Articles | Volume 3, issue 2
https://doi.org/10.5194/wes-3-767-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-3-767-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Oct 2018
Research article |
| 24 Oct 2018
| 24 Oct 2018
From wind to loads: wind turbine site-specific load estimation with surrogate models trained on high-fidelity load databases
Nikolay Dimitrov
CORRESPONDING AUTHOR
DTU Wind Energy, Technical University of Denmark, Risø Campus, Frederiksborgvej 399, 4000 Roskilde, Denmark
Mark C. Kelly
DTU Wind Energy, Technical University of Denmark, Risø Campus, Frederiksborgvej 399, 4000 Roskilde, Denmark
Andrea Vignaroli
DTU Wind Energy, Technical University of Denmark, Risø Campus, Frederiksborgvej 399, 4000 Roskilde, Denmark
Jacob Berg
DTU Wind Energy, Technical University of Denmark, Risø Campus, Frederiksborgvej 399, 4000 Roskilde, Denmark
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83 citations as recorded by crossref.
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- Power Enhancement of a Vertical Axis Wind Turbine Equipped with an Improved Duct M. Ranjbar et al. 10.3390/en14185780
- Statistical modeling of fully nonlinear hydrodynamic loads on offshore wind turbine monopile foundations using wave episodes and targeted CFD simulations through active sampling S. Guth et al. 10.1002/we.2880
- Recursive Bayesian estimation of wind load on a monopile-supported offshore wind turbine using output-only measurements A. Mehrjoo et al. 10.1016/j.ymssp.2024.112183
- Investigation of Sensitivity Analysis of Crucial Dynamic Characteristics of Offshore Wind Turbine Utilizing Polynomial Chaos Expansion F. Han et al. 10.1115/1.4067797
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- Probabilistic surrogate modeling of damage equivalent loads on onshore and offshore wind turbines using mixture density networks D. Singh et al. 10.5194/wes-9-1885-2024
- Physics-Informed Neural Network surrogate model for bypassing Blade Element Momentum theory in wind turbine aerodynamic load estimation S. Baisthakur & B. Fitzgerald 10.1016/j.renene.2024.120122
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- Probabilistic surrogate modeling of offshore wind-turbine loads with chained Gaussian processes D. Singh et al. 10.1088/1742-6596/2265/3/032070
- Statistical impact of wind-speed ramp events on turbines, via observations and coupled fluid-dynamic and aeroelastic simulations M. Kelly et al. 10.5194/wes-6-1227-2021
- Wind load assessment in marine and offshore engineering standards H. Kozmar et al. 10.1016/j.oceaneng.2022.110872
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- Probabilistic fatigue surrogate model of bimodal tension process for a semi-submersible platform Y. Zhao & S. Dong 10.1016/j.oceaneng.2020.108501
- Optimal design of experiments for computing the fatigue life of an offshore wind turbine based on stepwise uncertainty reduction A. Cousin et al. 10.1016/j.strusafe.2024.102483
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- Wind farm layout optimization with load constraints using surrogate modelling R. Riva et al. 10.1088/1742-6596/1618/4/042035
- Conditional variational autoencoders for probabilistic wind turbine blade fatigue estimation using Supervisory, Control, and Data Acquisition data C. Mylonas et al. 10.1002/we.2621
- Data‐driven modeling for fatigue loads of large‐scale wind turbines under active power regulation J. Yang et al. 10.1002/we.2589
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- A digital twin solution for floating offshore wind turbines validated using a full-scale prototype E. Branlard et al. 10.5194/wes-9-1-2024
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- A control-oriented load surrogate model based on sector-averaged inflow quantities: capturing damage for unwaked, waked, wake-steering and curtailed wind turbines A. Guilloré et al. 10.1088/1742-6596/2767/3/032019
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- Wind turbine site-specific load estimation using artificial neural networks calibrated by means of high-fidelity load simulations L. Schröder et al. 10.1088/1742-6596/1037/6/062027
- Risk-based approach for rational categorization of damage observations from wind turbine blade inspections N. Dimitrov 10.1088/1742-6596/1037/4/042021
81 citations as recorded by crossref.
