Walther, Jessica ; Weigold, Matthias (2021)
A Systematic Review on Predicting and Forecasting the Electrical Energy Consumption in the Manufacturing Industry.
In: Energies, 2021, 14 (4)
doi: 10.26083/tuprints-00019293
Article, Secondary publication, Publisher's Version
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Item Type: | Article |
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Type of entry: | Secondary publication |
Title: | A Systematic Review on Predicting and Forecasting the Electrical Energy Consumption in the Manufacturing Industry |
Language: | English |
Date: | 13 August 2021 |
Place of Publication: | Darmstadt |
Year of primary publication: | 2021 |
Publisher: | MDPI |
Journal or Publication Title: | Energies |
Volume of the journal: | 14 |
Issue Number: | 4 |
Collation: | 24 Seiten |
DOI: | 10.26083/tuprints-00019293 |
Corresponding Links: | |
Origin: | Secondary publication via sponsored Golden Open Access |
Abstract: | In the context of the European Green Deal, the manufacturing industry faces environmental challenges due to its high demand for electrical energy. Thus, measures for improving the energy efficiency or flexibility are applied to address this problem in the manufacturing industry. In order to quantify energy efficiency or flexibility potentials, it is often necessary to predict or forecast the energy consumption. This paper presents a systematic review of state-of-the-art of existing approaches to predict or forecast the energy consumption in the manufacturing industry. Seventy-two articles are classified according to the defined categories System Boundary, Modelling Technique, Modelling Focus, Modelling Horizon, Modelling Perspective, Modelling Purpose and Model Output. Based on the reviewed articles future research activities are derived. |
Status: | Publisher's Version |
URN: | urn:nbn:de:tuda-tuprints-192934 |
Classification DDC: | 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering |
Divisions: | 16 Department of Mechanical Engineering > Institute of Production Technology and Machine Tools (PTW) |
Date Deposited: | 13 Aug 2021 13:08 |
Last Modified: | 06 Dec 2024 10:53 |
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/19293 |
PPN: | 484539035 |
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