Transcript Security of Supply Issues: Technical & Economic Aspects

Security of Supply Issues:
Technical & Economic Aspects
Chen-Ching Liu
Advanced Power Technologies Center
University of Washington
Outline

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
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Blackout and cascaded events
Shortage of transmission enhancement
Defense system technology
Flexible grid configuration
Future areas - Transmission economics and
Microgrids
U.S. Blackout (Aug. 14, 2003)
The system becomes unstable
The system become vulnerable
High temperature in Midwest. FE
870 MW nuclear power plant was
down for maintenance.
MISO SE is ineffective from 12:15
to 16:04.
Eastlake unit 5 in northern Ohio
tripped due to an exciter failure @
13:31.
A series of 138-kV lines tripped in
the vicinity of Akron @ 15:39.
345-kV line (Stuart – Atlanta)
tripped @ 14:02.
Voltages in the Akron area fell
below low limits.
Loss of the FE Control Center
function shortly after 14:14.
345-kV line (Sammis – Star) tripped
@ 16:05
Star-South Canton tie line between
FE and AEP tripped and reclosed
@ 14:27.
Transient instability began after
16:10, and large power swings
occurred.
Total blackout
A sequence of lines outages
westward and northward across
Ohio and into Michigan, and then
eastward, splitting New York from
Pennsylvania and New Jersey.
Some NERC Recommendations
•
•
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•
•
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Strengthen the NERC compliance enforcement program.
Evaluate vegetation management procedures and results.
Evaluate reactive power and voltage control practices.
Improve system protection to slow or limit the spread of future
cascading outages.
Install additional time-synchronized recording devices as
needed.
Re-evaluate system design, planning, and operating criteria.
Load Shedding
According to the Final NERC Report on August
14, 2003, Blackout, at least 1,500 to 2,500 MW
of load in Cleveland-Akron area has had to be
shed to prevent the blackout.
Planned Generation Capacity & Transmission
Enhancement in U.S.
Planned Capacity
( 25% increase )
Projected Demand
( 18% increase )
Estimated
Capacity Margin
(5% increase )
Planned Transmission
( 3.5% increase )
Actual data (1999~2000)
Source: “Reliability Assessment 2001-2010 Report” by NERC, 2001.
Information Administration Website: “http://www.eia.doe.gov/cneaf/electricity/page/fact_sheets/transmission.html”
Defense Plans
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Coordination of a number of special
protection schemes for the entire system
Modification is required (e.g., BPA needs to
update the SPSs regularly)
Build a defense system that performs selfhealing control actions in an adaptive manner
Strategic Power Infrastructure Defense
(SPID)
–
Design self-healing strategies and adaptive
reconfiguration schemes
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To achieve autonomous, adaptive, and preventive
remedial control actions
To provide adaptive/intelligent protection
To minimize the impact of power system vulnerability
Research consortium with UW, Iowa State, Arizona State
and Virginia Tech, sponsored by EPRI, U.S. DoD and 4
institutions, $ 3M total, 1998-2001
Vulnerability Assessment
Protection
A
B
Dynamics and Control
CBA
CBB
Transient
Stability
Communication
Oscillator
y Stability
Pi
Vulnerability Regions
Intelligent System Models for the Complex Networks
•Model-based reasoning
•Physics •Rule-based system
•Evolutionary algorithm
•Decision-making
•ANN
•Generic tasks
•Forecasting
•Learning
•Self-healing
•Agent
•Multi-agent
System
•Adaptation
•Team work
•Coordination
•Negotiation
Multi-Agent System for SPID
Vulnerability
Assessment
Agents
DELIBERATIVE LAYER
Hidden
Failure
Monitoring Agents
Reconfiguration
Agents
Comm.
Agent
Knowledge/Decision
exchange
Restoration
Agents
Event
Identification
Planning
Agent
Agents
Triggering Events
COORDINATION LAYER
Event/Alarm
Filtering
Update Model
Agents
Plans/Decisions
Model
Update
Agents
Check
Consistency
Controls
Events/Alarms
Frequency
Stability
Agents
Fault
Isolation
Agents
Inputs
REACTIVE LAYER
Protection
Agents
Command
Interpretation
Agents
Inhibition Signal
Controls
Power System
Generation
Agents
Adaptive Self-healing:
Load Shedding Agent
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A control action might fail
Reinforcement Learning
–
–
Autonomous learning method based on interactions
with the agent’s environment
If an action is followed by a satisfactory state, the
tendency to produce the action is strengthened
Adaptive Self-healing:
Load Shedding Agent
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The 179 bus system resembling the western
U.S. system
ETMSP simulation
Remote load shedding scheme based on
frequency decline + frequency decline rate
Temporal Difference (TD) method is used for
adaptation: Need to find the learning factor for
convergence
Adaptive Self-healing:
Load Shedding Agent
179 bus system
Adaptive Self-healing:
Load Shedding Agent
60
frequency with 20 % load shedding
frequency
59.8
59.6
59.4
10% load shedding
59.2
59
58.8
58.6
0
50
100
150
200
Time (multiples of 0.02 sec)
250
Adaptive Self-healing:
Load Shedding Agent
Normalized frequency
2.5
Expected normalized system
frequency that makes the system
stable
a=0.55
2
1.5
1
a=0.75
0.5
0
0
20
40
60
80
100
120
Number of trials
140
160
180
“The load shedding agent is
able to find the proper
control action in an adaptive
manner based on responses
from the real power system”
Flexible Grid Configuration to Enhance
Robustness
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Flexible grid configuration can play a significant role
in defense against catastrophic events
Power infrastructure must be more intelligent and
flexible
–
To allow coordinated operation and control measures to
absorb the shock and minimize potential damages caused
by radical events
Area-Partitioning Algorithm

