web based online adequacy reliability information system ... · reliability information system for...
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Web Based Online Adequacy Reliability Information System for
Power Systems Including Intermittent Resource Generators
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IEEE PES GM2014July 27~31, 2014
Gaylord National Resort & Convention CenterNational Harbor, MD, USA
Dr. Jaeseok Choi, Dept. of Electrical Eng.
Gyeongsang National University, Jinju, GN, Korea
Adequacy of Power Systems with Renewable Energy Sources (panel session) Thursday, 31 July, 2014 8:00 AM-12:00 PM National Harbor 8
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I. IntroductionØ Web Based Online Real-time Reliability Integrated Information System is asked
rapidly for more efficiency and demand response in recent.
Ø Specially, the utilization of renewable resources has been receiving considerableattention in recent years. Furthermore, this system is more important forimplementing the smart grid.
Ø This paper describes a Web Based Online Real-time Reliability IntegratedInformation System, which is called as WORRIS v7.0 developed in this study.
Ø Grid constrained reliability evaluation is very important for grid expansion planningand operation when WTGs are added in a power system.
Ø In this paper, a new methodology for grid constrained probabilistic reliabilityevaluation of power systems including WTG is proposed.
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1. Eventual purpose diagram of WORRIS of power system and demand response
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2. Kinds of Uncertainties in Power Systems
u Aleatory uncertainty: Outage of Unit (Ex, Outage of Generator,Lines..)
u Epistemic uncertainty: Uncertainty of Information(Ex, Forecast of Load, Supply of Resources) [11,12].
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3. What is the relationship between uncertainties and flexibility in the new future power system?
V2G+/-
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4. Probabilistic Reliability Indices
1. Loss of Load Expectation (LOLE)• DLOLE [days/yr] • HLOLE [hours/yr]2. Expected Unserved Energy (EUE) or Expected Energy Not
Supplied (EENS)• EUE or EENS [MWh/yr]3. Frequency and Duration of Capacity Shortage Events
(F&D).4. Energy Index of Reliability (EIR)• EIR = 1- EENS/Total Demand Energy
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5. Power System Reliability Concept In New Era
Supply
Demand
Uncertainties: - Unit Outage- Resources Supply of REG- Supply of HEN - Supply from V2G etc.
Uncertainties: - Load forecasting - Demand Response- Charging of V2G etc.
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II. The Multi-state Operation Model of WTG
*This picture is HWN-WF in Jeju
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Power output [MW]
RV coVciV Wind Velocity
RP
Where, Vin: the cut-in speed [m/sec].VR: the rated speed [m/sec].Vco: the cut-out speed [m/sec].PR: the rated power [MW].
Pi = 0 0≤SWbi<Vci
= PR (A+BxSWbi+CxSWbi2) Vci≤SWbi<VR
= PR VR≤SWbi≤Vco
= 0 SWbi>Vco
( )( ) ( )
3
2V + V1
A = V V + V - 4 V V 2VV - V
ci Rci ci ciR R
Rci R
é ùæ öê úç ÷
è øê úë û
( )( ) ( )
3
2V + V1
B = 4 V + V - 3V + V2VV - V
ci Rci ciR R
Rci R
é ùæ öê úç ÷
è øê úë û
( )
3
2V + V1
C = 2 - 4 2VV - V
ci R
Rci R
é ùæ öê úç ÷
è øê úë û
* A,B,C parameters
A typical power output model of WTG
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Windvelocity[m/sec]
Power output [MW]
RV coVciV
RP
Windvelocity[m/sec]
Power
Probability
pdf Table of WTG multi-state model
Power ProbabilityP1P2···
Pn
PB1PB2
···
PBn
The outage capacity pdf of WTG
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11*This picture is SSN-WF in Jeju
III. Reliability Evaluation of A Composite Power System including
