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Open Access Journal Article

Optimization of Wind Farm Layout Using Multi-Objective Genetic Algorithms

by Emma Smith 1,*
1
Emma Smith
*
Author to whom correspondence should be addressed.
TASC  2023 5(1):40; https://doi.org/10.69610/j.tasc.20230616
Received: 21 April 2023 / Accepted: 23 May 2023 / Published Online: 16 June 2023
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Abstract

The efficient design of wind farm layouts is crucial for maximizing energy production while minimizing environmental impact and land use. This paper presents a novel approach to optimize wind farm layouts using multi-objective genetic algorithms (MOGAs). The MOGAs are employed to address the complex trade-offs between various objectives such as energy output, land utilization, and visual impact assessment. The proposed method incorporates a multi-objective optimization framework that simultaneously considers these objectives while exploring the search space through genetic algorithmic operators. The results demonstrate that the MOGAs effectively converge towards optimal solutions that balance the competing objectives. Furthermore, the computational efficiency of the algorithm is validated through various case studies, showcasing its applicability for practical wind farm layout optimization. This study contributes to the advancement of wind farm design by providing a robust and adaptable tool for decision-makers in the renewable energy sector.

Keywords: Wind Farm Layout, Multi-Objective Genetic Algorithms, Energy Production, Land Utilization, Environmental Impact Assessment.;
Copyright: © 2023 by Smith. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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ACS Style
Smith, E. Optimization of Wind Farm Layout Using Multi-Objective Genetic Algorithms. Transactions on Applied Soft Computing, 2023, 5, 40. https://doi.org/10.69610/j.tasc.20230616
AMA Style
Smith E. Optimization of Wind Farm Layout Using Multi-Objective Genetic Algorithms. Transactions on Applied Soft Computing; 2023, 5(1):40. https://doi.org/10.69610/j.tasc.20230616
Chicago/Turabian Style
Smith, Emma 2023. "Optimization of Wind Farm Layout Using Multi-Objective Genetic Algorithms" Transactions on Applied Soft Computing 5, no.1:40. https://doi.org/10.69610/j.tasc.20230616
APA style
Smith, E. (2023). Optimization of Wind Farm Layout Using Multi-Objective Genetic Algorithms. Transactions on Applied Soft Computing, 5(1), 40. https://doi.org/10.69610/j.tasc.20230616

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