Performance Evaluation of Grid-Connected Photovoltaic System using SHO-VPTIDF

The design of a Spotted Hyena Optimization Algorithm-Variable Parameter Tilt Integral Derivative with Filter (SHO-VPTIDF) controller for improved performance and enhanced devaluation of harmonic components of grid-connected photovoltaic systems is the main objective of the suggested manuscript. The SHO-VPTIDF controller is proposed by reformulating Tilt Integral Derivative Controller with Filter (TIDCF). The TIDCF is characterized by longer simulation time, lower robustness, longer settling time, attenuated ability for noise rejection, and limited use. This research gap is addressed by replacing the constant gains of TIDCF by variable parameter tilt integral derivative with filter. The VPTIDF replaces the constant gains of TIDCF with error varying control parameters to improve the robustness of the system. The photovoltaic system with nonlinearities causes power quality issues and occasional faults, which can be detected by using Levenberg-Marquardt Algorithm (LMA) based machine learning technique. The novelties of the proposed manuscript including improved stability, better robustness, upgraded accuracy, better harmonic mitigation ability, and improved ability to handle uncertainties are verified in a Matlab simulink environment. In this manuscript, the SHO-VPTIDF and the Direct and Quadrature Control based Sinusoidal Pulse Width Modulation (DQCSPWM) method are employed for fault classification, harmonic diminishing, stability enhancement, better system performance, better accuracy, improved robustness, and better capabilities to handle system uncertainties.