Implementation of a torque and a collective pitch controller in a wind turbine simulator to characterize the dynamics at three control regions

As the capacity of wind turbines has increased, the loads on crucial components such as a gearbox, a generator, and blades are significantly increasing. An intelligent online monitoring system is indispensable to protect the excessive load on core components and manage a wind farm efficiently. In order to verify new online monitoring and diagnostic methods for such a monitoring system in advance, a wind turbine simulator is essential. For this purpose, we developed a simulator that has similar dynamics to an actual 3 MW wind turbine, and is thereby able to acquire a state of operation that closely resembles that of the 3 MW wind turbine under a variety of wind conditions.This paper describes the implementation of a torque and a collective pitch controller, which is used for a new type of simulator with the intention of exploiting online monitoring and diagnostic methods. The torque and the collective pitch controllers were developed to facilitate variable speed-variable pitch control strategies in the wind turbine simulator. Experiments demonstrated that three control regions were successfully deployed on the simulator, and thereby the simulator was operated at all control regions in a stable and accurate manner. Moreover, the strain and vibration measured from the blade and the gearbox showed different trends at three control regions. Therefore, a new type of simulator is an effective means to develop diagnostic and prognostic algorithms as well as online monitoring methods reflecting the dependency of dynamic characteristics on the control regions.     

Performance enhancement and load reduction of a 5 MW wind turbine blade

A wind turbine rotor blade, based on the U.S. National Renewable Energy Laboratory (NREL) 5 MW reference turbine, is optimized for minimum cost of energy through simultaneous consideration of aerodynamics and bend-twist coupling. Eighty-three total design variables are considered, encompassing airfoil shapes, chord and twist distributions, and the degree of bend-twist coupling in the blade. A recently developed method requiring significantly less computation than finite element analysis is used for planning and predicting the bend-twist coupling behavior of the rotor. Airfoil performance is computed using XFOIL, while the wind turbine loads and performance are computed using the NREL FAST code. The objective function is annual cost of energy (COE), where reductions in flapwise bending loads and blade surface area are assumed to decrease rotor cost through reduced material requirements. The developed optimization process projects decreased blade loads while maintaining wind turbine performance.     

S-Transform and its contribution to wind turbine condition monitoring

Condition monitoring (CM) has long been recognised as one of the best methods of reducing the operation and maintenance (O&M) costs of wind turbines (WTs). However, its potential in the wind industry has not been fully exploited. One of the major reasons is due to the lack of an efficient tool to properly process the WT CM signals, which are usually non-stationary in both time and frequency domains owing to the constantly varying operational and loading conditions experienced by WTs. For this reason, S-transform and its potential contribution to WT CM are researched in this paper. Following the discussion of the superiorities of S-transform to the Short-Time Fourier Transform (STFT) and Wavelet Transform, two S-transform based CM techniques are developed, dedicated for use on WTs. One is for tracking the energy variations of those fault-related characteristic frequencies under varying operational conditions (the energy rise of these frequencies usually indicates the presence of a fault); another is for assessing the health condition of WT gears and bearings, which have shown significant reliability issues in both onshore and offshore wind projects. In the paper, both proposed techniques have been verified experimentally, showing that they are valid for detecting both the mechanical and electrical faults occurring in the WT despite its varying operational and loading conditions.     

Aeroservoelastic design definition of a 20 MW common research wind turbine model

Wind turbine upscaling is motivated by the fact that larger machines can achieve lower levelized cost of energy. However, there are several fundamental issues with the design of such turbines, and there is little public data available for large wind turbine studies. To address this need, we develop a 20 MW common research wind turbine design that is available to the public. Multidisciplinary design optimization is used to define the aeroservoelastic design of the rotor and tower subject to the following constraints: blade‐tower clearance, structural stresses, modal frequencies, tip‐speed and fatigue damage at several sections of the tower and blade. For the blade, the design variables include blade length, twist and chord distribution, structural thicknesses distribution and rotor speed at the rated. The tower design variables are the height, and the diameter distribution in the vertical direction. For the other components, mass models are employed to capture their dynamic interactions. The associated cost of these components is obtained by using cost models. The design objective is to minimize the levelized cost of energy. The results of this research show the feasibility of a 20 MW wind turbine and provide a model with the corresponding data for wind energy researchers to use in the investigation of different aspects of wind turbine design and upscaling. Copyright © 2016 John Wiley & Sons, Ltd.     

