Research Group | ETA
Research project

KI4ETA | Artifical Intelligence for Energy Technology and Applications in Production

Coordinator: Benedikt Grosch M. Sc. Daniel Fuhrländer-Völker M. Sc.
Subproject manager: Heiko Ranzau M. Sc
Funded by: Federal Ministery of Economic Affairs and Climate Action (BMWK) in progress
Duration: 06/2021 – 05/2024

Objectives

KI4ETA has set the goal to lead the way towards achieving the CO2-free production of the future. This requires closing the energy efficiency gap, which describes the difference between available technological solutions and actual energy efficiency measures applied in industrial facilities today. KI4ETA will utilize an integrated, platform-based approach based on artificial intelligence (AI) to achieve this. The result of this will be the digitally interconnected, energy efficient, and energy flexible factory. Facilities within the factory will be connected to and controlled by an energy management platform which also communicates with energy grid operators and utility companies to achieve optimal use of available resources.

Overall, KI4ETA will close the control loop of the digital factory from data logging in greenfield and brownfield to intelligent, energy efficient, and flexible control of machines and building systems. This will be accomplished while acknowledging production quality, safety, and security of the factory as important factors.

Approach

KI4ETA has seven sub-projects which interact to close the control loop of the digital factory as shown in figure 1. A smart energy management platform will be developed in sub-project 1. The platform will be used to collect data from the factory and to support data acquisition and data processing with intelligent functionality. The effort for implementation and management of IT infrastructure also plays an important role for data acquisition. Therefore, to allow for fast and cheap connection of new devices, networking of different devices in the factory will be analyzed and improved in sub-project 2.

Building on the implemented IT infrastructure, sub-project 3 will provide a method to improve energy transparency through energy monitoring. The AI based method should simplify data evaluation and thus enable quick implementation of economically viable energy efficiency measures. In sub-project 4, the collected data is pre-processed and used to create models for the automated generation of suggestions for energy efficiency measures. Such data-based models will also be utilized in sub-project 5 to optimize energy consumption of factory operations with energy flexibility measures.

Since every factory is a part of energy grids and networks, sub-project 6 covers the sector coupling aspects of the digitally interconnected, efficient factory. This may include energy exchange via power grids and district heating systems as well as utilization of the energy capacity of electric vehicles to improve energy flexibility.

Since all sub-projects of KI4ETA are interconnected, sub-project 7 consists of overarching, practical use cases with industry partners and in the ETA-Factory. The findings from other sub-projects will be analyzed regarding their energy savings and flexibility potential as well as their suitability for actual industrial implementation. This ensures that project results are easy to apply in industrial scenarios.

Funding source