Intermittent Generator, WTG
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Lx Lx
ojx
Effective Load- HLI
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IC : total installed generating capacity [MW] Lp : system peak load[MW]Ä: operator meaning convolution integralHLIΦ0(xe - xoi)= HLIΦ(xL )HLIfoi(xoi): the probability distribution function of outage capacity of generator #i
1
1
( ) ( ) ( )
( ) ( )
HLI i e HLI i e HLI oi oi
HLI i e oi HLI oi oi
x x f x
x x f x dx
-
-
F = F Ä
= F -ò
The effective load duration curve (ELDC), HLIΦ(x)
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Reliability indices of LOLEHLI(Loss of load expectation) and EENSHLI(Expected energy not served)
[hours/yr]
[MWh/yr]
IC : total installed generating capacity [MW]
Lp : system peak load [MW]
ICxHLIHLI )x(LOLE=
= F
ò+
=LpIC
IC HLIHLI dx)x(EENS F
Reliability Evaluation at HLI including WTG
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k Lx2 2, tCT q
, i tiCT q
, NT tNTCT q
1 1, tCT q
)( ojosik xf
Lk x Lk xLk xLk x
Lk x
å1
1
ik
ikqAP
2
2
ik
ikqAP
ijk
ijk
qAP
iNSk
iNSkqAP
sijk
sijk
qAP
k Lx
k oNGjx k NGj
k NGj
APq
ìïíïî
2 2, 0tCT q =
, 0i tiCT q =
, 0NT tNTCT q =
1 1, 0tCT q =
(a) Actual system
(b) Synthesized fictitious equivalent generator
(c) Equivalent system
Composite power system effective load model at HLII (CMELDC)
7) J. Choi, R. Billinton, M. Futuhi-Firuzabed,"Development of A Nodal Effective Load ModelConsidering Transmission System ElementUnavailabilities" IEE. G.T&D, pp.79-89, Vol.152, No.1,Jan. 2005.
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Ä : the operator representing the convolution integral
kF0 = original load duration curve at load point #k
Kfosi : outage capacity pdf of the synthesized fictitious generator created by generators 1 to i, at load point #k.
( ) ( ) ( )
( ) ( )
k i e k o e k osi oi
k o e oi k osi oi oi
x x f x
x x f x dx
F = F Ä
= F -ò
CMELDC at HLII including WTG
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[hours/yr]
[MWh/yr]
EIRk= 1-EENSk/DENGk [PU]
Lpk: peak load at load point k [MW]
APk: maximum arrival power at load point k [MW]DENGk : demand energy at bus #k
kAPxNGkk )x(LOLE=
= F
ò+
= kk
k
LpAP
AP NGkk dx)x(EENS F
Bus(Nodal) Reliability Evaluation at HLII including WTG
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[MWh/yr]
[MW/cur.yr]
[hours/yr]
EIRHLII= 1-EENSHLII/DENGHLII [PU]
NL : number of load pointsELCk= EENSk/LOLEkEIR : Energy Index of Reliability
/HLII HLII HLIILOLE EENS ELC=
1
NL
HLII kk
EENS EENS=
= å
1
NL
HLII kk
ELC ELC=
= å
Reliability indices of the bulk system
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Expected Deterministic Reliability Indices of Bulk System
[%] 100)(
[%] 100
[%] 100
´-
=
´-
=
´-
=
Pt
Pt
Pd
Pdd
Py
Pyy
LLtEOPEORR
LLSCESRR
LLTIC
EIRR
EIRR : Expected Installed Reserve RateESRR : Expected Supply Reserve RateEORR : Expected Operating Reserve RateLPy : Peak Load for a yearLPd : Peak Load for a dayLPt : Peak Load for ‘t’
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kk
kkdk
ii
MSkkdk
MSiid
kkyk
iiy
FORAVR
tAVRtWTGtCGtEOP
AVRWTGCGSC
AVRWTGCGTIC
-=
´+=
´+=
´+=
åå
åå
åå
ÎÎ
ÎÎ
ÎÎ
1
)()()()(21
21
21
xx
rr
rr
TICy : Total Install Capacity for a yearSCd : Supply Capacity for a dayEOP(t) : Expected Operating Power for ‘t’CGi : Capacity of i time Conventional Generator WTGk : Capacity of i time Wind Turbine Generator AVRk :
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The step-by-step process for evaluating the reliability of a power system involving WTGs
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IV. Case Studies
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A map of Jeju Island
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Wind Speed around KoreaWind speed at surrounding of Jeju island
* Total W/P 249.1MW construction is submitted by IPP at Jeju island until 2012.
