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A methodology for the low-cost optimisation of small wind turbine performance

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  • Arroyo, A.
  • Manana, M.
  • Gomez, C.
  • Fernandez, I.
  • Delgado, F.
  • Zobaa, Ahmed F.

Abstract

The increasing use of small wind energy has made it necessary to develop new methods to improve the efficiency of this technology. This improvement is best achieved considering the interaction between the various components, such as the wind rotors, the electrical generators, the rectifiers and the inverters, as opposed to studying the individual components in isolation. This paper describes a methodology to increase the efficiency of Small Wind Turbines (SWTs) equipped with a Permanent Magnet Synchronous Machine (PMSM). To achieve this objective, capacitor banks will be connected between the PMSM and the rectifier. This methodology is motivated by two clear aims. The first one is to operate the SWT with its maximum power coefficient Cp. The second one is to select the most suitable capacitor bank for each wind speed to optimise the energy supplied to the grid. The methodology will be tested on a commercial 3.5kW SWT, and the results will be studied to determine its feasibility.

Suggested Citation

  • Arroyo, A. & Manana, M. & Gomez, C. & Fernandez, I. & Delgado, F. & Zobaa, Ahmed F., 2013. "A methodology for the low-cost optimisation of small wind turbine performance," Applied Energy, Elsevier, vol. 104(C), pages 1-9.
    • Handle: RePEc:eee:appene:v:104:y:2013:i:c:p:1-9
    DOI: 10.1016/j.apenergy.2012.10.068
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    References listed on IDEAS

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    Cited by:

    1. Chi-Jeng Bai & Wei-Cheng Wang & Po-Wei Chen & Wen-Tong Chong, 2014. "System Integration of the Horizontal-Axis Wind Turbine: The Design of Turbine Blades with an Axial-Flux Permanent Magnet Generator," Energies, MDPI, vol. 7(11), pages 1-21, November.
    2. Xu, F.J. & Yuan, F.G. & Hu, J.Z. & Qiu, Y.P., 2014. "Miniature horizontal axis wind turbine system for multipurpose application," Energy, Elsevier, vol. 75(C), pages 216-224.
    3. Wang, Long & Wang, Tongguang & Wu, Jianghai & Chen, Guoping, 2017. "Multi-objective differential evolution optimization based on uniform decomposition for wind turbine blade design," Energy, Elsevier, vol. 120(C), pages 346-361.
    4. Carré, Aurélien & Gasnier, Pierre & Roux, Émile & Tabourot, Laurent, 2022. "Extending the operating limits and performances of centimetre-scale wind turbines through biomimicry," Applied Energy, Elsevier, vol. 326(C).
    5. Bertašienė, Agnė & Azzopardi, Brian, 2015. "Synergies of Wind Turbine control techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 336-342.
    6. Chehouri, Adam & Younes, Rafic & Ilinca, Adrian & Perron, Jean, 2015. "Review of performance optimization techniques applied to wind turbines," Applied Energy, Elsevier, vol. 142(C), pages 361-388.
    7. Chen, Guodong & Jiao, Jiu Jimmy & Jiang, Chuanyin & Luo, Xin, 2024. "Surrogate-assisted level-based learning evolutionary search for geothermal heat extraction optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).

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