Safe-Guarding Artificial Intelligence in Power Systems

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To cope with the challenges of a sustainable energy supply, methods from artificial intelligence are increasing deployed in power systems. Often, artificial intelligence is encoded in the form of neural networks, which are very difficult to analyze and verify. Artificial intelligence will have an increasing role in power systems, whose correct behavior has to be a top priority. However, despite the rise of artificial intelligence in power systems, current solutions do not provide any correctness guarantees. Thus, the main objective of this proposal is to safeguard methods from artificial intelligence in power systems using methods from formal verification.To safeguard artificial intelligence and in particular techniques from machine learning, we propose to build a formally-correct safety layer. Our safety layer will verify just-in-time whether the proposed actions generated from an artificial intelligence fulfill the system specification. If a proposed action is not safe, the safety layer will execute a fail-safe controller that brings the power system into a safe operating condition. Our proposed architecture has the big advantage that artificial intelligence techniques do not have to be certified---only the safety layer requires certification. Even when changing the artificial intelligence module, all its decisions stay safe due to our proposed safety layer. Our safety layer is composed of 1) a module for automatic conformance checking, 2) a module for scalable reachability analysis, 3) a fail-safe controller, and 4) a just-in-time verification module.The outcome of this project will be the first formally-correct safety layer for artificial intelligence in power systems. We will demonstrate the usefulness of our methods within the Center for Combined Smart Energy Systems (CoSES) at the Technical University of Munich. CoSES is not only a research facility, but also an open, interdisciplinary research group covering expertise from several chairs and departments, ranging from energy management to communication technology. In particular, we will investigates microgrids that combine electrical as well as the thermal energy systems.