Maximum power point tracking supported proton exchange membrane fuel cell based intelligent dynamic voltage restorer

Abstract

In modern era, electrical power utilities are more concerned about power quality. In this endeavour, dynamic voltage restorer (DVR) provides adequate support to the system. Accordingly, the present work illustrates intelligent hybrid control mechanism for DVR. Artificial neural network (ANN) is incorporated to obtain real-time optimal gains under distinct voltage situations. Closed loop type 2 fuzzy logic (CLT2-FL) is also realized in order to assist the ANN supported unit concomitantly. In order to enhance the potential of the present DVR, a CLT2-FL controlled maximum power point tracking (MPPT) based proton exchange membrane fuel cell arrangement is also explored in the present study. CLT2-FL module is adopted in DC-DC converter topology to provide simultaneous supply to the loads at different and regulated voltage levels. Consequently, the results are evaluated and compared to the state-of-the-arts which unveil the efficacy of the implemented controller against the oddity seen in the voltage waveform, thereby, exhibiting better voltage regulation and less harmonics. The effectiveness of the implemented MPPT unit from the viewpoints of convergence speed and oscillations is also established.