Datum
2019-05-29Metadata
Zur Langanzeige
Aufsatz
Signal based non-intrusive load decomposition
Zusammenfassung
Driven by both regulatory and monetary interests the development of energy monitoring systems has been accelerated in recent years. Thus, a large amount of data is collected and stored in huge databases. This is a decisive step towards sustainable production systems since you can’t improve what you don’t know. This paper aims to use the datasets currently available and to combine databases to gather additional information on production systems, in particular energy flows. Therefore, an algorithm has been developed that combines energy consumption data from production lines with production information to estimate the consumption of connected subsystems. This paper analyzes the algorithm with case studies from companies with their specific databases and will show a deviation of less than 5 % of accumulated energy. Hence, the algorithm is able to create a more detailed analysis of production systems without additional sensor installations by combining existing databases.
Zitierform
In: Procedia Manufacturing Volume 33 (2019-05-29) , S. 554-561 ; EISSN 2351-9789Zitieren
@article{doi:10.17170/kobra-202012092466,
author={Weiß, Tim and Dunkelberg, Heiko and Seevers, Jan-Peter},
title={Signal based non-intrusive load decomposition},
journal={Procedia Manufacturing},
year={2019}
}
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2020-12-11T15:21:00Z 2020-12-11T15:21:00Z 2019-05-29 doi:10.17170/kobra-202012092466 http://hdl.handle.net/123456789/12160 eng Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ energy energy efficiency NILM, non-intrusive load monitoring sustainable production load decomposition 620 Signal based non-intrusive load decomposition Aufsatz Driven by both regulatory and monetary interests the development of energy monitoring systems has been accelerated in recent years. Thus, a large amount of data is collected and stored in huge databases. This is a decisive step towards sustainable production systems since you can’t improve what you don’t know. This paper aims to use the datasets currently available and to combine databases to gather additional information on production systems, in particular energy flows. Therefore, an algorithm has been developed that combines energy consumption data from production lines with production information to estimate the consumption of connected subsystems. This paper analyzes the algorithm with case studies from companies with their specific databases and will show a deviation of less than 5 % of accumulated energy. Hence, the algorithm is able to create a more detailed analysis of production systems without additional sensor installations by combining existing databases. open access Weiß, Tim Dunkelberg, Heiko Seevers, Jan-Peter doi:10.1016/j.promfg.2019.04.069 Energie Energieeffizienz Nachhaltigkeit Produktion publishedVersion EISSN 2351-9789 Procedia Manufacturing 554-561 Volume 33 false
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