To develop a k-way partitioning algorithm,
which uses the information available in network
matrices and divides the power grid into k
disjoint areas while minimizing load-generation
imbalance for each area
Area-Partitioning Algorithm
1
1
0.1
6
2
2
0.1
1
5
3
0.1
1
4
Flexible Grid Configuration by
Partitioning
Risk Management of Power Infrastructure
High Risk Alert
Flexible Grid Configuration by Partitioning
Lower the Risk Level
Self-sufficient Sub-networks
Alert is Over
Normal Configuration (Wide Area Grid)
Cascaded Events - Simulation
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Compute Power Flows after Tripping
–
–
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Identify New Network Configuration and Solve Power
Flows Again
–
–
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Six lines are found with limit violations
Trip these lines, Bus170 and 171 become isolated buses
Fifteen lines are found with limit violations
Trip these lines, seven buses become isolated buses
Continue This Simulation Procedure
–
Finally the system collapses: most transmission lines are
tripped and most loads are lost
Flexible Grid Configuration to
Absorb the Shock

Split the System into Two Areas
–
–
–
Seeds=[Bus 83, Bus 47]
Area One: 92 buses, 117 branches
Area Two: 87 buses, 140 branches
WECC 179-bus System Example
230kV
345kV
500kV
35
34
33
32
31
30
74
80
79
65
66
75
78
69
72
76
73
82
87
77
67
91- 94
88
95-98
71
89 90
70 68
83
81
36
99
86 180
84
85
168 170
172
169
173
156
114
100
125
6
158 164
166
106
122
159
45 160
101
115
121
165
113
120
11
5
167
155
44
124
111
157 161 162
112
171
105
123
117 116
119
163
134 104
118
135
132
133
48
48
104
107
175, 177, 179
103
39
46
102 63
48
48
56
62
149
147
148 2726
22
58
57
47
54
51
152
141
140
53 52
144
61
137
9
14 29 28
24
10
3
142 146
145 136
23
25
19
2
16 15
17 18
7
20
21
138 139
55
50
42
64
143
154
150
60(3) 48
41
43
38
37
49153 151
59
42
174, 176, 178
110
40
8
12 13
108109
4
Split System into Two Areas
230kV
345kV
500kV
35
34
33
32
31
30
74
80
79
65
66
75
78
69
72
76
73
82
87
77
67
91-94
70 68
83
172
89 90
81
36
99
86 180
84
85
168 170
173
156
157 161 162
112
171
169
111
88
95-98
71
114
124
100
125
113
120
101
115
121
106
122
105
123
117 116
119
134 104
118
104
107
155
44
108109
165
159
6
45 160
174, 176, 178
11
5
167
135
132
133
110
103
158 164
166
102
163
8
12 13
48
48
63
39
46
48
42
62
147
148 2726
22
53 52
145
149
152
141
140
61
144
137
9
14 29 28
24
10
3
142 146
23
25
136
19
2
55
58
57
47
54
51
50
42
150
60(3) 48
41
43
64
143
154
49153 151
59
48
56
38
37
175, 177, 179
40
16 15
17 18
7
20
21
138 139
4
Flexible Grid Configuration to
Absorb the Shock

