A Cognitive Radio-Based Energy-Efficient System for Power Transmission Line Monitoring in Smart Grids

The research in industry and academia on smart grids is predominantly focused on the regulation of generated power and management of its consumption. Because transmission of bulk-generated power to the consumer is immensely reliant on secure and efficient transmission grids, comprising huge electric...

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Bibliographic Details
Published in:Journal of sensors 2017-01, Vol.2017 (2017), p.1-12
Main Authors: Koo, Insoo, Hyun, Seung Ho, Lee, Young-Doo, Ahmed, Saeed
Format: Article
Language:English
Subjects:
Batteries
Cognitive radio
Electricity distribution
Energy consumption
Energy efficiency
Energy management
Energy transmission
Integer programming
International conferences
Maximization
Mechanical drives
Monitoring
Monitoring systems
Multimedia communications
Power consumption
Power management
Power transmission
Provisioning
Radio networks
Resource allocation
Sensors
Smart grid technology
Telecommunications industry
Transmission lines
Wireless communications
Wireless networks
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Summary:The research in industry and academia on smart grids is predominantly focused on the regulation of generated power and management of its consumption. Because transmission of bulk-generated power to the consumer is immensely reliant on secure and efficient transmission grids, comprising huge electrical and mechanical assets spanning a vast geographic area, there is an impending need to focus on the transmission grids as well. Despite the challenges in wireless technologies for SGs, cognitive radio networks are considered promising for provisioning of communications services to SGs. In this paper, first, we present an IEEE 802.22 wireless regional area network cognitive radio-based network model for smart monitoring of transmission lines. Then, for a prolonged lifetime of battery finite monitoring network, we formulate the spectrum resource allocation problem as an energy efficiency maximization problem, which is a nonlinear integer programming problem. To solve this problem in an easier way, we propose an energy-efficient resource-assignment scheme based on the Hungarian method. Performance analysis shows that, compared to a pure opportunistic assignment scheme with a throughput maximization objective and compared to a random scheme, the proposed scheme results in an enhanced lifetime while consuming less battery energy without compromising throughput performance.
ISSN:1687-725X
1687-7268
DOI:10.1155/2017/3862375