Showing papers on "Turbine published in 2013"

Fault-Tolerant Control of Wind Turbines: A Benchmark Model

Abstract: This paper presents a test benchmark model for the evaluation of fault detection and accommodation schemes. This benchmark model deals with the wind turbine on a system level, and it includes sensor, actuator, and system faults, namely faults in the pitch system, the drive train, the generator, and the converter system. Since it is a system-level model, converter and pitch system models are simplified because these are controlled by internal controllers working at higher frequencies than the system model. The model represents a three-bladed pitch-controlled variable-speed wind turbine with a nominal power of 4.8 MW. The fault detection and isolation (FDI) problem was addressed by several teams, and five of the solutions are compared in the second part of this paper. This comparison relies on additional test data in which the faults occur in different operating conditions than in the test data used for the FDI design.

Progress and recent trends of wind energy technology

Abstract: In this paper, along with the progress of modern wind energy technology, the trends of wind energy technology and potential challenges have been studied thoroughly. It is estimated that within the next 2–3 decades, the Vertical Axis Wind Turbine (VAWT) can dominate the wind-energy technology. The VAWT requires less land space and using the same space; it is capable of producing more wind energy than that of its counterpart. By implying the Fish Schooling Concept effectively and successfully, it is possible to advance the wind-energy technology more. In the last 3–4 decades, the wind turbine capacity has been increased around 30–40 times. With the increase of wind energy capacity, the demand of the energy storage system has been increased significantly. Along with the many energy storage systems, fuel cells and batteries are the two most promising devices to meet the demand in RE systems. The wind-energy technology is established itself but not yet fully mature and hence there are many areas where improvements are required to reduce the cost of wind energy.

Nonlinear model predictive control of wind turbines using LIDAR

Abstract: LIDAR systems are able to provide preview information of wind disturbances at various distances in front of wind turbines. This technology paves the way for new control concepts in wind energy such as feedforward control and model predictive control. This paper compares a nonlinear model predictive controller with a baseline controller, showing the advantages of using the wind predictions in the optimization problem to reduce wind turbine extreme and fatigue loads on tower and blades as well as to limit the pitch rates. The wind information is obtained by a detailed simulation of a LIDAR system. The controller design is evaluated and tested in a simulation environment with coherent gusts and a set of turbulent wind fields using a detailed aeroelastic model of the wind turbine over the full operation region. Results show promising load reduction up to 50% for extreme gusts and 30% for lifetime fatigue loads without negative impact on overall energy production. This controller can be considered as an upper bound for other LIDAR assisted controllers that are more suited for real time applications. Copyright © 2012 John Wiley & Sons, Ltd.

Wind turbine reliability analysis

Abstract: Against the background of steadily increasing wind power generation worldwide, wind turbine manufacturers are continuing to develop a range of configurations with different combinations of pitch control, rotor speeds, gearboxes, generators and converters. This paper categorizes the main designs, focusing on their reliability by bringing together and comparing data from a selection of major studies in the literature. These are not particularly consistent but plotting failure rates against hours lost per failure reveals that problems with blades and gearboxes tend to lead to the greatest downtimes. New, larger wind turbines tend to fail more frequently than smaller ones so condition monitoring will become increasingly necessary if levels of reliability are to be improved.

Open-Circuit Fault Diagnosis in PMSG Drives for Wind Turbine Applications

Abstract: Condition monitoring and fault diagnosis are currently considered crucial means to increase the reliability and availability of wind turbines and, consequently, to reduce the wind energy cost. With similar goals, direct-drive wind turbines based on permanent magnet synchronous generators (PMSGs) with full-scale power converters are an emerging and promising technology. Numerous studies show that power converters are a significant contributor to the overall failure rate of modern wind turbines. In this context, open-circuit fault diagnosis in the two power converters of a PMSG drive for wind turbine applications is addressed in this paper. A diagnostic method is proposed for each power converter, allowing real-time detection and localization of multiple open-circuit faults. The proposed methods are suitable for integration into the drive controller and triggering remedial actions. In order to prove the reliability and effectiveness of the proposed fault diagnostic methods, several simulation and experimental results are presented.

Review of morphing concepts and materials for wind turbine blade applications

Abstract: With increasing size of wind turbines, new approaches to load control are required to reduce the stresses in blades. Experimental and numerical studies in the fields of helicopter and wind turbine blade research have shown the potential of shape morphing in reducing blade loads. However, because of the large size of modern wind turbine blades, more similarities can be found with wing morphing research than with helicopter blades. Morphing technologies are currently receiving significant interest from the wind turbine community because of their potential high aerodynamic efficiency, simple construction and low weight. However, for actuator forces to be kept low, a compliant structure is needed. This is in apparent contradiction to the requirement for the blade to be load carrying and stiff. This highlights the key challenge for morphing structures in replacing the stiff and strong design of current blades with more compliant structures. Although not comprehensive, this review gives a concise list of the most relevant concepts for morphing structures and materials that achieve compliant shape adaptation for wind turbine blades.

