Maximizing wind farm efficiency by positioning wind turbines optimally and accounting for hub height

被引:2
作者
Cavalcanti, Matheus Beserra [2 ]
Gomes, Herbert Martins [1 ,2 ]
机构
[1] Univ Fed Rio Grande do Sul, Grad Program Mech Engn, Ave Sarmento Leite,425,2 Andar, BR-90050170 Porto Alegre, RS, Brazil
[2] Univ Fed Rio Grande do Sul, Grad Program Civil Engn, Ave Osvaldo Aranha,99,3 Andar, BR-90050170 Porto Alegre, RS, Brazil
关键词
Metaheuristic optimization; Wind turbines; Micrositing; Wake interference; QPSO; LAYOUT OPTIMIZATION; PLACEMENT;
D O I
10.1007/s11081-023-09822-y
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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 (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.
引用
收藏
页码:605 / +
页数:535
相关论文
共 35 条
  • [1] Abeeolica, 2021, WIND POW EXC 20 GW I
  • [2] [Anonymous], 2022, HORNS REV 1
  • [3] Cavalcanti MB, 2023, THESIS FED U RIO GRA
  • [4] Wind farm layout optimization using genetic algorithm with different hub height wind turbines
    Chen, Ying
    Li, Hua
    Jin, Kai
    Song, Qing
    [J]. ENERGY CONVERSION AND MANAGEMENT, 2013, 70 : 56 - 65
  • [5] Crasto G, 2008, EUR WIND EN C EXH
  • [6] Custodio RS, 2013, SYNERGIA
  • [7] Devibala P., 2012, INT J ENG CS TECHNOL, V0102, P1
  • [8] Eletrosul SC, 2014, WIND ATL RIO GRAND S
  • [9] Design of wind farm layout using ant colony algorithm
    Eroglu, Yunus
    Seckiner, Serap Ulusam
    [J]. RENEWABLE ENERGY, 2012, 44 : 53 - 62
  • [10] Solving the wind farm layout optimization problem using random search algorithm
    Feng, Ju
    Shen, Wen Zhong
    [J]. RENEWABLE ENERGY, 2015, 78 : 182 - 192