Use “Power Redispatching & Load Shedding”
in Area Two
–
Totally, 188 + 64.4 + 60 = 312.4 MW load are shed
Bus
Original Load
Load Shed
Load Supplied
#
(MW)
(MW)
(MW)
8
239
188
51
16
793.4
64.4
729
154
1066
60
1006
Alert is Over (Wide-Area Grid)
230kV
345kV
500kV
35
34
33
32
31
30
74
80
79
65
66
75
78
69
72
76
73
82
87
77
67
91- 94
88
95-98
71
89 90
70 68
83
81
36
99
86 180
84
85
168 170
172
169
173
156
114
100
125
6
158 164
166
106
122
159
45 160
101
115
121
165
113
120
11
5
167
155
44
124
111
157 161 162
112
171
105
123
117 116
119
163
134 104
118
135
132
133
48
48
104
107
175, 177, 179
103
39
46
102 63
48
48
56
62
149
147
148 2726
22
58
57
47
54
51
152
141
140
53 52
144
61
137
9
14 29 28
24
10
3
142 146
145 136
23
25
19
2
16 15
17 18
7
20
21
138 139
55
50
42
64
143
154
150
60(3) 48
41
43
38
37
49153 151
59
42
174, 176, 178
110
40
8
12 13
108109
4
Investment & Return Analysis of
Transmission Expansion
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Economics of transmission expansion should be analyzed from
an investment / return point of view.
- Economic value of transmission capacity improvement
- Economic incentives of transmission owners
- Economic incentives of generators
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Techniques for electricity price
forecasting can be used for
economic analysis of transmission
expansion.
Example: Investment & Return Analysis of
Transmission Expansion
0
1
$15
2
$15
...
T
...
Period
...
$15
...
Revenue
if Price
is high
...
Revenue
if Price
is low
Discount rate = 10%
Initial
Investment
Cost of investment = $84
$5

$5
...
$5
The expected present value of the discounted stream of
revenues ($100) exceeds the investment cost ($84).
 Invest now
Wait for One Period to Decide
0
1
$15
2
$15
...
T
...
Period
...
$15
...
Revenue
if Price
is high
...
Revenue
if Price
is low
Discount rate = 10%
Initial
Investment
Cost of investment = $84
$5
$5
...
$5
 Don’t invest
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If price is low, $50 < $ 84

If price is high, $150 > $ 84

Expected payoff (= 0.5*($150-$84)/1.1 = $30).
Waiting for one period is better than investing now since $30 >
$16.

 Invest
Value of Investment Opportunity

An investment project whose revenue follows a geometric
Brownian motion

Value of waiting

Overall value of the investment opportunity
Micro Grid Concept
Distant or remote locations
-Islands
-Regions with no pre-existing infrastructure
 Special power needs
-Chip fabrication plants
-Financial centers

Wind Generators
CADET Technical Brochure 68 “33.6 MW Wind Farm near Carno” EA, OECD, 1998
Example
Load BusGS-1
Load Bus GS-2
Load Bus GS-3
Load Bus GS-4
Load Bus GS-5
Frequency Response with no
Control Agent
60.04
GS-3
GS-5
60.02
Frequency (hertz)
60
59.98
59.96
59.94
59.92
0
5
10
15
Time (seconds)
20
25
30
Inter-Machine Oscillations

With no control agent there are clear
indications of inter-machine oscillation
Results:
•Unnecessary flow oscillations of power along tie lines
•Unnecessary stress on the machines
•Excessively large overshoots
•Excessively long settling times
Control Agent Scheme

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Measure the load at each of the load buses.
Measure the frequency at each of the load
buses.
When a load change is sensed the control
agent generates control signals based on the
current rotational energy of the rotors.
Frequency Response with a Control Agent
60.01
GS-3
GS-5
60.005
60
Frequency (hertz)
59.995
59.99
59.985
59.98
59.975
59.97
59.965
59.96
0
5
10
15
Time (seconds)
20
25
30
Grand Challenges

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Prevention of Major Blackouts
Energy Crisis in Western U.S.
Evolution of Electricity Markets
Alternative Energy and Distributed Generation
Engineering / Technology, Economics,
Public Policy