Post on 18-Sep-2018
transcript
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Panel Session at IEEE PES GM 2015
Microgrids in Distrib tion S stem RestorationDistribution System Restoration
Chen‐Ching LiuBoeing Distinguished Professor Washington State University
(Also Professor, University College Dublin)
Research Sponsored by PNNL and Dept of Energy
SGIGs on Distribution Automation SGIGs on Distribution Automation
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• Deployment of technologies and systems for improving distribution system operations, including: (1) outage management with devices such as automated circuit switches and reclosers, and (2) voltage/volt‐ampere reactive (VAR) control with field devices such as automated capacitors, voltage regulators, and voltage sensors.
Installed SGIG Automated SwitchesInstalled SGIG Automated Switches
Example:
Avista Utilities WAAvista Utilities, WA
Spokane and Pullman
(WSU) Smart Circuit
Installed SGIG Automated Capacitors
(WSU) Smart Circuit
Project Cost: $40MProject Cost: $40M
Fed Funding: $20M
Source: http://energy.gov/sites/prod/files/Smart%20Grid%20Investment%20Grant%20Program%20-%20Progress%20Report%20July%202012.pdf
Fed Funding: $20M
Reliability ImprovementsReliability Improvements3
• 48 SGIGs are applying DA technologies to improve reliability:• 42 deploying automated feeder switches (1 to > 1000’s of switches)p y g ( )
– Enables fault location, isolation and service restoration functions
• System integration schemes (AMI/OMS/DMS/SCADA/GIS)– 26 projects are applying distribution management systems– 36 implementing AMI outage notification– 22 deploying equipment health sensors
I i i l l f 4 P j (1 250 f d ) A il 1 2011 h h M h 31 2012• Initial results from 4 Projects (1,250 feeders) ‐ April 1, 2011 through March 31, 2012
Source: http://tcipg.org/sites/tcipg.org/files/slides/2013_02-01_Arnold.pdf
Distribution System Restoration (DSR)4
Distribution System Restoration (DSR)• A smart grid application and an important objective of
distribution automation.• Restore critical load during extreme events.• A typical multi‐objective, combinatorial problem with
constraints, including topological and electrical constraints.
Restore loads in a secure and efficient manner
Selecting and sequencing a set of switching
operationsReduce the duration of outages and improve
reliability
Distribution System
Restoration
reliability
Service Restoration with DA (1)*5
Service Restoration with DA (1)1. Fault occurs 2. Open CB
3. Find fault 4. Isolation
Korean Electric Power Company: Intelligent DA System
Service Restoration with DA (2)*6
Service Restoration with DA (2)5. Transfer outage area 6. Execute restoration plan
7 Field crew7. Field crew
KEPCO: Intelligent DA System
Basic DSR Strategies*7
Basic DSR StrategiesSingle Double Tripleg p
Single & level‐2 Double & level‐2 Selfg
KEPCO: Intelligent DA System
Problem Formulation
A constrained multi-objective problem
Objectives: - (minimize the total number of switch operations)
( i i th t f t t l l d t d)- (maximize the amount of total load restored)
Subject to following constraints:
, Line Capacity Constraint ,
Node Voltage Constraint, Node Voltage Constraint ,
, Transformer Capacity Constraint,
A radial network structure is maintained,
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,
Unbalanced three phase power flow is satisfied.
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J. Li, X. Y. Ma, C. C. Liu, K. Schneider, “Distribution System Restoration with Microgrigd Using Spanning Tree Search,” IEEE Trans Power Systems Nov 2014 pp 3021 3029
Distribution Network Topology and Spanning TreeIEEE Trans. Power Systems, Nov. 2014, pp. 3021-3029
Radial structure of the distribution network can be represented by a spanning tree.
Restoration can be formulated as a problem of finding a desired spanning tree structure and a sequence of operations that change one spanning tree into anotherspanning tree into another.
Spanning Tree Representation for Distribution Feeders
J. Li, X. Y. Ma, C. C. Liu, K. Schneider, “Distribution System Restoration with Microgrigd Using Spanning Tree Search,” IEEE Trans. Power Systems, Nov. 2014, pp. 3021-3029.
Proposed Distribution System Restoration AlgorithmEach Class of Spanning Trees Candidate TopologiesEach Class of Spanning Trees Candidate Topologies
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Microgrids Enhance Restoration Capability
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Microgrids Enhance Restoration Capability
• Generation resources and control capabilities of• Generation resources and control capabilities of microgrids enhance fast recovery of distribution systems.
