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Outline The EU context Model description Case Study Results Results
Reserve procurement in power systems with highrenewable capacity:
How does the time framework matter?
G. Oggioni(1) R. Dominguez(2) Y. Smeers(3)
(1) University of Brescia, Italy (2) Universidad de Castilla-La Mancha, Toledo, Spain(3)CORE, Universite catholique de Louvain, Belgium
Mercati energetici e metodi quantitativi:un ponte tra Universita ed Impresa
PadovaOctober 13th, 2016
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Outline The EU context Model description Case Study Results Results
Outline
1 The European context
2 Model descriptionModel common assumptionsModel 1: joint procurement of energy and reaserveModel 2: reserve procured before day aheadModel 3: reserve procured after day ahead
3 Case Study
4 Results
5 Conclusions
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Outline The EU context Model description Case Study Results Results
Reserve procurement and RES integration
Renewable energy integration requires flexibility because of:
Uncertainty;
Variability.
The schedule of an adequate reserve level is becoming extremely importantbecause:
The increasing integration of stochastic (renewable) energy production makespower systems unstable
It guarantees security of supply and system balance in real time!
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Outline The EU context Model description Case Study Results Results
Towards the Internal European Electricity MarketThird Energy Package and Network Codes
The European Commission envisages the coordination of:
The energy day-ahead markets (Price Coupling of Regions);
The reserve procurement mechanisms;
The congestion management;
The energy balancing markets.
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Outline The EU context Model description Case Study Results Results
Goals
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Outline The EU context Model description Case Study Results Results
Our goals in this paper...
Q1: Does the time framework for reserve procurement matter?
We analyze and compare the efficiency levels of three power systems where:
1 Energy and reserves are jointly scheduled by an Independent System Operator(as in the US)
2 Reserves are scheduled before the clearing of the day-ahead energy market(as in Central European countries)
3 Reserves are schedule after the clearing of the day-ahead energy market(as in Italy, Spain, Portugal)
Q2: Does a coordinated reserve procurement increase the system efficiency?
We compare the efficiency levels of the three power systems above assuming acoordinated and not-coordinated reserve schedule.
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Outline The EU context Model description Case Study Results Results
Models
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Outline The EU context Model description Case Study Results Results
Common assumptions
Model common assumptions
Spatial granularity: nodal level both in day-ahead energy and ancillaryservice markets
Reserves: Conventional and downward/upward spinning reserves
Generating units: Stochastic (wind and solar PV) vs. dispatchable units(nuclear, coal, CCGT)
Dispatchable units
Qualified Non-qualified
Coal NuclearCCGT
Demand response: demand side management with downward/upwarddeviations in real time
Uncertainty characterization: day-ahead forecasts and real time scenarios fordemand level and renewable power availability
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Outline The EU context Model description Case Study Results Results
Model 1
Model 1: Energy and reserve needs are jointly scheduled
Model 1 is a two-stage stochastic programming problem as illustrated below:
FirstStage SecondStage
D-1(Dayahead)
ISObalancesthesystemonthebasisof
RTscenarios
ISOco-optimizestheenergyandthereserve
procurement
s1
s2
s3
D(Realtime)
Figure: Decision-making process of Model 1
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Outline The EU context Model description Case Study Results Results
Model 2
Model 2: Reserve scheduled before the day-ahead energy market
Model 2 is a three-stage stochastic programming problem as illustrated below:
FirstStage SecondStage ThirdStage
f1
PXclearstheenergymarket
TSOprocuresreserves
PXclearstheenergymarket
PXclearstheenergymarket
TSObalancesthesystemonthebasisofRTscenarios
f2
f3
S1f1S2f1
S3f1
S1f2S2f2
S3f2
S1f3
S2f3
S3f3
MODEL2
W-1(Weekahead)
D-1(Dayahead)
D(Realtime)
Figure: Decision-making process of Model 2
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Outline The EU context Model description Case Study Results Results
Model 3
Model 3: Reserve scheduled after the day-ahead energy market
Model 3 is formulated as illustrated below:
FirstStage SecondStage TSObalancesthe
systemonthebasisofRTscenarios
TSOre-dispatchesenergyandprocures
reservesPXclearstheenergymarket
s1
s2
s3
D-1(Dayahead)
D(Realtime)
D-1(Dayahead)
Figure: Decision-making process of Model 3
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Outline The EU context Model description Case Study Results Results
Case Study
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Outline The EU context Model description Case Study Results Results
Case study
Nodal network: IEEE 24-node networkwith 38 transmission lines
Capacity:
Technology Capacity (MW)
CCGT 2250Coal 700
Nuclear 900
Wind 2100Solar 750
Total 6700
Total demand (17 nodes): 3135 MW
Uncertainty: 3 day-ahead forecastsand 3 real time scenarios perday-ahead forecast
18 21 22
17
16 19 20
23
1514 13
11 1224
3 9 10
6
4
5
21 7
8
W
WCCGT
CCGT
N
PVW CCGT CCGT PV
W
CCGT
PV
W WCCGT
CO
Z2
Z1
Z3
PV
CO
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Outline The EU context Model description Case Study Results Results
Reserve procurement
Coordinated procurement: Reserve need is determined on the whole marketas a unique zone (1 zone);
Not-coordinated procurement: Reserve needs are defined at zonal level (3zones/countries).
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Outline The EU context Model description Case Study Results Results
Results
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Outline The EU context Model description Case Study Results Results
Operating costsCoordinated reserve procurement ($):
1 Zone
Model 1 Model 2 Model 3(Expected) (Expected)
Total operating costs 826,180 837,708 827,296
DA operating costs 822,345 851,960 823,532RT operating costs 3,835 -14,252 3,764
Not-coordinated reserve procurement ($):
3 Zones
Model 1 Model 2 Model 3(Expected) (Expected)
Total operating costs 834,007 843,395 5,060,361
DA operating costs 829,937 860,962 858,323DA unserved demand value - - 4,201,153RT operating costs 4,070 -17,568 884RT unserved demand value - - -
Not-coordinated reserve procurement and increased installed capacity ($):
3 Zones (Increased capacity)
Model 1 Model 2 Model 3(Expected) (Expected)
Total operating costs 772,771 775,675 776,195
DA operating costs 786,711 798,431 792,769RT operating costs -13,940 -22,756 -16,574
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Outline The EU context Model description Case Study Results Results
Conclusions
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Outline The EU context Model description Case Study Results Results
Conclusions
As expected, the market structure represented through Model 1 (one ISO)results as the most efficient market under all reserve procurementassumptions.
We also verified that the not-coordinated reserve procurement based onmultiple reliability zones leads to higher total operating costs thanconsidering the power system as a whole.
Model 3 in the coordinated reserve procurement case results almost asefficient as Model 1.
But it becomes inefficient (unserved demand) in the not-coordinated reserveprocurement because of the limits imposed on the cross-border exchanges.
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