An ontological approach for automatic tracking causes of blackouts in power systems

In recent years, the occurrence and damages of the blackouts in power systems saw an increase. Many of them are due to the impacts of climate change. However, tracing all blackouts that happened in the world and associating them with specific causes is quite challenging due to the huge amount of information over the Internet. In this paper, we proposed a framework for automatically analyzing the information collected from Internet based on the Ontological Approach coupled with Artificial Intelligence (AI) tailored for Natural Language Processing, which permits information extraction from reports to better understand the major entities of a power outage, their role, and the connections among them. However, our test shows that, despite the promising results of Named Entity Recognition in other fields, the lack of a standard ontology for blackout analysis is both the proof and the cause for the missed chance of exploiting this AI branch.