Overall design optimization of wind farms

  • Gonzalez J
  • Rodriguez A
  • Mora J
 et al. 
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An Evolutive Algorithm (EA) for wind farm optimal overall design is presented. The algorithm objective is to optimize the profits given an investment on a wind farm. Net Present Value (NPV) will be used as a figure of the revenue in the proposed method. To estimate the NPV is necessary to calculate the initial capital investment and net cash flow throughout the wind farm life cycle. The maximization of the NPV means the minimization of the investment and the maximization of the net cash flows (to maximise the generation of energy and minimise the power losses). Both terms depend mainly on the number and type of wind turbines, the tower height and geographical position, electrical layout, among others. Besides, other auxiliary costs must be to keep in mind to calculate the initial investment such as the cost of auxiliary roads or tower foundations. The difficulty of the problem is mainly due to the fact that there is neither analytic function to model the wind farm costs nor analytic function to model net generation. The complexity of this problem arises not only from a technical point of view, due to strong links between its variables, but also from a purely mathematical point of view. The problem consists of both discrete and continuous variables, being therefore an integer-mixed type problem. The problem exhibits manifold optimal solutions (convexity), some variables have a range of non allowed values (solutions space not simply connected) and others are integers. This fact makes the problem non-derivable, preventing the use of classical analytical optimization techniques. (C) 2010 Elsevier Ltd. All rights reserved.

Author-supplied keywords

  • electrical design
  • evolutive algorithms
  • micrositing
  • optimization
  • wake effect
  • wind farm

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  • J S Gonzalez

  • A G G Rodriguez

  • J C Mora

  • M B Payan

  • J R Santos

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