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    A novel multi-area distribution state estimation approach for active networks

    , Article Energies ; Volume 14, Issue 6 , 2021 ; 19961073 (ISSN) Gholami, M ; Abbaspour Tehrani Fard, A ; Lehtonen, M ; Moeini-Aghtaie, M ; Fotuhi Firuzabad, M ; Sharif University of Technology
    MDPI AG  2021
    Abstract
    This paper presents a hierarchically distributed algorithm for the execution of distribution state estimation function in active networks equipped with some phasor measurement units. The proposed algorithm employs voltage-based state estimation in rectangular form and is well-designed for large-scale active distribution networks. For this purpose, as the first step, the distribution network is supposed to be divided into some overlapped zones and local state estimations are executed in parallel for extracting operating states of these zones. Then, using coordinators in the feeders and the substation, the estimated local voltage profiles of all zones are coordinated with the local state... 

    Online nonlinear structural damage detection using hilbert Huang transform and artificial neural networks

    , Article Scientia Iranica ; Volume 26, Issue 3A , 2019 , Pages 1266-1279 ; 10263098 (ISSN) Vazirizade, M ; Bakhshi, A ; Bahar, O ; Sharif University of Technology
    Sharif University of Technology  2019
    Abstract
    In order to implement a damage detection strategy and assess the condition of a structure, Structural Health Monitoring (SHM) as a process plays a key role in structural reliability. This paper aims to present a methodology for online detection of damages that may occur during a strong ground excitation. In this regard, Empirical Mode Decomposition (EMD) is superseded by Ensemble Empirical Mode Decomposition (EEMD) in the Hilbert Huang Transformation (HHT). Although analogous with EMD, EEMD brings about more appropriate Intrinsic Mode Functions (IMFs). IMFs are employed to assess the first-mode frequency and mode shape. Afterwards, Artificial Neural Network (ANN) is applied to predict story... 

    Online nonlinear structural damage detection using hilbert huang transform and artificial neural networks

    , Article Scientia Iranica ; Volume 26, Issue 3A , 2019 , Pages 1266-1279 ; 10263098 (ISSN) Vazirizade, M ; Bakhshi, A ; Bahar, O ; Sharif University of Technology
    Sharif University of Technology  2019
    Abstract
    In order to implement a damage detection strategy and assess the condition of a structure, Structural Health Monitoring (SHM) as a process plays a key role in structural reliability. This paper aims to present a methodology for online detection of damages that may occur during a strong ground excitation. In this regard, Empirical Mode Decomposition (EMD) is superseded by Ensemble Empirical Mode Decomposition (EEMD) in the Hilbert Huang Transformation (HHT). Although analogous with EMD, EEMD brings about more appropriate Intrinsic Mode Functions (IMFs). IMFs are employed to assess the first-mode frequency and mode shape. Afterwards, Artificial Neural Network (ANN) is applied to predict story...