Prediction of Arc Voltage of Electric Arc Furnace Based on Improved Back Propagation Neural Network

The Production of the quality steel is achieved by melting iron and steel scraps by utilizing electric power in an electric arc furnace, it acts as one of the major troublesome load in the electric power system due to high nonlinear and chaotic nature, thereby creating severe power quality disturban...

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Vydané v:SN computer science Ročník 2; číslo 3; s. 167
Hlavní autori: Vinayaka, K. U., Puttaswamy, P. S.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Singapore Springer Singapore 01.05.2021
Springer Nature B.V
Predmet:
Algorithms
Approximation
Back propagation
Back propagation networks
Computer Imaging
Computer Science
Computer simulation
Computer Systems Organization and Communication Networks
Data Science and Communication
Data Structures and Information Theory
Electric arc furnaces
Electric potential
Electric power systems
Energy consumption
Information Systems and Communication Service
Linear equations
Neural networks
Original Research
Pattern Recognition and Graphics
Propagation
Real time
Software Engineering/Programming and Operating Systems
Steel production
Vision
Voltage
Neural network
Electric arc furnace
BP algorithm
Prediction model
ISSN:2662-995X, 2661-8907
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Shrnutí:The Production of the quality steel is achieved by melting iron and steel scraps by utilizing electric power in an electric arc furnace, it acts as one of the major troublesome load in the electric power system due to high nonlinear and chaotic nature, thereby creating severe power quality disturbances to the interconnected network, therefor the need for model to describe the behavior of electric arc furnace in a simulation of electrical power system become significant, the relation between the arc voltage and arc current is pivotal in defining the characteristics of an electric arc furnace, in this paper, the Voltage and current characteristics based on real time data is discussed, then arc voltage prediction using improved back propagation neural network based on arc current under different zones of operation are simulated using MATLAB/SIMULINK, the results infer the validation of test results with the actual values and effectiveness of prediction by adoption of improved back propagation algorithm and efficient in terms of prediction with reduced errors.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:2662-995X
2661-8907
DOI:10.1007/s42979-021-00556-1