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Transcript of Http:// Smart Grid: Where Computation, Communication and Power Systems Meet Sandeep K. Shukla...
http://www.hume.ictas.vt.edu
Smart Grid: Where Computation, Communication and Power Systems Meet
Sandeep K. [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
About ACM
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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 becomeincreasingly interconnected and interdependent
… this creates an increased possibility that a ratherminor and routine disturbance can cascade into a
regional outage
… it also creates new assurance challenges thatcan only be met by a partnership between owners
and operators and government at all levels.”
President’s Commission onCritical 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
9
renewable coal
natural gas nuclear
Transmission
10
substation
substation
substation
substation
substation
substation
substation
power tower
power tower
power tower
power tower
power tower
power pole
power pole
Distribution
11
residential
residential
residential
residential
residential
industrial
industrial
What is “Smart Grid”
12
http://www.elp.com/index/display/article-display/0045209435/articles/utility-products/volume-7/issue-7/product-focus/test-__measurement/measurement-tools.html
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
16
Control Center
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
18
Power System Simulation
Cyber & Network Simulation
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.
Synchronization
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]
19
[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.
Continuous Time System Simulation
• Discretize differential equations and time
20
Power System Dynamic Simulation
21
Initialize all state variables
Calculate state variable derivatives
Calculate secondary variables
Calculate network boundary variables
Integration step
t0
t=t+Δt
one
roun
d
t ………………
t0
A simulation round
Discrete Event System Simulation
• Occurrence of events are not uniform• Event-Driven
– Scheduler– Event Queue– Event Processing
22
Communication Network Simulation
23
1 2
4
3
Synchronization with errors in EPOCHS
24
event 1
event 2
t
………………
event 3
event 4
Stands for a round of power system dynamic simulation
Stands for a communication network event
Start Synchronization Point 1
Synchronization Point 2
t
event 5
event 6
………………
………………
X
X
Error 1
Error 2Power
Communication
Global Event-Driven Synchronization
25
event 1
event 2 ………………
event 3
event 4
Stands for a round of power system dynamic simulation
Stands for a communication network event
Start
t
event 5
event 6
………………
√
√
event 1
event 2
event 3
event 4 ………………
Global Event Queue
Power
Communication
Implementation of the Co-simulation Framework GECO
• PSLF– Power system– Written in
Java– Script: EPCL
26
• NS2– Communication
network– Written in C++– Script: OTcl
Co-Simulation Platform Structure
27
BasicModel
DynamicModel
PSLF Simulation
PSLFInterface
PowerCommunication
Protocols
NS2 Simulation
NS2Interface
PowerApplications
PowerApplications
…………
………………
………………
GlobalScheduler
GlobalEvent List
GECO To Study All PMU linear state estimator
• Global Event-driven Co-simulation
Power System Models
PSLF Simulation
PSLFInterface
PDC Applications
NS2 Simulation
NS2Interface
Super PDC Applications
PMUApplications
…………
………………
………………
GlobalScheduler
GlobalEvent List
State Estimation
MatrixInterface
Linear State Estimator
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
29
Distance Relay Protection Zones
• Primary: Zone 1• Backup: Zone 2, Zone 3• Time-delayed manner for backups: Zone 2(300ms), Zone 3(1s)
30
Problems with Backup Relays• Drawbacks
– Long waiting time– Over sensitivity– Hidden failures
• However, zone 3 is still needed
31
[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.
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
33
Supervisory Scheme Operation (Slave)
34
Supervisory Scheme Operation (Master)
35
Ad-Hoc Protection Scheme
36
Ad-Hoc Scheme Operation (Peer)
37
Relay Searching
• Find the responsible relay group
38
Searching Algorithm
39
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
Robustness against primary failure
43
AM
S
Supervisory Protection on 39-bus System (Case 2)
44
Robustness against hidden failure
45
AM
S
Supervisory Protection Communication Delay
46
Relay Agent ID
Supervisory Protection Communication Delay Analysis
47
Ad-hoc Protection Communication Delay
48
Relay Agent ID
Supervisory Protection with Link Failure
49
Relay Agent ID
Supervisory Protection Delay with Link Failure
50
Ad-hoc Protection with Link Failure
51
Relay Agent ID
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
56
Timer to catch up measurement rate
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
PDC1
SPDC
PDC2
PDC3 PDC4
58
Area 1
Area 2
Area 3
Area 4
Co-Simulation Settings
59
[1] Kun Zhu, M. Chenine, and L. Nordstrom. ICT architecture impact on wide area monitoring and control systems’ reliability. 26(4):2801–2808, 2011.
[1]
[1]
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)
62
Network Link Failure at Bus16-Bus17 (Tp=60ms)
63
Network Link Congestion at Bus16-Bus17
64
Router Congestion: Bus16
65
Data Spoofing: Bus 3
66
Data Spoofing : Bus 3 (with a Real Fault)
67
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