Authors: Ekiyor, L. P, Amadi, H. N., Wokoma, B. A., Uwho, K. O
Abstract: The study examines power quality improvement in Rumuomoi distribution network addressing issues such as harmonic distortion and voltage sags which degrade system efficiency and affect sensitive loads by implementing an Adaptive Neuro-fuzzy Inference System (ANFIS)-controlled Unified Power Quality Conditioner (UPQC). The challenge (harmonic distortion and voltage sag) arise due to the increasing penetration of nonlinear loads, such as variable frequency drives, rectifiers, and industrial machinery, which introduce significant current and voltage harmonics into the distribution network, leading to excessive Total Harmonic Distortion (THD), voltage instability, and inefficient power distribution. Conventional PID controllers often exhibit limitations in dynamic compensation, adaptability, and optimal performance under varying load conditions, necessitating an intelligent control approach that can effectively mitigate power quality disturbances in real-time. Fast Fourier Transformation analysis in MATLAB/Simulink software was used to evaluate performance of the network before and after UPQC( series APF and shunt APF) installation comparing total harmonic distortion and voltage sag. The result obtained from base case simulation shows that the nonlinear load injected harmonic distortion at PCC (point common coupling) that violates the statutory limit of 5% IHD (individual harmonic distortion) and 8% VTHD (voltage total harmonic distortion) according to IEEE 519-2022 standard for low and medium voltage system. The highest harmonic current distortion consists of 5th order resulting to a total harmonic distortion of 12.59%. However, the performance of the ANFIS-controlled UPQC demonstrates significant improvements, with a reduction of total harmonic distortion from 12.59% to 0.15% which is below 5% ensuring compliance with IEEE 519 harmonic standards. Furthermore, the ANFIS-controlled UPQC effectively mitigates voltage sag conditions, restoring voltage deviations within ±5% of nominal values, which is critical for ensuring the stability and reliability of sensitive electrical loads. The practical implications of this study highlight the feasibility of deploying ANFIS-controlled UPQC in distribution networks to achieve IEEE 519 power quality standards, ensuring efficient, reliable, and high-quality power delivery for industrial, commercial, and residential applications.
DOI: https://doi.org/10.5281/zenodo.19400815
