Towards Diagnosing Cascading Outages in Cyber Physical Energy Systems using Temporal Causal Models

Ajay Chhokra, Abhishek Dubey, Nagbhushan Mahadevan, Daniel Allen Balasubramanian, and Gabor Karsai
Submission Type: 
Full Paper
Supporting Agencies (optional): 
NSF
AttachmentSizeTimestamp
phmc_17_048.pdf725.74 KBSeptember 12, 2017 - 7:04am

Cascading failures in critical cyber physical systems such as power systems are rare but lead to huge social and economic implications. Timely diagnosis of faults in these systems is a challenging task due to inherent heterogeneity and scale of the system. In the past, we have successfully demonstrated a robust technique for diagnosing independent component faults using Temporal Causal Diagrams (TCD) at the sub-system level. In this paper, we present a systematic approach of using the sub-system level fault models to auto-generate a system-level fault model that helps in diagnosing cascading failures. We show the time complexity of our model generation algorithm using industry standard Power Transmission networks. Further, we describe the updates to the existing TCD reasoner algorithms and report the TCD diagnosis results for simulated multi fault scenario on a standard power system.

Publication Year: 
2017
Publication Volume: 
8
Publication Control Number: 
048
Page Count: 
1
Submission Keywords: 
Temporal Causal Diagrams
model based diagnostics
Power systems
Cyber Physical Energy Systems
Submission Topic Areas: 
Model-based methods for fault detection, diagnostics, and prognosis
Submitted by: 
  
 
 
 

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