Sub-Area 2.2 Automation & Control
The overall aim of Sub-Area 2.2 is the optimal operation of sustainable biorefinery and renewable energy systems. To achieve this, we adress three main tasks:
Optimal operation (control) of biorefinery and energy technologies: The first step towards a highly efficient, sustainable and flexible system is efficient individual technologies that can be operated flexibly. For this reason, we develop advanced control systems for biotechnological, thermochemical and thermal plants (e.g. gas generation or solar thermal plants).
Optimal interaction of different technologies and systems: At the system level, it is then necessary to ensure optimal interaction of all components and systems. To this end, we are developing various methods for the predictive control of hybrid energy and resource systems, with a particular focus on the specific consideration of the individual sectors (e.g. different temperature levels in the heating sector).
Highly automated operational management by new digital services: In addition to the actual controls, we are working on new digital services that allow a significant increase in the degree of automation of the plants’ and systems’ operational management (e.g. methods for automatic plant monitoring, plant simulators for training purposes, ...). We mainly focus on the use of digital twins, but purely data-based methods are also used.
A large focus is on model-based methods in order to achieve the broadest possible use of the methods developed. As these methods support a transfer of the results to similar plants and systems due to the explicit consideration of the physical correlations. A second methodological focus is to always implement and validate our methods on real plants, throughout the entire chain of our work - from the early development of new methods to demonstration plants and market launch support for our company partners.
However, the development of all these methods always has the overall goal of improving the operation of the considered plants and systems by making them more reliable, cost- and resource-efficient, and flexible.