clemson university’s synchrophasor - …rtpis.org/psc14/presentations/panel...
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CLEMSON UNIVERSITY’S SYNCHROPHASOR
ENGINEERING EDUCATION PROGRAM (CU-SHEEP)
G. Kumar Venayagamoorthy, PhD, FIET, FSAIEE
Duke Energy Distinguished Professor &
Director & Founder of the Real-Time Power and Intelligent Systems Laboratory
The Holcombe Department of Electrical & Computer Engineering
Clemson University
E-mail: [email protected]
http://people.clemson.edu/~gvenaya
http://rtpis.org
Acknowledgment:
US DOE: DE-OE0000660
US DOE CU-ShEEP Project
The objective of this project is to establishcollaboration with a local utility – Duke Energyand others, in establishing a SituationalIntelligence (SI) Laboratory that will be drivenfrom a Real-Time Grid Simulation Laboratoryand introduce new content in the power andenergy systems engineering research andeducation at Clemson University, especially inthe area of synchrophasor technology and itsapplication in a smart grid environment.
US DOE CU-ShEEP Project
• The SI lab is a unique research and rapid prototyping/customizing laboratory for new real-time situational intelligence (SI) and intelligent control technologies for electric power control center deployment.
• Algorithms and methods for real-time situational awareness (SA) and intelligence (SI) and visualizations for control centers are developed using in-house and third party software.
• The laboratory is focused on applications for generation, transmission, and distribution systems and microgrid control center operations.
• The SI Lab has system operator consoles besides the large control room displays.
• Many of the applications are parallelized for implementation on Clemson Palmetto cluster. Data is transmitted using a dedicated (~10-mile) high-speed fiber optic connection between the SI Lab and the Clemson data center.
• Students education and training on synchrophasor technology as part of undergraduate and graduate curricula.
• Development of new contents on synchrophasors and its applications in over ten courses offered at the undergraduate/graduate levels.
• Clemson’s synchrophasor engineering education with local utility’s participation.
• Three short courses in synchrophasor and related technologies. These courses are intended for utility and industrial professionals.
EDUCATION OUTCOMES
• Students involved with CU-ShEEP are expected to have experiential training opportunities at utilities and vendors. Short courses in synchrophasors and their applications in the control centers for non-power system, utility and industrial engineers are under developed.
• Development of future workforce of electrical engineers, computer scientists and non-power system engineers who are knowledgeable about and experienced in synchrophasor analysis.
• The project innovations/findings will be shared with other academic institutions and synchrophasor communities.
EDUCATION OUTCOMES
• Researchers and students gaining hands-on experience on real-time grid simulation, control center operations and synchrophasor measurements.
• Development of distributed computing algorithms for analyzing and predicting smart grid data.
• Applications of synchrophasor phasor data for real-time power system operations such as online generator coherency analysis; online oscillation of synchronous generators; and as tie-line bias control of a power system with high penetration of variable generation.
• Security evaluation of synchrophasor network for power system operations.
• Development of situational awareness and situational intelligence algorithms and visualization tools for enhanced control center operations.
RESEARCH OUTCOMES
Situational Awareness (SA)in a Control Center
When a disturbance happens, the operator isthinking:
• Received a new alert!• Is any limit in violation?
• If so, how bad?• Problem location?
• What is the cause?• Any possible immediate corrective or mitigative
action?• What is the action?• Immediate implementation or can it wait?
• Has the problem been addressed?• Any follow up action needed?
7
Situational Intelligence
• Integrate historical and real-time data to implement near-futuresituational awareness
Intelligence (near-future) = function(history, current status, some predictions)
• Predict security and stability limits• RT operating conditions• Oscillation monitoring• Dynamic models• Forecast load• Predict/forecast generation• Contingency analysis
• Real-time and predictive visualizations• Integrate all applications• Topology updates and geographical influence (PI and GIS – Google
earth tools)
Predictions is critical for Real-Time
Monitoring
8
11
0 2 4 6 8 10 12 14 16 180.994
0.996
0.998
1
1.002
1.004
1.006
Time [s]
speed in p
.u.
