Background:

Energy-intensive industries currently face massive financial challenges, among them rising energy costs. Current regulatory mechanisms, such as the Energy Industry Law (Energiewirtschaftsgesetz, EnWG) [1], enable the use of dynamic electricity tariffs and participation in flexibility markets, schemes from which such organizations could significantly benefit. Through the ongoing project EKoREK [2], data on the energy consumption of devices and machinery in an aluminum casting facility in Lower Saxony have been gathered, providing a foundation for developing innovative concepts for energy cost optimization. This information can be integrated into data-driven models to study the potential for cost reduction [3].

Objective:

The main goal is to explore scenarios that evaluate the potential for reduction of energy costs in energy-intensive industries, with the use case of an aluminum casting facility in Lower saxony. The available data is to be evaluated and used as basis for modelling of the components and for the simulation of component interaction to search for optimization potentials regarding costs. The conceptual framework for cost optimization is to be presented as a reproduceable artifact, which can enable replication of results in similar organizations.

Literature:

[1] Bundesministerium für Wirtschaft und Klimaschutz (2022): Energiewirtschaftsgesetz (EnWG) vom 7. Juli 2005 (BGBl. I S. 1970, 3621), zuletzt geändert durch Artikel 1 des Gesetzes vom 14. Juli 2024 (BGBl. I Nr. 161 vom 16. Mai 2024).

[2] Zentrum für digitale Innovationen Niedersachsen (o. J.): Transferprojekt EKoREK: Energiekosten energieintensiver KMU reduzieren. Abgerufen am 26. März 2026, von https://zdin.de/news-und-medien/news-wissenschaft/transferprojekt-ekorek-energiekosten-energieintensiver-kmu-reduzieren

[3] Wicaksono, H.; Trat, M.; Bashyal, A.; Boroukhian, T.; Felder, M. (2024): Artificial-intelligence-enabled dynamic demand response system for maximizing the use of renewable electricity in production processes. In: The International Journal of Advanced Manufacturing Technology, Jg. 138, S. 247–271. https://doi.org/10.1007/s00170-024-13372-7

Possible work packages (depending on work scope):

·         Analysis of gathered data of energy use of machines and components

·         Modelling and simulation of machine park for minimization of energy costs

·         Development of a Conceptual Framework for energy optimization in energy intensive SMEs

·         Concept validation: Development of KPIs and qualitative validation

Prerequisites (depending on scope):

·         Required knowledge on energy systems, modelling and simulation, scripting languages.

·         Preferred knowledge of ML models and optimization frameworks

·         Preferred knowledge of regulatory frameworks and German Language