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 ?