Modelling large-scale wind penetration in New Zealand with Plexos Magnus Hindsberger EPOC winter...
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Transcript of Modelling large-scale wind penetration in New Zealand with Plexos Magnus Hindsberger EPOC winter...
Modelling large-scale wind penetration in New Zealand
with Plexos
Magnus Hindsberger
EPOC winter workshopAuckland, 5 September 2008
Outline
• Background• Plexos model• Wind output series• Reserve requirements• Model results • Interaction with plug-in hybrid electric vehicles• Future work
Wind power integration in New Zealand- a scenario analysis of 15-25 % wind power in the electricity market in 2025
Iben Moll Rasmussen
Mikkel Windolf
Background of analysis
• Current wind capacity: 321 MW• Current projects: ~ 6000 MW
• Need to understand:– Wind variability issues, such as reserve
requirements, grid flows and market price impacts
– Interaction with electric vehicles, including charging on a day to day basis
• Developed by Drayton Analytics, now Energy Exemplar
• PLEXOS 4.0 released in 2000. Plexos 5.0 appeared 2008
• Co-optimization engine based on PhD thesis of Glenn Drayton (University of Canterbury, 1997)
• PLEXOS licensed in 17+ countries worldwide
• PLEXOS consists of 4 main modules:– LT-Plan
– PASA
– MT-Plan
– ST-Plan
Plexos model overview
MS Access
Wind data• Starting point:
– 1 wind farm output series, 2004+– 1 wind speed series measured at 70 m, 2005+– 1 wind speed series measured from the top of a
building, 2005-2007
• For the first model, 3 regional series were used based on the data above.
• Newly obtained:– Multiple 10 m. data series from around NZ– 3 data series from Belmont Regional park
Wind power modelling in Plexos
Method:• Point measurement
to wind farm or regional output
• Generic power curve– Mix of Vestas and
Siemens turbines
30 wind speed time series
Wind output series
Exp. regional utilisation time
Scaled wind output series
Plexos input filesReal wind farm output
Verification
Wind farm output
• Method to go from point estimates to wind farm/region output
Estimating smoothing
Belmont Regional Park sites:• Tower 21 30 m.• Tower 66A 44 m.• Tower 75: 42 m.
Distances [km]
Tower 21 & Tower 66A
6
Tower 21 & Tower 75
3
Tower 66A & Tower 75
4
Large wind farm/groups of wind farms(app. 6 km2)
-4,00 -2,00 0,00 2,00 4,000%
10%
20%
30%
Per
cen
t
m/s
Wind series
Data from NIWA: 2005-2007, typically measured at 10 m.
Achievements
• 1 hour resolution allowing short-term issues to be analysed.
• Using historical data where good records are available, limit our number of wind series compared with using synthetic data.
• But it provides the following benefits:– Regional correlation is kept– Correlation with demand is kept (if same demand year
is used)
• Much better than our previous data
Reserves modelling
• Most simple model is persistence forecast:
– Wind(T+1) = Wind(T)
• May be too simple as not taking into account point on power output curve
Reserves modelling
+400 MW- 600 MW
Typically harder to predict timing of a change than the magnitude of the change as shown below (Western Denmark case)
Reserves modellingWind farm 1
0
2
4
6
8
10
1 2 3 4 5 6 7 8 9 10
Hour
MW
Production
Production T+1
Production T-1
Reserves
Wind farm 2
0
2
4
6
8
10
1 2 3 4 5 6 7 8 9 10
Hour
MW
Production
Production T+1
Production T-1
Reserves
Final reserves combined wind farms
0
2
4
6
8
1 2 3 4 5 6 7 8 9 10
Hour
MW
20% ofProduction
Reservescombined
Final Reserves
Combined wind farms
0
5
10
15
1 2 3 4 5 6 7 8 9 10
Hour
MW
ProductioncombinedProduction T+1
Production T-1
ReservescombinedReserves farm1+2
One has to be created per island and per year of wind data
Reserves modelling
• Wind risk is in addition to normal reserves as set by risk-setting unit:– Reservest = LargestRiskt + WindRiskt
• For this analysis, we fixed largest risk to North Island CCGT and South Island generator at Clyde.
