turbine fatigue definitions. We propose an improved fatigue definition that simultaneously considers the mean wind speed, wind wake turbulence, and electric power generation. Further, based on timed automata theory, a power dispatch approach is proposed to balance the fatigue loads on turbines in a wind farm. A control topology is constructed to describe the logical states of the wind farm main controller (WFMC) in an offshore wind farm. With this novel power control approach, the WFMC can re-dispatch the reference power to the wind turbines according to their cumulative fatigue value and the real wind conditions around the individual turbines in every power dispatch time interval. A workflow is also designed for the control approach implementation. Finally, to validate this proposed approach, wind data from the Horns Rev offshore wind farm in Denmark are used for a numerical simulation. All the simulation results with 3D and 2D figures illustrate that this approach is feasible to balance the loads on an offshore wind farm. Some significant implications are that this novel approach can cut the maintenance cost and also prolong the service life of OWFs.

Wind shear estimation model using load measurement of wind turbine tower and surrogate model

AbstractA wind shear estimation method based on fore‐aft moment is proposed to estimate wind shear strength without a Doppler lidar. We construct wind shear estimation models (WSEMs) using surrogate models whose input is the time‐averaged fore‐aft moment and various supervisory control and data acquisition (SCADA) system data. Learning data for the WSEMs are generated by numerical simulation or field measurement of a real turbine using SCADA, strain gauges, and Doppler lidar. By using simulation data, we construct 20 WSEMs with various input combinations and surrogate methods to select a model with the highest accuracy. The best WSEM is constructed with the universal Kriging surrogate model and uses the fore‐aft moment and wind speed as its input. Subsequently, the best WSEM is applied to a real turbine to validate its accuracy in real wind conditions, and we confirm that the WSEM has reasonable accuracy. However, the estimation error in the real wind condition is about twice as high as that in the simulation due to the real wind shear not completely corresponding to the assumed wind profile and a large yaw error. Further improvement in wind shear estimation accuracy will be achieved by adding yaw error and turbulence intensity to the input variables and applying the WSEM to wind farms on simple terrain or offshore wind farms where wind profile error decreases.

State-parameter estimation approach for data-driven wildland fire spread modeling: Application to the 2012 RxCADRE S5 field-scale experiment

Data assimilation is an emerging and powerful tool towards real-time flame front monitoring for wildland fire applications. The key idea is to regularly update the state and/or parameters of a fire spread model using observed firelines in order to improve a forecast on future fire locations. The merits of combining state estimation and parameter estimation through a hybrid state-parameter estimation algorithm are demonstrated through the 2012 RxCADRE S5 field-scale controlled burn experiment. For state estimation, we adopt a cost-effective Luenberger observer formulation to reconstruct a complete view of the burning state at a given time. For parameter estimation, we use an ensemble transform Kalman filter to solve the inverse modeling problem consisting of inferring more realistic wind conditions given observations of the actual burning state. The data-driven model relies on a front shape similarity measure derived from image segmentation theory to quantify position errors. We show that the hybrid approach provides an efficient framework to address all sources of model uncertainties and to select burning scenarios that are most likely to occur. Parameter estimation is a key component of the data-driven model by reducing model bias. Using the fire spread model in forecast mode is then an asset to accurately track the flame front dynamics at future lead times.

Improving wind farm power output through deactivating selected wind turbines

Wind energy is becoming the fastest growing and most inexpensive renewable source, even surpassed natural gas. The environmental advantages coupled with the significant financial benefits have created a positive prognosis for wind energy continuously growing. However, the complexity and limited availability of wind resources create challenges that need to be addressed in order to continue improving wind energy harvesting. This paper developed a new concept to modify wind farm’s layout by deactivating selected wind turbines to maximize its total power output under different wind conditions. Different wind conditions create different wake effects, while most wind farms cannot change their layouts to cope with the changing wind conditions. Through deactivating selected wind turbines to effectively reduce or eliminate some turbulent wakes, it is possible to improve a wind farm’s total power output by creating a net gain for the entire wind farm. A new method was developed to identify the best combinations of deactivated wind turbines under different wind conditions to achieve maximum power output. Several case studies with real wind farms and real wind conditions were conducted together with sensitivity analysis. The promising results demonstrated the effectiveness of the new method and the new concept, named layout optimization through selective deactivation. Several factors were identified as influencing factors on the effectiveness of the new concept.

