Analyzing Power Grid, ICT, and Market Without Domain Knowledge Using Distributed Artificial Intelligence
Veröffentlichungsdatum
2020
Zusammenfassung
Modern cyber-physical systems (CPS), such as our energy infrastructure, are becoming increasingly complex: An ever-higher share of Artificial Intelligence (AI)-based technologies use the Information and Communication Technology (ICT) facet of energy systems for operation optimization, cost efficiency, and to reach CO2 goals worldwide. At the same time, markets with increased flexibility and ever shorter trade horizons enable the multi-stakeholder situation that is emerging in this setting. These systems still form critical infrastructures that need to perform with highest reliability. However, today’s CPS are becoming too complex to be analyzed in the traditional monolithic approach, where each domain, e.g., power grid and ICT as well as the energy market, are considered as separate entities while ignoring dependencies and side-effects. To achieve an overall analysis, we introduce the concept for an application of distributed artificial intelligence as a self-adaptive analysis tool that is able to analyze the dependencies between domains in CPS by attacking them. It eschews preconfigured domain knowledge, instead exploring the CPS domains for emergent risk situations and exploitable loopholes in codices, with a focus on rational market actors that exploit the system while still following the market rules.
Schlagwörter
Cyber-Physical Systems Analysis
;
Distributed Artificial Intelligence
;
Reinforcement Learning
;
ICT Security
;
Market Design
Institution
Dokumenttyp
Bericht, Report
Startseite
1
Endseite
12
Zweitveröffentlichung
Nein
Sprache
Englisch