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  4. Energy Efficiency Optimization using AutomationML modeling and an EnPI methodology
 
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2019
Conference Paper
Title

Energy Efficiency Optimization using AutomationML modeling and an EnPI methodology

Abstract
Industrial facilities are complex and heterogeneous systems in permanent technological change. The ambitions towards smart factories heighten the requirements for the flexible interconnection of various devices. These industrial entities are controlled, observed and optimized by many services. The tuning of process parameters of several linked components in order to boost the overall energy efficiency is one example of such services. AutomationML (AML) provides a hierarchical description language for industrial systems considering both structure and properties. An extension of the established standard allows for intuitive modeling of energy optimization problems. An approved energy performance indicator (EnPI) methodology was integrated in the libraries of AML in order to simplify and shorten the modeling procedure for the optimization task. The procedure is demonstrated using the example of an industrial cooling system.
Author(s)
Thiele, Gregor
Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK  
Khorsandi, Niloufar
Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK  
Krüger, Jörg  
Mainwork
24th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2019. Proceedings  
Project(s)
EnEffReg
Funder
Bundesministerium für Wirtschaft und Energie BMWi (Deutschland)  
Conference
International Conference on Emerging Technologies and Factory Automation (ETFA) 2019  
DOI
10.1109/ETFA.2019.8869235
Language
English
Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK  
Keyword(s)
  • energy efficiency

  • performance optimization

  • AutomationML

  • plant modeling

  • industrial cooling system

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