scholarly journals T2FL: An Efficient Model for Wind Turbine Fatigue Damage Prediction for the Two-Turbine Case

Energies ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 1306 ◽  
Author(s):  
Christos Galinos ◽  
Jonas Kazda ◽  
Wai Hou Lio ◽  
Gregor Giebel
Keyword(s):  
Wind Turbine ◽  
Fatigue Damage ◽  
Surrogate Model ◽  
Wind Farm ◽  
Computationally Efficient ◽  
Detailed Model ◽  
Set Point ◽  
Power Set ◽  
Fatigue Loads ◽  
Aeroelastic Simulations

Wind farm load assessment is typically conducted using Computational Fluid Dynamics (CFD) or aeroelastic simulations, which need a lot of computer power. A number of applications, for example wind farm layout optimisation, turbine lifetime estimation and wind farm control, requires a simplified but sufficiently detailed model for computing the turbine fatigue load. In addition, the effect of turbine curtailment is particularly important in the calculation of the turbine loads. Therefore, this paper develops a fast and computationally efficient method for wind turbine load assessment in a wind farm, including the wake effects. In particular, the turbine fatigue loads are computed using a surrogate model that is based on the turbine operating condition, for example, power set-point and turbine location, and the ambient wind inflow information. The Turbine to Farm Loads (T2FL) surrogate model is constructed based on a set of high fidelity aeroelastic simulations, including the Dynamic Wake Meandering model and an artificial neural network that uses the Bayesian Regularisation (BR) and Levenberg–Marquardt (LM) algorithms. An ensemble model is used that outperforms model predictions of the BR and LM algorithms independently. Furthermore, a case study of a two turbine wind farm is demonstrated, where the turbine power set-point and fatigue loads can be optimised based on the proposed surrogate model. The results show that the downstream turbine producing more power than the upstream turbine is favourable for minimising the load. In addition, simulation results further demonstrate that the accumulated fatigue damage of turbines can be effectively distributed amongst the turbines in a wind farm using the power curtailment and the proposed surrogate model.

scholarly journals Surrogate based aeroelastic design optimization of tip extensions on a modern 10MW wind turbine

2020 ◽  
Author(s):  
Thanasis Barlas ◽  
Néstor Ramos-García ◽  
Georg Raimund Pirrung ◽  
Sergio González Horcas
Keyword(s):  
Wind Turbine ◽  
Design Optimization ◽  
Surrogate Model ◽  
Bending Moment ◽  
Vortex Method ◽  
Optimized Design ◽  
Near Wake ◽  
Direct Optimization ◽  
Design Variables ◽  
Aeroelastic Simulations

Abstract. Advanced aeroelastically optimized tip extensions are among rotor innovation concepts which could contribute to higher performance and lower cost of wind turbines. A novel design optimization framework for wind turbine blade tip extensions, based on surrogate aeroelastic modeling is presented. An academic wind turbine is modelled in an aeroelastic code equipped with a near wake aerodynamic module, and tip extensions with complex shapes are parametrized using 11 design variables. The design space is explored via full aeroelastic simulations in extreme turbulence and a surrogate model is fitted to the data. Direct optimization is performed based on the surrogate model, seeking to maximize the power of the retrofitted turbine within the ultimate load constraints. The presented optimized design achieves a load neutral gain of up to 6 % in annual energy production. Its performance is further evaluated in detail by means of the near wake model used for the generation of the surrogate model, and compared with a higher fidelity aerodynamic module comprising a hybrid filament-particle-mesh vortex method with a lifting-line implementation. A good agreement between the solvers is obtained at low turbulence levels, while differences in predicted power and flap-wise blade root bending moment grow with increasing turbulence intensity.

