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A Gravitational Search Algorithm (GSA) based Photo-Voltaic (PV) excitation control strategy for single phase operation of three phase wind-turbine coupled induction generator

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  • Chatterjee, Arunava
  • Roy, Krishna
  • Chatterjee, Debashis

Abstract

Three phase induction generators are widely used for single phase operation in wind based micro-generation schemes to cater single phase loads due to various advantages. This paper presents an improved control methodology for self excited three phase induction generator operating in single phase mode. The excitation is controlled through an inverter with Photo-Voltaic (PV) panels providing power to the dc bus. The proposed technique enables the generator for building up voltage from low wind speeds compared to conventional three phase machines. A capacitor connected across load terminals reduces the reactive power supplied by the inverter connected across the other two phases. Gravitational search algorithm (GSA) is used to calculate the switching angles of the inverter under various load and wind speeds for minimum Total Harmonic Distortion (THD) of the generated voltage. The proposed induction generator is aimed to be conveniently used in remote and grid isolated areas as a portable source of electrical power driving single phase loads. Simulations and experiments performed on a 3-phase 1 kW, 415 V, 50 Hz, 1440 r/min induction machine validates the proposed concept.

Suggested Citation

  • Chatterjee, Arunava & Roy, Krishna & Chatterjee, Debashis, 2014. "A Gravitational Search Algorithm (GSA) based Photo-Voltaic (PV) excitation control strategy for single phase operation of three phase wind-turbine coupled induction generator," Energy, Elsevier, vol. 74(C), pages 707-718.
    • Handle: RePEc:eee:energy:v:74:y:2014:i:c:p:707-718
    DOI: 10.1016/j.energy.2014.07.037
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    3. Hannan, M.A. & Ali, Jamal A. & Mohamed, Azah & Hussain, Aini, 2018. "Optimization techniques to enhance the performance of induction motor drives: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1611-1626.
    4. Arturo Valdivia-González & Daniel Zaldívar & Erik Cuevas & Marco Pérez-Cisneros & Fernando Fausto & Adrián González, 2017. "A Chaos-Embedded Gravitational Search Algorithm for the Identification of Electrical Parameters of Photovoltaic Cells," Energies, MDPI, vol. 10(7), pages 1-25, July.

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