• Grid connected mode and• Grid‐connected mode andisolated mode.
• When a blackout occurs, microgrids can be controlled
d ffMicrogrid
to provide an efficient DSR strategy to reduce the
f hrestoration time of the distribution system.
Restoration schemes considering DERs and Microgrids
Integrate Microgrids into DSR Algorithm12
Integrate Microgrids into DSR Algorithm
• Microgrids are modeled as virtual feeders• Generation limits of DERs are formulated as electrical constraints of the distribution feeders.
• The island configuration Microgrid Virtual FeederThe island configuration of the microgrid can be modeled as a supplemental
F2 F3
1 26
7 8 9 14 15 16 17 18
13 19
Microgrid Virtual Feeder
ode ed as a supp e e atopology constraint of the distribution system. F5
F41 2
4
512
11 10
2021
23
22
yF1 3 11 10
Load NodeClosed Switch
(branch)Open Switch
(branch)
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Example – Microgrid Supports Fast
• One line diagram of Pullman WSU System
Example Microgrid Supports Fast Recovery of Distribution Systems
• One‐line diagram of Pullman‐WSU System
1
13
(Root)
SPU121 48 34 37
29
35
41
30
32 21 2322 24 27
414
7 12
SPU12249
39
43 15 16
City Hall & Police Station
G3 2 1 MW
3
5
9
SPU123
SPU124
50
171840
3831
36 42Hospital
G3
G2 1.1 MW
2.1 MW
26 8 10
SPU12451 20 19
G1 1.1 MW
11 SPU125 52 46 45 33 44 47 28 25 26
WSU MicrogridSPU Substation
Load Sections Normally Closed Switch Normally Open SwitchLoad Sections Normally Closed Switch Normally Open Switch
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Example – Microgrid Supports FastExample Microgrid Supports Fast Recovery of Distribution Systems (Conti.)
• Scenario Description– A severe event happened in the South Pullman 115kV– A severe event happened in the South Pullman 115kV Substation.
– As a result all 5 feeders served by the substation are outAs a result, all 5 feeders served by the substation are out of service.
• Feeders: SPU121, SPU122, SPU123, SPU124, SPU125• Critical loads: Hospital, City Hall, Courthouse and Police Station
– No source in the Avista system can be used for restoration.– WSU generators will be used to restore critical loads.
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Example – Microgrid Supports FastExample Microgrid Supports Fast Recovery of Distribution Systems (Conti.)
• Spanning Tree Search algorithm is applied to find the restoration paths from DERs to critical loads.
Critical Load13SPU121
48 34 37
29
35
41
30
32 21 2322 24 27
14SPU122
49
39
43 15 16
1718
City Hall & Police Station
G3 2.1 MW
Critical Load10
9SPU123
SPU12451
50
184038
31
36 42
20 19
Hospital
G1
G2
1.1 MW
1.1 MW
Source11
SPU12552 46 45 33 44 47 28 25 26
WSU Microgrid
Example – Microgrid Supports Fast16
Example Microgrid Supports Fast Recovery of Distribution Systems (Conti.)
• Restoration Path: G3 17 19 20 34 37 41 32 39 42 36 38 40
13SPU121
48 34 37
29
35
41
30
32 21 2322 24 27City Hall
City Hall, Courthouse, Police Station Hospital
14SPU122
49
39
43 15 16
171840 31
City Hall, Courthouse
& Police Station
G3 2.1 MW
G3, a diesel generator, is used to pick up critical loads i e City Hall
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9SPU123
SPU12451
50
038
31
36 42
20 19
Hospital
G1
G2
1.1 MW
1.1 MW loads, i.e., City Hall, Courthouse, Police Station and Hospital.
11SPU125
52 46 45 33 44 47 28 25 26
WSU Microgrid
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Example – Microgrid Supports FastExample Microgrid Supports Fast Recovery of Distribution Systems (Conti.)
