Critical analysis of methods for mathematical modelling of wind turbines

Accurate modelling is crucial in designing an optimum system. Wind speed distribution of selected site, hub height and power output curve of chosen wind turbine, are the main factors which influence the performance of wind turbines, and therefore, these must be properly accounted for during modelling of the wind turbines.This paper presents comparative study of various methods for mathematical modelling of wind turbines, with reference to three commercially available wind turbins, with the help of an algorithm developed.It has been found that modelling methods, based on fundamental equations of power available in the wind, are cumbersome to use and do not correctly replicate the behaviour of actual wind turbines.Models based on a presumed shape of power curve, though simple to use, also lack the desired accuracy; however, they give satisfactory response for higher annual average wind speeds.Modelling methods in which actual power curve of a wind turbine is used for developing characteristic equations, by utilising curve fitting techniques of method of least squares and cubic spline interpolation, give accurate results for wind turbines having smooth power curve; whereas, for turbines having not so smooth power curve, model based on method of least squares is best suited.     

The wake structure in a 2D grid installation of the horizontal axis micro wind turbines

In order to develop applications for micro-wind turbines, an experimental analysis of the flow field around integrated micro-wind turbines was performed. The wake flows of a single turbine and 5×5 array unit were measured by using hot-wire and ultrasonic anemometers and particle image velocimetry (PIV). The present array of turbines follows a fundamental lattice layout; however, it has the flexibility to optimize its layout according to the environmental conditions. hot-wire and ultrasonic anemometers and PIV measurements were used for stand-alone turbines and their integrated systems. Comparisons between the mean velocity field and turbulent intensity were described for stand-alone full-scale and 1/10-scale wind turbine models. Thereafter, a typical array of the 1/10-scale model was assumed and its wake flow was investigated in a wind tunnel. The velocity profile and turbulence behind the array were measured and studied at different streamwise locations. The scale effect and model similarities were discussed. The experimental results show that a zone exists with constant and linear wake deficit ratios in the downstream regions.     

A Bayesian hierarchical assessment of night shift working for offshore wind farms

This article presents a Bayesian data-modelling approach to assessing operational efficiency at offshore wind farms. Input data are provided by an operational database provided by a large offshore wind farm which employs an advanced data management system. We explore the combination of datasets making up the database, using them to train a Bayesian hierarchical model which predicts weekly lost production from corrective maintenance and time-based availability. The approach is used to investigate the effect of technician work shift patterns, specifically addressing a strategy involving night shifts for corrective maintenance which was employed at the site throughout the winter. It was found that, for this particular site, there is an approximate annual increase in time-based technical availability of 0.64%. We explore the effect of modelling assumptions on cost savings; specifically, we explore variations in failure rate, price of electricity, number of technicians working night shift, extra staff wages, months of the year employing 24/7 working and extra vessel provision. Results vary quite significantly among the scenarios investigated, exemplifying the need to consider the question on a farm-by-farm basis.     

Modelling the effects of environmental conditions on wind turbine failures

Operation and maintenance is one of the main cost drivers of modern wind farms and has become an emerging field of research over the past years. Understanding the failure behaviour of wind turbines (WTs) can significantly enhance operation and maintenance processes and is essential for developing reliability and strategic maintenance models. Previous research has shown that especially the environmental conditions, to which the turbines are exposed to, affect their reliability drastically. This paper compares several advanced modelling techniques and proposes a novel approach to model WT system and component failures based on the site‐specific weather conditions. Furthermore, to avoid common problems in failure modelling, procedures for variable selection and complexity reduction are discussed and incorporated. This is applied to a big failure database comprised of 11 wind farms and 383 turbines. The results show that the model performs very well in several situations such as modelling general WT failures as well as failures of specific components. The latter is exemplified using gearbox failures.     

Very short-term wind speed forecasting with Bayesian structural break model

This paper examines a new time series method for very short-term wind speed forecasting. The time series forecasting model is based on Bayesian theory and structural break modeling, which could incorporate domain knowledge about wind speed as a prior. Besides this Bayesian structural break model predicts wind speed as a set of possible values, which is different from classical time series model's single-value prediction This set of predicted values could be used for various applications, such as wind turbine predictive control, wind power scheduling. The proposed model is tested with actual wind speed data collected from utility-scale wind turbines.     

