LiDAR measurements for an onshore wind farm: Wake variability for different incoming wind speeds and atmospheric stability regimes

Wind measurements were performed with the UTD mobile LiDAR station for an onshore wind farm located in Texas with the aim of characterizing evolution of wind‐turbine wakes for different hub‐height wind speeds and regimes of the static atmospheric stability. The wind velocity field was measured by means of a scanning Doppler wind LiDAR, while atmospheric boundary layer and turbine parameters were monitored through a met‐tower and SCADA, respectively. The wake measurements are clustered and their ensemble statistics retrieved as functions of the hub‐height wind speed and the atmospheric stability regime, which is characterized either with the Bulk Richardson number or wind turbulence intensity at hub height. The cluster analysis of the LiDAR measurements has singled out that the turbine thrust coefficient is the main parameter driving the variability of the velocity deficit in the near wake. In contrast, atmospheric stability has negligible influence on the near‐wake velocity field, while it affects noticeably the far‐wake evolution and recovery. A secondary effect on wake‐recovery rate is observed as a function of the rotor thrust coefficient. For higher thrust coefficients, the enhanced wake‐generated turbulence fosters wake recovery. A semi‐empirical model is formulated to predict the maximum wake velocity deficit as a function of the downstream distance using the rotor thrust coefficient and the incoming turbulence intensity at hub height as input. The cluster analysis of the LiDAR measurements and the ensemble statistics calculated through the Barnes scheme have enabled to generate a valuable dataset for development and assessment of wind farm models.     

Wake impacts on downstream wind turbine performance and yaw alignment

Aerodynamic wake interaction between commercial scale wind turbines can be a significant source of power losses and increased fatigue loads across a wind farm. Significant research has been dedicated to the study of wind turbine wakes and wake model development. This paper profiles influential wake regions for an onshore wind farm using 6 months of recorded SCADA (supervisory control and data acquisition) data. An average wind velocity deficit of over 30% was observed corresponding to power coefficient losses of 0.2 in the wake region. Wind speed fluctuations are also quantified for an array of turbines, inferring an increase in turbulence within the wake region. A study of yaw data within the array showed turbine nacelle misalignment under a range of downstream wake angles, indicating a characteristic of wind turbine behaviour not generally considered in wake studies. The turbines yaw independently in order to capture the increased wind speeds present due to the lateral influx of turbulent wind, contrary to many experimental and simulation methods found in the literature. Improvements are suggested for wind farm control strategies that may improve farm‐wide power output. Additionally, possible causes for wind farm wake model overestimation of wake losses are proposed.Copyright © 2012 John Wiley & Sons, Ltd.     

A pragmatic approach to wind farm simulations using the dynamic wake meandering model

This paper presents a computationally efficient method for using the dynamic wake meandering model to conduct simulations of wind farm power production. The method is based on creating a database, which contains the time and rotor‐averaged wake effect at any point downstream of a wake‐emitting turbine operating in arbitrary ambient conditions and at an arbitrary degree of wake influence. This database is later used as a look‐up table at runtime to estimate the operating conditions at all turbines in the wind farm, thus eliminating the need to run the dynamic wake meandering model at runtime. By using the proposed method, the time required to conduct wind farm simulations is reduced by three orders of magnitude compared with running the standalone dynamic wake meandering model at runtime. As a result, the wind farm production dynamics for a farm of 100 turbines at 10,000 different sets of ambient conditions run on a normal laptop in 1 h. The method is validated against full scale measurements from the Smøla and OWEZ wind farms, and fair agreement is achieved. Copyright © 2014 John Wiley & Sons, Ltd.     

An experimental investigation on the effect of individual turbine control on wind farm dynamics

Individual wind turbines in a wind farm typically operate to maximize their performance with no consideration of the impact of wake effects on downstream turbines. There is potential to increase power and reduce structural loads within a wind farm by properly coordinating the turbines. To effectively design and analyze coordinated wind turbine controllers requires control‐oriented turbine wake models of sufficient accuracy. This paper focuses on constructing such a model from experiments. The experiments were conducted to better understand the wake interaction and impact on voltage production in a three‐turbine array. The upstream turbine operating condition was modulated in time, and the dynamic impact on the downstream turbine was recorded through the voltage output time signal. The flow dynamics observed in the experiments were used to improve a static wake model often used in the literature for wind farm control. These experiments were performed in the atmospheric boundary layer wind tunnel at the Saint Anthony Falls Laboratory at the University of Minnesota using particle image velocimetry for flow field analysis and turbine voltage modulation to capture the physical evolution in addition to the dynamics of turbine wake interactions. Copyright © 2015 John Wiley & Sons, Ltd.     

