Measurements for energy efficiency and transition to renewable energy sources
The energy transition poses major challenges for the industry. We develop concepts for a sustainable energy supply for industrial companies with the aim of converting to 100% renewable energy in the near future. For this purpose, we develop transition paths, taking into account state-of-the-art technologies, costs and other operational framework conditions.
Sector coupling and circular economy
In the future, energy systems must become more efficient and resilient. To achieve this, it is essential to optimally couple and interconnect energy flows from different sources and with different energy carriers. Coupled energy systems also make it possible to integrate renewable energy sources to a greater extent, reduce energy losses and at the same time increase supply stability through redundancies.
An important concept in this context is the Industrial Energy Hub. Here, the focus is on the joint consideration of energy supply and production at the site. In the future, the concept of circular economy will also gain in importance. We are working on a holistic view of the entire industrial process including energy supply, as this is the only way to achieve our sustainability goals.
Projects: EDCS, Sinfonies, I4RD
Publications: Assessing the potential of combined production and energy management in Industrial Energy Hubs – Analysis of a chipboard production plant, opens an external URL in a new window, Combined optimization for retrofitting of heat recovery and thermal energy supply in industrial systems, opens an external URL in a new window
Energy 4.0 and process improvement
Internet and communication technologies have permeated and revolutionized our entire lives. These technologies also open up many new possibilities for industrial applications. We are working to fully exploit the potential of these technologies in industrial energy systems and processes. In this context, the buzzword Energy 4.0 has been coined for energy systems. Our research focuses on the development of concepts for networked, flexible and intelligent energy systems of the latest generation.
Modeling with analytical and data-driven approaches
The foundation for most digital methods is an accurate, fast model of the underlying process. We combine our expert knowledge with classic and novel modeling methods, such as machine learning and data-driven approaches, to develop the optimal model for each use case.
Publications: Grey Box Modeling of a Packed-Bed Regenerator Using Recurrent Neural Networks, opens an external URL in a new window, Mechanistic Grey-Box Modeling of a Packed-Bed Regenerator for Industrial Applications, opens an external URL in a new window, MILP model for a packed bed sensible thermal energy storage, opens an external URL in a new window
Optimization with mathematical methods
Determining the optimal configuration for the power system of a given industrial operation or calculating the optimal operating trajectory under the given circumstances is a major challenge due to the rapidly increasing complexity of these problems. We develop specialized formulations and solution approaches for design and operational optimization of industrial processes based on mathematical programming.
Publications: Combined optimization for retrofitting of heat recovery and thermal energy supply in industrial systems, opens an external URL in a new window, Optimizing the utilization of excess heat for district heating in a chipboard production plant, opens an external URL in a new window, Assessing the potential of combined production and energy management in Industrial Energy Hubs – Analysis of a chipboard production plant, opens an external URL in a new window
Innovative automation approaches
Optimal control of plants and real-time monitoring with integrated error detection and diagnosis have the potential to make industrial processes significantly more efficient. Thereby, the digital twin approach opens up completely new possibilities. In collaboration with the Faculty of Computer Science, we are, for example, creating a specialized digital twin platform. For this platform, we are developing innovative services that create the actual added value of this technology.
Publications: Toward a Practical Digital Twin Platform Tailored to the Requirements of Industrial Energy Systems, opens an external URL in a new window, Framework for Automated Data-Driven Model Adaption for the Application in Industrial Energy Systems, opens an external URL in a new window