Wind around South Korea and Jeju Island
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Power System of Jeju Island
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Load variation curve patterns for a normal day at the load buses
0
20
40
60
80
100
120
140
160
180
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Time[hour]
Loa
d[M
W]
Bus 2 Bus 3 Bus 7 Bus 8 Bus 9 Bus 4 Bus 11
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Bus number
Unit Name Type C[MW] No. FOR
10 HWN1 WTG 50 1 -
9 SSN2 WTG 30 1 -
4 HLM3 WTG 20 1 -
1 HVDC HVDC 150 2 0.0285 NMJ1 T/P 100 2 0.0121 JJU1 T/P 75 1 0.0151 JJU2 T/P 75 1 0.012
1 HNM1 C/C 105 1 0.013
1 JJU3 G/T 55 1 0.013
1 JJU4 D/P 10 4 0.0185 NMJ2 D/P 20 2 0.018
Total 990 17 -
Line # SB EB Capacity Type cct FOR
1 1 2 300 T/L 2 0.001713
2 1 2 200 C/L 2 0.001000
3 2 3 200 T/L 2 0.005710
4 3 4 200 T/L 1 0.001142
5 4 6 200 T/L 1 0.001142
6 3 6 200 T/L 1 0.001142
7 6 7 200 T/L 1 0.001142
8 5 6 226 C/L 2 0.001000
9 7 8 200 T/L 1 0.005710
10 6 8 200 T/L 1 0.001142
11 8 9 200 T/L 1 0.004568
12 8 1 200 T/L 1 0.001142
13 1 10 200 T/L 1 0.004568
14 10 9 200 T/L 1 0.001142
15 2 11 220 C/L 1 0.001000
The system’s generation capacity = 990MWLoad peak = 681MW
Generators and Transmission System Dataof Jeju Power System (2012 year)
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HWN-WF SSN-WF HLM-WF
A 0.1203 0.1111 0.0928
B -0.06 [m/sec]-1 -0.063[m/sec]-1 -0.0649[m/sec]-1
C 0.0072 [m/sec]-2 0.0081[m/sec]-2 0.0093[m/sec]-2
Wind DataWind farm HWN-WF SSN-WF HLM-WF
Peak speed 45 m/s 40 m/s 35 m/s
Mean wind speed 8.5 m/s 7.6 m/s 6.4 m/s
Standard deviation 7 m/s 6 m/s 5 m/s
WTG DataWTG capacity 50MW 30MW 20MW
Cut-in speed(Vci) 5 m/s 5 m/s 5 m/s
Rated speed(VR) 16 m/s 15 m/s 14 m/s
Cut-out speed(Vco) 25 m/s 25 m/s 25 m/s
Data of HWN, SSN and HLM wind farms
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OCPDF of HWN wind farm (11-state model)
OCPDF of SSN wind farm (7-state model) OCPDF of HLM wind farm (5-state model)
The outage capacity probability distribution function (OCPDF)
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Reliability Indices at Buses of Jeju System
Grid not constrained Case Grid constrained CaseLOLE [10-
3hours/day] 3.452 19.532
EENS [MWh/day] 0.121973 12.092548EIR [pu] 0.99999 0.999189
System Reliability Indices of Jeju System
Load Point # Load Name Lp
LOLEk[hours/day]
EENSk[MWh/day]
EIRk[pu]
1 JEJU 200 0.019294 3.282110 0.999196
2 SIJU 230 0.019624 3.823397 0.999186
3 SEGP 100 0.019623 1.662342 0.999186
4 HALA 50 0.019620 0.831175 0.999186
5 SUSN 30 0.019616 0.498704 0.999186
6 HALM 20 0.019607 0.332482 0.999186
7 SAJI 100 0.019623 1.662342 0.999186
Results
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V. A Web based Online Real-time Reliability Integrated Information
System(WORRIS)http://worris.gsnu.ac.kr
*This picture is HWN-WF in Jeju
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http://worris.gsnu.ac.kr
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1. Project pane : Control parameters
1. Execution pane : Three buttons
3. Generator data pane :The characteristic data of each
generator
4. Transmission line list pane :The transmission line data
5. Load Information pane : The load information
1. WORRIS CmRelWin Interface
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The WORRIS PRI results for the Jeju power system
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The WORRIS PRI results for the Jeju city
