Transcript Where Computation, Communication & Power Systems Meet

Smart Grid: Where Computation,
Communication and Power Systems
Meet
Sandeep K. Shukla
[email protected]
with Hua Lin, Yi Deng, James Thorp, Lamine Mili
This work was partially supported by NSF grant EFRI-0835879 & an NSF IUCRC - S2ERC Project
http://www.hume.ictas.vt.edu
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Outline
• Motivation
– Need for Infrastructure Interdependence Study
– Power System & Computing/communication – Smart Grid
•
•
•
•
Need for Co-Simulation
GECO – Our Co-simulator
Designing New Relaying Scheme with GECO
All PMU-State Estimator with GECO
– Experimental Framework
– Experimental Results and Interpretations
• Conclusions
Infrastructure Interdependencies
“Our nation’s infrastructures have become
increasingly interconnected and interdependent
… this creates an increased possibility that a rather
minor and routine disturbance can cascade into a
regional outage
… it also creates new assurance challenges that
can only be met by a partnership between owners
and operators and government at all levels.”
President’s Commission on
Critical Infrastructure Protection 1997
Examples of Critical Infrastructures
•
•
•
•
•
•
•
•
•
Energy (electric power, oil, natural gas)
Telecommunications
Transportation
Water systems
Banking and finance
Emergency services
Government services
Agriculture
Others
* CMU SEI Study
What is “Power System”
8
Generation
renewable
natural gas
coal
nuclear
9
Transmission
substation
power tower
substation
power tower
substation
power tower
substation
substation
power tower
power pole
power tower
substation
power pole
substation
10
Distribution
industrial
residential
residential
industrial
residential
residential
residential
11
What is “Smart Grid”
http://www.elp.com/index/display/article-display/0045209435/articles/utility-products/volume-7/issue-7/product-focus/test-__measurement/measurement-tools.html
12
Smart Grid Vision
• Generation:
– Micro-grid
– Renewable energy
– Gas turbines
• Transmission:
– Wide area monitoring
– Wide area protection and control
– Real-time state estimation
•
Distribution Level:
– Smart metering
– Demand response
– Self-healing distribution network
13
Communication Infrastructure
14
Communication Techniques
• Communication Link
–
–
–
–
–
Telephone
Microwave
Co-axial
Fiber
Power line communication
• Communication Network
–
–
–
–
LAN
WAN
MAN
WLAN
15
A Wide Area Measurement Scenario
Control
Center
16
Motivation
• Smarter Grid entails more Cyber components
• Wide area measurement and Control
• Communication Infrastructure
• New Cyber Security Vulnerabilities
• Smart Grid is a Extremely Large Scale Cyber Physical System
• ELCPS
• Physical Dynamics controlled by Cyber Networked Control
• Attack on the networked control can lead to disastrous Physical Dynamics
• Need to Study ELCPS
• Too large for Analytical Study
• Scalable but Accurate Co-Simulation is needed
• Need for co-simulation tools
• Leveraging Existing Scalable Tools
• Study Wide Area Control issues but Security is Extremely
Important to Study
Co-Simulation for CPS
To design a CPS system, engineers need tools to explore possible architectures,
protocols, and configurations.
Smart Grid engineers should be able to precisely model the power system and the
communication network together so that the system behaviors can be suitably
predicted.
Power System
Simulation
Synchronization
Cyber & Network
Simulation
18
Other Power System/Cyber Co-Simulators
•
•
•
•
•
•
EPOCHS: PSLF + NS2 [Cornell]
DEVS method: adevs + NS2 [ORNL]
PowerWorld + RINSE [UIUC]
PowerWorld + OPNET [UIUC]
PowerWorld + NS3 [Ga Tech]
OPNET extension [Jia Tong]
[1] K. Hopkinson, X. Wang, R. Giovanini, J. Thorp, K. Birman, and D. Coury. Epochs: a platform for agent-based electric power and communication simulation built from
commercial off-the-shelf components.
