A continuous developmental model for wind farm layout optimization

Dennis G. Wilson, Sylvain Cussat-Blanc, K. Veeramachaneni, Una-May O’Reilly, H. Luga
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引用次数: 14

Abstract

We present DevoII, an improved cell-based developmental model for wind farm layout optimization. To address the shortcomings of discretization, DevoII's gene regulatory networks control cells that act in a continuous rather than discretized grid space. We find that DevoII is competitive, and in some cases, superior with respect to state-of-the-art global, stochastic search approaches when a suite of algorithms is evaluated on different wind scenarios. The modularity of the genetic regulatory network computational paradigm in terms of isolating its search algorithm, the regulatory network simulation and the cell simulation, allowed this improvement to largely focus upon cell simulation. This indicates a robustness property of the paradigm's design. As well, wflo highlights how developmental models can be considered more efficient than other optimization methods because of their "optimize once, use-many" adaptability.
风电场布局优化的连续发展模型
我们提出了DevoII,一个改进的基于细胞的风电场布局优化发展模型。为了解决离散化的缺点,DevoII的基因调控网络控制在连续而不是离散网格空间中的细胞。我们发现DevoII是有竞争力的,在某些情况下,相对于最先进的全局随机搜索方法,当一套算法在不同的风情景下进行评估时,它更优越。基因调控网络计算范式的模块化将其搜索算法、调控网络模拟和细胞模拟分离开来,这使得这种改进主要集中在细胞模拟上。这表明了范式设计的稳健性。此外,wflo还强调了开发模型如何被认为比其他优化方法更有效,因为它们具有“一次优化,多次使用”的适应性。
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