Romania has a high wind potential, representing more than 14,000 MW. After significant investments of over 5 billion euros made starting 2010, many wind farms were developed in regions with efficient potential, from the South-East part of the country. Nowadays, in January 2018, in Romania were registered 3025 MW produced by wind energy, representing around 30% of the total generated energy. To establish the efficient areas for future wind power plants a massive campaign of wind’s monitoring was developed, in the entire country. The paper presents a solution of the numerical modeling for the registered environmental data, significant atmospheric parameters. The complex realized database will allow future implementations of wind power plants. The data measured and stored refer at wind intensity and direction, pressure, temperature, humidity, solar radiation, and drew points, performed during four years with masts of height 70 m, situated at distance of 20 km each other. By numerical modeling is created a correlation and prediction of the measured data, plotted in correspondence to each elevation of the measuring stations. It was also analyzed the perturbations induced by the masts presence. Firstly, are mentioned some aspects referring to the masts installation, the solution adopted for a proper distribution through the analyzed area. The database elaboration was a challenge, due to the large amount of data recorded at intervals of 10 minutes (some parameters at 10 seconds) for a period of four years, for more than 12 parameters instantly. Besides these, there were stored and some other data referring at daily produced energy with some existent wind turbines. They will be considered as data input for future developments, with new generations of turbines, more efficient. It is created an original method to compact the database in order to use small amounts of computer memory. With the daily collected data was made and stored separately the average, maximum, and minimum wind velocity, for each day and month, from the measurements at time interval of 10 minutes. The relations between the values registered are within classification areas CL-4 and CL-8, allowing performing illustrations of over-prediction and under-prediction. The wind velocities under 4 m/s are stored in a separate folder because they are not useful in wind turbine functioning. These values are used only for estimation the future wind farms efficiency. The uncertainties are analyzed and are assessed the limits of errors, for the land classification CL-4. There are presented numerical results, some conclusions, and references.
{"title":"Numerical Modeling and Prediction of the Significant Parameters for Wind Monitoring","authors":"V. Radulescu","doi":"10.1115/iowtc2019-7518","DOIUrl":"https://doi.org/10.1115/iowtc2019-7518","url":null,"abstract":"\u0000 Romania has a high wind potential, representing more than 14,000 MW. After significant investments of over 5 billion euros made starting 2010, many wind farms were developed in regions with efficient potential, from the South-East part of the country. Nowadays, in January 2018, in Romania were registered 3025 MW produced by wind energy, representing around 30% of the total generated energy. To establish the efficient areas for future wind power plants a massive campaign of wind’s monitoring was developed, in the entire country. The paper presents a solution of the numerical modeling for the registered environmental data, significant atmospheric parameters. The complex realized database will allow future implementations of wind power plants. The data measured and stored refer at wind intensity and direction, pressure, temperature, humidity, solar radiation, and drew points, performed during four years with masts of height 70 m, situated at distance of 20 km each other. By numerical modeling is created a correlation and prediction of the measured data, plotted in correspondence to each elevation of the measuring stations. It was also analyzed the perturbations induced by the masts presence. Firstly, are mentioned some aspects referring to the masts installation, the solution adopted for a proper distribution through the analyzed area. The database elaboration was a challenge, due to the large amount of data recorded at intervals of 10 minutes (some parameters at 10 seconds) for a period of four years, for more than 12 parameters instantly. Besides these, there were stored and some other data referring at daily produced energy with some existent wind turbines. They will be considered as data input for future developments, with new generations of turbines, more efficient. It is created an original method to compact the database in order to use small amounts of computer memory. With the daily collected data was made and stored separately the average, maximum, and minimum wind velocity, for each day and month, from the measurements at time interval of 10 minutes. The relations between the values registered are within classification areas CL-4 and CL-8, allowing performing illustrations of over-prediction and under-prediction. The wind velocities under 4 m/s are stored in a separate folder because they are not useful in wind turbine functioning. These values are used only for estimation the future wind farms efficiency. The uncertainties are analyzed and are assessed the limits of errors, for the land classification CL-4. There are presented numerical results, some conclusions, and references.","PeriodicalId":131294,"journal":{"name":"ASME 2019 2nd International Offshore Wind Technical Conference","volume":"223 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123241873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wind turbines are subjected to dynamic loads during their service life. The yaw bearing is an important part which also bears these loads. In this study, a series of 5-megawatt (MW) wind turbines are analyzed for their dynamic response under normal operating conditions while exposed to turbulent wind. These models are Onshore, Monopile, ITI Barge, Spar, Tension-Leg Platform (TLP), Semi-Submerisible. TurbSim is used to prescribe turbulent-wind inflow and a time domain FAST code is applied in order to conduct the Aero-Hydro-Servo-Elastic coupled analysis on the yaw loads of the wind turbines. Three different average wind velocities are examined to compare the load response of the wind turbine to turbulent wind on the yaw bearing. A Gumbel distribution coupled maximum likelihood method is used to predict ultimate loads. And the rain flow counting algorithm, the linear cumulative damage law and S-N curve theory are used to predict the damage equivalent load. The results should aid the fatigue design of yaw bearing and the yaw control system according to different wind turbine design.