• Validation by GridLAB‐D Power FlowG3 17 19 20 34 37 41 32 39 42 36 38 40
City Hall, Courthouse, Police Station Hospital
PNNL Test SystemWith Microgrids18
PNNL Test System With MicrogridsZ31 Z35
Z29
Z17 Z20
Z25
Z28
Z39
Microgrid 1
Z38 Z3
Z33
Z12
Z40
Z13
Z15
M
F-a Z1 Z24 Z22 Z4 Z30 Z18 Z23 Z6 Z7 Z19 Z2 Z14 Z16 Z9 Z26 Z27
Z34 Z21
Z37
Z31
Z8
Z36
Z35
Z5
Z32
Z17 Z20 Z39 Z38
Z10
Z3
Z11
Z12 Z13
Microgrid 2T2Z68 Z55 M
FB-a
F-b Z41 Z64 Z62 Z44 Z70 Z58 Z63 Z46 Z47 Z59 Z42 Z54 Z56 Z49 Z66 Z67
Z71
Z48
Z75
Z45
Z69
Z57 Z60
Z65
Z79 Z78
Z50
Z43
Z73
Z52
Z80T1
T3FB-b
Z74 Z61
Z77
Z76 Z72 Z51 Z53
F Z94 Z106 Z107
Z111
Z88
Z116Z115
Z85
Z109
Z97 Z100
Z105
Z119 Z118
Z90
Z83
Z113
Z93
Microgrid 3
T3
T7
T6
Sub-Transmission
Z108 Z95
MS
F-c Z81 Z104 Z102 Z84 Z110 Z98 Z103 Z86 Z87 Z99 Z82 Z94 Z96 Z89 Z106 Z107
Z114 Z101
Z117
Z85
Z112
Z90
Z91Z92
Z120
Z149 Z145 Z153
T4T5
Node
Z148 Z135
FB-c
F-d Z121 Z144 Z142 Z124 Z150 Z138 Z143 Z126 Z127 Z139 Z122 Z134 Z136 Z129 Z146 Z147
Z154 Z141
Z151
Z128
Z155
Z156
Z125
Z152
Z137 Z140 Z159 Z158
Z130
Z123
Z131Z132Z160
Z133Microgrid 4
M
FB-d
Z157
Voltage Regulator Tie/Microgrid SwitchF-a Feeder Id Sectionalizing Switch M MicrogridLoad Zone Feeder Breaker
Example19
Example• A fault occurs at zone Z43A fault occurs at zone Z43
F-a Z1 Z24 Z22 Z4 Z30 Z18 Z23 Z6 Z7 Z19 Z2 Z14 Z16 Z9 Z26 Z27
Z31
Z8
Z35
Z5
Z29
Z17 Z20
Z25
Z28
Z39
Microgrid 1
Z38
Z10
Z3
Z33
Z12
Z40
Z13
Z15
M
FB
Z34 Z21
Z37
Z36 Z32 Z11
F b
Z71 Z75
Z69
Z57 Z60
Z65
Z79 Z78
Z50
Z43
Z73
Z52
Z80
Microgrid 2
T1
T2Z68 Z55 M
FB-a
Restoration Scheme•Close: 73-Microgrid 2F-b Z41 Z64 Z62 Z44 Z70 Z58 Z63 Z46 Z47 Z59 Z42 Z54 Z56 Z49 Z66 Z67
Z74 Z61
Z77
Z48
Z76
Z45
Z72
Z50
Z51 Z53
Z111 Z116Z115
Z109
Z97 Z100
Z105
Z119 Z118 Z83
Z113
Z93
Microgrid 3
T3
T7
T6
Sub-
Z108 Z95
MS
FB-b
Close: 73 Microgrid 2
• Without Microgrid 2F-c Z81 Z104 Z102 Z84 Z110 Z98 Z103 Z86 Z87 Z99 Z82 Z94 Z96 Z89 Z106 Z107
Z114 Z101
Z117
Z111
Z88
Z115
Z85
Z112
Z97 Z100 Z119 Z118
Z90
Z83
Z91Z92
Z120
Z93
Z149 Z145 Z153
T4T5
Sub-Transmission
Node
Z148 Z135
FB-c
• Without Microgrid 2,zone Z73 cannot berestored!