Site-Specific Design Optimization of 1.5–2.0 MW Wind Turbines

2001 ◽  
Vol 123 (4) ◽  
pp. 296-303 ◽  
Author(s):  
Peter Fuglsang ◽  
Kenneth Thomsen
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Load Prediction ◽  
Specific Design ◽  
Site Specific ◽  
Cost Of Energy ◽  
Fatigue Loads

A method is presented for site-specific design of wind turbines where cost of energy is minimized. A numerical optimization algorithm was used together with an aeroelastic load prediction code and a cost model. The wind climate was modeled in detail including simulated turbulence. Response time series were calculated for relevant load cases, and lifetime equivalent fatigue loads were derived. For the fatigue loads, an intelligent sensitivity analysis was used to reduce computational costs. Extreme loads were derived from statistical response calculations of the Davenport type. A comparison of a 1.5 MW stall regulated wind turbine in normal onshore flat terrain and in an offshore wind farm showed a potential increase in energy production of 28% for the offshore wind farm, but also significant increases in most fatigue loads and in cost of energy. Overall design variables were optimized for both sites. Compared to an onshore optimization, the offshore optimization increased swept area and rated power whereas hub height was reduced. Cost of energy from manufacture and installation for the offshore site was reduced by 10.6% to 4.6¢. This reduction makes offshore wind power competitive compared with today’s onshore wind turbines. The presented study was made for one wind turbine concept only, and many of the involved sub models were based on simplified assumptions. Thus there is a need for further studies of these models.

scholarly journals A Model to Calculate Fatigue Damage Caused by Partial Waking during Wind Farm Optimization

2020 ◽  
Author(s):  
Andrew P. J. Stanley ◽  
Jennifer King ◽  
Christopher Bay ◽  
Andrew Ning
Keyword(s):  
Fatigue Damage ◽  
Wind Farm ◽  
Wind Farms ◽  
Fatigue Loading ◽  
Layout Optimization ◽  
Computationally Efficient ◽  
Wind Farm Layout ◽  
Wind Farm Layout Optimization ◽  
Velocity Turbulence ◽  
Research And Design

Abstract. Wind turbines in wind farms often operate in waked or partially waked conditions, which can greatly increase the fatigue damage. Some fatigue considerations may be included, but currently a full fidelity analysis of the increased damage a turbine experiences in a wind farm is not considered in wind farm layout optimization because existing models are too computationally expensive. In this paper, we present a model to calculate fatigue damage caused by partial waking on a wind turbine that is computationally efficient and can be included in wind farm layout optimization. The model relies on analytic velocity, turbulence, and loads models commonly used in farm research and design, and captures some of the effects of turbulence on the fatigue loading. Compared to high-fidelity simulation data, our model accurately predicts the damage trends of various waking conditions. We also perform example wind farm layout optimizations with our presented model in which we maximize the annual energy production (AEP) of a wind farm while constraining the damage of the turbines in the farm. The results of our optimization show that the turbine damage can be significantly reduced, more than 10 %, with only a small sacrifice of around 0.07 % to the AEP, or the damage can be reduced by 20 % with an AEP sacrifice of 0.6 %.

A review on fatigue damages in the wind turbines: Challenges in determining and reducing fatigue failures in wind turbine blades

2019 ◽  
Vol 44 (4) ◽  
pp. 434-451
Author(s):  
Karthikeyan Ravikumar ◽  
Rajkumar Subbiah ◽  
Nalini Ranganathan ◽  
Joseph Bensingh ◽  
Abdul Kader ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Crack Growth ◽  
Fatigue Damage ◽  
Wind Turbines ◽  
Turbine Blades ◽  
Wind Turbine Blades ◽  
Aerodynamic Loads ◽  
The World ◽  
Fatigue Loads ◽  
Fatigue Failures

The wind energy has been recognised as one of the rising sustainable energies in the world. The wind turbines are subjected to high aerodynamic loads and they cause vibrations due to the wake formation. The magnitude of the applied loads has significant effects on the crack propagation. The fatigue loads have been identified as one of the key sources of damage, with delamination as the main cause for the failure of the turbine blades. The article presents a review of fatigue damages that have been experienced in the wind turbine blades, and factors that are influenced due to the fatigue loads are discussed. The causes and effects of the fatigue loads have been highlighted, and the ways for preventing the fatigue damage by improving the design lifetime are mainly concentrated in review. The overall review gives an idea for determining and reducing the crack growth in wind turbine blades.

