A Solar PV Integrated UPQC to Enhance Power Quality using SEA Gull ANFIS Algorithm

Abstract

A PV (photovoltaic) controller is a device used in solar energy systems to manage the charging of batteries from solar panels efficiently. Total Harmonic Distortion (THD) reduction in PV (photovoltaic) systems is crucial for ensuring the efficient and reliable operation of the system while minimizing potential interference with the grid or other connected electrical equipment. This paper proposes an effective THD reduction model for PV applications. The proposed model incorporates the Unified Power Quality Conditioners (UPQC) for photovoltaic (PV). The UPQC in the PV is Optimized with the Seagull model for the estimation of values in the PV system. The optimization is performed with the Second-order derivatives of the Enhanced Second-Order Generalized Integrator (ESOGI). The derived model of the ESOGI model uses the Adaptive Neuro-Fuzzy Inference System (ANFIS) with SeaGull Optimization (SGO) for the voltage regulation in the PV system. The performance of the proposed model is implemented and tested with the different parameters illustrated that the performance of UPQC systems in terms of Total Harmonic Distortion (THD), Voltage Regulation, Power Factor Improvement, Reactive and Real Power Compensation, Voltage Stability, and Grid Stability. The proposed methodology demonstrates significant reductions in THD, tighter voltage regulation, enhanced power factor, and improved grid stability compared to conventional control techniques. The ESOGI-ANFIS-SGO optimization approach exhibits robustness and adaptability in handling variations in PV power output and grid conditions.