Paper Info
Title
Neuro-fuzzy modeling and prediction of current total harmonic distortion for high power nonlinear loads
Abstract
The paper presents the results of the modeling and the prediction of the total harmonic distortion (THD) of the current and the voltage for a nonlinear high power load. Modeling was performed using intelligent techniques based on neural networks and fuzzy inference. To achieve this, data were measured in the electrical installation of a non-linear electrical load, in this case a high-power electric arc furnace. These data were measured over the entire duration of a steel charge. The measured data was used to train a neuro fuzzy adaptive system. Following training, tests with different architectures have been performed with the neuro fuzzy adaptive system. The modeling and prediction results are useful in designing harmonic current filters. The presence of these harmonic currents decreases productivity and affects the quality of power.
Year
DOI
Venue
2018
10.1109/INISTA.2018.8466290
2018 Innovations in Intelligent Systems and Applications (INISTA)
Keywords
Field
DocType
modeling and prediction,total harmonic distortion,ANFIS,fuzzy
Electric arc furnace,Neuro-fuzzy,Total harmonic distortion,Nonlinear system,Electrical load,Computer science,Control theory,Voltage,Harmonic,Harmonic analysis
Conference
ISBN
Citations 
PageRank 
978-1-5386-5151-3
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Manuela Panoiu1136.61
Caius Pănoiu285.46
Loredana Ghiormez343.00