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ZENODO
Doctoral thesis . 2021
License: CC BY
Data sources: ZENODO
ZENODO
Thesis . 2021
License: CC BY
Data sources: Datacite
ZENODO
Thesis . 2021
License: CC BY
Data sources: Datacite
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Modellierung des elektrischen Energiesystems eines Elektrostahlwerkes

Modeling the Energy System of an Electric Steel Mill
Authors: Marschnig, Aaron;

Modellierung des elektrischen Energiesystems eines Elektrostahlwerkes

Abstract

Abstract The share of steel production via the scrap-electric arc furnace route tends to increase worldwide, since steel can be recycled almost completely. In addition to the lower specific energy consumption and lower emissions, the scrap-electric arc furnace route is more environmentally friendly than other steel production routes. In order to be able to derive further optimization possibilities for this process route regarding energy efficiency and demand side management, load profiles of the consumers are required for the different operational load situations in order to be able to evaluate further optimization options for this process route. The aim of this master’s thesis is to develop an electric energy system model for the Breitenfeld Edelstahl steel mill. This model is aimed to offer the possibility of analyzing and evaluating potentials for demand side management and optimization options. For this purpose, process parameters and power are recorded for the respective electrical units in the steel mill. These real electrical load scenarios are analyzed, and synthetic load profiles are created for active, reactive and apparent power with a temporal resolution of one minute. For modeling the synthetic load profiles, a uniform concept is established and different stochastic as well as statistical methods are used. By combining the individual synthetic load profiles, the energy system model is obtained, which depicts the energy system of the steel mill. Finally, the synthetically generated load profiles for the respective units as well as the overall energy system are validated. For this purpose, the data generated from the simulation is compared with the measured data and the results are analyzed and evaluated regarding to their accuracy.

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Keywords

Energy, Energy Efficiency, Oxy-Fuel Combustion, CO2 Reduction, Electric Steel Production, New Energy for Industry, Optimization Measures, Markov Chain, Energy System Model, Demand Side Management, Consumption Load Profiles, Innovation Network, Synthetic Load Profiles, NEFI, Climate and Energy Fund, Industry, Oxysteel, Vorzeigeregion

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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