A Comparative Study on Adaptive Control Algorithms for Grid-tie Inverter

• Published in: 2020 International Conference on Power Electronics and Renewable Energy Applications (PEREA) pp. 1 - 6
• Main Authors: S., Chaithanya, K., Anjali Anand
• Format: Conference Proceeding
• Language: English
• Published: IEEE 27.11.2020
• Subjects: Adaptive control; Adaptive Linear Control; Convergence; Grid-tied inverter; Harmonic analysis; Least Mean-based algorithms; Load management; Power quality; Power quality improvement; Power system stability; Voltage source inverters
• DOI: 10.1109/PEREA51218.2020.9339808

Adaptive linear control algorithms are used as a power quality enhancement solution for harmonics elimination, load balancing and power factor correction in the distribution system. This paper presents a comparative study on the performance of a grid-tied voltage source inverter with various Adaptive Linear Neural Network (ADALINE) control algorithms including Least Mean Square (LMS), Least Mean Fourth (LMF) and Least Mean Mixed Norm (LMMN). These adaptive control algorithms are simulated using MATLAB SIMULINK for a two-level inverter with non-linear and unbalanced loads at the point of common coupling. Simulation results under various load variations ensure the superiority of LMMN algorithm over LMS and LMF in performance and convergence speed.