Increasing flexibility for energy-intensive industry is gaining more and more importance due to the changing energy market towards volatile energy sources. Flexibility can be achieved by adapting the energy supply processes and integrating new components, e.g. energy storages. Another way to increase flexibility is to optimize the plant operation to exploit the full potential of the industrial plant. This paper presents a concept for optimal plant control for more flexible operation, using a two-stage optimization approach, combining a quadratic and a nonlinear optimization problem formulation. The optimization concept is demonstrated by means of a simple model plant. The input parameters are energy prices and production schedules respectively heat demands to be satisfied by the plant’s energy supply system. The output is the optimal control trajectory for the considered plant components. Four different scenarios, with varying plant configurations, are simulated and the results are discussed in terms of the optimization approach and the impact of different plant configurations.
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ASME 2016 International Mechanical Engineering Congress and Exposition
November 11–17, 2016
Phoenix, Arizona, USA
Conference Sponsors:
- ASME
ISBN:
978-0-7918-5065-7
PROCEEDINGS PAPER
Dynamic and Predictive Optimization Concept for Energy Supply Systems in the Energy-Intensive Industry
Martin Koller,
Martin Koller
Technical University of Vienna, Vienna, Austria
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René Hofmann
René Hofmann
Technical University of Vienna, Vienna, Austria
Search for other works by this author on:
Martin Koller
Technical University of Vienna, Vienna, Austria
René Hofmann
Technical University of Vienna, Vienna, Austria
Paper No:
IMECE2016-66536, V011T15A024; 10 pages
Published Online:
February 8, 2017
Citation
Koller, M, & Hofmann, R. "Dynamic and Predictive Optimization Concept for Energy Supply Systems in the Energy-Intensive Industry." Proceedings of the ASME 2016 International Mechanical Engineering Congress and Exposition. Volume 11: Systems, Design, and Complexity. Phoenix, Arizona, USA. November 11–17, 2016. V011T15A024. ASME. https://doi.org/10.1115/IMECE2016-66536
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