Performance of a 3 kW wind turbine generator with variable pitch control system

A prototype 3 kW horizontal upwind type wind turbine generator of 4 m in diameter has been designed and examined under real wind conditions. The machine was designed based on the concept that even small wind turbines should have a variable pitch control system just as large wind turbines, especially in Japan where typhoons occur at least once a year. A characteristic of the machine is the use of a worm and gear system with a stepping motor installed in the center of the hub, and the rotational main shaft. The machine is constructed with no mechanical breaking system so as to avoid damage from strong winds. In a storm, the wind turbine is slowed down by adjusting the pitch angle and the maximum electrical load. Usually the machine is controlled at several stages depending on the rotational speed of the blades. Two control methods have been applied: the variable pitch angle, and regulation of the generator field current. The characteristics of the generator under each rotational speed and field current are first investigated in the laboratory. This paper describes the performances of the wind turbine in terms of the functions of wind turbine rotational speed, generated outputs, and its stability for wind speed changes. The expected performances of the machine have been confirmed under real wind conditions and compared with numerical simulation results. The wind turbine showed a power coefficient of 0.257 under the average wind speed of 7.3 m/s.     

A brief status on condition monitoring and fault diagnosis in wind energy conversion systems

There is a constant need for the reduction of operational and maintenance costs of Wind Energy Conversion Systems (WECSs). The most efficient way of reducing these costs would be to continuously monitor the condition of these systems. This allows for early detection of the degeneration of the generator health, facilitating a proactive response, minimizing downtime, and maximizing productivity. Wind generators are also inaccessible since they are situated on extremely high towers, which are normally 20 m or more in height. There are also plans to increase the number of offshore sites increasing the need for a remote means of WECS monitoring that eliminates some of the difficulties faced due to accessibility problems. Therefore and due to the importance of condition monitoring and fault diagnosis in WECS (blades, drive trains, and generators), and keeping in mind the need for future research, this paper is intended as a brief status describing different types of faults, their generated signatures, and their diagnostic schemes.     

Study of damage and repair of blades of a 300 kW wind turbine

The inspection of damages detected in some blades of 300 kW wind turbines revealed that the nature of these damages was probably due to a fatigue mechanism. The causes that had originated the failure (superficial cracks, geometric concentrator, abrupt change of thickness) have been studied, verifying, by means of the simplified evaluation procedure of fatigue life of the “Germanischer Lloyd” (GL) standard, that these causes can explain the failure detected in the period of time in which it happened.     

Seismic fragility analysis of 5 MW offshore wind turbine

Considering nonlinear soil–pile interaction, seismic fragility analysis of offshore wind turbine was performed. Interface between ground soils and piles were modeled as nonlinear spring elements. Ground excitation time histories were applied to spring boundaries. Two methods of applying ground motion were compared. Different time histories from free field analysis were applied to each boundary in the first loading plan (A). They were compared with the second loading plan (B) in which the same ground motion is applied to all boundaries. Critical displacement for wind turbine was proposed by using push-over analysis. Both the stress based and the displacement based fragility curves were obtained using dynamic responses for different peak ground accelerations (PGAs). In numerical example, it was shown that seismic responses from loading plan A are bigger than from plan B. It seems that the bigger ground motion at surface can cause less response at wind turbine due to phase difference between ground motions at various soil layers. Finally, it can be concluded that layer by layer ground motions from free field analysis should be used in seismic design of offshore wind turbine.     

Reducing sensor complexity for monitoring wind turbine performance using principal component analysis

Availability and reliability are among the priority concerns for deployment of distributed generation (DG) systems, particularly when operating in a harsh environment. Condition monitoring (CM) can meet the requirement but has been challenged by large amounts of data needing to be processed in real time due to the large number of sensors being deployed. This paper proposes an optimal sensor selection method based on principal component analysis (PCA) for condition monitoring of a DG system oriented to wind turbines. The research was motivated by the fact that salient patterns in multivariable datasets can be extracted by PCA in order to identify monitoring parameters that contribute the most to the system variation. The proposed method is able to correlate the particular principal component to the corresponding monitoring variable, and hence facilitate the right sensor selection for the first time for the condition monitoring of wind turbines. The algorithms are examined with simulation data from PSCAD/EMTDC and SCADA data from an operational wind farm in the time, frequency, and instantaneous frequency domains. The results have shown that the proposed technique can reduce the number of monitoring variables whilst still maintaining sufficient information to detect the faults and hence assess the system’s conditions.     

