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

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 Adaptiv...

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Bibliographic Details
Published in2020 International Conference on Power Electronics and Renewable Energy Applications (PEREA) pp. 1 - 6
Main Authors S., Chaithanya, K., Anjali Anand
Format Conference Proceeding
LanguageEnglish
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
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DOI10.1109/PEREA51218.2020.9339808

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Summary: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.
DOI:10.1109/PEREA51218.2020.9339808