scholarly journals Validation of a lookup-table approach to modeling turbine fatigue loads in wind farms under active wake control

2019 ◽  
Vol 4 (4) ◽  
pp. 549-561 ◽  
Author(s):  
Hector Mendez Reyes ◽  
Stoyan Kanev ◽  
Bart Doekemeijer ◽  
Jan-Willem van Wingerden
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
Power Production ◽  
Computational Effort ◽  
Lookup Table ◽  
Good Prediction ◽  
Load Modeling ◽  
Modeling Approach ◽  
Fatigue Loads ◽  
Aeroelastic Simulations

Abstract. Wake redirection is an active wake control (AWC) concept that is known to have a high potential for increasing the overall power production of wind farms. Being based on operating the turbines with intentional yaw misalignment to steer wakes away from downstream turbines, this control strategy requires careful attention to the load implications. However, the computational effort required to perform an exhaustive analysis of the site-specific loads on each turbine in a wind farm is unacceptably high due to the huge number of aeroelastic simulations required to cover all possible inflow and yaw conditions. To reduce this complexity, a practical load modeling approach is based on “gridding”, i.e., performing simulations only for a subset of the range of environmental and operational conditions that can occur. Based on these simulations, a multi-dimensional lookup table (LUT) can be constructed containing the fatigue and extreme loads on all components of interest. Using interpolation, the loads on each turbine in the farm can the be predicted for the whole range of expected conditions. Recent studies using this approach indicate that wake redirection can increase the overall power production of the wind farm and at the same time decrease the lifetime fatigue loads on the main components of the individual turbines. As the present level of risk perception related to operation with large yaw misalignment is still substantial, it is essential to increase the confidence level in this LUT-based load modeling approach to further derisk the wake redirection strategy. To this end, this paper presents the results of a series of studies focused on the validation of different aspects of the LUT load modeling approach. These studies are based on detailed aeroelastic simulations, two wind tunnel tests, and a full-scale field test. The results indicate that the LUT approach is a computationally efficient methodology for assessing the farm loads under AWC, which achieves generally good prediction of the load trends.

scholarly journals More accurate aeroelastic wind-turbine load simulations using detailed inflow information

2019 ◽  
Vol 4 (2) ◽  
pp. 303-323
Author(s):  
Mads Mølgaard Pedersen ◽  
Torben Juul Larsen ◽  
Helge Aagaard Madsen ◽  
Gunner Christian Larsen
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Turbulence Intensity ◽  
Atmospheric Stability ◽  
Pitot Tube ◽  
Wind Speeds ◽  
Inflow Turbulence ◽  
Mean Wind Speed ◽  
Fatigue Loads ◽  
Aeroelastic Simulations

Abstract. In this paper, inflow information is extracted from a measurement database and used for aeroelastic simulations to investigate if using more accurate inflow descriptions improves the accuracy of the simulated wind-turbine fatigue loads. The inflow information is extracted from nearby meteorological masts (met masts) and a blade-mounted five-hole pitot tube. The met masts provide measurements of the inflow at fixed positions some distance away from the turbine, whereas the pitot tube measures the inflow while rotating with the rotor. The met mast measures the free-inflow velocity; however the measured turbulence may evolve on its way to the turbine, pass beside the turbine or the mast may be in the wake of the turbine. The inflow measured by the pitot tube, in comparison, is very representative of the wind that acts on the turbine, as it is measured close to the blades and also includes variations within the rotor plane. Nevertheless, this inflow is affected by the presence of the turbine; therefore, an aerodynamic model is used to estimate the free-inflow velocities that would have occurred at the same time and position without the presence of the turbine. The inflow information used for the simulations includes the mean wind speed field and trend, the turbulence intensity, the wind-speed shear profile, atmospheric stability-dependent turbulence parameters, and the azimuthal variations within the rotor plane. In addition, instantaneously measured wind speeds are used to constrain the turbulence. It is concluded that the period-specific turbulence intensity must be used in the aeroelastic simulations to make the range of the simulated fatigue loads representative for the range of the measured fatigue loads. Furthermore, it is found that the one-to-one correspondence between the measured and simulated fatigue loads is improved considerably by using inflow characteristics extracted from the pitot tube instead of using the met-mast-based sensors as input for the simulations. Finally, the use of pitot-tube-recorded wind speeds to constrain the inflow turbulence is found to significantly decrease the variation of the simulated loads due to different turbulence realizations (seeds), whereby the need for multiple simulations is reduced.

