| Title |
Signal based non-intrusive load decomposition |
| ID_Doc |
17489 |
| Authors |
Weiss, T; Dunkelberg, H; Seevers, JP |
| Title |
Signal based non-intrusive load decomposition |
| Year |
2019 |
| Published |
|
| DOI |
10.1016/j.promfg.2019.04.069 |
| Abstract |
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. (C) 2019 The Authors. Published by Elsevier B.V. |
| Author Keywords |
energy; energy efficiency; NILM; non-intrusive load monitoring; sustainable production; load decomposition |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000560232900070 |
| WoS Category |
Green & Sustainable Science & Technology; Engineering, Manufacturing |
| Research Area |
Science & Technology - Other Topics; Engineering |
| PDF |
https://doi.org/10.1016/j.promfg.2019.04.069
|