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  • Peak-Load Management in Commercial Systems With Electric Vehicles

    Author(s)
    Mahmud, Khizir
    Hossain, MJ
    Ravishankar, Jayashri
    Griffith University Author(s)
    Hossain, Jahangir
    Year published
    2019
    Metadata
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    Abstract
    Electric vehicles (EVs) are getting popular as one of the effective solutions for increased energy efficiency in commercial systems. This paper proposes an improved algorithm for commercial peak-load management using EVs, battery-energy-storage systems, and photovoltaic units. It uses the bidirectional vehicle-to-grid technique to utilize the energy from EVs in a parking lot. The proposed system has been tested in a real power distribution network in realistic load and weather conditions. The financial benefit of the system is also investigated, and it is found that the industrial peak load can be reduced by 50%, and ...
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    Electric vehicles (EVs) are getting popular as one of the effective solutions for increased energy efficiency in commercial systems. This paper proposes an improved algorithm for commercial peak-load management using EVs, battery-energy-storage systems, and photovoltaic units. It uses the bidirectional vehicle-to-grid technique to utilize the energy from EVs in a parking lot. The proposed system has been tested in a real power distribution network in realistic load and weather conditions. The financial benefit of the system is also investigated, and it is found that the industrial peak load can be reduced by 50%, and the energy cost can be reduced by up to 27.3%. It also enhances the load factor by 9%. The performance of the proposed control algorithm is compared with that of an artificial-neural-network-based technique and tested in a laboratory prototype. From simulated and experimental results, it is found that the proposed approach provides substantial savings, while reducing the peak demand of the existing grids.
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    Journal Title
    IEEE SYSTEMS JOURNAL
    Volume
    13
    Issue
    2
    DOI
    https://doi.org/10.1109/JSYST.2018.2850887
    Subject
    Electrical engineering
    Electronics, sensors and digital hardware
    Publication URI
    http://hdl.handle.net/10072/385584
    Collection
    • Journal articles

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