Next generation hybrid based flying squirrel search optimization approach for cubic boost converter used in solar photovoltaic system

Abstract

Renewable energy sources (RES) reveal potential for the near future since they are sustainable and generate clean energy. Currently grid-connected solar photovoltaic (SPV) systems are becoming increasingly significant in meeting energy demand and contributing to clean energy production. The power electronic converter (PEC) plays a significant role in conversion, regulating and controlling the flow of power from RES. This research primarily focuses on high-gain cubic boost converter (HG-CBC) and simulated with the help of MATLAB/Simulink. The results are evaluated and contrasted with both traditional and other high-gain boost converters, focusing on the boost factor (B) and the total part count. It is essential to integrate SPV modules with MPPT system to capture the peak power available under varying temperature (T) and solar irradiation (G) levels. This research introduces a new hybrid based flying squirrel search optimization (FSSO) approach combined with Perturb & Observe (P&O) MPPT approach which allows for faster MPP, lesser oscillations at the output and high accuracy with less convergence time in contrast with P&O and FSSO MPPT. The proposed hybrid based HFSSO with P&O MPPT with HG-CBC exhibits low output voltage ripples of 0.039 % and a contrast lower rising time of 0.264 s and settled at 0.6 s.