Nonlinear, reduced order, distributed state estimation in microgrids

Shivam Saxena, Amir Asif, Hany Farag

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    5 Scopus citations

    Abstract

    Recent developments in microgrids place strict constraints on the underlying state estimation technology, including the need for a dynamic and distributed approach. Since the problem is reminiscent of classical information fusion [2], the paper explores the application of a fusion-based reduced order, distributed unscented particle filter (FR/DUPF) for dynamic state estimation in microgrids. By partitioning the nonlinear microgrid into a network of nsub localized and dynamically coupled systems, the FR/DUPF provides computational savings of a factor of nsub over its centralized version. Monte Carlo simulations verify its accuracy by confirming that estimates from the FR/DUPF and centralized filter evolve close to the ground truth.

    Original languageBritish English
    Title of host publication2015 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages2874-2878
    Number of pages5
    ISBN (Electronic)9781467369978
    DOIs
    StatePublished - 4 Aug 2015
    Event40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Brisbane, Australia
    Duration: 19 Apr 201424 Apr 2014

    Publication series

    NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
    Volume2015-August
    ISSN (Print)1520-6149

    Conference

    Conference40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015
    Country/TerritoryAustralia
    CityBrisbane
    Period19/04/1424/04/14

    Keywords

    • Distributed estimation
    • Distributed generation
    • Islanded grids
    • Microgrids
    • Nonlinear estimation
    • Particle filters

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