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    Power transaction management amongst coupled microgrids in remote areas

    Access Status
    Fulltext not available
    Authors
    Batool, Munira
    Islam, Syed
    Shahnia, Farhad
    Date
    2017
    Type
    Conference Paper
    
    Metadata
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    Citation
    Batool, M. and Islam, S. and Shahnia, F. 2017. Power transaction management amongst coupled microgrids in remote areas, 2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), pp. 775-780: IEEE.
    Source Title
    2017 IEEE Innovative Smart Grid Technologies - Asia: Smart Grid for Smart Community, ISGT-Asia 2017
    Source Conference
    2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia)
    DOI
    10.1109/ISGT-Asia.2017.8378449
    ISBN
    978-1-5386-4950-3
    School
    School of Electrical Engineering, Computing and Mathematical Science (EECMS)
    URI
    http://hdl.handle.net/20.500.11937/72688
    Collection
    • Curtin Research Publications
    Abstract

    © 2017 IEEE. Large remote areas normally have isolated and self-sufficient electricity supply systems, often referred to as microgrids. These systems also rely on a mix of dispatchable and non-dispatcha- ble distributed energy resources to reduce the overall cost of electricity production. Emergencies such as shortfalls, overloading, and faults can cause problems in the operation of these remote area microgrids. This paper presents a power transaction management scheme amongst a few such microgrids when they are coupled provisionally during emergencies. By definition, power transaction is an instance of buying and selling of electricity amongst problem and healthy microgrids. The developed technique aims to define the suitable power generation from all dispatchable sources and regulate the power transaction amongst the coupled microgrids. To this end, an optimization problem is formulated that aims to define the above parameters while minimizing the costs and technical impacts. A mixed- integer linear programming technique is used to solve the formulated problem. The performance of the proposed management strategy is evaluated by numerical analysis in MATLAB.

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