Heuristic Optimization in the Eolic Park Design

Abstract

Optimization of energy costs by the location of turbines in the wind farm design is a problem that, in the last two decades, has become important. In order to solve it, Metaheuristics techniques of high level have been applied. In this article, an Eolic park model is detailed, and the importance of an optimal design of wind farms is stressed proposing the best location of the turbines in a layout. The layout refers to the discretization of the search field in a grid by means of a Cartesian coordinate arrangement for later encoding in a binary string: A one represents a turbine to be installed in the indicated position and a zero indicates otherwise. As such, this article shows the different metaheuristics applied to solve this problem and how these have had better results than empirical techniques traditionally used. On the other hand, a high level metaheuristic technique based on the hunting of the lion ant larva (Ant Lion Optimizer) and a technique derived from this work that uses binary variables (Binary Ant Lion Optimizer) are used. Finally, a wind farm design problem is introduced. This problem uses an energy cost estimator that has models of wind distribution, wake effect, and cost function. This problem was studied to determine the lowest cost through low level heuristics and through metaheuristics; the best result was given by using the algorithm of binary variables with low level heuristics.