• DocumentCode
    2629178
  • Title

    Control of shunt custom power device based on Anti-Hebbian learning algorithm

  • Author

    Arya, Sabha Raj ; Singh, Bhim ; Chandra, Ambrish ; Al-Haddad, Kamal

  • Author_Institution
    Dept. of Electr. Eng., Indian Inst. of Technol., Delhi, Delhi, India
  • fYear
    2012
  • fDate
    25-28 Oct. 2012
  • Firstpage
    1246
  • Lastpage
    1251
  • Abstract
    This paper presents an implementation of shunt custom power device namely distribution static compensator (DSTATCOM) using a neural network based Anti Hebbian control algorithm for power quality improvement under linear/nonlinear type consumer loads. Learning based Anti-Hebbian control algorithm is used for extraction of fundamental active and reactive power components of load currents in terms of weighted signals which are used for deriving the reference source currents. This control algorithm is implemented on a developed DSTATCOM using a DSP for reactive power compensation, harmonic elimination and load balancing. Simulation and test results demonstrate satisfactory performance of proposed control algorithm for the control of DSTATCOM under time varying loads.
  • Keywords
    neurocontrollers; power supply quality; reactive power control; static VAr compensators; DSP; DSTATCOM; active power components; anti Hebbian control algorithm; antiHebbian learning algorithm; control algorithm; distribution static compensator; harmonic elimination; load balancing; load currents; neural network; power quality improvement; reactive power components; shunt custom power device control; time varying loads; Digital signal processing; Harmonic analysis; Load modeling; Manganese; DSTATCOM; Harmonics; Load Balancing; Neural Network; PFC; Reactive Power Compensation; ZVR;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society
  • Conference_Location
    Montreal, QC
  • ISSN
    1553-572X
  • Print_ISBN
    978-1-4673-2419-9
  • Electronic_ISBN
    1553-572X
  • Type

    conf

  • DOI
    10.1109/IECON.2012.6388592
  • Filename
    6388592