F-d Z121 Z144 Z142 Z124 Z150 Z138 Z143 Z126 Z127 Z139 Z122 Z134 Z136 Z129 Z146 Z147
Z154 Z141
Z157
Z151
Z128
Z155
Z156
Z125
Z152
Z137 Z140 Z159 Z158
Z130
Z123
Z131Z132Z160
Z133Microgrid 4
M
FB-d
Voltage Regulator Tie/Microgrid SwitchF-a Feeder Id Sectionalizing Switch M MicrogridLoad Zone Feeder Breaker
Restoration with/without Microgrids20
Restoration with/without Microgrids• Microgrid Enhance Restoration CapabilityMicrogrid Enhance Restoration Capability
– Using the capability of microgrids to pick up more interrupted load (Scenario 1 & 2)( )
– Microgrids reduce the number of switching operations during restoration (Scenario 3)
Scenario # Fault Location Switching Operations without Microgrids Switching Operations with Microgrids
1 Zone Z43 ‐‐‐ Close: 73‐Microgrid2
2 Zone Z139
Open: 46‐47, 96‐89Close: 136‐120, 53‐96, 45‐90
Partial Restoration, 315.04 kVA load should be shed at F‐b
Open:50‐43, 90‐92Close: 45‐90, 73‐Microgrid2,
136‐120
3 Zone Z23Open: 49‐50, 90‐92
Close: 78‐9, 53‐96, 136‐120Close: 39‐Microgrid1
Improvement in Reliability21
Improvement in Reliability
• SAIDI, SAIFI and Outage Cost are calculated. *Index Without Microgrids With Microgrids ImprovementIndex Without Microgrids With Microgrids Improvement
SAIDI(minute/year) 196.54 182.64 7.07%
SAIFI (/year) 0.7800 0.7800 0 % **
Outage Cost 3729 8 3426 5 8 13%g(k$/year) 3729.8 3426.5 8.13%
* Assume that the permanent failure rate for each zone is 0.02, the mean ti t t ( l) it h i 90 i t d th t f ttime to operate a (manual) switch is 90 minutes, and the cost for outage load is $1 per kW per minute, respectively.** In order to improve SAIFI, remote-controlled ability should be added.
Differences Between Typical Outages and
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Differences Between Typical Outages and Catastrophic Outages Due to Extreme Events
Typical Outages Catastrophic Outages
• Single fault: In most cases, there is only f l d
• Multiple faults: Multiple electrical f ili i d done faulted component.
• Small amount of load and a small number of customers are involved.
facilities are damaged.
• Large amount of load and a large number of customers are out of
• Power is available: Most power so rces are orking and sta connected
services.
• Lack of power: Power sources can not access the load or are o t of ser icesources are working and stay connected.
• T&D network remains intact: Outage loads are easily connected to sources.
access the load or are out of service.
• T&D network damaged: Overhead lines, transformers, substations are
• Easy to repair and restore
damaged.
• Difficult to repair and restore
Further InformationFurther InformationY X C C Li H G ”R li bili A l i f Di ib i S C id i S i• Y. Xu, C. C. Liu, H. Gao,”Reliability Analysis of Distribution Systems Considering Service Restoration,” IEEE PES ISGT, Feb. 2015.
• J. Li, X. Y. Ma, C. C. Liu, K. Schneider, “Distribution System Restoration with Microgrigd Using Spanning Tree Search “ IEEE Trans Power Systems Nov 2014 pp 3021‐3029Using Spanning Tree Search, IEEE Trans. Power Systems, Nov. 2014, pp. 3021‐3029.
• S. I. Lim, S. J. Lee, M. S. Choi, D. J. Lim, and B. N. Ha, “Service Restoration Methodology for Multiple Fault Case in Distribution Systems,” IEEE Trans. Power Systems, Nov. 2006.
• S. J. Lee, S. I. Lim, B. S. Ann, “Service Restoration of Primary Distribution Systems Based onS. J. Lee, S. I. Lim, B. S. Ann, Service Restoration of Primary Distribution Systems Based on Fuzzy Evaluation of Multi‐Criteria,” IEEE Trans. Power Systems, Aug. 1998, pp. 1156‐1163.
• M. S. Tsai, C. C. Liu, V. N. Mesa and R. Hartwell, "IOPADS (Intelligent Operational Planning Aid for Distribution Systems)," IEEE Trans. Power Delivery, July 1993, pp. 1562‐1569.
• C. C. Liu, S. J. Lee and K. Vu, "Loss Minimization of Distribution Feeders: Optimality and Algorithms" IEEE Trans. Power Delivery, April 1989, pp. 1281‐1289.
• C.C. Liu, S.J. Lee, S.S. Venkata, “An Expert System Operational Aid for Restoration and Loss Reduction of Distribution Systems” IEEE Trans. Power Systems, May 1988, pp. 619‐626.