Application of gray relational analysis to k-means clustering for dynamic equivalent modeling of wind farm

Considering the characteristics of dynamic gray correlation among operational conditions of wind turbines, an innovative clustering method for dynamic equivalent modeling of wind farms (WFs) based on the dynamic gray cluster algorithm is proposed. The proposed method is used to determine the number and composition of equivalent wind turbine (WT) groups that can be used to represent a WF. Based on an analysis of auto-correlation coefficients among the various monitoring items of a supervisory control and data acquisition (SCADA) system for a WT, the time span of clustering samples is determined. Then, a correlation matrix of the clustering samples is constructed by using the dynamic gray relational analysis method. Finally, WTs are divided into groups by analyzing the abovementioned correlation matrix by using the k-means clustering algorithm, and WTs belonging to the same group are considered equivalent to one turbine to realize dynamic equivalent modeling of WFs. The method is demonstrated on a WF comprising 22 WTs connected to an IEEE 39 bus test system. Dynamic responses of the proposed model for the WF are compared against the response of the detailed model and other models for various scenarios. The comparison results show that the proposed dynamic equivalent model can describe the dynamic response characteristics of a WF with accuracy similar to that of the detailed model, and the proposed model is simpler and has lower computational complexity.     

Transient stability of a fixed speed wind farm

A typical fixed speed wind farm connected to a simple grid is modelled. Using this model, a three-phase fault is applied close to the wind farm, and cleared by disconnecting the affected line. The effect of several electric, mechanical and operational parameters on the critical fault-clearing time of this base case is evaluated and discussed. The studied parameters are the short-circuit power at the connection bus, the reactive power compensation, the distance to the fault, the rotor inertia, the hub-generator resonant frequency, the wind speed and the power output. For each parameter, the relationship between its value and the critical fault-clearing time is shown graphically. The results help to understand the transient stability phenomena in fixed speed wind farms, and could help to design fixed speed wind farms attending to transient stability requirements.     

Two improvements to the dynamic wake meandering model: including the effects of atmospheric shear on wake turbulence and incorporating turbulence build‐up in a row of wind turbines

The dynamic wake meandering (DWM) model is an engineering wake model designed to physically model the wake deficit evolution and the unsteady meandering that occurs in wind turbine wakes. The present study aims at improving two features of the model:

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Centralised power control of wind farm with doubly fed induction generators

At the moment, the control ability of wind farms is a prime research concern for the grid integration of large wind farms, due to their required active role in the power system. This paper describes the on-going work of a research project, whose overall objective is to analyse and assess the possibilities for control of different wind farm concepts. The scope of this paper is the control of a wind farm made up exclusively of doubly fed induction generators. The paper addresses the design and implementation issues of such a controller and focuses on the ability of the wind farm control strategy to regulate the wind farm power production to the reference power ordered by the system operators. The presented wind farm control has a hierarchical structure with both a central control level and a local control level. The central wind farm control level controls the power production of the whole farm by sending out reference power signals to each individual wind turbine, while the local wind turbine control level ensures that the reference power signal send by the central control level is reached. The performance of the control strategy is assessed and discussed by means of simulations illustrated both at the wind farm level and at each individual wind turbine level.     

Offshore wind farm wake recovery: Airborne measurements and its representation in engineering models

We present an analysis of wind measurements from a series of airborne campaigns conducted to sample the wakes from two North Sea wind farm clusters, with the aim of determining the dependence of the downstream wind speed recovery on the atmospheric stability. The consequences of the stability dependence of wake length on the expected annual energy yield of wind farms in the North Sea are assessed by an engineering model. Wakes are found to extend for significantly longer downstream distances (>50 km) in stable conditions than in neutral and unstable conditions (  15 km). The parameters of one common engineering model are modified to reproduce the observed wake decay at downstream distances  30 km. More significant effects on the energy yield are expected for wind farms separated by distances  30 km, which is generally the case in the North Sea, but additional data would be required to validate the suggested parameter modifications within the engineering model. A case study is accordingly performed to show reductions in the farm efficiency downstream of a wind farm. These results emphasize not only the importance of understanding the impact of atmospheric stability on offshore wind farms but also the need to update the representation of wakes in current industry models to properly include wake‐induced energy losses, especially in large offshore clusters.     

