Power Quality Enhancement using Kalman Filter Estimated TLO Fuzzy TID-based SHAF

Abstract

This article presents a Shunt Hybrid Active Filter (SHAF) designed to reduce harmonics and compensate reactive power in nonlinear load environments. The proposed system utilizes a Kalman Filter (KF) for reference current estimation and a Fuzzy Tilt Integral Derivative (TID) controller optimized with Teaching-Learning Optimization (TLO) for improved performance. The SHAF system employs a novel control strategy that relies solely on source current sensing, eliminating the need for traditional (id-iq) or (p-q) techniques. The Fuzzy TID controller parameters are tuned using the TLO method, minimizing Integral Time Absolute Error (ITAE). The system's performance is evaluated under nonlinear loads and compared with that of conventional TID and PID controllers. Simulation results demonstrate the proposed system's superior performance, achieving a Total Harmonic Distortion (THD) of 1.16%, well below the IEEE 519 standard of 5%. The Input Power Factor (IPF) is 0.9977, nearly unity. Case studies confirm that the proposed TLO Fuzzy TID Controlled SHAF outperforms other control strategies in harmonic compensation. The proposed system's performance is attributed to the effective tuning of Fuzzy TID controller parameters using the TLO method. The Kalman Filter's accurate reference current estimation and the optimized control strategy contribute to the system's robustness. However, the system's performance may degrade under highly dynamic or unpredictable nonlinear load variations. The proposed SHAF system demonstrates excellent harmonic reduction and reactive power compensation capabilities. Future research directions include investigating real-time implementation using advanced control platforms, comparing the performance of TLO with other optimization techniques, and exploring applications in power quality improvement and renewable energy systems.