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Towing Test Data Set of the Kyushu University Kite System

Author

Listed:
  • Mostafa A. Rushdi

    (Interdisciplinary Graduate School of Engineering Sciences (IGSES - ESST), Kyushu University, 6-1 Kasugakoen, Kasuga, Fukuoka 816-8580, Japan
    Faculty of Engineering and Technology, Future University in Egypt (FUE), 5th Settlement, New Cairo 11835, Egypt)

  • Tarek N. Dief

    (Research Institute for Applied Mechanics (RIAM), Kyushu University, 6-1 Kasugakoen, Kasuga, Fukuoka 816-8580, Japan)

  • Shigeo Yoshida

    (Research Institute for Applied Mechanics (RIAM), Kyushu University, 6-1 Kasugakoen, Kasuga, Fukuoka 816-8580, Japan)

  • Roland Schmehl

    (Faculty of Aerospace Engineering, Delft University of Technology, 2629 HS Delft, The Netherlands)

Abstract

Kites can be used to harvest wind energy with substantially lower material and environmental footprints and a higher capacity factor than conventional wind turbines. In this paper, we present measurement data from seven individual tow tests with the kite system developed by Kyushu University. This system was designed for 7 kW traction power and comprises an inflatable wing of 6 m 2 surface area with a suspended kite control unit that is towed on a relatively short tether of 0.4 m by a truck driving at constant speed along a straight runway. To produce a controlled relative flow environment, the experiment was conducted only when the background wind speed was negligible. We recorded the time-series of 11 different sensor values acquired on the kite, the control unit and the truck. The measured data can be used to assess the effects of the towing speed, the flight mode and the lengths of the control lines on the tether force.

Suggested Citation

  • Mostafa A. Rushdi & Tarek N. Dief & Shigeo Yoshida & Roland Schmehl, 2020. "Towing Test Data Set of the Kyushu University Kite System," Data, MDPI, vol. 5(3), pages 1-18, August.
    • Handle: RePEc:gam:jdataj:v:5:y:2020:i:3:p:69-:d:394012
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    References listed on IDEAS

    as
    1. Mostafa A. Rushdi & Ahmad A. Rushdi & Tarek N. Dief & Amr M. Halawa & Shigeo Yoshida & Roland Schmehl, 2020. "Power Prediction of Airborne Wind Energy Systems Using Multivariate Machine Learning," Energies, MDPI, vol. 13(9), pages 1-23, May.
    2. Cherubini, Antonello & Papini, Andrea & Vertechy, Rocco & Fontana, Marco, 2015. "Airborne Wind Energy Systems: A review of the technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1461-1476.
    3. Bechtle, Philip & Schelbergen, Mark & Schmehl, Roland & Zillmann, Udo & Watson, Simon, 2019. "Airborne wind energy resource analysis," Renewable Energy, Elsevier, vol. 141(C), pages 1103-1116.
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