Project Description

The Industry4Redispatch (I4RD) project aims to provide industrial flexibility for redispatch measures. The increasing integration of renewable energy sources has led to a growing need for redispatch, with costs in Austria rising significantly. Until now, redispatch has primarily involved power plants. I4RD expands these possibilities by incorporating industrial plants and establishing the necessary technical, regulatory, and organizational conditions for this. The focus is on automating industrial processes and developing a redispatch module.

In the previous project, EDCSproof, a model predictive control system for managing energy in industrial energy systems was developed. This control system takes into account forecasts for the behavior of individual components such as heat storage and heat exchangers, as well as production schedules, weather data, and price specifications. These forecasts allow for a reduction in both energy consumption and the switching operations of heat pumps. Due to the modular design of the control concept, it can be transferred to other plants.

Project Content

As part of Industry4Redispatch, the energy management system was implemented in existing food industry facilities and tested over several weeks. The optimization problem solved by the model predictive controller is particularly challenging because switching variables (such as turning heat pumps on and off) lead to a mixed-integer problem that must be solved in short time intervals. By using a hierarchical control structure and model simplifications, the real-time capability of the methods was ensured.

Through predictive control, heat storage systems can be charged and discharged at optimal times, significantly improving energy efficiency. In tests conducted on industrial facilities, an efficiency increase of up to 19 percentage points and a reduction in switching operations by up to 47% compared to the existing control system were achieved.

Veröffentlichungen

Fuhrmann, Florian, Alexander Schirrer, and Martin Kozek. "Model-based energy management systems: Weighting of multiobjective functions using the Volatile Energy Prices Scalarization (VEPS)., opens an external URL in a new window" Computers & Chemical Engineering 169 (2023): 108078.

Fuhrmann, Florian, Alexander Schirrer, and Martin Kozek. "Model-predictive energy management system for thermal batch production processes using online load prediction., opens an external URL in a new window" Computers & Chemical Engineering 163 (2022): 107830.

Fuhrmann, Florian, Bernd Windholz, Alexander Schirrer, Sophie Knoettner, Karl Schenzel, and Martin Kozek. "Energy management for thermal batch processes with temporarily available energy sources–Laboratory experiments., opens an external URL in a new window" Case Studies in Thermal Engineering 39 (2022): 102473.

Cooperation Partners

Project Duration

  • März 2021 – Mai 2025

Contact