[2] J. Nutaro, P. T. Kuruganti, L. Miller, S. Mullen, and M. Shankar. Integrated hybridsimulation of electric power and communications systems. In Proc. IEEE Power Engineering
Society General Meeting, pages 1–8, 2007.
[3] C. M. Davis, J. E. Tate, H. Okhravi, C. Grier, T. J. Overbye, and D. Nicol. Scada cybersecurity testbed development. In Proc. 38th North American Power Symp. NAPS 2006, pages
483–488, 2006.
[4] D. C. T. C. Malaz Mallouhi, Youssif Al-Nashif and S. Hariri. A testbed for analyzing security of scada control systems (tasscs). In Second IEEE PES Innovative Smart Grid
Technologies Conference, 2011.
[5] X. Tong. The co-simulation extending for wide-area communication networks in power system. In Proc. Asia-Pacific Power and Energy Engineering Conf. (APPEEC), pages 1–4,
2010.
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Continuous Time System Simulation
• Discretize differential equations and time
20
Power System Dynamic Simulation
t0
Initialize all state variables
Calculate secondary variables
Calculate state variable
derivatives
one round
Calculate network boundary
variables
Integration step
t=t+Δt
A simulation round
………………
t
t0
21
Discrete Event System Simulation
• Occurrence of events are not uniform
• Event-Driven
– Scheduler
– Event Queue
– Event Processing
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Communication Network Simulation
3
1
2
4
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Synchronization with errors in EPOCHS
Stands for a round of power system dynamic simulation
Stands for a communication network event
Error 1
X
………………
t
Power
Error 2
X
event 6
event 5
event 4
event 3
event 2
event 1
………………
t
Communication
Start
Synchronization
Point 1
Synchronization
Point 2
………………
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Global Event-Driven Synchronization
Stands for a round of power system dynamic simulation
Stands for a communication network event
√
Power
………………
t
Start
event 6
event 5
event 4
event 3
event 2
event 1
Communication
………………
√
event 4
event 3
event 2
event 1
………………
Global Event Queue
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Implementation of the Co-simulation Framework
GECO
• PSLF
– Power system
– Written in
Java
– Script: EPCL
• NS2
– Communication
network
– Written in C++
– Script: OTcl
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Co-Simulation Platform Structure
PSLF Simulation
Basic
Model
Dynamic
Model
NS2
Interface
PSLF
Interface
…………
Power
Applications
………………
Power
Applications
………………
Global
Scheduler
Power
Communication
Protocols
Global
Event List
NS2 Simulation
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GECO To Study All PMU linear state estimator
• Global Event-driven Co-simulation
PSLF Simulation
State Estimation
Power System Models
Linear State
Estimator
Matrix
Interface
NS2
Interface
PSLF
Interface
Super PDC
Applications
…………
………………
PMU
Applications
………………
Global
Scheduler
PDC Applications
Global
Event List
NS2 Simulation
Internal Data Transfer
External Data Transfer
Power System Protection
• Relays protect power systems when faults happen
– Over current
– Over voltage
– Directional
– Distance (Impedance)
– Differential
– Pilot
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Distance Relay Protection Zones
• Primary: Zone 1
• Backup: Zone 2, Zone 3
• Time-delayed manner for backups: Zone 2(300ms), Zone 3(1s)
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Problems with Backup Relays
• Drawbacks
– Long waiting time
– Over sensitivity
– Hidden failures
• However, zone 3 is still needed
[1] S. Protection and C. T. Force. Rationale for the use of local and remote (zone 3) protective relaying backup systems. Technical
report, North American Electric Reliability Council, 2005.
