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    Master control unit based power exchange strategy for interconnected microgrids

    Access Status
    Fulltext not available
    Authors
    Batool, M.
    Islam, Syed
    Shahnia, Farhad
    Date
    2018
    Type
    Conference Paper
    
    Metadata
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    Citation
    Batool, M. and Islam, S. and Shahnia, F. 2018. Master control unit based power exchange strategy for interconnected microgrids, 2017 Australasian Universities Power Engineering Conference: IEEE.
    Source Title
    2017 Australasian Universities Power Engineering Conference, AUPEC 2017
    Source Conference
    2017 Australasian Universities Power Engineering Conference
    DOI
    10.1109/AUPEC.2017.8282475
    ISBN
    9781538626474
    School
    School of Electrical Engineering, Computing and Mathematical Science (EECMS)
    URI
    http://hdl.handle.net/20.500.11937/69446
    Collection
    • Curtin Research Publications
    Abstract

    © 2017 IEEE. Large remote area networks normally have self-suffi-cient electricity systems. These systems also rely on non-dispatchable DGs (N-DGs) for overall reduction in cost of electricity production. It is a fact that uncertainties included in the nature of N-DGs as well as load demand can cause cost burden on islanded microgrids (MGs). This paper proposes development of power exchange strategy for an interconnected MGs (IMG) system as part of large remote area network with optimized controls of dispatchable (D-DGs) which are members of master control unit (MCU). MCU analysis includes equal cost increment principle to give idea about the amount of power exchange which could take place with neighbor MGs in case of overloading situation. Sudden changes in N-DGs and load are defined as interruptions and are part of analysis too. Optimization problem is formulated on the basis of MCU adjustment for overloading or under loading situation and suitability of support MG (S-MG) in IMG system for power exchange along with key features of low cost and minimum technical impacts. Mixed integer linear programming (MILP) technique is applied to solve the formulated problem. The impact of proposed strategy is assessed by numerical analysis in MATLAB programming under stochastic environment.

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