Affiliations: [a] Department of EEE, Kumaraguru College of Technology, Coimbatore, Tamilnadu, India
| [b] Department of Electrical & Electronics Engineering, Dr. N.G.P Institute of Technology, Coimbatore, Tamilnadu, India
Correspondence:
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Corresponding author. Sureshkumar Rajagopal, M.E., (Ph.D), Assistant Professor, Department of EEE, Kumaraguru College of Technology, Coimbatore, Tamilnadu, India. E-mail: sureshpls45@gmail.com.
Abstract: As the move towards Grid Integrated-Photovoltaic (GI-PV) system is proposed to improve the power quality development. A novel Adaptive Neuro-Fuzzy Inference System (ANFIS) based on improved Moth Flame Optimization (MFO) algorithm is described for grid integrated approach. The solar integration of Maximum Power Point (MPP) fed into modified Switched Boost Inverter (SBI) is presented, this GI-PV connected circuit has become prominent research in a recent scenario for energy demand. Proposed MFOA-ANFIS controller has generated the duty cycle pulses to each converter circuit. The benefit of grid-tied SBI is direct control outer-loop employed to obtain MFO-ANFIS techniques. To maintain a constant voltage DC-link is employed for inner-loop, this presence of constant DC-power to grid loads with support of MFO-ANFIS assists Proportional Integral Differential (PID) method. The results acquired by the simulation expressed that the proposed controller is addressed to maintain active and reactive power exchange, regulate DC bus-link voltages, grid voltage, and grid current. The effectiveness of the practical implication research is achieved by the output as represented as minimum grid harmonics, load current, and compensator current as verified in MATLAB/Simulink platform.
Keywords: Grid Integrated-Photovoltaic, Maximum Power Point, Adaptive Neuro-Fuzzy Inference System, Moth Flame Optimization Algorithm