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Network-based Backup Relay Protection
• Backup distance relays proactively communicate
with other relays to obtain wider system visibility
and make global protection decision
– Software agents take control
– Supervisory (master - slave)
– Ad-hoc (peer - peer)
32
Supervisory Protection Scheme
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Supervisory Scheme Operation (Slave)
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Supervisory Scheme Operation (Master)
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Ad-Hoc Protection Scheme
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Ad-Hoc Scheme Operation (Peer)
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Relay Searching
• Find the responsible relay group
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Searching Algorithm
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Decision Making
• Decision is made by “OR” manner voting
• Upper and lower time threshold
40
Co-Simulation Settings
• New England 39-bus system
• Communication network share same topology with
power system
• 100Mbps bandwidth and 3ms latency for each
communication link
• Without background traffic
41
Supervisory Protection on 39-bus System (Case 1)
42
AMS
Robustness against primary failure
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Supervisory Protection on 39-bus System (Case 2)
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AMS
Robustness against hidden failure
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Supervisory Protection Communication Delay
Relay Agent ID
46
Supervisory Protection Communication Delay Analysis
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Ad-hoc Protection Communication Delay
Relay Agent ID
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Supervisory Protection with Link Failure
Relay Agent ID
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Supervisory Protection Delay with Link Failure
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Ad-hoc Protection with Link Failure
Relay Agent ID
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Comparison
• Real system implementation
– Supervisory: extra master agent needed
– Ad-hoc: peer relays store system information locally
– Hybrid mode
• Reaction time
– Supervisory: long, uneven
– Ad-hoc: short, even
• Robustness to network failures
– Supervisory: increase by 20%-100%
– Ad-hoc: increase by multiple times
52
Outline
•
•
•
•
•
Motivation
Need for Co-Simulation
GECO – Our Co-simulator
Relay Case Study
All PMU-State Estimator
– Experimental Framework
– Experimental Results and Interpretations
• Conclusions
Power System State Estimation
• Conventional
– Slow scanning rate
– Power injection, power flow, voltage magnitude
– Non-linear, iterative solution
• All-PMU
– 30 times/sec
– Complex voltage and current
– Linear, non-iterative solution
Cyber Security Considerations
• All-PMU state estimation is superior than
conventional ones.
• But it can still be vulnerable to cyber attacks or
network failures.
– Intranet not completely safe
– Many conceivable threat models
WAMS Infrastructure
Timer to catch up
measurement rate
56
Outline
•
•
•
•
•
Motivation
Need for Co-Simulation
GECO – Our Co-simulator
Relay Case Study
All PMU-State Estimator
– Experimental Framework
– Experimental Results and Interpretations
• Conclusions
New England 39-bus System
Area 2
Area 1
PDC2
PDC1
SPDC
PDC3
PDC4
Area 4
Area 3
58
Co-Simulation Settings
[1]
[1]
[1] Kun Zhu, M. Chenine, and L. Nordstrom. ICT architecture impact on wide area monitoring and control systems’ reliability. 26(4):2801–2808, 2011.
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Outline
•
•
•
•
•
Motivation
Need for Co-Simulation
GECO – Our Co-simulator
Relay Case Study
All PMU-State Estimator
– Experimental Framework
– Experimental Results and Interpretations
• Conclusions
Co-Simulation Results
• Use estimated voltage at Bus 3 to represent if the
estimation is done successfully
• Attacks at critical locations to show typical
vulnerability
Network Link Failure at Bus16-Bus17 (Tp=50ms)
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Network Link Failure at Bus16-Bus17 (Tp=60ms)
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Network Link Congestion at Bus16-Bus17
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Router Congestion: Bus16
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Data Spoofing: Bus 3
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Data Spoofing : Bus 3 (with a Real Fault)
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Outline
•
•
•
•
•
Motivation
Need for Co-Simulation
GECO – Our Co-simulator
Relay Case Study
All PMU-State Estimator
– Experimental Framework
– Experimental Results and Interpretations
• Conclusions
Conclusions
• Smart Grid is an ELCPS
• Cyber Security Vulnerability for WAMS applications must be studied
in depth
• Co-Simulation is a good way to study Smart Grid applications
• GECO is built for such studies
• These case studies enhanced our confidence in GECO as a tool to
study new smart grid protocols and cyber security impacts on
smart grid
• Can we draw any general conclusions?
– Possibly not without stretching our imagination
– Need for identifying critical bottle neck links and nodes and safe
guarding them
– Further studies needed to develop
• More threat models
• Defense mechanisms against threat models