Development of small domestic wind turbine with scoop and prediction of its annual power output

Based on an unperturbed airflow assumption and using a set of validated modelling methods, a series of activities were carried out to optimise an aerodynamic design of a small wind turbine for a built up area, where wind is significantly weaker and more turbulent than those open sites preferable for wind farms. These activities includes design of the blades using a FORTRAN code; design of the nose cones and nacelles, which then constituted the rotor along with the blades; optimisation of the rotor designs in the virtual wind tunnel developed in the first part of the study; and finally, estimation of the annual power output of this wind turbine calculated using hourly wind data of a real Scottish Weather Station. The predicted annual output of the finalised rotor was then compared with other commercial turbines and result was rather competitive.     

Intelligent integrated maintenance for wind power generation

A novel architecture and system for the provision of Reliability Centred Maintenance (RCM) for offshore wind power generation is presented. The architecture was developed by conducting a bottom‐up analysis of the data required to support RCM within this specific industry, combined with a top‐down analysis of the required maintenance functionality. The architecture and system consists of three integrated modules for intelligent condition monitoring, reliability and maintenance modelling, and maintenance scheduling that provide a scalable solution for performing dynamic, efficient and cost‐effective preventative maintenance management within this extremely demanding renewable energy generation sector. The system demonstrates for the first time the integration of state‐of‐the‐art advanced mathematical techniques: Random Forests, dynamic Bayesian networks and memetic algorithms in the development of an intelligent autonomous solution. The results from the application of the intelligent integrated system illustrated the automated detection of faults within a wind farm consisting of over 100 turbines, the modelling and updating of the turbines' survivability and creation of a hierarchy of maintenance actions, and the optimizing of the maintenance schedule with a view to maximizing the availability and revenue generation of the turbines. © 2015 The Authors. Wind Energy published by John Wiley & Sons Ltd     

A hybrid actuator disc – Full rotor CFD methodology for modelling the effects of wind turbine wake interactions on performance

The performance of individual wind turbines is crucial for maximum energy yield, however, their performance is often reduced when turbines are placed together in an array. The wake produced by the rotors interacts with downstream turbines, resulting in a reduction in power output. In this paper, we demonstrate a new and faster modelling technique which combines actuator disc theory, modelled using wind tunnel validated Computational Fluid Dynamics (CFD), and integrated into full rotor CFD simulations. This novel hybrid of techniques results in the ability to analyse performance when simulating various array layouts more rapidly and accurately than using either method on its own.It is shown that there is a significant power reduction from a downstream turbine that is subjected to the wake of an upstream turbine, and that this is due to both a reduction in power in the wind and also due to changes in the aerodynamics. Analysis of static pressure along the blade showed that as a result of wake interactions, a large reduction in the suction peak along the leading edge reduced the lift generated by the rotor and so reduced the torque production and the ability for the blade to extract energy from the wind.     

建筑密度对建筑物群内风能利用的影响

针对建筑物群内风能应用问题,采用CFD方法,对建筑密度分别为26%、20%、18%、16%、14%的5种建筑物群周围风速和湍流强度特征开展研究,分析建筑密度对建筑物群内风力机合理安装位置的影响方式。结果表明：在低于1.5H高度范围内,建筑物群的建筑密度越大,同一安装高度上适合于安装风力机的区域就越大,即越有利于建筑物群内风能的应用;在高度高于1.5H后,建筑密度对建筑物群内风力机安装位置的影响消失;无论建筑密度大小,在低于1.2H的高度范围内,建筑物群内不适合安装风力机;在高度高于1.45H后,可优先考虑将风力机安装于建筑物群内中间一排建筑物顶面,在建筑物顶面可优先将风力机安装于拐角位置;5种建筑密度的建筑物群内只考虑风速要求即可确定风力机的合理安装位置。     

Roof mounting site analysis for micro-wind turbines

Building-integrated micro-wind turbines are promising low-cost renewable energy devices. However, the take-up of micro-wind turbines in high density suburban environments is still very limited due to issues such as: a) low wind speeds; b) high turbulence intensity; and c) the perception of potentially high levels of aerodynamic noise generated by the turbines. The wind flow field above the roof of buildings in this environment is different to that over flat terrain or around isolated buildings. The effect of the local suburban topology on the wind speed and turbulence intensity fields in a given locality is therefore an important determinant of the optimal location of micro-wind turbines. This paper presents a numerical study of above roof wind flow characteristics in three suburban landscapes characterized by houses with different roof profiles, namely: pitched roofs, pyramidal roofs and flat roofs. Computational Fluid Dynamic (CFD) technique has been used to simulate the wind flow in such environments and to find the optimum turbine mounting locations. Results show how the wind flow characteristics are strongly dependent on the profile of the roofs. It is found that turbines mounted on flat roofs are likely to yield higher and more consistent power for the same turbine hub elevation than the other roof profiles.     