• Will create a separate reserve market in Plexos in the future and go back to dynamic risk for the generators/HVDC.
Wind scenarios
North I sland Reference Compact Wind Disperse Wind 25 % WindNorthland & North Shore 299 320 570Auckland 40 40Bay of PlentyLower Waikato & Waikato 228 228Taranaki 100 100 110Hawkes Bay 102 147 388 388Central/Manawatu 356 854 401 631Wellington 213 323 323 644SUM North I sland 1070 1324 1800 2611
South I sland Reference Compact Wind Disperse Wind 25 % WindNelson/Marlborough 50 300West Coast 63 63Christchurch 163 363Waitaki ValleyOtago, Southland & Fiordland 258 1160 408 728SUM South I sland 258 1160 684 1454
SUM North + South I sland 1328 2484 2484 4065
I nstalled MW in 2025
90 % renewables
Wind energy share ~10% ~15% ~15% ~25%
Expected results
• Increased wind penetration will lead to:– Less efficient thermal generation– Higher reserve costs– Higher costs for peaking capacity– Higher transmission costs
• Dispersed wind will lead to lower costs than a concentrated wind development
• Market prices may be lowered significantly
Not analysed
Results - reservesNorth Island 2025
0%
10%
20%
30%
40%
50%
60%
0 1000 2000 3000 4000 5000 6000 7000 8000 9000
Per
cent of in
stal
led cap
acity Compact Wind
(Persistence)
Compact Wind(Accurate)
Disperse Wind(Persistence)
Disperse Wind(Accurate)
South Island 2025
0%
10%
20%
30%
40%
50%
60%
0 1000 2000 3000 4000 5000 6000 7000 8000 9000
Perc
ent o
f in
stal
led
capa
city Compact Wind
(Persistence)
Compact Wind(Accurate)
Disperse Wind(Persistence)
Disperse Wind(Accurate)
Costs ($mill)
Accurate forecast
Persistence
forecast
Compact Wind
33 285
Disperse Wind
23 356
Costs of reserves for persistence forecast vs. a more accurate forecast
Same max capacity, but high difference in costs
Clear diversification benefit
Results - Transmission
Losses (GWh) Reference Compact Wind Disperse Wind 25% WindNorth Island 963 1,434 1,138 1,902South Island 671 839 664 745SUM 1,633 2,274 1,802 2,646
Hours Congested Reference Compact Wind DisperseWind 25% WindNorth Island 1215 9384 7825 26664South Island 23 136 98 186HVDC 38 454 201 2142SUM 1276 9974 8124 28992
Transmission losses
Transmission congestion
More (compact) wind appear to lead to higher transmission related costs
Results - Generation
05
1015202530354045505560
Reference Compact Wind Disperse Wind 25% Wind IEA NZ 2006
ReviewScenario
Yea
rly G
ener
atio
n in 2
025
[TW
h]
Wind
Thermal
Hydro
Geothermal
Cogen
Generation share in 2025 (normal inflow year)
Little non-zero SRMC capacity
Wind impact on prices
• Wind revenue vs. average revenue in Western Denmark, ~20% wind (annual energy) and export capability
20%
30%
40%
50%
60%
70%
80%
90%
100%
110%
120%
2000
-01
2000
-07
2001
-01
2001
-07
2002
-01
2002
-07
2003
-01
2003
-07
2004
-01
2004
-07
2005
-01
2005
-07
2006
-01
2006
-07
2007
-01
2007
-07R
even
ue
(gen
erat
ion
wei
gh
ted
) o
f w
ind
po
wer
Results – Market pricesCompact Wind 2025 North Island
y = -0.0184x + 95.496
0
50
100
150
200
250
300
0 400 800 1200 1600 2000 2400
Wind Generation [MW]
Pric
e N
I [$
/MW
h]
Disperse Wind 2025 North Island
y = -0.013x + 101
0
50
100
150
200
250
300
0 400 800 1200 1600 2000 2400
Wind Generation [MW]
Pri
ce N
I [$
/MW
h]
25% Wind 2025 North Island
y = -0.0097x + 72.176
0
50
100
150
200
250
300
0 400 800 1200 1600 2000 2400
Wind Generation [MW]
Pri
ce N
I [$
/MW
h]
Wind spill (GWh) Reference Compact wind Disperse Wind 25% windNorth Island 2 85 11 232South Island 56 219 56 273SUM 58 304 68 505
25% wind scenario lower price significantly when generation is high
Also impact on wind spill
