(2) Priyanka Chaudhary (Noida International University, India)
(3) * Owais Ahmad Shah (K.R. Mangalam University, India)
*corresponding author
AbstractA proposal is presented for a low voltage (LV) grid integrated single-stage solar photovoltaic (SPV) system, accompanied by a hybrid control methodology aimed at optimizing system performance. To address prevailing challenges, the hybrid method incorporates the Adaptive Neuro-Fuzzy Inference System (ANFIS). Anticipated benefits of this initiative include efficient power distribution, load connectivity facilitated by the system, and operational functionalities such as mode zero voltage regulation and power factor adjustment. These functionalities collectively enhance energy quality by mitigating harmonic components, compensating for reactive power, and ensuring load balance. The proposed control strategy for a photovoltaic (PV) system interfaced with the grid is designed to exhibit rapid response times in both static and dynamic conditions. Comparative analyses were conducted between the output of our method and that of several competing approaches. The MATLAB/Simulink platform is employed for the purpose of demonstrating the developed system. The results show the extent to which the proposed controller works with reactive power compensation and load balancing to minimize network harmonics and maximize power consumption while keeping power factor functions at unity.
KeywordsANN Controller for Solar Photovoltaic; Bidirectional DC/DC Converter; Battery Storage System; Fuel Cell
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DOIhttps://doi.org/10.31763/ijrcs.v4i1.1242 |
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