Prediction of Extreme Wind Speed for Offshore Wind Farms Considering Parametrization of Surface Roughness

Large-scale offshore wind farms (OWF) are under construction along the southeastern coast of China, an area with a high typhoon incidence. Measured data and typhoon simulation model are used to improve the reliability of extreme wind speed (EWS) forecasts for OWF affected by typhoons in this paper....

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Main Authors: Xinwen Ma, Yan Chen, Wenwu Yi, Zedong Wang
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/14/4/1033
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spelling doaj-0da2934f3ca64ce093969a6bc21464c32021-02-17T00:02:24ZengMDPI AGEnergies1996-10732021-02-01141033103310.3390/en14041033Prediction of Extreme Wind Speed for Offshore Wind Farms Considering Parametrization of Surface RoughnessXinwen Ma0Yan Chen1Wenwu Yi2Zedong Wang3College of Engineering, Shantou University, Shantou 515063, ChinaCollege of Engineering, Shantou University, Shantou 515063, ChinaCollege of Engineering, Shantou University, Shantou 515063, ChinaCollege of Engineering, Shantou University, Shantou 515063, ChinaLarge-scale offshore wind farms (OWF) are under construction along the southeastern coast of China, an area with a high typhoon incidence. Measured data and typhoon simulation model are used to improve the reliability of extreme wind speed (EWS) forecasts for OWF affected by typhoons in this paper. Firstly, a 70-year historical typhoon record database is statistically analyzed to fit the typhoon parameters probability distribution functions, which is used to sample key parameters when employing Monte Carlo Simulation (MCS). The sampled typhoon parameters are put into the Yan Meng(YM) wind field to generate massive virtual typhoon in the MCS. Secondly, when typhoon simulation carried out, the change in wind field roughness caused by the wind-wave coupling is studied. A simplified calculation method for realizing this phenomenon is applied by exchanging roughness length in the parametric wind field and wave model. Finally, the extreme value theory is adopted to analyze the simulated typhoon wind data, and results are verified using measured data and relevant standards codes. The EWS with 50-year recurrence of six representative OWF is predicted as application examples. The results show that the offshore EWS is generally stronger than onshore; the reason is sea surface roughness will not keep growing accordingly as the wind speed increases. The traditional prediction method does not consider this phenomenon, causing it to overestimate the sea surface roughness, and as a result, underestimate the EWS for OWF affected by typhoons. This paper's methods make the prediction of EWS for OWF more precise, and results suggest the planer should choose stronger wind turbine in typhoon prone areas.https://www.mdpi.com/1996-1073/14/4/1033wind-wave couplingMonte Carlo simulationoffshore typhoon farmsroughness lengthextreme wind speed
collection DOAJ
language English
format Article
sources DOAJ
author Xinwen Ma
Yan Chen
Wenwu Yi
Zedong Wang
spellingShingle Xinwen Ma
Yan Chen
Wenwu Yi
Zedong Wang
Prediction of Extreme Wind Speed for Offshore Wind Farms Considering Parametrization of Surface Roughness
Energies
wind-wave coupling
Monte Carlo simulation
offshore typhoon farms
roughness length
extreme wind speed
author_facet Xinwen Ma
Yan Chen
Wenwu Yi
Zedong Wang
author_sort Xinwen Ma
title Prediction of Extreme Wind Speed for Offshore Wind Farms Considering Parametrization of Surface Roughness
title_short Prediction of Extreme Wind Speed for Offshore Wind Farms Considering Parametrization of Surface Roughness
title_full Prediction of Extreme Wind Speed for Offshore Wind Farms Considering Parametrization of Surface Roughness
title_fullStr Prediction of Extreme Wind Speed for Offshore Wind Farms Considering Parametrization of Surface Roughness
title_full_unstemmed Prediction of Extreme Wind Speed for Offshore Wind Farms Considering Parametrization of Surface Roughness
title_sort prediction of extreme wind speed for offshore wind farms considering parametrization of surface roughness
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2021-02-01
description Large-scale offshore wind farms (OWF) are under construction along the southeastern coast of China, an area with a high typhoon incidence. Measured data and typhoon simulation model are used to improve the reliability of extreme wind speed (EWS) forecasts for OWF affected by typhoons in this paper. Firstly, a 70-year historical typhoon record database is statistically analyzed to fit the typhoon parameters probability distribution functions, which is used to sample key parameters when employing Monte Carlo Simulation (MCS). The sampled typhoon parameters are put into the Yan Meng(YM) wind field to generate massive virtual typhoon in the MCS. Secondly, when typhoon simulation carried out, the change in wind field roughness caused by the wind-wave coupling is studied. A simplified calculation method for realizing this phenomenon is applied by exchanging roughness length in the parametric wind field and wave model. Finally, the extreme value theory is adopted to analyze the simulated typhoon wind data, and results are verified using measured data and relevant standards codes. The EWS with 50-year recurrence of six representative OWF is predicted as application examples. The results show that the offshore EWS is generally stronger than onshore; the reason is sea surface roughness will not keep growing accordingly as the wind speed increases. The traditional prediction method does not consider this phenomenon, causing it to overestimate the sea surface roughness, and as a result, underestimate the EWS for OWF affected by typhoons. This paper's methods make the prediction of EWS for OWF more precise, and results suggest the planer should choose stronger wind turbine in typhoon prone areas.
topic wind-wave coupling
Monte Carlo simulation
offshore typhoon farms
roughness length
extreme wind speed
url https://www.mdpi.com/1996-1073/14/4/1033
work_keys_str_mv AT xinwenma predictionofextremewindspeedforoffshorewindfarmsconsideringparametrizationofsurfaceroughness
AT yanchen predictionofextremewindspeedforoffshorewindfarmsconsideringparametrizationofsurfaceroughness
AT wenwuyi predictionofextremewindspeedforoffshorewindfarmsconsideringparametrizationofsurfaceroughness
AT zedongwang predictionofextremewindspeedforoffshorewindfarmsconsideringparametrizationofsurfaceroughness
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