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- Surrogate models for predicting stall-induced vibrations on wind turbine blades C. Santhanam et al. 10.1088/1742-6596/2265/3/032005
- Improving site-dependent power curve prediction accuracy using regression trees S. Barber & H. Nordborg 10.1088/1742-6596/1618/6/062003
- Virtual sensors for wind turbines with machine learning‐based time series models N. Dimitrov & T. Göçmen 10.1002/we.2762
- Fatigue reliability analysis of floating offshore wind turbines under the random environmental conditions based on surrogate model G. Zhao et al. 10.1016/j.oceaneng.2024.119686
- Power Enhancement of a Vertical Axis Wind Turbine Equipped with an Improved Duct M. Ranjbar et al. 10.3390/en14185780
- Statistical modeling of fully nonlinear hydrodynamic loads on offshore wind turbine monopile foundations using wave episodes and targeted CFD simulations through active sampling S. Guth et al. 10.1002/we.2880
- Recursive Bayesian estimation of wind load on a monopile-supported offshore wind turbine using output-only measurements A. Mehrjoo et al. 10.1016/j.ymssp.2024.112183
- Investigation of Sensitivity Analysis of Crucial Dynamic Characteristics of Offshore Wind Turbine Utilizing Polynomial Chaos Expansion F. Han et al. 10.1115/1.4067797
- Given-data probabilistic fatigue assessment for offshore wind turbines using Bayesian quadrature E. Fekhari et al. 10.1017/dce.2023.27
- Probabilistic surrogates for flow control using combined control strategies C. Debusscher et al. 10.1088/1742-6596/2265/3/032110
- On long-term fatigue damage estimation for a floating offshore wind turbine using a surrogate model D. Liu et al. 10.1016/j.renene.2024.120238
- Optimizing wind farm control through wake steering using surrogate models based on high-fidelity simulations P. Hulsman et al. 10.5194/wes-5-309-2020
- Probabilistic surrogate modeling of damage equivalent loads on onshore and offshore wind turbines using mixture density networks D. Singh et al. 10.5194/wes-9-1885-2024
- Physics-Informed Neural Network surrogate model for bypassing Blade Element Momentum theory in wind turbine aerodynamic load estimation S. Baisthakur & B. Fitzgerald 10.1016/j.renene.2024.120122
- Surrogate Modeling and Aeroelastic Analysis of a Wind Turbine with Down-Regulation, Power Boosting, and IBC Capabilities V. Pettas & P. Cheng 10.3390/en17061284
- Variable importance analysis of wind turbine extreme responses with Shapley value explanation X. Zhang & N. Dimitrov 10.1016/j.renene.2024.121049
- Surrogate model for fast simulation of turbine loads in wind farms E. Bossanyi 10.1088/1742-6596/2265/4/042038
- A study of Stall-Induced Vibrations using Surrogate-Based Optimization C. Santhanam et al. 10.1016/j.renene.2023.05.054
- Data-driven surrogate model for wind turbine damage equivalent load R. Haghi & C. Crawford 10.5194/wes-9-2039-2024
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- Influence of wind-wave characteristics on floating wind turbine loads: A sensitivity analysis across different floating concepts L. Reddy et al. 10.1088/1742-6596/2767/6/062030
- Østerild: A natural laboratory for atmospheric turbulence A. Peña 10.1063/1.5121486
- Incorporation of floater rotation and displacement in a static wind farm simulator R. Riva et al. 10.1088/1742-6596/2767/6/062019
- Wind turbine load estimation using machine learning and transfer learning G. Xu et al. 10.1088/1742-6596/2265/3/032108
- Probabilistic surrogate modeling of offshore wind-turbine loads with chained Gaussian processes D. Singh et al. 10.1088/1742-6596/2265/3/032070
- Statistical impact of wind-speed ramp events on turbines, via observations and coupled fluid-dynamic and aeroelastic simulations M. Kelly et al. 10.5194/wes-6-1227-2021
