Least mean squares and recursive least squares algorithms for total harmonic distortion reduction using shunt active power filter control

Abstract

This paper deals with the use of least mean squares (LMS, NLMS) and recursive least squares (RLS) algorithms for total harmonic distortion (THD) reduction using shunt active power filter (SAPF) control. The article presents a pilot study necessary for the construction of our own controlled adaptive modular inverter. The objective of the study is to find an optimal algorithm for the implementation. The introduction contains a survey of the literature and summarizes contemporary methods. According to this research, only adaptive filtration fulfills our requirements (adaptability, real-time processing, etc.). The primary benefit of the paper is the study of the efficiency of two basic approaches to adaptation ((N)LMS and RLS) in the application area of SAPF control. The study examines the impact of parameter settings (filter length, convergence constant, forgetting factor) on THD, signal-to-noise ratio (SNR), root mean square error (RMSE), percentage root mean square difference (PRD), speed, and stability. The experiments are realized with real current and voltage recordings (consumer electronics such as PC source without power factor correction (PFC), HI-FI amplifier, etc.), which contain fast dynamic transient phenomena. The realized model takes into account a delay caused by digital signal processing (DSP) (the implementation of algorithms on field programmable gate array (FPGA), approximately 1-5 s) and a delay caused by the reaction time of the proper inverter (approximately 100 s). The pilot study clearly showed that the RLS algorithm is the most suitable for the implementation of an adaptive modular inverter because it achieved the best results for all analyzed parameters.