Explainability can help cyber-physical systems alleviating risk in automating decisions that are affecting our life. Building an explainable cyber-physical system requires deriving explanations from system events and causality between the system elements. Cyber-physical energy systems such as smart grids involve cyber and physical aspects of energy systems and other elements, namely social and economic. Moreover, a smart-grid scale can range from a small village to a large region across countries. Therefore, integrating these varieties of data and knowledge is a fundamental challenge to build an explainable cyber-physical energy system. This paper aims to use knowledge graph based framework to solve this challenge. The framework consists of an ontology to model and link data from various sources and graph-based algorithm to derive explanations from the events. A simulated demand response scenario covering the above aspects further demonstrates the applicability of this framework.
|Title of host publication||MSCPES'21 : Proceedings of the 9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems|
|Editors||Peter Palensky, Anurag Srivastava|
|Place of Publication||New York|
|Publisher||Association for Computing Machinery|
|Pages||1 - 6|
|Publication status||Published - 19 May 2021|
|Event||9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2021, Held as part of the Cyber-Physical Systems and Internet-of-Things Week 2021 - Virtual, Online, United States|
Duration: 18 May 2021 → …
|Conference||9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2021, Held as part of the Cyber-Physical Systems and Internet-of-Things Week 2021|
|Period||18/05/21 → …|
Bibliographical noteFunding Information:
This work was funded by the Austrian Research Promotion Agency (FFG) in the PoSyCo project (FFG No. 3036508).
© 2021 ACM.
Austrian Classification of Fields of Science and Technology (ÖFOS)
- 102001 Artificial intelligence
- 102015 Information systems
- 102022 Software development
- Knowledge Graphs
- Smart Grid Simulation
- Smart grids