Vertical wind profile characterization and identification of patterns based on a shape clustering algorithm
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AuthorMolina García, Ángel; Fernández Guillamón, Ana; Gómez Lázaro, Emilio; Honrubia Escribano, Andrés; Bueso Sánchez, María del Carmen
Research GroupIngeniera Electrica y Energias Renovables
Knowledge AreaIngeniería Eléctrica
SponsorsThe authors are grateful for the financial support from the Spanish Ministry of the Economy and Competitiveness and the European Union —ENE2016-78214-C2-2-R—and the Spanish Education, Culture and Sport Ministry —FPU16/0428
Bibliographic CitationA. Molina-García, A. Fernández-Guillamón, E. Gómez-Lázaro, A. Honrubia-Escribano and M. C. Bueso, "Vertical Wind Profile Characterization and Identification of Patterns Based on a Shape Clustering Algorithm," in IEEE Access, vol. 7, pp. 30890-30904, 2019.
Wind power generation
Wind power plants are becoming a generally accepted resource in the generation mix of many utilities. At the same time, the size and the power rating of individual wind turbines have increased considerably. Under these circumstances, the sector is increasingly demanding an accurate characterization of vertical wind speed profiles to estimate properly the incoming wind speed at the rotor swept area and, consequently, assess the potential for a wind power plant site. The present paper describes a shape-based clustering characterization and visualization of real vertical wind speed data. The proposed solution allows us to identify the most likely vertical wind speed patterns for a specific location based on real wind speed measurements. Moreover, this clustering approach also provides characterization and classification of such vertical wind profiles. This solution is highly suitable for a large amount of data collected by remote sensing equipment, where wind speed values at different heights ...
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