{"title":"Dynamic Load Response Analysis on Yaw Bearing of Wind Turbine to Turbulent Wind","authors":"Jianwen Xu","doi":"10.1115/iowtc2019-7588","DOIUrl":"https://doi.org/10.1115/iowtc2019-7588","url":null,"abstract":"\u0000 Wind turbines are subjected to dynamic loads during their service life. The yaw bearing is an important part which also bears these loads. In this study, a series of 5-megawatt (MW) wind turbines are analyzed for their dynamic response under normal operating conditions while exposed to turbulent wind. These models are Onshore, Monopile, ITI Barge, Spar, Tension-Leg Platform (TLP), Semi-Submerisible. TurbSim is used to prescribe turbulent-wind inflow and a time domain FAST code is applied in order to conduct the Aero-Hydro-Servo-Elastic coupled analysis on the yaw loads of the wind turbines. Three different average wind velocities are examined to compare the load response of the wind turbine to turbulent wind on the yaw bearing. A Gumbel distribution coupled maximum likelihood method is used to predict ultimate loads. And the rain flow counting algorithm, the linear cumulative damage law and S-N curve theory are used to predict the damage equivalent load. The results should aid the fatigue design of yaw bearing and the yaw control system according to different wind turbine design.","PeriodicalId":131294,"journal":{"name":"ASME 2019 2nd International Offshore Wind Technical Conference","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131845218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Magnus Harrold, P. Thies, P. Halswell, L. Johanning, David Newsam, C. B. Ferreira
Existing mooring systems for floating offshore wind turbines are largely based on designs from the oil and gas industry. Even though these can ensure the safe station keeping of the floating wind platform, the design of the mooring system is currently largely conservative, leading to additional expense in an industry striving to achieve cost reduction. Recent interest in the usage of mooring materials with non-linear stiffness has shown that they have the potential to reduce peak line loads, ultimately reducing cost. This paper reports on the combined physical testing and numerical modeling of a hydraulic-based mooring component with these characteristics. The results suggest that the inclusion of the component as part of the OC4 semi-submersible platform can reduce the peak line loads by 10%. The paper also discusses a number of challenges associated with modeling and testing dynamic mooring materials.
