Kurzfassung
Das Thema Energieeffizienz ist im Zuge der Energiewende eine zentrale Herausforderung für den industriellen Sektor. Die systematische Erfassung und Bewertung des Energieverbrauchs bietet die Grundlage für die automatisierte Optimierung von Anlagen. Im Projekt EnEffReg entwickelten Fraunhofer IPK und ÖKOTEC Energiemanagement GmbH ein universell einsetzbares Framework zur automatisierten Generierung von Sollwerten. Die praktische Erprobung erfolgte an Standorten bei der Bayer AG, thyssenkrupp Steel Europe AG sowie der Daimler AG. Der vorliegende Beitrag fasst die theoretischen Arbeiten und aus Experimenten gewonnene Erfahrungen zusammen.
Abstract
The topic of energy efficiency is a central challenge for the industrial sector in the wake of the energy turnaround. The systematic recording and evaluation of energy consumption provides the basis for the automated optimization of plants. In the EnEffReg project, Fraunhofer IPK and ÖKOTEC Energiemanagement GmbH developed a universally applicable framework for the automated generation of target values. The practical testing took place at plants of Bayer AG, thyssenkrupp Steel Europe AG and Daimler AG. This article summarizes the theoretical work and experience gained from experiments.
Literatur
1. The Salzburg Statement of the Club of Rome. Technological Forecasting and Social Change6 (1974), S. 261–26610.1016/0040-1625(74)90026-2Search in Google Scholar
2. Georgescu-Roegen, N.: The Entropy Law and the Economic Process in Retrospect. Eastern Economic Journal12 (1986) 1, S. 3–25Search in Google Scholar
3. Dütschke, E.; Hirzel, S.; Idrissova, F.; Mai, M.; Mielicke, U.; Nabitz, L.: Energy Efficiency Networks — What Are the Processes that Make Them Work?Energy Efficiency11 (2018) 5, S. 1177–119210.1007/s12053-017-9606-4Search in Google Scholar
4. Heimann, O.; Thiele, G.: Ganzheitliche Regelung der Energieeffizienz. ZWF111 (2016) 11, S. 710–71310.3139/104.111622Search in Google Scholar
5. Miller, C.: Optimizing Centrifugal Chiller Systems. Engineered Systems % (2017). Online unter https://www.esmagazine.com/articles/98238-optimizing-centrifugal-chiller-systems [Zuletzt aufgerufen am 14.11.2017]Search in Google Scholar
6. Thiele, G.; Heimann, O.; Grabowski, K.; Krüger, J.: Framework for Energy Effciency Optimization of Industrial Systems Based on the Control Layer Model. Procedia Manufacturing 16th Global Conference on Sustainable Manufacturing, 201810.1016/j.promfg.2019.04.051Search in Google Scholar
7. Gomes, C.; Thule, C.; Broman, D.; Larsen, P.; Vangheluwe, H.: Co-Simulation: A Survey. ACM Computing Surveys (CSUR)51 (2018) 3, S. 1–3310.1145/3179993Search in Google Scholar
8. Heinzl, B.; Raich, Ph.; Preyser, F.; Kastner, W.: Simulation-based Assessment of Energy Efficiency in Industry: Comparison of Hybrid Simulation Approaches. IFAC-PapersOnLine51 (2018) 2, S. 689–69410.1016/j.ifacol.2018.03.117Search in Google Scholar
9. Sobottka, T.; Kamhuber, F.; Rössler, M.; Sihn, W.: Hybrid Simulation-based Optimization of Discrete Parts Manufacturing to Increase Energy Efficiency and Productivity. Procedia Manufacturing21 (2018), S. 413–42010.1016/j.promfg.2018.02.139Search in Google Scholar
10. Can, A.; Thiele, G.; Krüger, J.; Fisch, J.; Klemm, C.: A Practical Approach to Reduce Energy Consumption in a Serial Production Environment by Shutting Down Subsystems of a Machine Tool. In: Procedia Manufacturing – Proceedings of the 16th Global Conference on Sustainable Manufacturing (GCSM)33 (2019), S. 343–35010.1016/j.promfg.2019.04.042Search in Google Scholar
11. Drath, R.: Datenaustausch in der Anlagenplanung mit AutomationML: Integration von CAEX, PLCopen XML und COLLADA. Springer-Verlag, Berlin, Heidelberg201010.1007/978-3-642-04674-2Search in Google Scholar
12. Blochwitz, T. et al.: Functional Mockup Interface 2.0: The Standard for Tool independent Exchange of Simulation Models. In: Proceedings of the 9th International Modelica Conference, Munich, Germany2012, S. 173–18410.3384/ecp12076173Search in Google Scholar
13. Brunton, St. L.; Proctor, J. L.; Kutz, J. N.: Sparse Identication of Nonlinear Dynamics with Control (SINDYc). IFAC-PapersOnLine49 (2016) 18, S. 710–71510.1016/j.ifacol.2016.10.249Search in Google Scholar
© 2019, Carl Hanser Verlag, München
