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Cognitive radio sensor networks: Smart communication for smart grids—A case study of Pakistan

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  • Khan, Zeeshan Ali
  • Faheem, Yasir

Abstract

A smart grid has recently gained significant attention as it is an important direction of power system advancement. The integration of renewable energy (RE) resources to the power system and the reduction of energy losses need an efficient and low-cost communication infrastructure. Cognitive radio sensor networks (CRSN) can be integrated in a smart grid to meet these challenges. CRSN is a new paradigm of research where the best of wireless sensor networks (WSN) and cognitive radios (CR) is combined. The sensor networks monitor a physical parameter and the measures value is transmitted using the cognitive radio. Thus, CRSN can be used for realizing the sensing and communication part in a smart grid network. In this paper, a smart grid network is proposed using CRSN for implementing it in the remote areas of Pakistan. The service coverage map is taken from the Pakistan Telecommunication Authority (PTA) website that regulates the spectrum band in Pakistan. This can be used in developing countries to realize a cost effective smart grid for integrating the renewable resources and for reducing energy losses.

Suggested Citation

  • Khan, Zeeshan Ali & Faheem, Yasir, 2014. "Cognitive radio sensor networks: Smart communication for smart grids—A case study of Pakistan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 463-474.
    • Handle: RePEc:eee:rensus:v:40:y:2014:i:c:p:463-474
    DOI: 10.1016/j.rser.2014.07.144
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    References listed on IDEAS

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    1. Markovic, Dragan S. & Zivkovic, Dejan & Branovic, Irina & Popovic, Ranko & Cvetkovic, Dragan, 2013. "Smart power grid and cloud computing," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 566-577.
    2. Usman, Ahmad & Shami, Sajjad Haider, 2013. "Evolution of Communication Technologies for Smart Grid applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 191-199.
    3. Sahu, Bikash Kumar & Hiloidhari, Moonmoon & Baruah, D.C., 2013. "Global trend in wind power with special focus on the top five wind power producing countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 348-359.
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    Cited by:

    1. Emmanuel Ogbodo & David Dorrell & Adnan Abu-Mahfouz, 2021. "Energy-efficient distributed heterogeneous clustered spectrum-aware cognitive radio sensor network for guaranteed quality of service in smart grid," International Journal of Distributed Sensor Networks, , vol. 17(7), pages 15501477211, July.
    2. Tuballa, Maria Lorena & Abundo, Michael Lochinvar, 2016. "A review of the development of Smart Grid technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 710-725.
    3. Dileep, G., 2020. "A survey on smart grid technologies and applications," Renewable Energy, Elsevier, vol. 146(C), pages 2589-2625.
    4. Irfan, Muhammad & Iqbal, Jamshed & Iqbal, Adeel & Iqbal, Zahid & Riaz, Raja Ali & Mehmood, Adeel, 2017. "Opportunities and challenges in control of smart grids – Pakistani perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 652-674.
    5. Zahurul, S. & Mariun, N. & Grozescu, I.V. & Tsuyoshi, Hanamoto & Mitani, Yasunori & Othman, M.L. & Hizam, H. & Abidin, I.Z., 2016. "Future strategic plan analysis for integrating distributed renewable generation to smart grid through wireless sensor network: Malaysia prospect," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 978-992.

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