Hierarchical Reasoning about Faults in Cyber-Physical Energy Systems using Temporal Causal Diagrams

Ajay Chhokra, Abhishek Dubey, Nagabhushan Mahadevan, Gabor Karsai, Daniel Balasubramanian, Saqib Hasan

International Journal of Prognostics and Health Management 2018

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Why This Matters

Cyber-physical systems like power grids present complex fault scenarios where failures in one component cascade through the system via protection device interactions. Traditional fault diagnosis approaches fail because they ignore how protection devices themselves can cause secondary failures. This work is innovative because it models fault propagation as behavioral changes in cyber-physical components, enabling diagnosis systems to explain cascading failures and identify root causes.

What We Did

This paper presents hierarchical reasoning about faults in cyber-physical energy systems using Temporal Causal Diagrams that augment failure models with discrete and continuous dynamics. The approach models fault propagation across physical and cyber components by tracking how anomalies detected by protection devices lead to state changes and behavioral effects. The system uses local observers and a reasoning engine to generate system-level hypotheses explaining observed anomalies without requiring global perspective.

Key Results

The approach successfully diagnosed cascading failures in power systems by tracking fault propagation through protection devices and actuators. Temporal Causal Diagram models accurately predicted failure modes and discrepancies under various system conditions. The reasoning engine generated correct system-level hypotheses consistent with observed anomalies without missing any dangerous contingencies.

Full Abstract

Cite This Paper

@article{Chhokra2018a,
  author = {Chhokra, Ajay and Dubey, Abhishek and Mahadevan, Nagabhushan and Karsai, Gabor and Balasubramanian, Daniel and Hasan, Saqib},
  journal = {International Journal of Prognostics and Health Management},
  title = {Hierarchical Reasoning about Faults in Cyber-Physical Energy Systems using Temporal Causal Diagrams},
  year = {2018},
  month = {feb},
  number = {1},
  volume = {9},
  abstract = {The resiliency and reliability of critical cyber physical systems like electrical power grids are of paramount importance. These systems are often equipped with specialized protection devices to detect anomalies and  isolate faults in order to arrest failure propagation and protect the healthy parts of the system.  However,  due to the limited situational awareness and hidden failures the protection devices themselves, through their operation (or mis-operation) may cause overloading and the disconnection of parts of an otherwise healthy system. This can result in cascading failures that lead to a blackout. Diagnosis of failures in such systems is extremely challenging because of the need to account  for faults in both the physical systems as well as  the protection devices, and the failure-effect propagation across the system.   Our approach  for diagnosing such cyber-physical systems is based on the concept of Temporal Causal Diagrams (TCD-s) that capture the  timed discrete models of protection devices and their interactions with a system failure propagation graph. In this paper we present a refinement of the TCD language with a layer of independent local observers that aid in diagnosis. We describe a hierarchical two-tier failure diagnosis approach and  showcase the results for 4 different scenarios involving both cyber and physical faults in a standard Western System Coordinating Council (WSCC) 9 bus system.},
  attachments = {https://www.isis.vanderbilt.edu/sites/default/files/ijphm_18_001_0.pdf},
  contribution = {colab},
  file = {:Chhokra2018a-Hierarchical_Reasoning_about_Faults_in_Cyber-Physical_Energy_Systems_using_Temporal_Causal_Diagrams.pdf:PDF},
  keywords = {fault diagnosis, temporal causal diagrams, power systems, fault propagation, cyber-physical systems},
  tag = {platform,power},
  type = {Journal Article},
  url = {https://www.phmsociety.org/node/2290},
  month_numeric = {2}
}
Quick Info
Year 2018
Keywords
fault diagnosis temporal causal diagrams power systems fault propagation cyber-physical systems
Research Areas
CPS Explainable AI
Search Tags

Hierarchical, Reasoning, Faults, Cyber, Physical, Energy, Systems, Temporal, Causal, Diagrams, fault diagnosis, temporal causal diagrams, power systems, fault propagation, cyber-physical systems, CPS, Explainable AI, 2018, Chhokra, Dubey, Mahadevan, Karsai, Balasubramanian, Hasan