National costs assessment
Cheaper
Total modelled costs, 2025 ($mill) Reference Compact Wind Disperse Wind 25% Wind
Generation costs (fuel + VOM) 995 788 763 426
Emission costs (CO2) 317 201 194 110
Reserve costs 14 33 23 37
SUM 1,326 1,022 980 573
Difference to reference 0 -304 -346 -753
Cheaper
Total modelled costs, 2025 ($mill) Reference Compact Wind Disperse Wind 25% Wind
Modelled costs 1326 1022 980 573
Account for extra wind FOM 0 45 45 107
Account for extra wind CAPEX (annuity) 0 283 283 671
Total 1326 1351 1309 1351
Difference to reference 0 25 -17 25
Interaction with Plug-in Hybrid Electric Vehicles (PHEV)
Why of interest
• Due to the large potential for renewable electricity
generation in NZ, PHEV’s and later on EV’s are
likely in larger scale.
• This will affect the power system as:– Energy demand will be bigger– Load duration curve will change (charging)– They may provide reserve capacity (V2G)– They may be used for peak shifting (V2G)
• They will also improve the revenue of wind
Modelling in Plexos
• Daily energy requirement (per region)– Based on vehicle forecast and daily distance travelled– Currently free to choose time of recharge
• Max capacity (offtake or delivered) based on assumptions on recharge on standard household installations (220 V – 14 Amps)
• Cut-off price if petrol is cheaper, can be an issue during dry years. A $2/L petrol price was used.
PHEV recharging example
0
200
400
600
800
0 2 4 6 8 10 12 14 16 18 20 22
Hour 18-06-2025
MW
0
50
100
150
200
250
$/M
Wh
PHEV Load Wind Generation Price
PHEV price paid & cost savings
Price ($/MWh) / Cost savings ($ p.a.)
Average price paid by the PHEV’s
[$/MWh]
Annual cost savings per PHEV with a
petrol price of 1.5 $/L [$]
Annual cost savings per PHEV with a
petrol price of 2 $/L [$]
Reference 93-106 344-382 563-600
Compact Wind 62-83 401-465 620-684
Disperse Wind 72-88 393-428 612-647
25 % Wind 33-45 509-542 728-760
Potential wholesale price increase and thus extra wind generator revenue (less subsidy) yet to be analysed
It was previously shown that more wind power led to lower prices.
PHEV impact on prices
Disperse Wind 2025 North Island
y = -0.013x + 101
0
50
100
150
200
250
300
0 400 800 1200 1600 2000 2400
Wind Generation [MW]
Pri
ce N
I [$
/MW
h]
PHEV’s may increase price in high wind generation hoursGeneration
PriceDemand
More wind
PHEV demand
Supply
Future directions
Future direction
• Internalise experience– Value of HVDC overload capacity– Wind/hydro interaction
• Competition modelling– Cournot and RSI
• Grid Development Strategy– Extend wind/PHEV work to 2050– Understand peak capacity requirement including
Demand Side Response– Wind power variability and investment decisions in LT
GDS overview
Objective: To form a long term National Grid development strategy taking into account:
– New Zealand's future social, environmental and economic requirements; and
– long-term technology trends.
Process: The GDS process is likely to take about 18 months, culminating in a final strategy in the first half of 2010.
GDS process2008 2009 2010Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar
Electricity industry scenarios
Planning criteria / assumptions
Future transmission technology development
Transmission needs assessment
Forming options
Testing options against technical and economic criteria
Formulate Grid Development Strategy
Compile documentation
Publish Grid Development Strategy 25-Mar
• Scenario work package started last Friday. RFI published with deadline 19 September.
http://www.gridnewzealand.co.nz/grid-development-strategy
Questions ?