General study of the control principles and dynamic fault behaviour of variable-speed wind turbine and wind farm generic models

The interest towards generic models or sometimes also called standard models of wind turbine generators (WTGs) is significantly increasing. Mainly due to their improved power quality, better controllability and higher power extraction capability, variable-speed wind turbines driving a synchronous or an induction machine are capturing the global market. Throughout this paper, dynamic modelling and performance analysis of the generic models of the variable-speed WTGs, namely the doubly-fed induction generator and the fully-rated converter based WTGs, are achieved using integration between Matlab/Simulink and PSCAD/EMTDC simulation platforms. Later on, the performance of type-4 wind turbine driving a permanent magnet synchronous machine is analysed during fault and then compared with the case when driving a wound rotor induction machine. The differences in control principles and dynamic fault behaviour are highlighted. Afterwards, investigations on wind farm level are accomplished. A case study during which the developed generic models and the generic model of the variable-speed machine are compared is conducted. Different arrangements for the construction of the generic wind farm are considered.     

Valuing a wind farm construction: A contingent valuation study in Greece

Our analysis is based on data from a double-bounded dichotomous choice contingent valuation study implemented to elicit public attitudes towards renewable energy generation and their willingness to pay for the construction of a wind farm in the area of Messanagros in the island of Rhodes, Greece. Results indicate that there are significant positive values deriving from the proposed project. Respondents report a mean willingness to pay a premium in their bi-monthly electric bills of €8.86 for the sole purpose of the construction of the wind farm. The estimated economic benefits to the local population are weighed against the investment cost in a cost–benefit analysis to inform policy making and implications for EU energy policy are provided.     

Wind farm layout optimization using area dimensions and definite point selection techniques

Wind turbines are the biggest rotating machines on earth, operating in the lowest part of the earth boundary layer. Designing the layout scheme of wind farms is a challenging job to researchers, as there are many design objectives and constraints due to the multiple wake phenomena. This paper proposes an area rotation method to find the optimum dimensions of the wind farm shape, where maximum area could face the free stream velocity. Afterwards, a novel method called Definite Point Selection (DPS) is developed to place the turbines in order to operate at maximum, while providing obligatory space between adjacent turbines for operation safety. This method can be used to identify the zero wake effect points at wind farm. The result from this study shows that the proposed method is more effective to increase the overall power of a wind farm than the previous methods. Also, the power output of the wind farm by using combined area rotation and DPS methods was increased even when using the same number of wind turbines.     

Exergy analysis in a wind speed prognostic model as a wind farm sitting selection tool: A case study in Southern Greece

In the present paper, the wind potential of Central Peloponnese in Greece has been studied and the Exergy Analysis methodology was implemented as a wind farm sitting selection tool. The wind speed of the chosen regions of Central Peloponnese was studied and correlated based on the measurements of three specific sites in the wider area using a software based prognostic model using intercomparisons of cross-predictions among these sites. The Exergy Analysis implemented in this innovative wind speed forecasting model is used to identify the actual use of energy from the existing available energy and to evaluate the proposed sites appropriate for wind farm development ending up to an accurate wind map of the area.     

Comparative study of the behavior of wind-turbines in a wind farm

The Sotavento wind farm is an experimental wind farm which has different types of wind turbines. It is located in an area whose topography is moderately complex, and where wake effects can be significant. One of the objectives of Sotavento wind farm is to compare the performances of the different machines; particularly regarding power production, maintenance and failures. However, because of wakes and topography, the different machines are not working under identical conditions. Two linearized codes have been used to estimate topography effects: UPMORO and WAsP. For wind directions in which topography is abrupt, the non-linear flow equations have been solved with the commercial code FLUENT, although the results are only qualitatively used. For wake effects, the UPMPARK code has been applied. As a result, the incident velocity over each wind turbine is obtained, and the power production is estimated by means of the power curve of each machine. Experimental measurements give simultaneously the wind characteristics at the measuring stations, the wind velocity, at the nacelle anemometer, and the power production of each wind turbine. These experimental results are employed to validate the numerical predictions. The main objective of this work is to deduce and validate a relationship between the wind characteristics measured in the anemometers and the wind velocity and the power output in each machine.     

The impact of land use constraints in multi-objective energy-noise wind farm layout optimization

Recently the environmental impact of onshore wind farms is receiving major attention from both governments and wind farm designers. As land is more extensively exploited for wind farms, it is more likely for wind turbines to be in proximity with human dwellings, infrastructure (e.g. roads, transmission lines), and natural habitats (e.g. rivers, lakes, forests). This proximity makes significant portions of land unusable for the designers, introducing a set of land-use constraints. In this study, we conduct a constrained and continuous-variable multi-objective optimization that considers energy and noise as its objective functions, based on Jensen's wake model and the ISO-9613-2 noise standard. A stochastic evolutionary algorithm (NSGA-II) solves the optimization problem, while the land-use constraints are handled with static and dynamic penalty functions. Results of this study illustrate the effect of constraint severity and spatial distribution of unusable land on the trade-off between energy generation and noise production.     

