// e-Twins: Holistic digital twin tech for the energy system
Volatile renewables are figuring ever more prominently in the energy system. More and more electricity-driven devices such as vehicles and heat pumps are connecting to the grid. Coordinating these emerging power generators and consumers poses an increasingly challenging task. Digitalization is both a curse and a blessing in that respect. On the upside, data can be gathered and transmitted ever more cost-effectively. On the downside, through the overwhelming deluge of data the overview is quickly lost. Digital twins can help handle this information overload by providing a structured and uniform representation. And they can serve to tap this data’s full potential for new digital applications.
e-TWINS is a joint project pursued by the partners ZSW, TU Munich, Munich University of Applied Sciences, and Mesh Engineering. The objective is to model tomorrow’s power supply as a cellular, hierarchical system using self-learning digital twins. The e-TWINS project revolves around a holistic software framework in which digital twins are embedded. The ZSW experts and the project team base their work on Ditto, an open source project (https://www.eclipse.org/ditto/). These digital twins will draw on live operating data captured by sensors to identify the system’s internal status and external conditions. Data analytics tools and machine learning algorithms will also process this data to improve predictions about future behavior, mirror changes in the system over time, and correct for modeling inaccuracies.
Within the project, ZSW develops digital twins of photovoltaic and battery systems and connects these virtual models to the software framework. Its researchers are also developing optimization methods to maximize the efficiency and economy of renewable energy systems as well as probabilistic forecasts for wind and solar power and loads in the energy system.
The German Federal Ministry for Economic Affairs and Climate Action (BMWK) is funding the project as part of its 7th Energy Research Program (FKZ 03EI6020C). Slated to run for 42 months, the project is to be wrapped up on June 30, 2023.
