Genetic Algorithm-Based Optimization Framework for Offshore Wind Farm Layout Design

Offshore wind farms have emerged as a crucial component of renewable energy generation, offering higher energy production rates due to stronger and more consistent wind conditions. However, these advantages come with significant installation and maintenance costs, necessitating comprehensive optimization analyses of wind farms projects to ensure economic feasibility and maximize energy output. One of the most significant challenges in this context is the effective placement of wind turbines within an offshore wind farm, considering the historic wind intensity and direction of candidate areas, along with the impact of wake effects. This study presents a framework that integrates a genetic algorithm to optimize wind farms layouts with a simulation tool for evaluating configurations of wind farm projects. In this paper, we describe the optimization module implemented with genetic algorithms. Our approach aims to facilitate layouts optimization analysis for wind farms during the project phase, focusing on maximizing overall energy output by minimizing wake interference among turbines. The proposed approach demonstrates high modularity and achieves competitive results compared to established benchmarks, highlighting the effectiveness of our framework for optimization analysis in wind farm projects.