- Wind load assessment in marine and offshore engineering standards H. Kozmar et al. 10.1016/j.oceaneng.2022.110872
- Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals D. Conti et al. 10.5194/wes-6-841-2021
- Operational-based annual energy production uncertainty: are its components actually uncorrelated? N. Bodini & M. Optis 10.5194/wes-5-1435-2020
- From wind conditions to operational strategy: optimal planning of wind turbine damage progression over its lifetime N. Requate et al. 10.5194/wes-8-1727-2023
- Surrogate models for parameterized representation of wake‐induced loads in wind farms N. Dimitrov 10.1002/we.2362
- The surrogate model for short-term extreme response prediction based on ANN and Kriging algorithm G. Zhao et al. 10.1016/j.apor.2024.104196
- Global trends in the performance of large wind farms based on high-fidelity simulations S. Andersen et al. 10.5194/wes-5-1689-2020
- Atmospheric condition identification in multivariate data through a metric for total variation N. Hamilton 10.5194/amt-13-1019-2020
- From SCADA to lifetime assessment and performance optimization: how to use models and machine learning to extract useful insights from limited data N. Dimitrov & A. Natarajan 10.1088/1742-6596/1222/1/012032
- Retrospective de‐trending of wind site turbulence using machine learning F. Tough & E. Hart 10.1002/we.2720
- Enhanced shear and veer in the Taiwan Strait during typhoon passage S. Müller et al. 10.1088/1742-6596/2767/9/092030
- Data-Driven Stochastic Fatigue Load Modeling for Fatigue Failure Simulation of Onshore Wind Turbine Foundations R. Gao et al. 10.1061/AJRUA6.RUENG-1513
- Efficient layout optimization of offshore wind farm based on load surrogate model and genetic algorithm X. Zhang et al. 10.1016/j.energy.2024.133106
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- Research on dynamic response prediction of semi-submersible wind turbine platform in real sea test model based on machine learning H. Jiang et al. 10.1016/j.apor.2023.103808
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- Augmented Kalman filter with a reduced mechanical model to estimate tower loads on a land-based wind turbine: a step towards digital-twin simulations E. Branlard et al. 10.5194/wes-5-1155-2020
- Long-term fatigue damage assessment for a floating offshore wind turbine under realistic environmental conditions X. Li & W. Zhang 10.1016/j.renene.2020.06.043
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- Real-Time Hybrid Simulation with Polynomial Chaos NARX Modeling for Seismic Response Evaluation of Structures Subjected to Stochastic Ground Motions X. Gao et al. 10.1061/(ASCE)ST.1943-541X.0003451
- Reliability‐based layout optimization in offshore wind energy systems C. Clark et al. 10.1002/we.2664
- Analysis of the influence of climate change on the fatigue lifetime of offshore wind turbines using imprecise probabilities C. Hübler & R. Rolfes 10.1002/we.2572
- Reaction loads analysis of floating offshore wind turbines: Methods and applications in the modal-based modeling framework C. Høeg & Z. Zhang 10.1016/j.oceaneng.2022.112952
- Efficient fatigue damage estimation of offshore wind turbine foundation under wind-wave actions T. Li et al. 10.1016/j.jcsr.2024.108903
- Virtual fatigue diagnostics of wake-affected wind turbine via Gaussian Process Regression L. Avendaño-Valencia et al. 10.1016/j.renene.2021.02.003
- FarmConners market showcase results: wind farm flow control considering electricity prices K. Kölle et al. 10.5194/wes-7-2181-2022
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- A surrogate model approach for associating wind farm load variations with turbine failures L. Schröder et al. 10.5194/wes-5-1007-2020
- Data-driven time series forecasting of offshore wind turbine loads H. Muhammad Amri et al. 10.1088/1742-6596/2767/5/052060
