This project focuses on optimizing wind farm layouts using genetic algorithms (GAs), aiming to maximize energy production efficiency.
The optimization problem involves determining the optimal placement of wind turbines within a specified area to harness maximum wind energy. Genetic algorithms are employed for their ability to efficiently explore the solution space and find near-optimal solutions.
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Genetic Algorithms Implementation: Implemented using both custom algorithms and PyGAD library for comparison and optimization.
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Wind Farm Model: Utilizes the PyWake model to simulate wake effects and calculate the fitness of each layout configuration based on energy output.
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Main Solution: The best-performing solution can be found in
main_project_solution.ipynb, showcasing the optimal layout identified through the optimization process. -
Documentation and Presentation: Detailed documentation is available, including a presentation that explains the problem domain and the workings of genetic algorithms (
Wind Farm Layout Optimization problem - presentation.pdf). Refer to (Optymalizacja_układu_turbin_w_elektrowniach_wiatrowych_z_zastosowaniem_algorytmów_genetycznych.pdf) for additional detailed documentation on the project.