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    Power Quality Improvement Using an Enhanced Network-Side-Shunt-Connected Dynamic Voltage Restorer

    Access Status
    Fulltext not available
    Authors
    Fereidouni, Alireza
    Masoum, M.
    Moghbel, Moayed
    Date
    2015
    Type
    Journal Article
    
    Metadata
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    Citation
    Fereidouni, A. and Masoum, M. and Moghbel, M. 2015. Power Quality Improvement Using an Enhanced Network-Side-Shunt-Connected Dynamic Voltage Restorer. International Journal of Emerging Electric Power Systems. 16 (5): pp. 451-472.
    Source Title
    International Journal of Emerging Electric Power Systems
    DOI
    10.1515/ijeeps-2015-0019
    ISSN
    2194-5756
    School
    Department of Electrical and Computer Engineering
    URI
    http://hdl.handle.net/20.500.11937/35284
    Collection
    • Curtin Research Publications
    Abstract

    Among the four basic dynamic voltage restorer (DVR) topologies, the network-side shunt-connected DVR (NSSC-DVR) has a relatively poor performance and is investigated in this paper. A new configuration is proposed and implemented for NSSC-DVR to enhance its performance in compensating (un)symmetrical deep and long voltage sags and mitigate voltage harmonics. The enhanced NSSC-DVR model includes a three-phase half-bridge semi-controlled network-side-shunt-connected rectifier and a three-phase full-bridge series-connected inverter implemented with a back-to-back configuration through a bidirectional buck-boost converter. The network-side-shunt-connected rectifier is employed to inject/draw the required energy by NSSC-DVR to restore the load voltage to its pre-fault value under sag/swell conditions. The buck-boost converter is responsible for maintaining the DC-link voltage of the series-connected inverter at its designated value in order to improve the NSSC-DVR capability in compensating deep and long voltage sags/swells. The full-bridge series-connected inverter permits to compensate unbalance voltage sags containing zero-sequence component. The harmonic compensation of the load voltage is achieved by extracting harmonics from the distorted network voltage using an artificial neural network (ANN) method called adaptive linear neuron (Adaline) strategy. Detailed simulations are performed by SIMULINK/MATLAB software for six case studies to verify the highly robustness of the proposed NSSC-DVR model under various conditions.

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