Sensors 2010, 10(10), 9349-9358; doi:10.3390/s101009349
Article

A Reliable Data Delivery Mechanism for Grid Power Quality Using Neural Networks in Wireless Sensor Networks

1 Department of Information Media, University of Suwon/San 2-2, Wau-ri, Bongdam-eup, Hwaseong-si, Gyeonggi-do, 445-743, Korea 2 Department of Electrical Engineering, University of Incheon/12-1, Sondo-dong, Yeonsu-gu, Incheon, 406-840, Korea 3 Computer Science and Information Engineering, Inha University/253, Yonghyun-dong, Nam-gu, Incheon, 402-751, Korea
* Author to whom correspondence should be addressed.
Received: 23 August 2010; in revised form: 24 September 2010 / Accepted: 30 September 2010 / Published: 18 October 2010
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Abstract: Power grids deal with the business of generation, transmission, and distribution of electric power. Current systems monitor basic electrical quantities such as voltage and current from major pole transformers using their temperature. We improve the current systems in order to gather and deliver the information of power qualities such as harmonics, voltage sags, and voltage swells. In the system, data delivery is not guaranteed for the case that a node is lost or the network is congested, because the system has in-line and multi-hop architecture. In this paper, we propose a reliable data delivery mechanism by modeling an optimal data delivery function by employing the neural network concept.
Keywords: neural network; sensor network; cost function; data delivery mechanism; power quality

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MDPI and ACS Style

Lim, Y.; Kim, H.-M.; Kang, S. A Reliable Data Delivery Mechanism for Grid Power Quality Using Neural Networks in Wireless Sensor Networks. Sensors 2010, 10, 9349-9358.

AMA Style

Lim Y, Kim H-M, Kang S. A Reliable Data Delivery Mechanism for Grid Power Quality Using Neural Networks in Wireless Sensor Networks. Sensors. 2010; 10(10):9349-9358.

Chicago/Turabian Style

Lim, Yujin; Kim, Hak-Man; Kang, Sanggil. 2010. "A Reliable Data Delivery Mechanism for Grid Power Quality Using Neural Networks in Wireless Sensor Networks." Sensors 10, no. 10: 9349-9358.

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