A Comprehensive LVRT Control Strategy for DFIG Wind Turbines With Enhanced Reactive Power Support

Abstract: The paper presents a new control strategy to enhance the ability of reactive power support of a doubly fed induction generator (DFIG) based wind turbine during serious voltage dips. The proposed strategy is an advanced low voltage ride through (LVRT) control scheme, with which a part of the captured wind energy during grid faults is stored temporarily in the rotor's inertia energy and the remaining energy is available to the grid while the DC-link voltage and rotor current are kept below the dangerous levels. After grid fault clearance, the control strategy ensures smooth release of the rotor's excessive inertia energy into the grid. Based on these designs, the DFIG's reactive power capacity on the stator and the grid side converter is handled carefully to satisfy the new grid code requirements strictly. Simulation studies are presented and discussed.

Validation of a FAST semi-submersible floating wind turbine numerical model with DeepCwind test data

Abstract: There are global efforts in the offshore wind community to develop reliable floating wind turbine technologies that are capable of exploiting the abundant deepwater wind resource. These efforts require validated numerical simulation tools to predict the coupled aero-hydro-servo-elastic behavior of such systems. To date, little has been done in the public domain to validate floating wind turbine simulation tools. This work begins to address this problem by presenting the validation of a model constructed in the National Renewable Energy Laboratory (NREL) floating wind turbine simulator FAST with 1/50th-scale model test data for a semi-submersible floating wind turbine system. The test was conducted by the University of Maine DeepCwind program at Maritime Research Institute Netherlands' offshore wind/wave basin, located in the Netherlands. The floating wind turbine used in the tests was a 1/50th-scale model of the NREL 5-MW horizontal-axis reference wind turbine with a 126 m rotor diameter. This turbine was mounted to the DeepCwind semi-submersible floating platform. This paper first outlines the details of the floating system studied, including the wind turbine, tower, platform, and mooring components. Subsequently, the calibration procedures used for tuning the FAST floating wind turbine model are discussed. Following this calibration, comparisons of FAST predictions and test data are presented that focus on system global and structural response resulting from aerodynamic and hydrodynamic loads. The results indicate that FAST captures many of the pertinent physics in the coupled floating wind turbine dynamics problem. In addition, the results highlight potential areas of improvement for both FAST and experimentation procedures to ensure accurate numerical modeling of floating wind turbine systems.

Turbulent character of wind energy.

Abstract: Wind turbines generate electricity from turbulent wind. Large fluctuations, and, more importantly, frequent wind gusts cause a highly fluctuating electrical power feed into the grid. Such effects are the hallmark of high-frequency turbulence. Here we show evidence that it is the complex structure of turbulence that dominates the power output for one single wind turbine as well as for an entire wind farm. We illustrate the highly intermittent, peaked nature of wind power fed into the grid. Multifractal scaling is observed, as described initially by Kolmogorov's 1962 theory of turbulence. In parallel, we propose a stochastic model that converts wind speed signals into power output signals with appropriate multifractal statistics. As more and more wind turbines become integrated into our electric grids, a proper understanding of this intermittent power source must be worked out to ensure grid stability in future networks. Thus, our results stress the need for a profound understanding of the physics of turbulence and its impact on wind energy.

On the interaction between a turbulent open channel flow and an axial-flow turbine

Abstract: A laboratory experiment was performed to study the dynamically rich interaction of a turbulent open channel flow with a bed-mounted axial-flow hydrokinetic turbine. An acoustic Doppler velocimeter and a torque transducer were used to simultaneously measure at high temporal resolution the three velocity components of the flow at various locations upstream of the turbine and in the wake region and turbine power, respectively. Results show that for sufficiently low frequencies the instantaneous power generated by the turbine is modulated by the turbulent structure of the approach flow. The critical frequency above which the response of the turbine is decoupled from the turbulent flow structure is shown to vary linearly with the angular frequency of the rotor. The measurements elucidate the structure of the turbulent turbine wake, which is shown to persist for at least fifteen rotor diameters downstream of the rotor, and a new approach is proposed to quantify the wake recovery, based on the growth of the largest scale motions in the flow. Spectral analysis is employed to demonstrate the dominant effect of the tip vortices in the energy distribution in the near-wake region and uncover meandering motions.