{"title":"Demonstration of the Intelligent Mooring System for Floating Offshore Wind Turbines","authors":"Magnus Harrold, P. Thies, P. Halswell, L. Johanning, David Newsam, C. B. Ferreira","doi":"10.1115/iowtc2019-7544","DOIUrl":"https://doi.org/10.1115/iowtc2019-7544","url":null,"abstract":"\u0000 Existing mooring systems for floating offshore wind turbines are largely based on designs from the oil and gas industry. Even though these can ensure the safe station keeping of the floating wind platform, the design of the mooring system is currently largely conservative, leading to additional expense in an industry striving to achieve cost reduction. Recent interest in the usage of mooring materials with non-linear stiffness has shown that they have the potential to reduce peak line loads, ultimately reducing cost. This paper reports on the combined physical testing and numerical modeling of a hydraulic-based mooring component with these characteristics. The results suggest that the inclusion of the component as part of the OC4 semi-submersible platform can reduce the peak line loads by 10%. The paper also discusses a number of challenges associated with modeling and testing dynamic mooring materials.","PeriodicalId":131294,"journal":{"name":"ASME 2019 2nd International Offshore Wind Technical Conference","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132360916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Estimating reliably and rapidly the losses of wind turbine annual energy production due to blade surface damage is essential for optimizing maintenance planning and, in the frequent case of leading edge erosion, assessing the need for protective coatings. These requirements prompted the development of the prototype system presented herein, using machine learning, wind turbine engineering codes and computational fluid dynamics to estimate wind turbine annual energy production losses due to blade leading edge damage. The power curve of a turbine with nominal or damaged blade surfaces is determined respectively with the open-source FAST and AeroDyn codes of the National Renewable Energy Laboratory, both using the blade element momentum theory for turbine aerodynamics. The loss prediction system is designed to map a given three-dimensional geometry of a damaged blade onto a damaged airfoil database, which, in this study, consists of 2700+ airfoil geometries, each analyzed with Navier-Stokes computational fluid dynamics over the working range of angles of attack. To avoid the need for lengthy aerodynamic analyses to assess losses due to damages monitored during turbine operation, the airfoil force data of a damaged turbine required by AeroDyn are rapidly obtained using a machine learning method trained using the pre-existing airfoil database. Presented results focus on the analysis of a utility-scale offshore wind turbine and demonstrate that realistic estimates of the annual energy production loss due to leading edge surface damage can be obtained in just a few seconds using a standard desktop computer, highlighting the viability and the industrial impact of this new technology for wind farm energy losses due to blade erosion.
{"title":"Machine Learning-Aided Assessment of Wind Turbine Energy Losses due to Blade Leading Edge Damage","authors":"A. Cavazzini","doi":"10.1115/iowtc2019-7578","DOIUrl":"https://doi.org/10.1115/iowtc2019-7578","url":null,"abstract":"\u0000 Estimating reliably and rapidly the losses of wind turbine annual energy production due to blade surface damage is essential for optimizing maintenance planning and, in the frequent case of leading edge erosion, assessing the need for protective coatings. These requirements prompted the development of the prototype system presented herein, using machine learning, wind turbine engineering codes and computational fluid dynamics to estimate wind turbine annual energy production losses due to blade leading edge damage. The power curve of a turbine with nominal or damaged blade surfaces is determined respectively with the open-source FAST and AeroDyn codes of the National Renewable Energy Laboratory, both using the blade element momentum theory for turbine aerodynamics. The loss prediction system is designed to map a given three-dimensional geometry of a damaged blade onto a damaged airfoil database, which, in this study, consists of 2700+ airfoil geometries, each analyzed with Navier-Stokes computational fluid dynamics over the working range of angles of attack. To avoid the need for lengthy aerodynamic analyses to assess losses due to damages monitored during turbine operation, the airfoil force data of a damaged turbine required by AeroDyn are rapidly obtained using a machine learning method trained using the pre-existing airfoil database. Presented results focus on the analysis of a utility-scale offshore wind turbine and demonstrate that realistic estimates of the annual energy production loss due to leading edge surface damage can be obtained in just a few seconds using a standard desktop computer, highlighting the viability and the industrial impact of this new technology for wind farm energy losses due to blade erosion.","PeriodicalId":131294,"journal":{"name":"ASME 2019 2nd International Offshore Wind Technical Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126167967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qi Ye, Shanshan Cheng, Boksun Kim, K. Collins, G. Iglesias
This paper summarizes the assessment of the structural analysis and design of a floating foundation for offshore floating wind turbine (FWT) based on DNVGL standard and Eurocode in terms of economy and reliability. The wind loads are calculated using empirical equations. The wave loads are obtained and verified using various methods including hand calculation, AQWA and Flow-3D. It is found that the shell thickness could be reduced significantly by introducing the stiffeners (stringer or ring), which can decrease the weight of the hull and lower the cost. While DNVGL and Eurocode yield similar design solutions if using plane shell structures, Eurocode significantly underestimates the buckling resistance of stiffened cylindrical shells.
