Life-Cycle Techno-Economic Optimization of Complex-Terrain Wind Farms.

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Title: Life-Cycle Techno-Economic Optimization of Complex-Terrain Wind Farms.
Authors: Wang, Xin1 (AUTHOR), Li, Fashe1,2 (AUTHOR) lifashe@kust.edu.cn
Source: Energies (19961073). Jun2026, Vol. 19 Issue 11, p2489. 24p.
Subject Terms: *Multisensor data fusion, *Life cycle costing, *Topography, *Wind measurement, *Carbon emissions, *Energy industries, *Turbine efficiency, *Wind power plants
Geographic Terms: China
Abstract: To address the poor quality of early-stage wind measurement data and the limited representativeness of short-term observations for long-term climatic conditions in mountainous wind farms, this study takes a 150 MW wind power project in Guangxi, China, as a case study and proposes an integrated framework of "stepwise data fusion-key parameter refinement-life-cycle techno-economic optimization". For wind resource assessment, a two-stage fusion strategy combining same-mast correlation-based infilling and mesoscale data extrapolation was developed, effectively resolving the heterogeneous data quality among six meteorological masts and revealing significant spatial variations in the wind shear exponent (0.058–0.348). Based on a conservative criterion, the 50-year return-period maximum wind speed was determined to be 31.4 m/s. For turbine selection, the levelized cost of energy was adopted as the core evaluation metric to compare six turbine models rated at 6.0–6.25 MW. The results show that WTG5-200-6.25 is the optimal option, with a levelized cost of energy (LCOE) of 0.321 CNY/kWh, an annual grid-connected electricity generation of 269.915 GWh, and 1799 equivalent full-load hours. In addition, the project can save 82.9 thousand tons of standard coal annually and yield approximately CNY 311 million in carbon-trading revenue over 25 years. The proposed framework provides a useful reference for wind power projects in complex terrain. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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DbLabel: Energy & Power Source
An: 194587877
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  Label: Title
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  Data: Life-Cycle Techno-Economic Optimization of Complex-Terrain Wind Farms.
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  Data: <searchLink fieldCode="AR" term="%22Wang%2C+Xin%22">Wang, Xin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Fashe%22">Li, Fashe</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> lifashe@kust.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. Jun2026, Vol. 19 Issue 11, p2489. 24p.
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  Data: *<searchLink fieldCode="DE" term="%22Multisensor+data+fusion%22">Multisensor data fusion</searchLink><br />*<searchLink fieldCode="DE" term="%22Life+cycle+costing%22">Life cycle costing</searchLink><br />*<searchLink fieldCode="DE" term="%22Topography%22">Topography</searchLink><br />*<searchLink fieldCode="DE" term="%22Wind+measurement%22">Wind measurement</searchLink><br />*<searchLink fieldCode="DE" term="%22Carbon+emissions%22">Carbon emissions</searchLink><br />*<searchLink fieldCode="DE" term="%22Energy+industries%22">Energy industries</searchLink><br />*<searchLink fieldCode="DE" term="%22Turbine+efficiency%22">Turbine efficiency</searchLink><br />*<searchLink fieldCode="DE" term="%22Wind+power+plants%22">Wind power plants</searchLink>
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  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: To address the poor quality of early-stage wind measurement data and the limited representativeness of short-term observations for long-term climatic conditions in mountainous wind farms, this study takes a 150 MW wind power project in Guangxi, China, as a case study and proposes an integrated framework of "stepwise data fusion-key parameter refinement-life-cycle techno-economic optimization". For wind resource assessment, a two-stage fusion strategy combining same-mast correlation-based infilling and mesoscale data extrapolation was developed, effectively resolving the heterogeneous data quality among six meteorological masts and revealing significant spatial variations in the wind shear exponent (0.058–0.348). Based on a conservative criterion, the 50-year return-period maximum wind speed was determined to be 31.4 m/s. For turbine selection, the levelized cost of energy was adopted as the core evaluation metric to compare six turbine models rated at 6.0–6.25 MW. The results show that WTG5-200-6.25 is the optimal option, with a levelized cost of energy (LCOE) of 0.321 CNY/kWh, an annual grid-connected electricity generation of 269.915 GWh, and 1799 equivalent full-load hours. In addition, the project can save 82.9 thousand tons of standard coal annually and yield approximately CNY 311 million in carbon-trading revenue over 25 years. The proposed framework provides a useful reference for wind power projects in complex terrain. [ABSTRACT FROM AUTHOR]
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.3390/en19112489
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 24
        StartPage: 2489
    Subjects:
      – SubjectFull: Multisensor data fusion
        Type: general
      – SubjectFull: Life cycle costing
        Type: general
      – SubjectFull: Topography
        Type: general
      – SubjectFull: Wind measurement
        Type: general
      – SubjectFull: Carbon emissions
        Type: general
      – SubjectFull: Energy industries
        Type: general
      – SubjectFull: Turbine efficiency
        Type: general
      – SubjectFull: Wind power plants
        Type: general
      – SubjectFull: China
        Type: general
    Titles:
      – TitleFull: Life-Cycle Techno-Economic Optimization of Complex-Terrain Wind Farms.
        Type: main
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      – PersonEntity:
          Name:
            NameFull: Wang, Xin
      – PersonEntity:
          Name:
            NameFull: Li, Fashe
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 19961073
          Numbering:
            – Type: volume
              Value: 19
            – Type: issue
              Value: 11
          Titles:
            – TitleFull: Energies (19961073)
              Type: main
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