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    Optimized Energy Procurement for Cellular Networks with Uncertain Renewable Energy Generation

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    Type
    Conference Paper
    Authors
    Rached, Nadhir B.
    Ghazzai, Hakim cc
    Kadri, Abdullah
    Alouini, Mohamed-Slim cc
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Applied Mathematics and Computational Science Program
    Electrical Engineering Program
    Date
    2017-02-07
    Online Publication Date
    2017-02-07
    Print Publication Date
    2016-12
    Permanent link to this record
    http://hdl.handle.net/10754/623884
    
    Metadata
    Show full item record
    Abstract
    Renewable energy (RE) is an emerging solution for reducing carbon dioxide (CO2) emissions from cellular networks. One of the challenges of using RE sources is to handle its inherent uncertainty. In this paper, a RE powered cellular network is investigated. For a one-day operation cycle, the cellular network aims to reduce energy procurement costs from the smart grid by optimizing the amounts of energy procured from their locally deployed RE sources as well as from the smart grid. In addition to that, it aims to determine the extra amount of energy to be sold to the electrical grid at each time period. Chance constrained optimization is first proposed to deal with the randomness in the RE generation. Then, to make the optimization problem tractable, two well- know convex approximation methods, namely; Chernoff and Chebyshev based-approaches, are analyzed in details. Numerical results investigate the optimized energy procurement for various daily scenarios and compare between the performances of the employed convex approximation approaches.
    Citation
    Ben Rached N, Ghazzai H, Kadri A, Alouini M-S (2016) Optimized Energy Procurement for Cellular Networks with Uncertain Renewable Energy Generation. 2016 IEEE Global Communications Conference (GLOBECOM). Available: http://dx.doi.org/10.1109/glocom.2016.7842105.
    Sponsors
    This work was made possible by NPRP grant # 6-001-2-001 from the Qatar National Research Fund (A member of The Qatar Foundation). The statements made herein are solely the responsibility of the authors.
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2016 IEEE Global Communications Conference (GLOBECOM)
    DOI
    10.1109/glocom.2016.7842105
    Additional Links
    http://ieeexplore.ieee.org/document/7842105/
    ae974a485f413a2113503eed53cd6c53
    10.1109/glocom.2016.7842105
    Scopus Count
    Collections
    Conference Papers; Applied Mathematics and Computational Science Program; Electrical Engineering Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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