scholarly journals Receding Horizon Optimization of Wind Farm Active Power Distribution with Power Tracking Error and Transmission Loss

Processes ◽  
2018 ◽  
Vol 6 (12) ◽  
pp. 259 ◽  
Author(s):  
Jingchun Chu ◽  
Ling Yuan ◽  
Zhongwei Lin ◽  
Wei Xu ◽  
Zhenyu Chen
Keyword(s):  
Wind Turbine ◽  
Power Distribution ◽  
Wind Farm ◽  
Transmission Loss ◽  
Tracking Error ◽  
Active Power ◽  
Receding Horizon ◽  
Turbine Generator ◽  
Set Point ◽  
Wind Turbine Generator

In this paper, a receding-horizon optimization strategy is introduced to optimize the wind farm active power distribution with power tracking error and transmission loss. Based on the wind farm transmission connections, a wind farm can be divided into clusters, in which the wind turbine generator systems connected to one booster station can be taken as one cluster, and different clusters connected from booster stations to the farm-level main transformer output the electric power to the grid. Thus, in the proposed strategy, the power tracking characteristic of the wind turbine generator system is modeled as a first-order system to quantify the power tracking error during the power tracking dynamic process, where the power transmission losses from wind turbine generator systems to booster stations are also modeled and considered in the optimization. The proposed strategy is applied to distribute the active power set-point within a cluster while the clusters’ set-point still follows the conventional strategy of the wind farm. Simulation results show significant improvement for both optimization targets of the proposed strategy.

scholarly journals Validation of a lookup-table approach to modeling turbine fatigue loads in wind farms under active wake control

2019 ◽  
Author(s):  
Hector Mendez Reyes ◽  
Stoyan Kanev ◽  
Bart Doekemeijer ◽  
Jan-Willem van Wingerden
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
Power Production ◽  
Computational Effort ◽  
Lookup Table ◽  
Good Prediction ◽  
Operational Conditions ◽  
Modeling Approach ◽  
Fatigue Loads ◽  
Aeroelastic Simulations

Abstract. Wake redirection is an active wake control (AWC) concept that is known to have a high potential for increasing the overall power production of wind farms. Being based on operating the turbines with intentional yaw misalignment to steer wakes away from downstream turbines, this control strategy requires careful attention to the loads implications. However, the computational effort required to perform an exhaustive analysis of the site-specific loads on each turbine in a wind farm is unacceptably high due to the huge number of aeroelastic simulations required to cover all possible inflow and yaw conditions. To reduce this complexity, a practical loads modeling approach is based on gridding, i.e., performing simulations only for a subset of the range of environmental and operational conditions that can occur. Based on these simulations, a multi-dimensional lookup table (LUT) can be constructed containing the fatigue and extreme loads on all components of interest. Using interpolation, the loads on each turbine in the farm can the be predicted for the whole range of expected conditions. Recent studies using this approach indicate that wake redirection can increase the overall power production of the wind farm and at the same time decrease the lifetime fatigue loads on the main components of the individual turbines. As the present level of risk perception related to operation with large yaw misalignment is still substantial, it is essential to increase the confidence level in this LUT-based loads modeling approach to further derisk the wake redirection strategy. To this end, this paper presents the results of a series of studies focused on the validation of different aspects of the LUT loads modeling approach. These studies are based on detailed aeroelastic simulations, two wind tunnel tests, and a full-scale field test. The results indicate that the LUT approach is a computationally efficient methodology for assessing the farm loads under AWC, which achieves generally good prediction of the load trends.

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