Prediction of Energy Consumption in an Electric Arc Furnace Using Weka

Leon-Munizaga, Nury; Aguirre-Munizaga, Maritza; Lagos-Ortíz, Katty; Cioppo-Morstadt, Javier del

doi:10.1007/978-3-030-62015-8_5

Cited by 3 publications

(2 citation statements)

References 17 publications

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“…Modern EAFs, besides other forms of energy, such as gas burners and oxygen additions, in average consume from 400 to 500 kWh of electrical energy per ton of steel (Barker et al, 1998). In order to reach such as consumptions, several new technologies were introduced in the past decades, off-gas and slag heat recovery Gandt et al, 2016;Barati et al, 2011), CO post-combustion, oxy-fuel burners (Kirschen et al, 2008), oxygen addition , high power transformer (Bisio et al, 2000), bottom stirring, and many others Furthermore, several approaches to enhance or optimize the EAF control or its subsidiary systems have been proposed (Bekker et al 2000;Oosthuizen et al, 2004;MacRosy and Swartz, 2005;Saboohi et al, 2019;Leon et al, 2020), with the goal of lowering the production costs of the EAF, In this regard, electrical energy consumption (EEC) has also been a subject of considerate attention. Several studies on prediction of the EAFs EEC using different modeling approaches have been performed (Chen et al, 2018;Kovacic et al, 2019;Carlsson et al, 2019) based either on commercial software, regression methods or different artificial-intelligence approaches.…”

Section: Introductionmentioning

confidence: 99%

Effect of Heat Loss on the Working Index of Electric Arc Furnace (EAF)

Okediran

Adetunji²,

Adeboye³

et al. 2023

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Day in day out of human life the use of metal is inevitable, metals are needed for different purposes such as in construction of bridges houses, roads etc. but despite the availability of huge amount of metal, it does not meet the global demand thus this paper investigate the effect of reduction of power of heat loss on the cost of production of electric arc furnace. In order to achieve maximum precision during production, getting product at relatively reduced price has remained a major challenge to the scientists. The experiment was conducted at industrial scale whereby power of heat loss was varied from 7.707- 4.624 MW while energy consumption fell from 0.5463 to 0.5317 MW-Hour per ton and productivity q tremendously increased from 253.0 ton to 254.0 ton per hour . Data used were collected from active furnace in Zerepaves Metallurgical plant, Russia and further analyzed with software package for accuracy

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Section: Introductionmentioning

confidence: 99%

Effect of Heat Loss on the Working Index of Electric Arc Furnace (EAF)

Okediran

Adetunji²,

Adeboye³

et al. 2023

BENR

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“…Several studies on prediction of the EAFs' EEC using different modeling approaches have been performed [13][14][15][16], based either on commercial software, regression methods, or different artificial-intelligence approaches. The methods in such studies usually focus on calculating a reliable EEC forecast and not as much on the factors that cause the fluctuations in EECs, or on the ideas and solutions that would lead to lower EEC.…”

Section: Introductionmentioning

confidence: 99%

The Influence of Electric-Arc-Furnace Input Feeds on its Electrical Energy Consumption

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Škrjanc

2021

J. Sustain. Metall.

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Operation of the electric arc furnaces (EAFs) is a subject to consider fluctuations in terms of its key performance indicators, such as the electrical energy consumption (EEC), tap-to-tap time, steel yield, and others. In this paper, a more detailed analysis of the electric arc furnace data is performed, investigating its EEC. It is well known that the EEC is affected by the weight and the type of charged scrap, the operational delays, and the tapping temperature. On the other hand, one can also deduce that the feeds, such as the carbon and the oxygen, could also affect the EEC, due to their role in redox equations and impact to the bath energy balance. Therefore, special attention is devoted to the analysis of the carbon-to-oxygen ratio during the electric arc furnace operation and the consequent influence of the oxygen availability on the EEC. Statistical analysis of more than 2500 heats of data, which were clustered according to the produced steel grade and the charged scrap mixture, has revealed that besides the beforementioned factors, fluctuations in EEC could appear also due to different amounts of added carbon and oxygen. Since the furnace operators usually rely on predefined guidelines and their own experience when actuating the furnace, a simplistic statistical approach can be used to reveal some of the weaknesses in the control routines, which can be used as a starting point to improve their actuation, leading to decreased energy consumption. Graphical Abstract

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Predictive Models on Energy Consumption

Conejo

2024

Electric Arc Furnace: Methods to Decrease Energy Consumption

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Prediction of Energy Consumption in an Electric Arc Furnace Using Weka

Cited by 3 publications

References 17 publications

Effect of Heat Loss on the Working Index of Electric Arc Furnace (EAF)

Effect of Heat Loss on the Working Index of Electric Arc Furnace (EAF)

The Influence of Electric-Arc-Furnace Input Feeds on its Electrical Energy Consumption

Predictive Models on Energy Consumption

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