This thesis develops probabilistic models to formally verify a fault detection and service restoration system in a smart grid using a probabilistic model checker. It develops discrete time Markov chain models for fault detection, isolation and supply restoration for a Tianjin electric power network with 3 and 6 load switches. It also develops a communication protocol model. Temporal logic properties are defined and the models are verified. Results show the effect of wireless communication on failure probabilities compared to an ideal network.

1. FORMAL VERIFICATION OF FAULT DETECTION &
SERVICE RESTORE SYSTEM IN SMART GRID USING
PROBABILISTIC MODEL CHECKER
Presented by : Syed Atif Naseem
Supervisor :Assoc.Prof Diaa Gadelmavla
MASTER’S THESIS

2. AGENDA
 Introduction
 Objective
 Literature Review
 Model checking
 State of IED
 Tianjin Electric Network with Wireless Communication Link
 Methodology
 Development of Discrete Time Markov Model
 Development of Temporal Logic Property
 Functional Verification using Simulation
 Formal Function Verification
 Conclusion

3. Introduction
 Model Checking
 FDIR in Smart Grid
 Tianjin Electric Power Network
 Case 1: Development of Fault Detection, Isolation, Supply
Restoration DTMC model for three load switches.
 Case 2 : Development of Fault Detection, Isolation, Supply
Restoration DTMC model for Six load switches.
 Case 3 : Development of Communication Protocol of MAC layer
and Receiving Station of Communication System.
 Integration of FDIR Model with Communication Network
 Development of Temporal Logic Property

4. Objective
 Development of FDIR DTMC model for Tianjin Electric Power Network
 Development of IEEE 802.11 DCF communication model
 Coding of DTMC model on PRISM model
 Development of Temporal logic specification and applied on model to
verify it
 Comparison between FDIR model with wireless communication network
and ideal communication network
 To predict the failure probability of switching and communication failure
of distribution network
 To predict the successful isolation of sectionalizer with in the limited time
 To predict the probability to restore the network through Tie switch

5. Literature Review
Literature Techniques Formal Verification
Using distribution
automation for a self-
healing grid-2012
Compare centralized and
decentralized architecture
No
Fault Detection & Supply
restoration system - 2015
Restoration scheme No
Agent based restoration
with distributed energy
storage support in Smart
Grids-2012
Decentralized structure No
A multi-agent solution to
distribution systems
restoration- 2007
Different kinds of agents
to restore power system
No

6. Literature Review
Distributed restoration
system applying multi-
agent in distribution
automation system- 2008
Substation restoration
technique
No
Design and
implementation of
multiagent-based
distributed restoration
system in DAS- 2013
Shortening of restoration
time
No
Fault location and
isolation using multi agent
systems - 2013
Monitoring the limited
current
No

7. Literature Review
A multiagent distribution
system for service
restoration of fault
contingencies - 2011
MAS design for
restoration
No
Distributed power system
automation with IEC
61850 and intelligent
control- 2011
Integration Of technique No
A multiagent approach to
distribution system
restoration- 2003
Restoration scheme No
A multi-agent based
restoration approach in
Smart Grid- 2011
Restoration scheme No

8. Thesis Flow Diagram
LITERATURE
REVIEW
DECISION
MODEL
DEVELOPMENT
DEVELOPMENT
OF
SPECIFICATION
PROGRAMING
SIMULA
TION
RESULTS
REPORT
Idea

9. Building a DTMC Model
DTMC
MODEL
DEVELOPMENT
OF FAULT
DETECTION
MODEL
DEVELOPMENT
OF RECEIVING
STATION
MODEL
DEVELOPMENT
OF FAULT
ISOLATION
MODEL
DEVELOPMENT
OF SUPPLY
RESTORATION
MODEL
DEVELOPMENT
OF IEEE 802.11
DCF MODEL

10. Model Checking
System
FSM
Model Checker
Language
Properties
Temporal
Properties
PRISM Language
Model checker
True, Otherwise Counter Example

11. FDIR IED State
Normal
Fault
Outage
Restore

12. Tianjin Electric Network

13. Methodology
Identify
variable
Identify
modules
DTMC Simulation
Verified
Model
Checker
Tool
Developed
Properties
Fix It

14. Development of Fault Detection Model
Initialize Variables & Constants
Checking for Faults
Tripping of Substation & Fault Messages
Sent
Fault Messages received at Load Switches
Checking for TIE Switches
Starting Fault Detection
Process
Fault Detected in Load
Switches

15. Development of Fault Isolation Model
Switch Trip
Isolation Successful or Isolation Failure
Faulty Section
Initialize Variables & Constants

16. Development of Supply Restoration Model
Finding of TIE Switch
ISOM Message Received / Not Received
Restoration Successful or Restoration
Failure
Initialize Variables & Constants

17. Development of Communication Protocol at MAC
Layer
Channel Free
Transmission Data & Backoff=0
Transmission Data
Initialize Variables & Constants
Waiting of Backoff value to 0

18. Development of Receiving Station of the Communication
System
Received Packet/ Packet Not Received
Short Interface Space Sends
IED Activated
Initialize Variables & Constants
Acknowledgment Sends

19. Case 1: Fault Detection Model
(Three Load Switches)

20. Case 1: Fault Isolation Model
(Three Load Switches)

21. Case 1: Supply Restoration Model
(Three Load Switches)

22. Case 2: Fault Detection Model (Six
Load Switches)

23. Case 2: Fault Isolation Model (Six
Load Switches)

24. Case 2: Supply Restoration Model
(Six Load Switches)

25. Development of Communication
Protocol at MAC Layer

26. Receiving Station of Communication System

27. Development of Temporal Logic and
Probabilistic Properties
 Deadlock Freedom
 Detection of Fault Current
 Fault Isolation Model Turned On
 No Two Processes Run at the Same Time
 Restoration Model at 60 sec Time
 Probability of Fault Occurrence at Load Switch
 Probability of Fault Flag High at Load Switch
 Probability to Trip-off the Load Switch
 Probability to Recover the Network
 Probability to sends the Messages B/W IEDS

28. Functional Verification using
Simulation (Three Load Switches)

29. Formal Function Verification Results

30. Functional Verification using
Simulation (Six Load Switches)

31. Formal Function Verification Results

32. Integration of FDIR Model with Communication
Model

33. Comparison of Probabilities for Failure of
Components

34. Components Tripping off Probabilities

35. Load Switch Restoration Probabilities

36. Tie Switch Restoration Probabilities at
Different Time

37. Conclusion
 Development of Markovian Model of FDIR
 Development of Markovian Model of IEEE 802.11 DCF
 Developed the logical temporal properties
 Accuracy, reliability and efficiency of model verified through temporal logic properties
 Prediction of failure probabilities of components when FDIR connected with wireless and
Ethernet communication system
 Prediction of successful isolation probability of load switches when connected with
wireless and Ethernet communication system
 Prediction the successful restoration probability of TIE switches connected with wireless
and Ethernet communication system
 Analyzed the restoration time required for different pre-specified time period, increases the
probability factor of 0.03
 Expand the network by including six load switches and verified the model
 By increasing the number of load switches, failure probabilities increases where as
increases the number of TIE switches increases the successful restoration probability of
network.