BIG WIND STUDY

Resource Adequacy Technical Committee MeetingApril 6, 2011

April 6, 2011 2

Purpose of Study1. Estimate the Effective Load Carrying

Capability (ELCC) for NW wind turbines2. Quantify the relationship between

installed wind generation and light-load-hour overgeneration

3. Examine the effects of wind generation on thermal resource dispatch

April 6, 2011 3

Caveats Results are not for distribution BiOp data needs updating (again!) Still working on hydro shaping logic in

GENESYS Used constant DEC requirements for all

studies Ran limited number of games with

sequential hydro, lockstep temperature and random wind

April 6, 2011 4

Wind ELCC Assumptions 2015 operating year Existing resources Expected new conservation (short-term model) Ran Dec-Feb and Jul-Sep only Base case

Removed all wind Calculated total annual average curtailment per game

Study cases Added 200 MWa of shaped load Added increments of wind capacity until the total annual

average curtailment per game equaled that in the base Repeated above with greater amounts of load

April 6, 2011 5

Wind ELCC Results (200 MWa)

15% 20% 25% 30% 35% 40% 45%1200000

1250000

1300000

1350000

1400000

Average Load/Wind Capacity (%)

Tota

l Avg

Cur

tailm

ent

(MW

-hr

s)

Base Case

200 MWa Load, 500 MW Wind

200 MWa Load, 1000 MW Wind

ELCC = 26.4%

April 6, 2011 6

Wind ELCC ResultsAverage Inc

Load Inc (MWa) Wind Inc (MW) ELCC (%) ELCC (%)200 759 26.4 26.4400 1746 22.9 19.5600 2762 21.7 17.0800 3963 20.2 14.0

1000 5746 17.4 8.41200 7939 15.1 3.9

April 6, 2011 7

Wind ELCC Results

0 1000 2000 3000 4000 5000 6000 7000 8000 90000%

5%

10%

15%

20%

25%

30%

Average

Installed Wind Capacity (MW)

Win

d EL

CC (%

)

Current NW WindAbout 3100 MW

April 6, 2011 8

Overgeneration Study Assumptions

210 games, sequential hydro, lockstep thermal and random wind (screening studies)

2015 regional loads Existing resources 2015 Power Plan conservation (1,200

MWa) No thermal ramping logic (results in lower

overgeneration values) Wind was added with no additional load

April 6, 2011 9

0 1 2 3 4 5 6 7 8 90

200

400

600

800

1000

1200

1400

1600

1800

2000

Jul

Jun

May

Apr

Mar

Feb

Average Overgeneration Energy by Month

Installed Wind (GW)

Ove

rgen

erat

ion

(GW

-HR

S)

April 6, 2011 10

0 1 2 3 4 5 6 7 8 90

500

1000

1500

2000

2500

3000

Jul

Jun

May

Apr

Mar

Feb

Overgeneration in Average Megawatts(averaged over all hours of the month)

Installed Wind (GW)

Ove

rgen

erat

ion

(MW

a)

April 6, 2011 11

0 1 2 3 4 5 6 7 8 90

2000

4000

6000

8000

10000

12000

14000

Sep

Aug

Jul

Jun

May

Apr

Mar

Feb

Jan

Dec, OctNov

Highest Hour Overgeneration by Month

Installed Wind (GW)

Ove

rgen

erat

ion

(MW

-HR

S)

April 6, 2011 12

Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep0

50

100

150

200

250

300

350

400

450

Average Monthly DispatchBoardman

030006000

MW

a

Wind

April 6, 2011 13

1 41 81 1211612012412813213614014414815215616016416817210

5000

10000

15000

20000

25000

Aggregate Hourly Dispatch for MayNo Wind Case

DemandCurtThermalPurchHydroWind

Hour of Month

Meg

awat

ts

April 6, 2011 14

1 41 81 121161201241281321361401441481521561601641681721-5000

0

5000

10000

15000

20000

25000

Aggregate Hourly Dispatch for May3000 MW Wind Case

DemandCurtThermalPurchHydroWind

Hour of Month

Meg

awat

ts

April 6, 2011 15

1 41 81 121161201241281321361401441481521561601641681721-5000

0

5000

10000

15000

20000

25000

Aggregate Hourly Dispatch for May6000 MW Wind Case

DemandCurtThermalPurchHydroWind

Hour of Month

Meg

awat

ts

April 6, 2011 16

Next Steps Update BiOp data For overgeneration study, run scenarios

with no thermal cycling – to assess worst case magnitude

Continue to review hydro shaping logic Explore adding ramping logic for thermals