Advanced Algorithms for Wind Turbine Power Curve Modeling

Abstract: A wind turbine power curve essentially captures the performance of the wind turbine. The power curve depicts the relationship between the wind speed and output power of the turbine. Modeling of wind turbine power curve aids in performance monitoring of the turbine and also in forecasting of power. This paper presents the development of parametric and nonparametric models of wind turbine power curves. Parametric models of the wind turbine power curve have been developed using four and five parameter logistic expressions. The parameters of these expressions have been solved using advanced algorithms like genetic algorithm (GA), evolutionary programming (EP), particle swarm optimization (PSO), and differential evolution (DE). Nonparametric models have been evolved using algorithms like neural networks, fuzzy c-means clustering, and data mining. The modeling of wind turbine power curve is done using five sets of data; one is a statistically generated set and the others are real-time data sets. The results obtained have been compared using suitable performance metrics and the best method for modeling of the power curve has been obtained.

Effect of transients on Francis turbine runner life: a review

Abstract: The present electricity market and the injection of power generated using intermittent energy sources have brought instability in the operation of the power grid. This has resulted in frequent load variations, emergency shut-down and restart, total load rejections, and off-design operation of grid connected hydraulic turbines. The present paper reviews the available literature summarizing the effects of transients on Francis turbine investigated experimentally, numerically, and analytically. Transients create both steady and unsteady pressure loading on the runner blade, resulting in cyclic stresses and fatigue development in the runner. These effects shorten the runner life, increase cost of plant operation, and loss of power generation. The reviewed literature has shown that one start–stop cycle can shorten predefined refurbishment time up to 15 hours. Turbine start–stop cannot be avoided, but runner life may be improved by minimizing the unfavourable pressure loading on the blades during transients thr...

High-fidelity simulation comparison of wake mitigation control strategies for a two-turbine case

Abstract: Wind turbines arranged in a wind plant impact each other through their wakes. Wind plant control is an active research field that attempts to improve wind plant performance by modifying individual turbine controllers to take into account these turbine-wake interactions. In this paper, we use high-fidelity simulations of a two-turbine fully-waked scenario to investigate the potential of several wake mitigation strategies. The strategies, including modification of yaw and tilt angle, as well as repositioning of the downstream turbine, represent a mix of known and novel approaches. The simulation results are compared through change relative to a baseline operation in terms of overall power capture and loading on the upstream and downstream turbine.

Modeling turbine wakes and power losses within a wind farm using LES: An application to the Horns Rev offshore wind farm

Abstract: A modeling framework is proposed and validated to simulate turbine wakes and associated power losses in wind farms. It combines the large-eddy simulation (LES) technique with blade element theory and a turbine-model-specific relationship between shaft torque and rotational speed. In the LES, the turbulent subgrid-scale stresses are parameterized with a tuning-free Lagrangian scale-dependent dynamic model. The turbine-induced forces and turbine-generated power are modeled using a recently developed actuator-disk model with rotation (ADM-R), which adopts blade element theory to calculate the lift and drag forces (that produce thrust, rotor shaft torque and power) based on the local simulated flow and the blade characteristics. In order to predict simultaneously the turbine angular velocity and the turbine-induced forces (and thus the power output), a new iterative dynamic procedure is developed to couple the ADM-R turbine model with a relationship between shaft torque and rotational speed. This relationship, which is unique for a given turbine model and independent of the inflow condition, is derived from simulations of a stand-alone wind turbine in conditions for which the thrust coefficient can be validated. Comparison with observed power data from the Horns Rev wind farm shows that better power predictions are obtained with the dynamic ADM-R than with the standard ADM, which assumes a uniform thrust distribution and ignores the torque effect on the turbine wakes and rotor power. The results are also compared with the power predictions obtained using two commercial wind-farm design tools (WindSim and WAsP). These models are found to underestimate the power output compared with the results from the proposed LES framework.

Using Data-Mining Approaches for Wind Turbine Power Curve Monitoring: A Comparative Study

Abstract: Four data-mining approaches for wind turbine power curve monitoring are compared. Power curve monitoring can be applied to evaluate the turbine power output and detect deviations, causing financial loss. In this research, cluster center fuzzy logic, neural network, and k-nearest neighbor models are built and their performance compared against literature. Recently developed adaptive neuro-fuzzy-interference system models are set up and their performance compared with the other models, using the same data. Literature models often neglect the influence of the ambient temperature and the wind direction. The ambient temperature can influence the power output up to 20%. Nearby obstacles can lower the power output for certain wind directions. The approaches proposed in literature and the ANFIS models are compared by using wind speed only and two additional inputs. The comparison is based on the mean absolute error, root mean squared error, mean absolute percentage error, and standard deviation using data coming from three pitch regulated turbines rating 2 MW each. The ability to highlight performance deviations is investigated by use of real measurements. The comparison shows the decrease of error rates and of the ANFIS models when taking into account the two additional inputs and the ability to detect faults earlier.

