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    A Demand Response based solution to Overloading in Underdeveloped Distribution Networks

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    Type
    Article
    Authors
    Jibran, Muhammad
    Nasir, Hasan Arshad
    Qureshi, Faran Ahmed
    Ali, Usman
    Jones, Colin
    Mahmood, Imran
    KAUST Department
    Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
    Date
    2021-05-13
    Online Publication Date
    2021-05-13
    Print Publication Date
    2021-09
    Permanent link to this record
    http://hdl.handle.net/10754/669210
    
    Metadata
    Show full item record
    Abstract
    This paper addresses the problem of overloading in power distribution networks, which stems from the transmission systems being incapable of delivering power from source to consumers during peak hours. This causes frequent power-outages (or blackouts), requiring the consumers to rely on alternative energy sources, e.g. Uninterrupted Power Supply (UPS) systems with batteries to meet their essential needs. This paper proposes a demand response (DR) framework to eliminate the problem of network overloading. The flexibility in the consumption of batteries and air conditioners (ACs) is exploited in the proposed framework. The operation of ACs is manipulated while maintaining occupant comfort, and the power flow from mains and batteries is scheduled based on an ensemble of demand forecast avoiding network overloading and consequent power-outages. The problem is modeled in an optimal control setting and solved using a stochastic model predictive control strategy, and a computationally effective method is also proposed to efficiently solve the underlying optimization problems. Towards the end, simulation results show the efficacy of the proposed framework to avoid overloading.
    Citation
    Jibran, M., Nasir, H. A., Qureshi, F. A., Ali, U., Jones, C., & Mahmood, I. (2021). A Demand Response based solution to Overloading in Underdeveloped Distribution Networks. IEEE Transactions on Smart Grid, 1–1. doi:10.1109/tsg.2021.3079959
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    IEEE Transactions on Smart Grid
    DOI
    10.1109/TSG.2021.3079959
    Additional Links
    https://ieeexplore.ieee.org/document/9430607/
    ae974a485f413a2113503eed53cd6c53
    10.1109/TSG.2021.3079959
    Scopus Count
    Collections
    Articles; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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