Now showing items 1-4 of 4
Automatic Time Series Segmentation as the Basis for Unsupervised, Non-Intrusive Load Monitoring of Machine Tools
Detailed energy monitoring and benchmarking at the individual component level is necessary to increase energy efficiency in complex production systems. Non-intrusive load monitoring (NILM) provides an economical solution for operational state detection and load disaggregation without the need for large-scale use of fine-grained energy meters. Existing supervised NILM approaches require detailed training data including control information about individual devices. Unsupervised approaches, on the other hand, often ...
System efficient integration of standby control and heat pump storage systems in manufacturing processes
Prerequisite for system efficiency towards an industrial energy transition is the reducing of energy demand on the process level. In typical manufacturing systems with machine tools and washing machines, the proper design of intelligent standby control and heat pump storage system (HPS) represent high efficiency. The integration of HPS is complicated due to high non-continuity, especially when implementing a standby control system. Our approach aims at designing one single HPS for multiple heat sources and sinks. ...
Integration of Heat Pump Storage Systems in Manufacturing Systems via Data Farming and Monte Carlo Simulation
The electrification of industrial energy demand is essential for effective climate protection and a successful energy transition. In production systems with fluctuating heating and cooling demands, heat pumps can make a significant contribution to electrification and increased efficiency in a demand-oriented production with automated standby operation. In order to dimension a suitable heat pump storage system, well-founded statistical information about the production system is required. For the creation of stochastic ...
Signal based non-intrusive load decomposition
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 ...