{"title":"Structure Design and Assessment of a Floating Foundation for Offshore Wind Turbines","authors":"Qi Ye, Shanshan Cheng, Boksun Kim, K. Collins, G. Iglesias","doi":"10.1115/iowtc2019-7594","DOIUrl":"https://doi.org/10.1115/iowtc2019-7594","url":null,"abstract":"This paper summarizes the assessment of the structural analysis and design of a floating foundation for offshore floating wind turbine (FWT) based on DNVGL standard and Eurocode in terms of economy and reliability. The wind loads are calculated using empirical equations. The wave loads are obtained and verified using various methods including hand calculation, AQWA and Flow-3D. It is found that the shell thickness could be reduced significantly by introducing the stiffeners (stringer or ring), which can decrease the weight of the hull and lower the cost. While DNVGL and Eurocode yield similar design solutions if using plane shell structures, Eurocode significantly underestimates the buckling resistance of stiffened cylindrical shells.","PeriodicalId":131294,"journal":{"name":"ASME 2019 2nd International Offshore Wind Technical Conference","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124450755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Monopiles are nowadays the preferred substructure type for bottom-fixed offshore wind turbines at shallow to intermediate water depths. At these locations, the large waves that contribute to extreme loads are strongly nonlinear. Therefore they are not easily reproduced via the simple engineering models who are commonly used in the offshore industry. In the current approach, we develop a design pattern which improves this standard methodology. To retain nonlinearity in the force computations, we have precomputed a number of wave realizations by means of a potential fully-nonlinear code (OceanWave3D), for a wide span of nondimensional water depths and significant wave heights. The designer can then extract a wave kinematics time series from the precomputed set, scale it by the Froude law, and couple it with a suitable force model to compute loads. To complete the picture, slamming loads are calculated by means of the so-called pressure impulse model, recently developed at DTU. Rather than computing the time series of the slamming load, the model uses a few parameters, all except one determinable from the incident wave to calculate the pressure impulse. First comparisons with experimental results, obtained in the framework of the DeRisk project, are promising. The force and the wave elevation statistics from the precomputed simulations are in good agreement with the experiments. Some discrepancies are present, due to an imperfect scaling and to the differences in the physical and numerical domains. The computed loads from the slamming model match the experimental ones quite closely, when the wave celerity is extracted as the ratio between the time gradient and the x-wise space gradient of the surface elevation.
{"title":"Extreme Wave Loads on Monopile Substructures: Precomputed Kinematics Coupled With the Pressure Impulse Slamming Load Model","authors":"F. Pierella, A. Ghadirian, H. Bredmose","doi":"10.1115/iowtc2019-7618","DOIUrl":"https://doi.org/10.1115/iowtc2019-7618","url":null,"abstract":"\u0000 Monopiles are nowadays the preferred substructure type for bottom-fixed offshore wind turbines at shallow to intermediate water depths. At these locations, the large waves that contribute to extreme loads are strongly nonlinear. Therefore they are not easily reproduced via the simple engineering models who are commonly used in the offshore industry. In the current approach, we develop a design pattern which improves this standard methodology.\u0000 To retain nonlinearity in the force computations, we have precomputed a number of wave realizations by means of a potential fully-nonlinear code (OceanWave3D), for a wide span of nondimensional water depths and significant wave heights. The designer can then extract a wave kinematics time series from the precomputed set, scale it by the Froude law, and couple it with a suitable force model to compute loads. To complete the picture, slamming loads are calculated by means of the so-called pressure impulse model, recently developed at DTU. Rather than computing the time series of the slamming load, the model uses a few parameters, all except one determinable from the incident wave to calculate the pressure impulse.\u0000 First comparisons with experimental results, obtained in the framework of the DeRisk project, are promising. The force and the wave elevation statistics from the precomputed simulations are in good agreement with the experiments. Some discrepancies are present, due to an imperfect scaling and to the differences in the physical and numerical domains. The computed loads from the slamming model match the experimental ones quite closely, when the wave celerity is extracted as the ratio between the time gradient and the x-wise space gradient of the surface elevation.","PeriodicalId":131294,"journal":{"name":"ASME 2019 2nd International Offshore Wind Technical Conference","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115358008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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