- Surrogate model uncertainty in wind turbine reliability assessment R. Slot et al. 10.1016/j.renene.2019.11.101
- On the extension of streamwise turbulence intensity profile beyond the atmospheric surface layer under neutral to unstable stratifications M. Mataji 10.1016/j.jweia.2022.105100
- Probabilistic fatigue surrogate model of bimodal tension process for a semi-submersible platform Y. Zhao & S. Dong 10.1016/j.oceaneng.2020.108501
- Optimal design of experiments for computing the fatigue life of an offshore wind turbine based on stepwise uncertainty reduction A. Cousin et al. 10.1016/j.strusafe.2024.102483
- Surrogate models for the blade element momentum aerodynamic model using non-intrusive polynomial chaos expansions R. Haghi & C. Crawford 10.5194/wes-7-1289-2022
- Wind farm layout optimization with load constraints using surrogate modelling R. Riva et al. 10.1088/1742-6596/1618/4/042035
- Conditional variational autoencoders for probabilistic wind turbine blade fatigue estimation using Supervisory, Control, and Data Acquisition data C. Mylonas et al. 10.1002/we.2621
- Data‐driven modeling for fatigue loads of large‐scale wind turbines under active power regulation J. Yang et al. 10.1002/we.2589
- Wind farm layout optimization in complex terrain considering wind turbine fatigue load constraint W. Liu et al. 10.1063/5.0249777
- A digital twin solution for floating offshore wind turbines validated using a full-scale prototype E. Branlard et al. 10.5194/wes-9-1-2024
- Efficient Loads Surrogates for Waked Turbines in an Array K. Shaler et al. 10.1088/1742-6596/2265/3/032095
- Sensitivity of fatigue reliability in wind turbines: effects of design turbulence and the Wöhler exponent S. Mozafari et al. 10.5194/wes-9-799-2024
- Polymorphic uncertainty in met-ocean conditions and the influence on fatigue loads C. Hübler et al. 10.1088/1742-6596/1669/1/012005
- Modelling of turbine power and local wind conditions in wind farm using an autoencoder neural network S. Dou & N. Dimitrov 10.1088/1742-6596/2265/3/032069
- A Machine Learning Method for Modeling Wind Farm Fatigue Load Y. Miao et al. 10.3390/app12157392
- Multi-Criteria Optimization of Wind Turbines in an Offshore Wind Farm with Monopile Foundation Considering Structural Integrity and Energy Generation S. Ali et al. 10.3390/jmse12122313
- A control-oriented load surrogate model based on sector-averaged inflow quantities: capturing damage for unwaked, waked, wake-steering and curtailed wind turbines A. Guilloré et al. 10.1088/1742-6596/2767/3/032019
- Sensitivity analysis of the effect of wind characteristics and turbine properties on wind turbine loads A. Robertson et al. 10.5194/wes-4-479-2019
- System-level design studies for large rotors D. Zalkind et al. 10.5194/wes-4-595-2019
2 citations as recorded by crossref.
- Wind turbine site-specific load estimation using artificial neural networks calibrated by means of high-fidelity load simulations L. Schröder et al. 10.1088/1742-6596/1037/6/062027
- Risk-based approach for rational categorization of damage observations from wind turbine blade inspections N. Dimitrov 10.1088/1742-6596/1037/4/042021
Latest update: 06 Mar 2025
Short summary
Wind energy site suitability assessment procedures often require estimating the loads a wind turbine will be subject to when installed. The estimation is often time-consuming and requires several iterations. We have developed a procedure for quick and accurate estimation of site-specific wind turbine loads. Our approach employs computationally efficient parametric models that are calibrated to high-fidelity load simulations. The result is a significant reduction in computation efforts.
Wind energy site suitability assessment procedures often require estimating the loads a wind...
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