A large-eddy simulation study of wake propagation and power production in an array of tidal-current turbines

Abstract: This paper presents our initial work in performing large-eddy simulations of tidal turbine array flows. First, a horizontally periodic precursor simulation is performed to create turbulent flow data. Then those data are used as inflow into a tidal turbine array two rows deep and infinitely wide. The turbines are modelled using rotating actuator lines, and the finite-volume method is used to solve the governing equations. In studying the wakes created by the turbines, we observed that the vertical shear of the inflow combined with wake rotation causes lateral wake asymmetry. Also, various turbine configurations are simulated, and the total power production relative to isolated turbines is examined. We found that staggering consecutive rows of turbines in the simulated configurations allows the greatest efficiency using the least downstream row spacing. Counter-rotating consecutive downstream turbines in a non-staggered array shows a small benefit. This work has identified areas for improvement. For example, using a larger precursor domain would better capture elongated turbulent structures, and including salinity and temperature equations would account for density stratification and its effect on turbulence. Additionally, the wall shear stress modelling could be improved, and more array configurations could be examined.

Bleed air systems for use with aircrafts and related methods

Abstract: Bleed air systems for use with aircrafts and related methods are disclosed. An example apparatus includes a turbo-compressor including a compressor having a compressor inlet fluidly coupled to a low-pressure compressor of the aircraft engine and a compressor outlet fluidly coupled to a first system of an aircraft. The turbo-compressor also includes a turbine inlet fluidly coupled to a high-pressure compressor of the aircraft engine and a turbine outlet fluidly coupled to a second system of the aircraft.

Bearing Fault Diagnosis for Direct-Drive Wind Turbines via Current-Demodulated Signals

Abstract: Bearing faults account for a large portion of all faults in wind turbine generators (WTGs). Current-based bearing fault diagnosis techniques have great economic benefits and are potential to be adopted by the wind energy industry. This paper models the modulation effects of bearing faults on the stator currents of a direct-drive wind turbine equipped with a permanent-magnet synchronous generator (PMSG) operating with a variable shaft rotating frequency. Based on the analysis, a method consisting of appropriate current frequency and amplitude demodulation algorithms and a 1P-invariant power spectrum density algorithm is proposed for bearing fault diagnosis of variable-speed direct-drive wind turbines using only one-phase stator current measurements, where 1P frequency stands for the shaft rotating frequency of a wind turbine. Experimental results on a direct-drive wind turbine equipped with a PMSG operating in a wind tunnel are provided to verify the proposed fault diagnosis method. The proposed method is demonstrated to have advantages over the method of directly using stator current measurements for WTG bearing fault diagnosis.

Adaptive neuro-fuzzy approach for wind turbine power coefficient estimation

Abstract: Wind energy has become a large contender of traditional fossil fuel energy, particularly with the successful operation of multi-megawatt sized wind turbines. However, reasonable wind speed is not adequately sustainable everywhere to build an economical wind farm. In wind energy conversion systems, one of the operational problems is the changeability and fluctuation of wind. In most cases, wind speed can vacillate rapidly. Hence, quality of produced energy becomes an important problem in wind energy conversion plants. Several control techniques have been applied to improve the quality of power generated from wind turbines. In this study, the adaptive neuro-fuzzy inference system (ANFIS) is designed and adapted to estimate optimal power coefficient value of the wind turbines. Neural network in ANFIS adjusts parameters of membership function in the fuzzy logic of the fuzzy inference system (FIS). The back propagation learning algorithm is used for training this network. This intelligent controller is implemented using Matlab/Simulink and the performances are investigated. The simulation results presented in this paper show the effectiveness of the developed method.

Validation of the dynamic wake meander model for loads and power production in the Egmond aan Zee wind farm

Abstract: This paper investigates wake effects on load and power production by using the dynamic wake meander (DWM) model implemented in the aeroelastic code HAWC2. The instationary wind farm flow characteristics are modeled by treating the wind turbine wakes as passive tracers transported downstream using a meandering process driven by the low frequent cross-wind turbulence components. The model complex is validated by comparing simulated and measured loads for the Dutch Egmond aan Zee wind farm consisting of 36 Vestas V90 turbine located outside the coast of the Netherlands. Loads and production are compared for two distinct wind directions—a free wind situation from the dominating southwest and a full wake situation from northwest, where the observed turbine is operating in wake from five turbines in a row with 7D spacing. The measurements have a very high quality, allowing for detailed comparison of both fatigue and min–mean–max loads for blade root flap, tower yaw and tower bottom bending moments, respectively. Since the observed turbine is located deep inside a row of turbines, a new method on how to handle multiple wakes interaction is proposed. The agreement between measurements and simulations is excellent regarding power production in both free and wake sector, and a very good agreement is seen for the load comparisons too. This enables the conclusion that wake meandering, caused by large scale ambient turbulence, is indeed an important contribution to wake loading in wind farms. Copyright © 2012 John Wiley & Sons, Ltd.