Fundamental time–domain wind turbine models for wind power studies

One critical task in any wind power interconnection study involves the modelling of wind turbines. This paper provides the most basic yet comprehensive time–domain wind turbine model upon which more sophisticated models along with their power and speed control mechanisms, can be developed. For this reason, this paper concentrates on the modelling of a fixed-speed wind turbine. The model includes turbine's aerodynamic, mechanical, and electrical components. Data for the rotor, drive-train, and electrical generator are given to allow replication of the model in its entirety. Each of the component-blocks of the wind turbine is modelled separately so that one can easily expand the model to simulate variable-speed wind turbines or customise the model to suit their needs. Then, an aggregate wind turbine model, or wind farm, is developed. This is followed by four case studies to demonstrate how the models can be used to study wind turbine operation and power grid integration issues. Results obtained from the case studies show that the models perform as expected.     

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.     

Wind energy statistics for large arrays of wind turbines (New England and Central U.S. Regions)

The performance characteristics have been simulated for large dispersed arrays of 500–1500 kW wind turbines producing power and feeding it directly into the New England or Central U.S. utility distribution grids. These studies, based on design power performance curves, indicate that in good wind environments the 500 kW generators can average (on an annual basis) up to 240 kW mean power output, and the 1500 kW generators can average up to 350 kW mean power output. Higher mean power output (averaging up to 470 kW) is indicated, however from a hypothetical 1125 kW rated power unit designed to operate at wind speeds near those observed throughout the study area, rather than the higher design operating wind speed of the 1500 kW unit. The beneficial effect of operating large disperse arrays of wind turbines is that available power output can be increased—if winds are not blowing over one part of the array, chances are they will over some other part of the array. These studies indicate that wind power availability levels of 200 kW per 1125 kW generator were 77–93 per cent, depending on season. Reasonably steady high wind power in winter and high afternoon peak wind power in summer (corresponding to peak air conditioning load) means that significant peak load displacement can be achieved without the use of storage.     

Reliability of wind turbine subassemblies

We have investigated the reliability of more than 6000 modern onshore wind turbines and their subassemblies in Denmark and Germany over 11 years and particularly changes in reliability of generators, gearboxes and converters in a subset of 650 turbines in Schleswig Holstein, Germany. We first start by considering the average failure rate of turbine populations and then the average failure rates of wind turbine subassemblies. This analysis yields some surprising results about which subassemblies are the most unreliable. Then we proceed to consider the failure intensity function variation with time for wind turbines in one of these populations, using the Power Law Process, of three subassemblies; generator, gearbox and converter. This analysis shows that wind turbine gearboxes seem to be achieving reliabilities similar to gearboxes outside the wind industry. However, wind turbine generators and converters are both achieving reliabilities considerably below that of other industries but the reliability of these subassemblies improves with time. The paper also considers different wind turbine concepts. Then we conclude by proposing that offshore wind turbines should be subject to more rigorous reliability improvement measures, such as more thorough subassembly testing, to eliminate early failures. The early focus should be on converters and generators.     

Aeroelastic analysis of a floating offshore wind turbine in platform‐induced surge motion using a fully coupled CFD‐MBD method

Modern offshore wind turbines are susceptible to blade deformation because of their increased size and the recent trend of installing these turbines on floating platforms in deep sea. In this paper, an aeroelastic analysis tool for floating offshore wind turbines is presented by coupling a high‐fidelity computational fluid dynamics (CFD) solver with a general purpose multibody dynamics code, which is capable of modelling flexible bodies based on the nonlinear beam theory. With the tool developed, we demonstrated its applications to the NREL 5 MW offshore wind turbine with aeroelastic blades. The impacts of blade flexibility and platform‐induced surge motion on wind turbine aerodynamics and structural responses are studied and illustrated by the CFD results of the flow field, force, and wake structure. Results are compared with data obtained from the engineering tool FAST v8.     

Failure rate,repair time and unscheduled O&M cost analysis of offshore wind turbines

Determining and understanding offshore wind turbine failure rates and resource requirement for repair are vital for modelling and reducing O&M costs and in turn reducing the cost of energy. While few offshore failure rates have been published in the past even less details on resource requirement for repair exist in the public domain. Based on ~350 offshore wind turbines throughout Europe this paper provides failure rates for the overall wind turbine and its sub‐assemblies. It also provides failure rates by year of operation, cost category and failure modes for the components/sub‐assemblies that are the highest contributor to the overall failure rate. Repair times, average repair costs and average number of technicians required for repair are also detailed in this paper. An onshore to offshore failure rate comparison is carried out for generators and converters based on this analysis and an analysis carried out in a past publication. The results of this paper will contribute to offshore wind O&M cost and resource modelling and aid in better decision making for O&M planners and managers. Copyright © 2015 John Wiley & Sons, Ltd.     

