Offshore Power-to-X platforms enable flexible conversion of renewable energy, but place high demands on adaptive process control due to volatile operating conditions. To face this challenge, using Digital Twins in Power-to-X platforms is a promising approach. Comprehensive knowledge integration in Digital Twins requires the combination of heterogeneous models and a structured representation of model information. The proposed approach uses a standardized description of behavior models, semantic technologies and a graph-based model understanding to enable automatic adaption and selection of suitable models. It is implemented using a graph-based knowledge representation with Neo4j, automatic data extraction from Asset Administration Shells and port matching to ensure compatible model configurations.
Cite
@article{arxiv.2507.03553,
title = {Model-Based Control for Power-to-X Platforms: Knowledge Integration for Digital Twins},
author = {Daniel Dittler and Peter Frank and Gary Hildebrandt and Luisa Peterson and Nasser Jazdi and Michael Weyrich},
journal= {arXiv preprint arXiv:2507.03553},
year = {2025}
}