Double-stage genetic algorithm for wind farm layout optimization on complex terrains

Abstract

This paper deals with the problem of optimal wind turbine micro siting on complex terrains. A realistic wind farm terrain can be very complex not only for the topography of the terrain but also for other factors. Such factors are the environmental impact of the wind farm, the costs of land, the costs of access roads, wind turbine installation and maintenance costs, the costs of electrical infrastructure, etc. A grid-based wind farm model that takes all of these factors into consideration is proposed. For the purpose of an optimization algorithm, a double-stage genetic algorithm is proposed. In the first stage, the optimal micro-areas for wind turbine positioning are determined, whereas the second stage defines precise optimal positions of wind turbine foundations. The double-stage genetic algorithm increases the accuracy of wind turbine positioning and decreases the dimensionality of the problem. The algorithm has been tested on a realistic wind farm terrain in Serbia.