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

Ajay Chhokra, Nagabhushan Mahadevan, Abhishek Dubey, Saqib Hasan, Daniel Allen Balasubramanian, and Gabor Karsai
Publication Target: 
IJPHM
Publication Issue: 
1
Submission Type: 
Full Paper
Supporting Agencies (optional): 
National Science Foundation
AttachmentSizeTimestamp
ijphm_18_001.pdf3.8 MBJanuary 30, 2018 - 5:56pm

Cyber-physical systems are often equipped with specialized fault management systems that observe the state of the system, decide if there is an anomaly and then take automated actions to isolate faults. For example, in electrical networks relays and breaks 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. Additionally, often there can be faults in the management system itself leading to situations where it is difficult to isolate failures. Our work presented in this paper is geared towards solution of this problem by describing the formalism of Temporal Causal Diagrams (TCD-s) that augment the failure models for the physical systems with discrete time models of protection elements, accounting for the complex interactions between the protection devices and the physical plants. We use the case study of the standard Western System Coordinating Council (WSCC) 9 bus system to describe four different fault scenarios and illustrate how our approach can help isolate these failures. Though, we use power networks as exemplars in this paper our approach can be applied to other distributed cyber-physical systems, for example water networks.

Publication Year: 
2018
Publication Volume: 
9
Publication Control Number: 
001
Page Count: 
22
Submission Keywords: 
Cyber Physical Energy Systems
Temporal Causal Diagrams
System Diagnosis
Power Transmission Networks
Submission Topic Areas: 
Model-based methods for fault detection, diagnostics, and prognosis
Submitted by: 
  
 
 
 

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