A novel optimization approach using multi-objective PSO incorporated with SEPIC and buck-boost converters for renewable energy sources

Dynamic conduct of sunlight-based vitality asset involves the need of hearty controllers that can merge to the Maximum Power Point (MPP) toward augment vitality reap. As of late, the sun powered vitality has turned out to be a standout amongst the most critical elective wellsprings of electric vitality, so it is vital to work Photovoltaic (PV) board at the ideal point to get the conceivable greatest productivity. In this article it particularly shows another improvement way to deal with expand the energy of a PV board utilizing Multi-objective Particle Swarm Optimization (PSO) advancement alongside buck-boost converters. The strategy which depends on target work speaks to the yield energy of the PV board and limitations, equity and imbalance. An enhanced SEPIC converter that joins a fixed step Model Predictive Controller (MPC), to accelerate the control circle which connected to a buck boost converter was investigated in this research article. The proposed system is of higher viability and strength over ordinary strategy and it separates most extreme information voltage and less total harmonic distortion in output. To check the converter's operation, the simulation result from MATLAB/SIMULINK is used.