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The WORRIS PRI results for the Seguipo city
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2. WORRIS PraWin Interface
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The WORRIS PRI results from PraWin
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The WORRIS DRI results from PraWin
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• TOC on Smart Grid Test Bed Town in Jeju
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ž This paper presents a new approach for grid constrained probabilistic reliabilityevaluation of power systems including wind turbine generators using thecomposite power system effective load model developed by the authors
ž It is expected that the proposed method can provide useful information indetermining the location of WTGs in view of composite power system reliability.
ž This paper also describes a Web Based Online Real-time Reliability IntegratedInformation System called WORRIS Version 7.0.
ž The results indicate how a web-based monitoring system could form the basisfor customers to observe power system reliability information including windturbine generators.
ž The present intent is not to create a real time reliability information system butto focus on developing a one day ahead system.
VI. Conclusions
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1) Nick Jenkins, Ron Allan, Peter Crossley, David Kirschen, Goran Strbac, “Embedded Generation”, pp. 31-38, 2000.
2) Rajesh Karki, Po Hu, Roy Billinton,“A Simplified Wind Power Generation Model for Reliability Evaluation”, IEEE Transactions on Energy Conversion, Vol.21, No.2, June 2006.
3) Singh, Lago-Gonzalez, “Reliability Modeling of Generation Systems Including Unconventional Energy Sources,” IEEE Transactions on Power Apparatus and Systems, Vol. PAS-104, No.5, May 1985.
4) Billinton, R., Gan, L, “Wind Power Modeling and Application in Generating Adequacy Assessment,” Proceedings, the 14th Power Systems Computation Conference, Sevilla, Spain, June24-28,2000.
5) Liang Wu, Jeongje Park, Jaeseok Choi, A. A. El-Keib, Mohammad Shahidehpour, and Roy Billinton, “Probabilistic Reliability Evaluation of Power Systems Including Wind Turbine Generators Using a Simplified Multi-State Model: A Case Study” IEEE, PES, GM2009, July 26-30, Calgary, 2009.
6) Jaeseok Choi, Hongsik Kim, Junmin Cha and Roy Billinton; "Nodal Probabilistic Congestion and Reliability Evaluation of a Transmission System under Deregulated Electricity Market", proc. of conference, Vancouver, Canada, IEEE, PES, SM2001, July 16-19, 2001.
7) J. Choi, R. Billinton and M. Futuhi-Firuzabed “Development of a New Nodal Effective Load Model Considering Transmission System Element Unavailabilities” to be published by IEE proceedings on GTD, 2005.
8) Roy Billinton, Wenyuan Li, “Reliability Assessment of Electric Power Systems Using Monte Carlo Methods", pp.24-30, 1994.
9) Roy Billinton and Wenyuan Li, Reliability Assessment of Electric Power Systems Using Monte Carlo Methods :Plenum Press,1994.
10) Roy Billinton and Ronald N. Allan, Reliability Evaluation of Power Systems: Second Edition, Plenum Press, 1996.
11) Jaeseok Choi, Timothy Mount, Robert Thomas and Roy Billinton, "Probabilistic Reliability Criterion for Planning Transmission System Expansions" IEEG,T&D, Vol.153, No.6, pp.719-727, November, 2006
References