The field performance of a remote 10 kW wind turbine

The collection and analysis of 15 months of continuously recorded field data from a small remote wind–diesel power system at a coastal farm site are reported. The paper focuses on the available wind data and the performance of the 10 kW Bergey wind turbine.     

Research on a power quality monitoring technique for individual wind turbines

The extensive deployment of megawatt-scale wind turbines is bringing more challenges to the safety and stability of electric grid than ever before. This is not only because of the unstable wind over time but the increased risk of power quality pollution by defective wind turbines particularly when the turbines today are still experiencing various reliability issues. To prevent the power quality pollution by defective turbines, a new power quality monitoring technique dedicated for individual wind turbines is developed in this paper, so that the quality of the power generated by an individual turbine can be monitored by the wind turbine condition monitoring system. Through simulated and physical experiments on a specially designed test rig, some encouraging results have been achieved. It has been shown that the proposed technique is not only valid for monitoring the power quality of an individual wind turbine, but helpful in detecting the mechanical and electrical faults occurring in the wind turbines.     

Wind resource assessment and comparative economic analysis using AMOS data on a 30 MW wind farm at Yulchon district in Korea

Detailed feasibility studies are necessary for wind farm development projects because the profitability changes greatly according to wind resource, wind turbine, CAPEX (capital expenduture), OPEX (operation expenditure), SMP (system marginal price), and REC (renewable energy certificate) price. Although measuring wind data over one year in the proposed site is essential, it is a cost-intensive and time-consuming process; hence, in the early stages of development, pre-feasibility studies are conducted using reference wind data from the neighboring areas. In the present study, a pre-feasibility study was conducted in Yulchon district of South Korea to develop a 30-MW wind farm. A wind resource map of Yulchon district was predicted using the AMOS (Aerodome Meteorological Observation System) wind data measured at Yeosu Airport. Three cases of wind farms each with different wind turbines were designed, and comparative economic analysis was carried out. The wind farm designed with SL3000/113 wind turbine recorded the highest profitability with project NPV of 33.62 billion KRW(33.29 million USD, 24.33 million EUR) and project IRR of 9.81%.     

Transformation algorithm of wind turbine blade moment signals for blade condition monitoring

To simplify signal analysis on wind turbine blades and enable their efficient monitoring, this paper presents a novel method of transforming blade moment signals on a horizontal axis 3-blade wind turbine. Instead of processing 3-blade moment signals directly, the proposed algorithm transforms the three sinusoidal signals into two static signals relative to the center of blade rotation through vector synthesis and coordinate transformation, and eliminates frequency components due to blade rotation from the obtained signals. Moreover, as an alternative to a rotational sensor, a blade rotation angle estimator is introduced. Its effectiveness was confirmed through simulations and field tests on an actual wind turbine.     

Vibration response of a 2.3 MW wind turbine to yaw motion and shut down events

Structural health monitoring (SHM) is a process of implementing a damage detection strategy for a mechanical system. Wind turbine machinery stands to benefit from SHM significantly as the ability to detect early stages of damage before significant malfunction or structural failure occurs would reduce costs of wind power projects by reducing maintenance costs. Vibration analysis of dynamic structural response is an approach to SHM that has been successfully applied to mechanical and civil systems and shows some promise for wind turbine application. Traditionally, a setback to turbine vibration‐based SHM techniques has been the unavailability of turbine vibration response data. This study begins to address this issue by presenting vibration response for a commercial 2.3 MW turbine to a limited number of operating conditions. A database of acquired vibration response signals detailing turbine response to yaw motion, start‐up, operation and shutdown has been assembled. A Daubechies sixth‐order wavelet was used to perform an eight‐level discrete wavelet decomposition such that general trends and patterns within the signals could be identified. With further development, the presented analysis of vibration response may be integrated into routines to reduce downtime and failure frequency of utility scale wind turbines. Copyright © 2011 John Wiley & Sons, Ltd.     

LCA sensitivity analysis of a multi-megawatt wind turbine

During recent years renewables have been acquiring gradually a significant importance in the world market (especially in the Spanish energetic market) and in society; this fact makes clear the need to increase and improve knowledge of these power sources. Starting from the results of a Life Cycle Assessment (LCA) of a multi-megawatt wind turbine, this work is aimed to assess the relevance of different choices that have been made during its development. Looking always to cover the largest possible spectrum of options, four scenarios have been analysed, focused on four main phases of lifecycle: maintenance, manufacturing, dismantling, and recycling. These scenarios facilitate to assess the degree of uncertainty of the developed LCA due to choices made, excluding from the assessment the uncertainty due to the inaccuracy and the simplification of the environmental models used or spatial and temporal variability in different parameters. The work has been developed at all times using the of Eco-indicator99 LCA method.     

