A Preliminary Analysis of Different Grid Sizes for Wind Farm Micrositing Using an Evolutionary Algorithm for Turaif, Saudi Arabia

Wind energy has brought a revolution in the domain of renewable energy, and is gradually replacing the traditional fossil fuels. A major challenge in harnessing maximum wind energy from a wind farm is the efficient placement of turbines within the farm, known as wind farm micrositing (WFM). The problem is classified as an NP-hard problem and therefore optimization algorithms from the domain of evolutionary computation and swarm intelligence have been traditionally employed. The optimal micrositing depends on several key factors, such as land topography, wind speed, wind direction, and grid size. While significant research has been carried out on many of these factors, the study on the impact of grid size on wind power generation has received little attention. This study provides a preliminary analysis on the impact of various unconventional grid sizes such as 11×11, 12×12, up to 15×15 through the use of a genetic algorithm. The performance is measured both in terms of the quality of solution produced as well as the execution time. Results indicate that increase in the grid size has a positive impact on the quality of solution, measured through conversion efficiency. However, the correlation between algorithmic execution time and grid size is almost negligible, as a change in grid size does not affect the execution time of the algorithm.