Maximizing Wind Farm Power Output by Modified Genetic Algorithm

Wind energy is a rapidly growing source of energy for the United States, but there are still technical problems to resolve before it can become the major source of energy production. One of the biggest problems with land based wind farms is minimizing wake- turbine interactions within a constrained space and thus maximizing power. When wind blows through a turbine's blades, a choppy, turbulent wake is created that interferes with the ability of nearby turbines to produce power. Research has already been done on finding ways to model wind farms and place the turbines in a way that minimizes wake- turbine interactions, but current methods are either computationally intensive or require proprietary software. I present a modified genetic algorithm that is able to produce reasonably optimized results in a relatively short amount of computation time. The algorithm presented is able to make use of the computation power of graphical processing units and multiple processors and by doing so produces results much quicker than an algorithm run sequentially on a single processor.