Performance analysis of an open-unified power quality conditioner

What is it about?

This paper presents a comprehensive performance analysis of an Open Unified Power Quality Conditioner (O- UPQC) integrated with two intelligent control strategies: Fuzzy Logic Control (FLC) and Adaptive Neuro-Fuzzy Inference System (ANFIS). The system is designed to mitigate power quality issues specifically voltage sags, swells, and harmonic distortion in photovoltaic (PV)-integrated distribution networks. A 9-level Cascaded H-Bridge Multilevel Inverter (CHBMLI) is employed to achieve enhanced voltage regulation and Total Harmonic Distortion (THD) mitigation. The system is evaluated under three modulation schemes: Phase Disposition (PD), Phase Opposition Disposition (POD), and Alternate Phase Opposition Disposition (APOD). Simulation results demonstrate that the ANFIS-based O-UPQC achieves THD reductions of up to 99.45 %, compared to 98.47 % using FLC, and improves the power factor from 0.86 to 0.99. Particularly under POD modulation, the ANFIS controller consistently outperforms FLC across all test cases, with enhanced harmonic suppression and better adaptability to dynamic load conditions. These findings highlight the potential of ANFIS-controlled O-UPQC systems in improving power quality in renewable-integrated, nonlinear, and disturbance-prone environments.

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Photo by American Public Power Association on Unsplash

Photo by American Public Power Association on Unsplash

Why is it important?

The main contributions of this study are as follows: • A novel implementation of an O-UPQC system combining PV inte gration with a 9-level CHBMLI architecture to achieve effective harmonic mitigation and voltage regulation. • Comparative performance analysis of FLC and ANFIS controllers under three carrier-based PWM modulation schemes (PD, POD, APOD) to evaluate dynamic compensation capabilities. • Quantitative benchmarking of PQ indices such as Total Harmonic Distortion (THD), power factor (PF), and voltage response to validate controller effectiveness. • Discussion of system scalability, computational complexity, and the potential challenges of real-time deployment for intelligent controllers.