Summary
The integration of AI-based systems offers significant potential to alleviate the challenges of increasing grid complexity and decreasing operational safety margins. However, in contrast to the rapid progress of AI in research and development, the deployment in critical infrastructure faces substantial barriers. The goal of this paper is to address limitations of the regulatory and technical frameworks and to offer guidance for implementing trustworthy AI. For this purpose, we provide an in-depth analysis of the current technical and regulatory landscape to identify significant barriers. Then, we propose a process driven approach, which consists of three stages:
Read more Read lessrequirement specifications, offline development and supervised online operation. Each of these stages is described in detail and criteria are developed that allow or prohibit transition from one stage to the next. The process driven approach is exemplified using a case study in which an
AI-based solution determines optimal protection settings for given power systems. Finally, the results of the analysis are discussed, and recommendations are made for the implementation of
AI in power systems.
Additional informations
| Publication type | Session Materials |
|---|---|
| Reference | D2_12461_2026 |
| Publication year | |
| Publisher | CIGRE |
| Country | Germany |
| Study committees | |
| File size | 572 KB |
| Price for non member | 30 € |
| Price for member | 30 € |
Authors
VOGT Mike - Fraunhofer IEE Germany; BROSINSKY Christoph - TEN Thüringer Energienetze GmbH & Co. KG Germany; BOUCHKATI Sarra - RWTH Aachen Germany; KUBIS Andreas - c.con Management Consulting GmbH Germany; KORDOWICH Georg - FAU ErlangenNürnberg Germany; CONRAD Timon - FAU ErlangenNürnberg Germany; MITRENTSIS Georgios - Hitachi Energy German AG Germany; LUTAT Philipp - RWTH Aachen Germany; DAUER Maximilian - Siemens AG Germany; STIASNY Jochen - TU Delft Netherlands; JAEGER Johann - FAU ErlangenNürnberg Germany; MIRZ Markus - PSI Software SE; ULBIG Andrea - RWTH Aachen Germany
Keywords
Artificial Intelligence, Power System Operation, Trustworthiness, Digitalization, Smart Grid, Machine Learning, Functional Safety
