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Optimizing the layout of onshore wind farms to minimize noise

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  • Wu, Xiawei
  • Hu, Weihao
  • Huang, Qi
  • Chen, Cong
  • Jacobson, Mark Z.
  • Chen, Zhe

Abstract

As wind farm numbers and areas increase worldwide, it has become increasingly important to examine the impact of wind energy on the surrounding environment. One effect in some scenarios is noise, which depends on the type and age of the wind turbines and the distances between them and the residential buildings. Previous research on wind farm layout optimization has been generally aimed at achieving the minimum investment cost or maximum captured energy. This approach does not entirely align with minimizing noise. This paper focuses on an optimal layout for a wind farm considering its noise, without sacrificing power production. By optimizing the wind farm layout, the minimum noise is set as the basic objective, and both the wake effect and distances among wind turbines are considered. The basic particle swarm optimization algorithm and its evolutionary version are adopted and compared for better performance of calculation cost. Two strategies are presented to address the problems in various scenarios and to demonstrate the applicability of the proposed method and its effectiveness in designing layouts that minimize noise. Compared to a reference layout, a stringent noise control strategy could reduce the noise by 11%, even if minor, and increase the power production by 3.1%. A flexible strategy could reduce the noise by 5.7% and increase the power production by 3.1%.

Suggested Citation

  • Wu, Xiawei & Hu, Weihao & Huang, Qi & Chen, Cong & Jacobson, Mark Z. & Chen, Zhe, 2020. "Optimizing the layout of onshore wind farms to minimize noise," Applied Energy, Elsevier, vol. 267(C).
    • Handle: RePEc:eee:appene:v:267:y:2020:i:c:s0306261920304086
    DOI: 10.1016/j.apenergy.2020.114896
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    2. Zheng, Yue & Wang, Jie-Sheng & Zhu, Jun-Hua & Zhang, Xin-Yue & Xing, Yu-Xuan & Zhang, Yun-Hao, 2024. "MORSA: Multi-objective reptile search algorithm based on elite non-dominated sorting and grid indexing mechanism for wind farm layout optimization problem," Energy, Elsevier, vol. 293(C).
    3. Gunther Glenk & Rebecca Meier & Stefan Reichelstein, 2021. "Cost Dynamics of Clean Energy Technologies," Schmalenbach Journal of Business Research, Springer, vol. 73(2), pages 179-206, June.
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    5. Leon Sander & Christopher Jung & Dirk Schindler, 2024. "Global Review on Environmental Impacts of Onshore Wind Energy in the Field of Tension between Human Societies and Natural Systems," Energies, MDPI, vol. 17(13), pages 1-33, June.
    6. Glenk, Gunther & Meier, Rebecca & Reichelstein, Stefan, 2021. "Cost dynamics of clean energy technologies," ZEW Discussion Papers 21-054, ZEW - Leibniz Centre for European Economic Research.
    7. Zilong, Ti & Xiao Wei, Deng, 2022. "Layout optimization of offshore wind farm considering spatially inhomogeneous wave loads," Applied Energy, Elsevier, vol. 306(PA).
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    13. Mittal, Prateek & Christopoulos, Giorgos & Subramanian, Sriram, 2024. "Energy enhancement through noise minimization using acoustic metamaterials in a wind farm," Renewable Energy, Elsevier, vol. 224(C).

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