Optimal Irregular Wind Farm Design for Continuous Placement of Wind Turbines with a Two-Dimensional Jensen-Gaussian Wake Model

Optimal design of wind turbine placement in a wind farm is one of the most effective tools to reduce wake power losses by alleviating the wake effect in the wind farm. In comparison to the discrete grid-based wind farm design method, the continuous coordinate method has the property of continuously varying the placement of wind turbines, and hence, is far more capable of obtaining the global optimum solutions. In this paper, the coordinate method was applied to optimize the layout of a real offshore wind farm for both simplified and realistic wind conditions. A new analytical wake model (Jensen-Gaussian model) taking into account the wake velocity variation in the radial direction was employed for the optimization study. The means of handling the irregular real wind farm boundary were proposed to guarantee that the optimized wind turbine positions are feasible within the wind farm boundary, and the discretization method was applied for the evaluation of wind farm power output under Weibull distribution. By investigating the wind farm layout optimization under different wind conditions, it showed that the total wind farm power output increased linearly with an increasing number of wind turbines. Under some particular wind conditions (e.g., constant wind speed and wind direction, and Weibull distribution), almost the same power losses were obtained under the wake effect of some adjacent wind turbine numbers. A common feature of the wind turbine placements regardless of the wind conditions was that they were distributed along the wind farm boundary as much as possible in order to alleviate the wake effect.

Implementations and Evaluations of Wind Turbine Inertial Controls With FAST and Digital Real-Time Simulations

This paper presents a novel simulation approach to evaluate new ancillary service controls in the context of large-scale wind power integration. We adopt and compare different types of turbine inertial control methods with the proposed modifications to cope with realistic wind conditions in the field. The simulation procedure is started with the software-based simulation, in which we employ the high-fidelity wind turbine simulator FAST that models a real three-bladed controls advanced research turbine (CART3). The advantages of using FAST are that it can provide convincing simulation results and address the interactions between turbine electrical and mechanical systems. The developed controller model is then rapidly prototyped for the real-time simulation with the hardware-in-the-loop scheme. CART3 will respond to a virtual frequency event triggered in the emulated electric grid modeled in a digital real-time simulator. The introduced simulation platform streamlines the procedure of designing turbine auxiliary controls, and these simulations results give insights on the turbine controls and their impacts on the interconnected power system, as well as the effects on turbine mechanical components. For example, the results indicate that the inertial controls tend to reduce the out-of-plane mechanical loadings in region 2, while such loadings are dominated by the pitch actions in region 3.

Performance of a Darrieus turbine on the roof of a building

Various efforts have been made to introduce micro wind turbines in urban areas. Their onsite wind generation can be beneficial, but general rules about their ideal placement in terms of energy extraction need to be identified. This paper investigates the performance of a Darrieus turbine when installed on the roof of a building and offers a rare analysis of the synergy between the turbine and the building. This study focuses on computational fluid dynamic (CFD) analysis of a vertical-axis wind turbine mounted on the upstream edge of a building. The CFD methodology is validated by comparing the calculated performance with experimental data. Three different turbine positions at different heights are investigated to capture the Cp–λ curve sensitivity. Positions 1 and 2 are at the edge of the building, whereas position 3 is a few meters away from the edge, directed towards the geometric center of the building. To simulate realistic atmospheric wind conditions, an atmospheric boundary layer is imposed at the inlet. The results show that the power coefficient is higher compared with a standalone turbine and that the location of the turbine on the building clearly affects the value of the tip-speed ratio at maximum power coefficient.

