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Wireless communication architectures based on data aggregation for internal monitoring of large-scale wind turbines

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  • Mohamed A. Ahmed
  • Young-Chon Kim

Abstract

Wireless networks are regarded as a promising candidate for condition monitoring systems of large-scale wind turbines due to the design flexibility, easy deployment, and reduced installation cost. This article investigates different data aggregation approaches of wireless-based architectures for the internal monitoring of a large-scale wind turbine. The main objective is to construct a wireless internal network inside the wind turbine nacelle, for collecting sensing data from different parts and transmitting the data to a remote control center through a wireless external network that serves the turbine towers of the wind farm. The proposed wireless network architectures consist of wireless sensor nodes, coordinator nodes, and a front-end device. The designs of the wireless-based architectures involve choices of physical components, sensor types, sampling rate, and data rate. Wi-Fi is a promising technology that is considered for the wind turbine internal network in this work. Through simulations, the network performance is evaluated with regard to end-to-end delay for different data aggregation approaches of wireless-based architectures.

Suggested Citation

  • Mohamed A. Ahmed & Young-Chon Kim, 2016. "Wireless communication architectures based on data aggregation for internal monitoring of large-scale wind turbines," International Journal of Distributed Sensor Networks, , vol. 12(8), pages 15501477166, August.
    • Handle: RePEc:sae:intdis:v:12:y:2016:i:8:p:1550147716662776
    DOI: 10.1177/1550147716662776
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    References listed on IDEAS

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    1. Gang Zheng & Hongbing Xu & Xinheng Wang & Jianxiao Zou, 2010. "Applications of WiMAX-based wireless mesh network in monitoring wind farms," International Journal of Networking and Virtual Organisations, Inderscience Enterprises Ltd, vol. 7(6), pages 535-548.
    2. García Márquez, Fausto Pedro & Tobias, Andrew Mark & Pinar Pérez, Jesús María & Papaelias, Mayorkinos, 2012. "Condition monitoring of wind turbines: Techniques and methods," Renewable Energy, Elsevier, vol. 46(C), pages 169-178.
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