Intelligent ExDoGBoost-Enabled UPFC System for Power Quality Enhancement in Grid-Connected PV System

Srividhya J. P, Meena D, Tamil Selvi S, Suresh R

Abstract


With increasing use of Renewable Energy Sources (RES) such as Photovoltaic (PV) systems, power quality has become a major challenge in modern grids. Harmonic distortions, voltage sag/swell, and load demand variations significantly affect stability and efficiency of power delivery. A Unified Power Flow Controller (UPFC) connected to a solar PV system is introduced as a sophisticated control scheme for enhancing power quality. The UPFC consists of a series and shunt converter working together to regulate voltage, manage power flow, and suppress harmonics. To ensure constant DC-link voltage under unpredictable PV conditions, an Extended Double Gain Step-Up Boost Converter (ExDoGBoost) is proposed, enabling high voltage gain and efficient energy conversion. For stable converter operation, a PI controller optimized using the Giant Trevally Optimization Algorithm (GTOA) provides effective DC voltage regulation, while a Decoupled Neural Network (DNN) generates adaptive reference currents to improve responsiveness under dynamic grid conditions. The integration of AI-based control with high-gain conversion significantly enhances the UPFC’s ability to mitigate voltage sag/swells, reduce Total Harmonic Distortion (THD) to 1.71%, and support reactive power adjustment. MATLAB simulations validate the proposed system, achieving 96% converter efficiency and appreciable power quality improvement, making it suitable for renewable-integrated distribution networks.


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DOI (PDF): https://doi.org/10.20508/ijsmartgrid.v10i2.717.g428

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