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Experimental evaluation of a tree-shaped quad-rotor wind turbine on power output controllability and survival shutdown capability

Author

Listed:
  • Jiang, Yichen
  • Liu, Shijie
  • Zao, Peidong
  • Yu, Yanwei
  • Zou, Li
  • Liu, Liqin
  • Li, Jiawen

Abstract

Vertical-axis wind turbines are considered to be a better choice for cities and isolated semi-urban areas. However, it is difficult to control their power outputs, especially at high wind speeds, which can potentially cause damage to the generator or the wind turbine structures. In this study, a tree-shaped quad-rotor wind turbine with an active yaw system was proposed to not only effectively control the wind turbine power output but also increase its shutdown capability under survival conditions. To evaluate the proposed design concept, experimental prototypes of the wind turbine and the active yaw system were built and tested in a wind tunnel. To simulate real working conditions, the rotor freely rotated with the change of the wind speed and turbine yaw angle and drove a generator to charge a 24-volt battery. The charging power was measured in the experiments. It was found that the power-extraction efficiency of the quad-rotor configuration was 23% larger than that of the single-rotor configuration. The rotor speed was effectively controlled by changing the turbine’s yaw angle. Under different wind speeds, the total power output of the wind turbine could be stabilized at the given rate. Under survival conditions, the active yaw system was able to adjust the turbine plane parallel to the wind direction and shutdown the rotors to minimize the rotors’ aerodynamic torques, preventing the generators from overspeeding.

Suggested Citation

  • Jiang, Yichen & Liu, Shijie & Zao, Peidong & Yu, Yanwei & Zou, Li & Liu, Liqin & Li, Jiawen, 2022. "Experimental evaluation of a tree-shaped quad-rotor wind turbine on power output controllability and survival shutdown capability," Applied Energy, Elsevier, vol. 309(C).
  • Handle: RePEc:eee:appene:v:309:y:2022:i:c:s030626192101597x
    DOI: 10.1016/j.apenergy.2021.118350
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    Cited by:

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    2. Chao Zhou & Bing Gao & Haiyue Yang & Xudong Zhang & Jiaqi Liu & Lingling Li, 2022. "Junction Temperature Prediction of Insulated-Gate Bipolar Transistors in Wind Power Systems Based on an Improved Honey Badger Algorithm," Energies, MDPI, vol. 15(19), pages 1-19, October.

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