05
1015
20
0
5
10
15
201
2
3
4
5
6
7
8
Time [s]Generator index
Gro
up index
Group
index
Offline
Clustering
during
0~18s
Online
Clustering
at 8s
Online
Clustering
at 10s
Online
Clustering
at 15s
1 G1, G8 G1,G8 G1,G2,G3,
G8,G10,G11,G12,G
13
G1,G8
2 G2,G3 G2,G3 G4,G5,G6,
G7,G9
G2,G3
3 G4,G5,G6,
G7,G9
G4,G5,G6,
G7
G14,G15,
G16
G4,G5,G6,
G7,G9
4 G10,G11 G9 G10,G11,
G12,G13
5 G12,G13 G10,G11 G14,G15,
G16
6 G14,G15,
G16
G12,G13
7 G14,G15,
G16
Online Coherency Analysis of Synchronous Generators in a Power System
100ms three phase fault at bus 8
Online Oscillation Monitoring of Synchronous Generators
Area 3
G7
G6
G9
G4
G5
G3
G8 G1
G2
G13
G12
G11
G10
G16
G15
G14
59
23
61
29
58
22
28
26
60
25
53
2
24
21
16
56
57
19
20
55
10
13
15
14
17
27
12
11
6
547
5
4
18
3
8
1
47
48 40
62
30
9
37
65
64
36
34
38
35
33
63
43
45
39
50
51
52
68
67
49
46
42
41
31
66
Area 1 Area 2
Area 4
New England Test System New York Power System
44
32
Area
5
-------------------------
6 6.5 7 7.5 8 8.5 9 9.5 10 10.5 11375.5
376
376.5
377
377.5
378
378.5
time (s)
angula
r s
peed (
rad/s
)
6 6.5 7 7.5 8 8.5 9 9.5 10 10.5 11376
376.2
376.4
376.6
376.8
377
377.2
time (s)
angula
r speed (
rad/s
)
Prony’s algorithm run on PMU data parsed on a PC
Modal damping and
frequencies
Modal damping and
frequencies
Modal damping and
frequencies
Gen. 1
-------- --------
Gen. 8 Gen. 16
Tie-Line Bias Control in a Power System with Large PV Plants
0 20 40 60 80 100 120160
160.5
161
161.5
162
162.5
163
163.5
164
164.5
165
Time in Seconds
PV
Outp
ut
Pow
er
in M
W
0 20 40 60 80 100 120130
135
140
145
Tie
-Lin
e P
ow
er
Flo
w in M
W
Time in Seconds
0 50 100 150 2000
50
100
150
200
250
300
Time (s)
Pow
er
(MW
)
0 50 100 150 200
200
250
300
350
400
Time (s)
Pow
er
(MW
)
0 20 40 60 80 100 12059.99
59.995
60
60.005
60.01
Time in Seconds
Are
a 1
PM
U F
requency in H
z
0 20 40 60 80 100 12059.98
59.99
60
60.01
60.02
60.03
Time in Seconds
Are
a 2
PM
U F
requency in H
z
Summary
• CU-ShEEP will educate our students and workforce in the
knowledge of synchrophasor technology and control center
operations.
• The project innovations/findings will be shared with other
academic institutions and synchrophasor communities through
workshops, panels at conferences and NAPSI meetings, and
publications.
• Possible areas of collaboration:
• Applications of situational awareness and situational
intelligence algorithms and visualization tools to other
utilities’ synchrophasor/micro-synchrophasor data from
transmission/distribution system, respectively.
• Custom distributed algorithms for other utility networks.
14
Thank You!G. Kumar Venayagamoorthy
Director and Founder of the Real-Time Power and Intelligent Systems Laboratory &Duke Energy Distinguished Professor of Electrical and Computer Engineering
Clemson University, Clemson, SC 29634
http://rtpis.org [email protected]
March 13, 2014