Wind tunnel study on wind and turbulence intensity profiles in wind turbine wake

In recent years, there has been a rapid development of the wind farms in Japan. It becomes very important to investigate the wind turbine arrangement in wind farm, in order that the wake of one wind turbine does not to interfere with the flow in other wind turbines. In such a case, in order to achieve the highest possible efficiency from the wind, and to install as many as possible wind turbines within a limited area, it becomes a necessity to study the mutual interference of the wake developed by wind turbines. However, there is no report related to the effect of the turbulence intensity of the external flow on the wake behind a wind turbine generated in the wind tunnel. In this paper, the measurement results of the averaged wind profile and turbulence intensity profile in the wake in the wind tunnel are shown when the turbulence intensity of the external wind was changed. The wind tunnel experiment is performed with 500mm-diameter two-bladed horizontal axis wind turbine and the wind velocity in wake is measured by an I-type hot wire probe. As a result, it is clarified that high turbulence intensities enable to the entrainment of the main flow and the wake and to recover quickly the velocity in the wake.     

Large eddy simulation of dynamically controlled wind turbines in an offshore environment

Accurate modelling of transient wind turbine wakes is an important component in the siting of turbines within wind farms because of wake structures that affect downwind turbine performance and loading. Many current industry tools for modelling these effects are limited to empirically derived predictions. A technique is described for coupling transient wind modelling with an aero‐elastic simulation to dynamically model both turbine operation and wake structures. The important feature of this approach is a turbine model in a flow simulation, which actively responds to transient wind events through the inclusion of controller actions such as blade pitching and regulation of generator torque. The coupled nature of the aero‐elastic/flow simulation also allows recording of load and control data, which permits the analysis of turbine interaction in multiple turbine systems. An aero‐elastic turbine simulation code and a large eddy simulation (LES) solver using an actuator disc model were adapted for this work. Coupling of the codes was implemented with the use of a software framework to transfer data between simulations in a synchronous manner. A computationally efficient simulation was developed with the ability to model turbines exhibiting standard baseline control operating in an offshore environment. Single and multiple wind turbine instances were modelled in a transient flow domain to investigate wake structures and wake interaction effects. Blade loading data were analysed to quantify the increased fluctuating loads on downwind turbines. The results demonstrate the successful implementation of the coupled simulation and quantify the effect of the dynamic‐turbine model. Copyright © 2012 John Wiley & Sons, Ltd.     

Uncertainty in wind climate parameters and their influence on wind turbine fatigue loads

According to the wind turbine standard IEC 61400-1, structural integrity of wind turbines is determined either by direct reference to wind data or by load calculation. In both cases, deterministic values are applied and uncertainties neglected for the wind climate parameters and the structural resistance.The uncertainty related to the wind climate parameters depends highly on the presence, duration and quality of on-site wind measurements, and the perturbations introduced by flow modelling. For the wind speed distribution, the uncertainty is considered in assessment of the annual energy production. For other wind climate parameters which potentially have a large influence on the wind turbine loads, the uncertainty is often not well investigated.This paper presents a probabilistic framework for assessment of the structural reliability level of wind turbines in fatigue loading. Uncertainty of the site specific wind climate parameters at each turbine position is estimated based on the local wind measurements, speed-up factors and the distance between the wind turbine and the measuring position. The framework is demonstrated for a wind turbine project in flat terrain. The results show that the uncertainty in the site specific wind climate parameters normally accounts for 10–30% of the total uncertainty in the structural reliability analyses.     

Survey of modelling methods for wind turbine wakes and wind farms

This article provides an overview and analysis of different wake‐modelling methods which may be used as prediction and design tools for both wind turbines and wind farms. We also survey the available data concerning the measurement of wind magnitudes in both single wakes and wind farms, and of loading effects on wind turbines under single‐ and multiple‐wake conditions. The relative merits of existing wake and wind farm models and their ability to reproduce experimental results are discussed. Conclusions are provided concerning the usefulness of the different modelling approaches examined, and difficult issues which have not yet been satisfactorily treated and which require further research are discussed. Copyright © 1999 John Wiley & Sons, Ltd.