UPQC-Based Power Quality Improvement in Grid-linked PV, Battery & Wind Systems

Abstract

This paper portrays an examination into the enhancement of power quality in grid-connected photovoltaic (PV), battery, and wind systems using Unified Power Quality Conditioner (UPQC). The incorporation of non-conventional energy resources such as PV, wind, and battery storage into the grid introduces challenges related to power fluctuations, voltage sags, harmonics, and power factor variations. To address these confronts, the UPQC approach is employed to improve power quality parameters and ensure grid stability. In this study, Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) techniques are utilized for both PV and wind energy systems to optimize power extraction from these sources. Additionally, Adaptive Neuro-Fuzzy Inference System (ANFIS) control is applied to the shunt and series inverters to regulate voltage levels, mitigate harmonics, and improve overall system efficiency. The ANFIS-based control strategy enhances the performance of the inverters by dynamically adjusting their parameters based on system operating conditions. Simulation results demonstrate the effectiveness of the proposed UPQC-based approach in mitigating power quality issues, reducing voltage fluctuations, improving power factor, and enhancing system stability during varying load conditions. The integration of P&O MPPT for PV and wind systems along with ANFIS control for inverters significantly contributes to the overall power quality enhancement in grid-linked non-conventional energy structures.