Fatigue damage mitigation of offshore wind turbines under real wind and wave conditions

Offshore wind turbines (OWTs) subjected to combined wind and wave loadings experience excessive vibrations which will increase fatigue loadings on the structure and reduce the fatigue life. In this paper, a three-dimensional pendulum tuned mass damper (3d-PTMD) is attached to the OWT to mitigate the bi-directional vibrations resulting from wind-wave misalignment so as to increase the fatigue life. An analytical model of the offshore wind turbine coupled with the 3d-PTMD is established using the Euler-Lagrangian equation. To predict long-term metocean condition, a statistical analysis for different properties of wind and wave loading such as, wind-wave misalignment, significant wave height and wind velocity is carried out. The aerodynamic wind loading is calculated using the blade element method and the wave loading is computed using the JONSWAP wave spectrum and Morison equation. Dual linear tuned mass dampers (TMDs) deployed in the side-side and fore-aft directions are used for comparison. The NREL monopile 5 MW baseline wind turbine is used to examine the performance of 3d-PTMD in a realistic metocean condition. The fatigue damage is estimated based on the rain-flow cycle counting method and Miner’s rule. Results indicate that the 3d-PTMD can increase the wind turbine tower fatigue life by more than 50% in comparison with the dual TMDs.

Numerical evaluation of station-keeping strategies for stratospheric balloons

The trajectory control of stratospheric balloons poses a great challenge, given their importance in scientific explorations and military applications. This has led to the investigation of several trajectory control methods, which aim to retain the balloon system within a specific region. In particular, the use of a control device tethered to the main balloon is required to provide sufficient lateral forces to counteract the air drag on the main balloon. The present study evaluates the performance of two kinds of balloon systems namely, the dual-balloon and balloon–stratosail systems that have a control device tethered to the main balloon. The study compares their performances in the context of realistic wind conditions, and presents the best working range for each of the system, which may be useful in improvising the design of control devices for future applications.

Reconnection in the Martian Magnetotail: Hall‐MHD With Embedded Particle‐in‐Cell Simulations

AbstractMars Atmosphere and Volatile EvolutioN (MAVEN) mission observations show clear evidence of the occurrence of the magnetic reconnection process in the Martian plasma tail. In this study, we use sophisticated numerical models to help us understand the effects of magnetic reconnection in the plasma tail. The numerical models used in this study are (a) a multispecies global Hall‐magnetohydrodynamic (HMHD) model and (b) a global HMHD model two‐way coupled to an embedded fully kinetic particle‐in‐cell code. Comparison with MAVEN observations clearly shows that the general interaction pattern is well reproduced by the global HMHD model. The coupled model takes advantage of both the efficiency of the MHD model and the ability to incorporate kinetic processes of the particle‐in‐cell model, making it feasible to conduct kinetic simulations for Mars under realistic solar wind conditions for the first time. Results from the coupled model show that the Martian magnetotail is highly dynamic due to magnetic reconnection, and the resulting Mars‐ward plasma flow velocities are significantly higher for the lighter ion fluid, which are quantitatively consistent with MAVEN observations. The HMHD with Embedded Particle‐in‐Cell model predicts that the ion loss rates are more variable but with similar mean values as compared with HMHD model results.

Statistical analysis of wind data using Weibull distribution for natural ventilation estimation

Incorporating natural ventilation in buildings can have significant benefits. Nevertheless, realistic wind conditions continually change. Airflow rate estimation methods that assume wind speed and direction as being constant are thus error-prone. To elucidate wind variability and its effect on airflow rate estimation, the Weibull distribution was used in the current study to represent high-resolution historical wind data, statistically, for a 1-year period. A preliminary investigation was carried out on categorizing the wind by its statistical characteristic, and two distinct wind speed distributions were found by applying the K-means algorithm in the categorization process. The yearly distribution of days in two different clusters showed seasonal changes. The wind data from the same clustering was grouped and utilized to estimate the airflow rate in the form of probability density. The results were in good agreement with the full-scale experiment measurements of a 10-day test in Austin, Texas. The proposed method could be used to characterize wind speed variances, especially with a small time step wind data and enables building designers to do a statistical analysis of airflow.