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<div class="csl-entry">Breitschopf, J., Sobottka, T., Zabik, G., & Ansari Chaharsoughi, F. (2024). Enabling industrial energy efficiency and flexibility with dynamic simulation-based optimization of manufacturing operations. In <i>31st CIRP Conference on Life Cycle Engineering</i> (pp. 921–926). https://doi.org/10.1016/j.procir.2024.02.031</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/207508
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dc.description.abstract
In the face of substantial environmental impact, energy-intensive industries are compelled to deal with a spectrum of future energy scenarios, including the adoption of electrification and hydrogen use. In addition, these sectors are under pressure to enhance energy efficiency and adaptability to reduce costs. The integrated planning and control of production and energy system components is challenging due to the complexity and lack of available methods, though. This paper addresses this gap, by introducing a simulation-based method that optimizes production and energy system components. The planning method is based on a multicriteria meta-heuristic with an integrated simulation of production and energy system behavior. It evauates different future energy scenarios with electrification and hydrogen use including variable energy markets and storage systems. The method is applied and validated in a case study in an energy-intensive steel production. The results show the significant benefits of the dynamic planning and optimization for various variables in two different heat-treatment process technologies.
