Enhancing the stability of active harmonic filter using artificial neural network-based current control scheme

A combination of shunt active harmonic filter (SAHF), and adjustable power factor correction (PFC) capacitors is generally employed in industrial applications to achieve cost effective solution for the load compensation. It has been experienced that SAHFs operating in conjunction with PFC capacitors...

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Bibliographic Details
Published in:IET power electronics 2020-12, Vol.13 (19), p.4601-4609
Main Authors: Vaidya, Tushar, Chatterjee, Kishore
Format: Article
Language:English
Subjects:
active filters
adaptive control
adaptive control mechanism
adjustable power factor correction capacitors
apparent power 20.0 kVA
artificial neural network‐based current control scheme
compensation
control system synthesis
controller design
cost effective solution
electric current control
harmonic components
load compensation
network conditions
neurocontrollers
operating conditions
PFC capacitors
PI control
power factor correction
power harmonic filters
reactive power
reactive power requirement
Research Article
resonant frequency
SAHF
shunt active harmonic filter
stability
stability enhancement
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Summary:A combination of shunt active harmonic filter (SAHF), and adjustable power factor correction (PFC) capacitors is generally employed in industrial applications to achieve cost effective solution for the load compensation. It has been experienced that SAHFs operating in conjunction with PFC capacitors may lose their stability while compensating certain harmonic components which are near the resonant frequency of the network. This resonant frequency is not known beforehand while designing the controller of the SAHF, and further it keeps on varying with time as the value of PFC capacitors vary based on the reactive power requirement of the load. Therefore, the conventional controllers having predetermined values for gains fail to stabilise the operation of the SAHF under varying operating conditions of the network. This necessitates the involvement of an adaptive control mechanism within the SAHF with which the SAHF exhibits stable operation even under varying network conditions. In order to accomplish this requirement an artificial neural network-based control scheme is proposed in this study. The proposed scheme is verified by conducting thorough simulation studies. The viability of the proposed scheme is also confirmed by carrying out detailed experimental studies on a laboratory prototype.
ISSN:1755-4535
1755-4543
DOI:10.1049/iet-pel.2020.0364