Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Maximizing wind farm efficiency by positioning wind turbines optimally and accounting for hub height
Wind energy is increasingly participating in the energy matrix of countries as an alternative source of sustainable energy. Wind farms (WF) are the rational way to generate this type of energy and Brazil is a country that has great potential to be explored. In this work, the layout of WF is optimized to maximize energy production, which is influenced by the wind conditions in the area where the business is located, as well as the number of wind turbines (WT) available and the geographical limits for their installation. The optimization is based on the QPSO metaheuristic algorithm, which enables easy continuum or discrete positioning WTs without utilizing derivatives and taking into account minimum distances between towers. The QPSO algorithm is tested in the evaluation of the Horns Rev 1 (2022) and for the analysis of a hypothetical WF located in Brazil. In the analysis of the Horns Rev 1, a comparison is made with the results reported in the literature. In the case of the hypothetical wind farm, a proposed methodology was presented to account for differences in height between wind turbines and the wake interference. For the horns Rev 1, QPSO was able to find more efficient solutions than other approaches reported in the literature. In the analysis of the hypothetical WF, the algorithm was able to explore the wind potential of the region, proposing optimized solutions for different terrain irregularities.
Maximizing wind farm efficiency by positioning wind turbines optimally and accounting for hub height
Wind energy is increasingly participating in the energy matrix of countries as an alternative source of sustainable energy. Wind farms (WF) are the rational way to generate this type of energy and Brazil is a country that has great potential to be explored. In this work, the layout of WF is optimized to maximize energy production, which is influenced by the wind conditions in the area where the business is located, as well as the number of wind turbines (WT) available and the geographical limits for their installation. The optimization is based on the QPSO metaheuristic algorithm, which enables easy continuum or discrete positioning WTs without utilizing derivatives and taking into account minimum distances between towers. The QPSO algorithm is tested in the evaluation of the Horns Rev 1 (2022) and for the analysis of a hypothetical WF located in Brazil. In the analysis of the Horns Rev 1, a comparison is made with the results reported in the literature. In the case of the hypothetical wind farm, a proposed methodology was presented to account for differences in height between wind turbines and the wake interference. For the horns Rev 1, QPSO was able to find more efficient solutions than other approaches reported in the literature. In the analysis of the hypothetical WF, the algorithm was able to explore the wind potential of the region, proposing optimized solutions for different terrain irregularities.
Maximizing wind farm efficiency by positioning wind turbines optimally and accounting for hub height
Optim Eng
Cavalcanti, Matheus Beserra (Autor:in) / Gomes, Herbert Martins (Autor:in)
Optimization and Engineering ; 25 ; 731-758
01.06.2024
28 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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