Kalman Filter Estimation Based Reduced Sensor Grid-Tied Inverter Using Hybrid-SOGI Resonant Control for Nonlinear Loads

Abstract

This study introduces an innovative approach to enhance the performance of grid-tied inverters (GTIs) operating with nonlinear local loads. It presents the integration of a Kalman Filter (KF) with a hybrid second-order generalized integrator (HSOGI) resonant controller. The KF accurately estimates the state variables of the inverter system, providing crucial information for precise control. Meanwhile, the HSOGI resonant controller, blending resonant control and second-order generalized integrator advantages, effectively mitigates harmonic content and enables independent active and reactive power control at the point of common coupling. The proposed topology aims to tackle harmonic distortion and fluctuations introduced by nonlinear loads while minimizing sensor requirements and addressing sampling delay and sensing noise effects on control performance. Through simulation using MATLAB Simulink and validation with a hardware prototype of a 2-kW IGBT-based three-phase voltage source inverter, the efficacy of the suggested approach is demonstrated under various loading scenarios. This research contributes a reliable method for improving power quality in GTI systems, offering potential benefits for diverse industrial applications.