Optimizing Wind Farm Layouts with Genetic Algorithms (Enhancing Efficiency in Wind Energy Planning and Utilization in Bosnia and Herzegovina)

Abstract

This paper proposes a genetic algorithm-based approach to optimize wind farm layouts in Bosnia and Herzegovina, a country with a high potential for wind energy production. The primary objective is to maximize the total power output derived from the wind farm while concurrently minimizing the wake effects resulting from turbine interactions. This balance is pivotal in ensuring the optimal utilization of wind energy resources. In this study, three different wind data scenarios are considered: a single wind direction with overall average velocity, the most prevalent wind direction with overall average velocity, and an all-encompassing wind direction analysis incorporating a weighted objective function. The results of the study suggest that the genetic algorithm is highly effective in identifying optimal solutions across each scenario. This serves as a testament to the algorithm's accuracy, robustness, and applicability in tackling real-world problems, thereby marking a significant step forward in the realm of wind farm optimization. The limitations of this research include the use of a simplified wake model and a fixed turbine type. The implications of this research include the potential for increasing the efficiency and profitability of wind farms in Bosnia and Herzegovina, as well as informing future research on more complex and realistic optimization problems.