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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| Header | DbId: enr DbLabel: Energy & Power Source An: 194587877 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Life-Cycle Techno-Economic Optimization of Complex-Terrain Wind Farms. – Name: Author Label: Authors Group: Au 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> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. Jun2026, Vol. 19 Issue 11, p2489. 24p. – Name: Subject Label: Subject Terms Group: Su 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> – Name: SubjectGeographic 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] |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=194587877 |
| 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 BibRelationships: HasContributorRelationships: – 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 |
| ResultId | 1 |