Influence of the variation of meteorological and operational parameters on estimation of the power output of a wind farm with active power control
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DOI: 10.1016/j.renene.2020.05.187
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Cited by:
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- Choupin, Ophelie & Del Río-Gamero, B. & Schallenberg-Rodríguez, Julieta & Yánez-Rosales, Pablo, 2022. "Integration of assessment-methods for wave renewable energy: Resource and installation feasibility," Renewable Energy, Elsevier, vol. 185(C), pages 455-482.
- Mingyu Li & Dongxiao Niu & Zhengsen Ji & Xiwen Cui & Lijie Sun, 2021. "Forecast Research on Multidimensional Influencing Factors of Global Offshore Wind Power Investment Based on Random Forest and Elastic Net," Sustainability, MDPI, vol. 13(21), pages 1-19, November.
- Carta, José A. & Díaz, Santiago & Castañeda, Alberto, 2020. "A global sensitivity analysis method applied to wind farm power output estimation models," Applied Energy, Elsevier, vol. 280(C).
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Keywords
Wind farm power output; Machine learning; Active power set-point; Nacelle orientation; Air density; Turbulence intensity;All these keywords.
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