Improving wind farm power output through deactivating selected wind turbines

被引:22
|
作者
Haces-Fernandez, Francisco [1 ]
Li, Hua [2 ]
Ramirez, David [3 ]
机构
[1] Texas A&M Univ Kingsville, Dept Environm Engn, 700 Univ Blvd, Kingsville, TX 78414 USA
[2] Texas A&M Univ Kingsville, Dept Mech & Ind Engn, 700 Univ Blvd,MSC 191, Kingsville, TX 78414 USA
[3] Texas A&M Univ Kingsville, Dept Environm Engn, 700 Univ Blvd,MSC 213, Kingsville, TX 78414 USA
基金
美国国家科学基金会;
关键词
Wind energy; Layout optimization; Wake effect; Deactivated wind turbines; LAYOUT OPTIMIZATION; GENETIC ALGORITHM; DATA-DRIVEN; WAKE; PLACEMENT; MODELS;
D O I
10.1016/j.enconman.2019.03.028
中图分类号
O414.1 [热力学];
学科分类号
摘要
Wind energy is becoming the fastest growing and most inexpensive renewable source, even surpassed natural gas. The environmental advantages coupled with the significant financial benefits have created a positive prognosis for wind energy continuously growing. However, the complexity and limited availability of wind resources create challenges that need to be addressed in order to continue improving wind energy harvesting. This paper developed a new concept to modify wind farm's layout by deactivating selected wind turbines to maximize its total power output under different wind conditions. Different wind conditions create different wake effects, while most wind farms cannot change their layouts to cope with the changing wind conditions. Through deactivating selected wind turbines to effectively reduce or eliminate some turbulent wakes, it is possible to improve a wind farm's total power output by creating a net gain for the entire wind farm. A new method was developed to identify the best combinations of deactivated wind turbines under different wind conditions to achieve maximum power output. Several case studies with real wind farms and real wind conditions were conducted together with sensitivity analysis. The promising results demonstrated the effectiveness of the new method and the new concept, named layout optimization through selective deactivation. Several factors were identified as influencing factors on the effectiveness of the new concept.
引用
收藏
页码:407 / 422
页数:16
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