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A Systematic Review on Predicting and Forecasting the Electrical Energy Consumption in the Manufacturing Industry

Walther, Jessica ; Weigold, Matthias (2021):
A Systematic Review on Predicting and Forecasting the Electrical Energy Consumption in the Manufacturing Industry.
In: Energies, 14 (4), p. 968. MDPI, ISSN 1996-1073,
DOI: 10.3390/en14040968,
[Article]

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.

Item Type: Article
Erschienen: 2021
Creators: Walther, Jessica ; Weigold, Matthias
Title: A Systematic Review on Predicting and Forecasting the Electrical Energy Consumption in the Manufacturing Industry
Language: English
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.

Journal or Publication Title: Energies
Journal volume: 14
Number: 4
Publisher: MDPI
Uncontrolled Keywords: energy, forecasting, manufacturing, modelling, prediction
Divisions: 16 Department of Mechanical Engineering
16 Department of Mechanical Engineering > Institute of Production Technology and Machine Tools (PTW)
16 Department of Mechanical Engineering > Institute of Production Technology and Machine Tools (PTW) > ETA Energy Technologies and Applications in Production
Date Deposited: 04 Mar 2021 06:34
DOI: 10.3390/en14040968
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