Design of Γ-Source Inverter with Finite Step Model Predictive Control Strategy

K. Gopalakrishnan, E. Prasannakumar

Abstract: The Techniques of maximum power point tracking (MPPT) implemented with finite step model predictive control (FSMPC) for the application of Γ -source inverter presented in this paper. Incremental conductance MPPT algorithm and FSMPC model is developed to control the output current of the Γ source inverter in order to extract maximum solar power from the panel. Impedance-source inverters are inverters with voltage-buck-boost capability that cannot be achieved by the traditional inverters. Their boost capability is introduced by shorting their phase-legs without causing damages. Present impedance-source inverters are however burdened by their low modulation ratio at high input-to-output gain. Such low modulation usually leads to high voltage stresses across the components and poor spectral performance at the inverter output. To avoid these problems, inverters with coupled transformers have been introduced, but they usually lead to high turns ratio, and hence many winding turns, at high gain. An alternative would then be the Γ -source inverters proposed in the paper, whose gain is raised by lowering their turns ratio towards unity. The output current, passive component voltage and current are well regulated with proposed MPPT based FSMPC control strategy.

Keywords:  MPPT–maximum power point tracking, FSMPC-finite step model protective control, PCC- Predictive current control, PWM-,Pulse with modulation TSI- t-source inverter ,SPV-solar photo voltaic, DM-differential mode, MPP–maximum power point.

Title: Design of Γ-Source Inverter with Finite Step Model Predictive Control Strategy

Author: K. Gopalakrishnan, E. Prasannakumar

International Journal of Electrical and Electronics Research

ISSN 2348-6988 (online)

Research Publish Journals

Vol. 3, Issue 2, April 2015 - June 2015

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Design of Γ-Source Inverter with Finite Step Model Predictive Control Strategy by K. Gopalakrishnan, E. Prasannakumar