Fault diagnosis for a wind turbine transmission system based on manifold learning and Shannon wavelet support vector machine

Fault diagnosis for wind turbine transmission systems is an important task for reducing their maintenance cost. However, the non-stationary dynamic operating conditions of wind turbines pose a challenge to fault diagnosis for wind turbine transmission systems. In this paper, a novel fault diagnosis method based on manifold learning and Shannon wavelet support vector machine is proposed for wind turbine transmission systems. Firstly, mixed-domain features are extracted to construct a high-dimensional feature set characterizing the properties of non-stationary vibration signals from wind turbine transmission systems. Moreover, an effective manifold learning algorithm with non-linear dimensionality reduction capability, orthogonal neighborhood preserving embedding (ONPE), is applied to compress the high-dimensional feature set into low-dimensional eigenvectors. Finally, the low-dimensional eigenvectors are inputted into a Shannon wavelet support vector machine (SWSVM) to recognize faults. The performance of the proposed method was proved by successful fault diagnosis application in a wind turbine's gearbox. The application results indicated that the proposed method improved the accuracy of fault diagnosis.     

In-service testing of wind turbine towers using a microwave sensor

A remote-sensing technique based on microwave interferometry is applied to dynamic testing of wind turbine towers for power generation. A high-speed interferometric radar is able to sample the structure at a rate high enough for modal and transient analysis. An experimental campaign is reported carried out on wind turbine towers of a power plant in north Sardinia, Italy.     

Characteristics of a highly efficient propeller type small wind turbine with a diffuser

We studied the improved effects a diffuser had on the output power of small wind turbine systems, aiming to introduce these systems to radio relay stations as an independent power supply system. A frustum-shaped diffuser was chosen from an economical standpoint and wind speed distribution. The effect the diffuser's shape had on the wind speed was analyzed by simulation and showed that the wind speed in the diffuser was greatly influenced by the length and expansion angle of the diffuser, and maximum wind speed increased 1.7 times with the selection of the appropriate diffuser shape. The wind speed in the diffuser was fastest near the diffuser's entrance. We conducted field tests using a real examination device with a diffuser and confirmed that the output power of the wind power generator increased by up to 2.4 times compared to that of a conventional turbine. Moreover, it was confirmed that the diffuser was especially useful where the wind direction was constant.     

Feasibility of a fully autonomous wireless monitoring system for a wind turbine blade

Condition monitoring (CM) of wind turbine blades has significant benefits for wind farm operators and insurers alike. Blades present a particular challenge in terms of operations and maintenance: the wide range of materials used in their construction makes it difficult to predict lifetimes; loading is stochastic and highly variable; and access can be problematic due to the remote locations where turbines are frequently located, particularly for offshore installations. Whilst previous works have indicated that Micro Electromechanical Systems (MEMS) accelerometers are viable devices for measuring the vibrations from which diagnostic information can be derived, thus far there has been no analysis of how such a system would be powered. This paper considers the power requirement of a self-powered blade-tip autonomous system and how those requirements can be met. The radio link budget is derived for the system and the average power requirement assessed. Following this, energy harvesting methods such as photovoltaics, vibration, thermal and radio frequency (RF) are explored. Energy storage techniques and energy regulation for the autonomous system are assessed along with their relative merits. It is concluded that vibration (piezoelectric) energy harvesting combined with lithium-ion batteries are suitable selections for such a system.     

The concept of a smart wind turbine system

A smart wind turbine concept with variable length blades and an innovative hybrid mechanical-electrical power conversion system was analyzed. The variable length blade concept uses the idea of extending the turbine blades when wind speeds fall below rated level, hence increasing the swept area, and thus maintaining a relatively high power output. It is shown for a typical site, that the annual energy output of such a wind turbine that could double its blade length, could be twice that of a corresponding turbine with fixed length blades. From a cost analysis, it is shown that the concept would be feasible if the cost of the rotor could be kept less than 4.3 times the cost of a standard rotor with fixed length blades. Given the variable length blade turbine system exhibits a more-or-less linear maximum power curve, as opposed to a non-linear curve for the standard turbine, an innovative hybrid mechanical-electrical power conversion system was proposed and tested proving the feasibility of the concept.