electric arc furnaces
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2022 ◽  
Author(s):  
Ebrahim Balouji

<div> <div> <div> <p>In this research work, deep machine learning based methods together with a novel data augmentation are developed for predicting flicker, voltage dip, harmonics and interharmonics originating from highly time-varying electric arc furnace (EAF) currents and voltage. The aim with the prediction is to counteract both the response and reaction time delays of active power filters (APFs) specifically designed for electric arc furnaces (EAF). Multiple synchronous Reference frame (MSRF) analysis is used to decompose the frequency components of the EAF current and voltage waveforms into dqo components. Then using low- pass filters and prediction of the future values of these dqo components, reference signals for APFs are generated. Three different methods have been developed. In two of them, a low- pass Butterworth filter is used together with a linear FIR based prediction or long short-term memory network (LSTM) for prediction. In the third method, a deep convolutional neural network (CNN) combined with a LSTM network is used to filter and predict at the same time. For a 40 ms prediction horizon, the proposed methods provide 2.06%, 0.31%, 0.99% prediction errors of the dqo components for the Butterworth and linear prediction, Butterworth and LSTM and CNN with LSTM, respectively. The error of the predicted reconstructed waveforms of flicker, harmonics, and interharmonics resulted in 8.5%, 1.90%, and 3.2% reconstruction errors for the above-mentioned methods. Finally, a Simulink and GPU based implementation of predictive APF using Butterworth filter + LSTM and a trivial APF resulted 96% and 60% efficiency on compensation of EAF current interharmonics. </p> </div> </div> </div>


2022 ◽  
Author(s):  
Ebrahim Balouji

<div> <div> <div> <p>In this research work, deep machine learning based methods together with a novel data augmentation are developed for predicting flicker, voltage dip, harmonics and interharmonics originating from highly time-varying electric arc furnace (EAF) currents and voltage. The aim with the prediction is to counteract both the response and reaction time delays of active power filters (APFs) specifically designed for electric arc furnaces (EAF). Multiple synchronous Reference frame (MSRF) analysis is used to decompose the frequency components of the EAF current and voltage waveforms into dqo components. Then using low- pass filters and prediction of the future values of these dqo components, reference signals for APFs are generated. Three different methods have been developed. In two of them, a low- pass Butterworth filter is used together with a linear FIR based prediction or long short-term memory network (LSTM) for prediction. In the third method, a deep convolutional neural network (CNN) combined with a LSTM network is used to filter and predict at the same time. For a 40 ms prediction horizon, the proposed methods provide 2.06%, 0.31%, 0.99% prediction errors of the dqo components for the Butterworth and linear prediction, Butterworth and LSTM and CNN with LSTM, respectively. The error of the predicted reconstructed waveforms of flicker, harmonics, and interharmonics resulted in 8.5%, 1.90%, and 3.2% reconstruction errors for the above-mentioned methods. Finally, a Simulink and GPU based implementation of predictive APF using Butterworth filter + LSTM and a trivial APF resulted 96% and 60% efficiency on compensation of EAF current interharmonics. </p> </div> </div> </div>


2021 ◽  
Vol 938 (1) ◽  
pp. 012003
Author(s):  
A G Ryazanov ◽  
G G Mikhailov ◽  
O V Khmeleva ◽  
Y D Savina ◽  
D M Galimov ◽  
...  

Abstract The technological development of the world community makes it necessary to resolve the issues of the produced industrial residues utilization. Worn-out galvanized metal cars, ceilings and other metal structures require orderly utilization. Utilization of galvanized scrap may be carried out in Electric Arc Furnaces (EAF) to obtain intermediate steel and EAF dust. Electric Arc Furnaces dus contains zinc, so it is used as a secondary raw material for the production of metallic zinc. Waelz oxides are formed in Waelz kilns, after the primary processing of EAF dust. Waelz oxide contains halides that must be removed first. Halides may be removed by heating to temperatures of about 1000°C. Dielectric (microwave) heating is a promising and environmentally friendly method for material processing. Microwave heating is carried out without burning natural gas, which leads to decrease of waste gases volume. The work experimentally confirmed the possibility of zinc-containing materials heating at electromagnetic emission exposure. The duration of products heating up to the temperature of 1000°C was 128 - 188 s. The residual content of chloride ions in the calcined products is less than 0.05 wt%.


2021 ◽  
Vol 5 (8 (113)) ◽  
pp. 6-16
Author(s):  
Volodymyr Turkovskyi ◽  
Anton Malinovskyi ◽  
Andrii Muzychak ◽  
Оlexandr Turkovskyi

AC steel arc furnaces are the most powerful units connected to the electrical grid, the operating mode of which is dynamic, asymmetrical and non-linear. That is why these furnaces cause the entire possible range of negative effects on the quality of electricity in the grid, in particular, fluctuations, asymmetry and non-sinusoidal voltage.Known proposals for improving the electromagnetic compatibility of electric arc furnaces are mainly focused on eliminating the consequences of their ne­gative impact on the power grid.The proposed approach and the corresponding technical solution are aimed at reducing the level of generation of a negative factor and at the same time reduce fluctuations, asymmetry and non-sinusoidal voltage. This result is obtained due to the fact that the proposed solution takes into account the peculiari­ties of the range of modes natural for arc furnaces. Optimal for such consumers is the use of a constant current power supply system I=const in the range of modes from operational short circuit to maximum load and the system U=const in the whole other range of modes. The implementation of such a system is carried out on the basis of a resonant converter «constant current – constant voltage».Studies have found that the use of such a power supply system, in comparison with the traditional circuit, makes it possible to reduce the non-sinusoidal voltage in a low-power grid from 3.2 % to 2.1 % and the unbalance coefficient from 3.66 to 1.35 %. Previously published data on a significant reduction in voltage fluctuations was also confirmed.The positive effect of such a system on the energy performance of the furnace itself is shown, manifes­ted in an increase in the arc power by 12.5 %, and the electrical efficiency by 5.1 %. This improves the productivity and efficiency of electric arc furnaces


Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 5058
Author(s):  
Zbigniew Olczykowski

In the case of three-phase arc furnaces, two types of asymmetry can be distinguished: constructional and operational. The structural asymmetry is related to the construction of high-current circuits supplying the arc furnace. The knowledge of the parameters of the high-current circuit allows to determine the operating characteristics of the arc device. The author proposed a method for calculating the real values of the resistance and reactance of the high-current circuit. For this purpose, tests were made to short-circuit the electrodes with the charge. During the short-circuit, with the use of a power quality analyzer, measurements of electrical indicators were carried out, which allow to determine the parameters of the high-current circuit. A new method for determining voltage operational unbalance is also presented in this paper. The theoretical considerations presented in the article were verified in industrial conditions.


Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3901
Author(s):  
Zbigniew Olczykowski ◽  
Zbigniew Łukasik

Due to the dynamic nature of load changes, arc devices are receivers that generate disturbances to the network that affect the power quality. The main disturbance generated by these receivers are voltage fluctuations. One of the effects of voltage fluctuations is the flicker of light caused by lighting receivers. The article presents an analysis of changes indicators flicker of light measured in networks supplying arc furnaces. The propagation of voltage fluctuations to the lines supplying lighting receivers was analyzed. The network parameters influencing the amount of light flicker were estimated. The paper presents a method for calculating the increased flicker of light when several electric arc furnaces are operated in parallel. The conclusions regarding the use of the presented research in practical applications are given in the summary.


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