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A new method for estimating the annual energy production of wind turbines in hot environments.

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Title: A new method for estimating the annual energy production of wind turbines in hot environments.
Authors: Al-Khayat, Mohammad1 (AUTHOR), AL-Rasheedi, Majed1 (AUTHOR) mrashedi@kisr.edu.kw
Source: Renewable & Sustainable Energy Reviews. May2024, Vol. 195, pN.PAG-N.PAG. 1p.
Subjects: International Electrotechnical Commission, Wind turbines, Wind power, Weibull distribution, Wind speed measurement, Distribution (Probability theory), Wind forecasting
Geographic Terms: Kuwait
Abstract: Accurately estimating wind turbines' annual energy production (AEP) is a paramount for planning and performance assessment of wind power projects. Inaccurate estimates during the planning phase could result in lower/higher project economic feasibility. This leads to financial consequences in the project's contractual agreement. Furthermore, comparing the effective turbine's operational performance under operational site conditions to the guaranteed performance is also critical. The current standard practice of the International Electrotechnical Commission (IEC) for calculating the AEP consists of using the site's Weibull parameters derived only from the wind speed measurements and ignoring the air temperature measurements impact wind turbine operation. This is inadequate under high-temperature environments, where various meteorological processes impact the wind frequency distribution function. Moreover, wind turbine output power typically starts derating at high air temperatures to prevent overheating the electric and mechanical systems. The current study proposes a new method by categorizing the wind speed data into bins of 0.5 °C each, where the frequency distribution and Weibull parameters are produced for each bin. Therefore, calculating the AEP by the new method requires creating several wind speed distribution functions for the temperature ranges ranging between derating cut-in temperature and shutdown temperature. The Weibull parameters are found to change significantly during high-temperature conditions. Validation conducted using multiple years of wind resource assessment and Shagaya wind farm power data has shown the newly developed method has higher accuracy than the standard IEC method in hot environments and can better predict the energy losses in the upcoming wind farms in the region. [Display omitted] • Annual wind farm energy production is vital for planning and performance evaluation. • Wind turbine output power derate at high air temperatures resulting in power losses. • Planning wind project in a hot environment requires temperature data at hub height. • Weibull parameters changes significantly during high temperature conditions. [ABSTRACT FROM AUTHOR]
Copyright of Renewable & Sustainable Energy Reviews is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
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Header DbId: egs
DbLabel: Engineering Source
An: 175874277
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
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  Data: A new method for estimating the annual energy production of wind turbines in hot environments.
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  Data: <searchLink fieldCode="AR" term="%22Al-Khayat%2C+Mohammad%22">Al-Khayat, Mohammad</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22AL-Rasheedi%2C+Majed%22">AL-Rasheedi, Majed</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> mrashedi@kisr.edu.kw</i>
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  Data: <searchLink fieldCode="DE" term="%22Kuwait%22">Kuwait</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: Accurately estimating wind turbines' annual energy production (AEP) is a paramount for planning and performance assessment of wind power projects. Inaccurate estimates during the planning phase could result in lower/higher project economic feasibility. This leads to financial consequences in the project's contractual agreement. Furthermore, comparing the effective turbine's operational performance under operational site conditions to the guaranteed performance is also critical. The current standard practice of the International Electrotechnical Commission (IEC) for calculating the AEP consists of using the site's Weibull parameters derived only from the wind speed measurements and ignoring the air temperature measurements impact wind turbine operation. This is inadequate under high-temperature environments, where various meteorological processes impact the wind frequency distribution function. Moreover, wind turbine output power typically starts derating at high air temperatures to prevent overheating the electric and mechanical systems. The current study proposes a new method by categorizing the wind speed data into bins of 0.5 °C each, where the frequency distribution and Weibull parameters are produced for each bin. Therefore, calculating the AEP by the new method requires creating several wind speed distribution functions for the temperature ranges ranging between derating cut-in temperature and shutdown temperature. The Weibull parameters are found to change significantly during high-temperature conditions. Validation conducted using multiple years of wind resource assessment and Shagaya wind farm power data has shown the newly developed method has higher accuracy than the standard IEC method in hot environments and can better predict the energy losses in the upcoming wind farms in the region. [Display omitted] • Annual wind farm energy production is vital for planning and performance evaluation. • Wind turbine output power derate at high air temperatures resulting in power losses. • Planning wind project in a hot environment requires temperature data at hub height. • Weibull parameters changes significantly during high temperature conditions. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Renewable & Sustainable Energy Reviews is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=175874277
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.rser.2024.114343
    Languages:
      – Code: eng
        Text: English
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        PageCount: 1
        StartPage: N.PAG
    Subjects:
      – SubjectFull: International Electrotechnical Commission
        Type: general
      – SubjectFull: Wind turbines
        Type: general
      – SubjectFull: Wind power
        Type: general
      – SubjectFull: Weibull distribution
        Type: general
      – SubjectFull: Wind speed measurement
        Type: general
      – SubjectFull: Distribution (Probability theory)
        Type: general
      – SubjectFull: Wind forecasting
        Type: general
      – SubjectFull: Kuwait
        Type: general
    Titles:
      – TitleFull: A new method for estimating the annual energy production of wind turbines in hot environments.
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          Name:
            NameFull: Al-Khayat, Mohammad
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            NameFull: AL-Rasheedi, Majed
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          Dates:
            – D: 01
              M: 05
              Text: May2024
              Type: published
              Y: 2024
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              Value: 195
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