Load sharing behavior analysis method of wind turbine gearbox in consideration of multiple-errors

Conducting a further analysis on loading sharing among compound planetary gear system in wind turbine gearbox, and making a meshing error analysis on the eccentricity error, gear thickness error, base pitch error, assembly error, and bearing error of wind turbine gearbox respectively. In view of the floating meshing error resulting from meshing clearance variation caused by the simultaneous floating of all gears, this paper establishes a refined mathematical model of two-stage power split loading sharing coefficient calculation in consideration of multiple errors. Also obtains the regular curves of the load sharing coefficient and floating orbits of center gears, and conducts a load sharing coefficient test experiment of compound planetary gear system to verify the research results, which can provide scientific theory evidence for proper tolerance distribution and control in design and process.     

Steady-state and dynamic modeling of biohydrogen production in an integrated biohydrogen reactor clarifier system

Steady-state operational data from the integrated biohydrogen reactor clarifier system (IBRCS) during anaerobic treatment of glucose-based synthetic wastewater at HRT of 8 h and SRT ranging from 26 to 50 h and organic loading rates of 6.5–206 gCOD/L-d were used to calibrate and verify a process model of the system developed using BioWin. The model accurately predicted biomass concentrations in both the bioreactor and the clarifier supernatant with average percentage errors (APEs) of 4.6% and 10%, respectively. Hydrogen production rates and hydrogen yields predicted by the model were in close agreement with the observed experimental results as reflected by an APE of less than 4%, while the hydrogen content was well correlated with an APE of 10%. The successful modeling culminated in the accurate prediction of soluble metabolites, i.e. volatile fatty acids in the reactor with an APE of 14%. The calibrated model confirmed the advantages of decoupling of the solids retention time (SRT) from the hydraulic retention time (HRT) in biohydrogen production, with the average hydrogen yield decreasing from 3.0 mol H₂/mol glucose to 0.8 mol H₂/mol glucose upon elimination of the clarifier. Dynamic modeling showed that the system responds favorably to short-term hydraulic and organic surges, recovering back to the original condition. Furthermore, the dynamic simulation revealed that with a prolonged startup periods of 10 and 30 days, the IBRCS can be operated at an HRT of 4 h and OLR as high as 206 gCOD/L-d without inhibition and/or marked performance deterioration.     

Evaluation of the wind direction uncertainty and its impact on wake modeling at the Horns Rev offshore wind farm

Accurately quantifying wind turbine wakes is a key aspect of wind farm economics in large wind farms. This paper introduces a new simulation post‐processing method to address the wind direction uncertainty present in the measurements of the Horns Rev offshore wind farm. This new technique replaces the traditional simulations performed with the 10 min average wind direction by a weighted average of several simulations covering a wide span of directions. The weights are based on a normal distribution to account for the uncertainty from the yaw misalignment of the reference turbine, the spatial variability of the wind direction inside the wind farm and the variability of the wind direction within the averaging period. The results show that the technique corrects the predictions of the models when the simulations and data are averaged over narrow wind direction sectors. In addition, the agreement of the shape of the power deficit in a single wake situation is improved. The robustness of the method is verified using the Jensen model, the Larsen model and Fuga, which are three different engineering wake models. The results indicate that the discrepancies between the traditional numerical simulations and power production data for narrow wind direction sectors are not caused by an inherent inaccuracy of the current wake models, but rather by the large wind direction uncertainty included in the dataset. The technique can potentially improve wind farm control algorithms and layout optimization because both applications require accurate wake predictions for narrow wind direction sectors. © 2013 The Authors. Wind Energy published by John Wiley & Sons, Ltd.     

The possibilities of cooperation between a hydrogen generator and a wind farm

In this paper, a hydrogen generator and a wind farm were taken as the research objects. The H₂ generator consisted characteristics of laboratory-tested electrolyzers were determined as a function of the hydrogen mass flow. Determining the auxiliary power index of the device allowed the efficiency of the hydrogen generator to be determined as a function of hydrogen mass flow as well as the hydrogen generator relative power. The dynamic characteristics of a generator were also presented. The possibility of a given wind farm cooperating with hydrogen generators that are characterized by different powers and various efficiencies was simulated. Algorithm enables determination of hydrogen generators efficiency for devices with various performance in nominal operation point is shown. It has been shown that proper selection of the power of the hydrogen generator in relation to the power of the wind farm can ensure a high efficiency for the device.