Enhancing Wind Farm Efficiency through Layout Optimization: A Comprehensive Review
Main Article Content
Abstract
Wind energy has emerged as a pivotal renewable energy source globally, with wind farms playing a crucial role in sustainable electricity generation. The efficiency of these wind farms heavily depends on the strategic placement of wind turbines within their layouts. This comprehensive review explores various methodologies and advancements in optimizing wind farm layouts to maximize energy yield and operational efficiency. Key considerations include the impact of turbine spacing, terrain complexity, wake effects, and environmental factors on overall performance. The review critically evaluates existing literature, highlighting strengths and limitations of different optimization techniques such as mathematical modeling, computational algorithms, and empirical studies. Moreover, it discusses emerging trends in layout design, including advanced modeling approaches and integration of machine learning algorithms for enhanced predictive accuracy. By synthesizing findings from diverse sources, this review aims to provide insights into the current state-of-the-art practices and future research directions in optimizing wind farm layouts for sustainable energy production.
Article Details

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This license requires that re-users give credit to the creator. It allows re-users to distribute, remix, adapt, and build upon the material in any medium or format, for noncommercial purposes only.
References
Mosetti, G., Poloni, C., & Diviacco, B. (1994). Wind farm layout optimization using genetic algorithm. Renewable Energy, 6(4), 343-353. https://doi.org/10.1016/0960-1481(94)90052-3
Deb, K., Mohan, M., & Mishra, T. N. (2017). Wind farm layout optimization considering energy generation and noise propagation. Renewable Energy, 105, 268-279. https://doi.org/10.1016/j.renene.2016.12.002
Chowdhury, S., Zhang, J., Messac, A., & Castillo, L. (2013). Optimizing the arrangement and the selection of turbines for wind farms subject to varying wind conditions. Renewable Energy, 52, 273-282. https://doi.org/10.1016/j.renene.2012.10.017
Herbert-Acero, J. F., Probst, O., Réthoré, P.-E., Larsen, G. C., & Castillo-Villar, K. K. (2014). A review of methodological approaches for the design and optimization of wind farms. Renewable and Sustainable Energy Reviews, 42, 1014-1026. https://doi.org/10.1016/j.rser.2014.10.004
Samorani, M. (2013). The wind farm layout optimization problem. European Journal of Operational Research, 231(1), 245-259. https://doi.org/10.1016/j.ejor.2013.06.015
Emami, A., & Noghreh, P. (2010). New approach on optimization in placement of wind turbines within wind farm by genetic algorithms. Renewable Energy, 35(7), 1559-1564. https://doi.org/10.1016/j.renene.2009.11.026
González, J. S., Payan, M. B., Santos, J. M. R., & Santos, J. R. (2010). Optimization of wind farm turbines layout using an evolutive algorithm. Renewable Energy, 35(8), 1671-1681. https://doi.org/10.1016/j.renene.2009.10.009
Kusiak, A., & Song, Z. (2010). Design of wind farm layout for maximum wind energy capture. Renewable Energy, 35(3), 685-694. https://doi.org/10.1016/j.renene.2009.08.019
Rivas, R., Riquelme, J., & García, A. (2011). Genetic algorithm for wind farm optimal layout considering multiple criteria. Renewable Energy, 36(2), 2845-2852. https://doi.org/10.1016/j.renene.2011.04.017
Huang, H., & Zhang, Y. (2015). Optimal wind farm layout design using genetic algorithms with different hub height wind turbines. Energy Conversion and Management, 89, 273-284. https://doi.org/10.1016/j.enconman.2014.09.074