Optimal Design of Islanded Microgrids Considering Distributed Dynamic State Estimation

Mohamed Zaki El-Sharafy, Shivam Saxena, Hany E. Farag

    Research output: Contribution to journalArticlepeer-review

    15 Scopus citations

    Abstract

    This article proposes an optimal zone clustering algorithm of islanded microgrids (IMG) based on supply adequacy taking into account the dynamic performance of distributed state estimation units. The IMG is partitioned into several localized, yet coupled zones, where each zone is responsible for its local state estimate and performs data fusion to reach consensus for shared state variables between zones. The technique proposes a novel algorithm to optimally define the placement of the virtual boundaries of the zones by minimizing the potential power transfer between adjacent zones. The proposed algorithm adopts the distributed particle filter (DPF) technique for the state estimation process. The proposed algorithm also has the ability to come up with one optimal configuration considering different events and scenarios that might occur in the IMG. Monte Carlo simulations demonstrate the efficacy of the proposed technique in the presence of severely corrupted measurements and state values as well as displaying tolerance to major load changes within the IMG. The DPF shows similar performance when compared to its centralized implementation while also providing computational savings by a factor of the number of zones.

    Original languageBritish English
    Article number9072665
    Pages (from-to)1592-1603
    Number of pages12
    JournalIEEE Transactions on Industrial Informatics
    Volume17
    Issue number3
    DOIs
    StatePublished - Mar 2021

    Keywords

    • Distributed particle filter (DPF)
    • dynamic state estimation
    • nonlinear estimation
    • power adequate microgrids

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