izpis_h1_title_alt

Comprehensive electric arc furnace electric energy consumption modeling : a pilot study
Kovačič, Miha (Avtor), Stopar, Klemen (Avtor), Vertnik, Robert (Avtor), Šarler, Božidar (Avtor)

.pdfPDF - Predstavitvena datoteka, prenos (1,43 MB)
MD5: 5E1BDBD54DF43EE5A6ACBA3981ACA1F8
URLURL - Izvorni URL, za dostop obiščite https://www.mdpi.com/1996-1073/12/11/2142 Povezava se odpre v novem oknu

Izvleček
The electric arc furnace operation at the Štore Steel company, one of the largest flat spring steel producers in Europe, consists of charging, melting, refining the chemical composition, adjusting the temperature, and tapping. Knowledge of the consumed energy within the individual electric arc operation steps is essential. The electric energy consumption during melting and refining was analyzed including the maintenance and technological delays. In modeling the electric energy consumption, 25 parameters were considered during melting (e.g., coke, dolomite, quantity), refining and tapping (e.g., injected oxygen, carbon, and limestone quantity) that were selected from 3248 consecutively produced batches in 2018. Two approaches were employed for the data analysis: linear regression and genetic programming model. The linear regression model was used in the first randomly generated generations of each of the 100 independent developed civilizations. More accurate models were subsequently obtained during the simulated evolution. The average relative deviation of the linear regression and the genetic programming model predictions from the experimental data were 3.60% and 3.31%, respectively. Both models were subsequently validated by using data from 278 batches produced in 2019, where the maintenance and the technological delays were below 20 minutes per batch. It was possible, based on the linear regression and the genetically developed model, to calculate that the average electric energy consumption could be reduced by up to 1.04% and 1.16%, respectively, in the case of maintenance and other technological delays.

Jezik:Angleški jezik
Ključne besede:steelmaking, electric arc furnaces, consumption, electric energy, melting, refining, tapping, modeling, linear regression, genetic programming
Vrsta gradiva:Članek v reviji (dk_c)
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FS - Fakulteta za strojništvo
Leto izida:2019
Št. strani:13 str.
Številčenje:Vol. 12, iss. 11, art. 2142
UDK:669.146:621.7(045)
ISSN pri članku:1996-1073
DOI:10.3390/en12112142 Povezava se odpre v novem oknu
COBISS.SI-ID:16647451 Povezava se odpre v novem oknu
Število ogledov:84
Število prenosov:36
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
 
Skupna ocena:(0 glasov)
Vaša ocena:Ocenjevanje je dovoljeno samo prijavljenim uporabnikom.
:
Objavi na:AddThis
AddThis uporablja piškotke, za katere potrebujemo vaše privoljenje.
Uredi privoljenje...

Gradivo je del revije

Naslov:Energies
Skrajšan naslov:Energies
Založnik:MDPI
ISSN:1996-1073
COBISS.SI-ID:518046745 Povezava se odpre v novem oknu

Gradivo je financirano iz projekta

Financer:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije (ARRS)
Številka projekta:P2-0162
Naslov:Tranzientni dvofazni tokovi

Financer:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije (ARRS)
Številka projekta:J2-7197

Financer:Drugi - Drug financer ali več financerjev
Program financ.:Štore-Steel

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
Začetek licenciranja:04.06.2019

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:izdelava jekla, električne obločne peči, poraba, električna energija, modeliranje, linearna regeresija, genetsko programiranje

Podobna dela

Podobna dela v RUL:
Podobna dela v drugih slovenskih zbirkah:

Komentarji

Dodaj komentar

Za komentiranje se morate prijaviti.

Komentarji (0)
0 - 0 / 0
 
Ni komentarjev!

Nazaj