Abstract
By optimizing the positions of wind turbines in a wind farm, the power loss caused by wake effects can be reduced maximally. A new methodology of layout optimization is proposed utilizing a full-field wake model that integrates the near-field and far-field wake models after modifications, and a random search (RS) algorithm improved with a scale factor for acceleration in high-density layouts. The methodology is applied to a floating wind farm composed of modular platforms, which have a novel configuration and the ability to face toward the wind direction. The applicability and efficiency of the methodology and the improved RS algorithm are validated. The power production of optimized layouts shows a flat crest with an increased number of wind turbines. There is a layout with maximal output power in the wind farm. The real optimal layout should be determined in consideration of both output power and cost. Two sizes of platforms with different number of modules are compared in the application. The wind farm with smaller platforms produces more power. For comparison, a pattern search (PS) algorithm is also implemented in the application. The improved RS algorithm shows outperformance compared with the original RS and the PS algorithm.
Highlights
Wind Farm Based on the Full-FieldIn the context of decreased demand of global energy, the wind industry, one of the renewable energy industries, still broke a growth record in 2020 with 53% year-over-year growth [1]
The wind industry has problems that it must face such as power losses caused by the wake effects, which appear in the downwind side of wind turbines and mainly refer to wind velocity deficits
Downstream wind turbines are affected by the wakes of two upstream wind turbines at most
Summary
Wind Farm Based on the Full-FieldIn the context of decreased demand of global energy, the wind industry, one of the renewable energy industries, still broke a growth record in 2020 with 53% year-over-year growth [1]. The wind industry has problems that it must face such as power losses caused by the wake effects, which appear in the downwind side of wind turbines and mainly refer to wind velocity deficits. The layout optimization of a wind farm is a feasible way to tackle this problem, which optimizes the positions of wind turbines to reduce the power loss at the design stage of the wind farm. The analytical wake model becomes an important tool of the layout optimization, because of acceptable accuracy to forecast the power production at low computational cost. Jensen [3] and Katic et al [4] developed an analytical model with a top-hat profile of the wake velocity deficit based on the mass conservation. Frandsen et al [7] introduced another kind of top-hat shape wake model by applying the conservation of momentum to a control volume around the turbine
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