power supply adequacy assessment model/methodology review steering subcommittee meeting january 29,...

Power Supply Adequacy AssessmentModel/Methodology Review

Steering Subcommittee Meeting January 29, 2010

January 29, 2010 Resource Adequacy Steering Committee

2

Outline• Model Validation

– Benchmarking Process– Sample Historical vs. Simulated Dispatch

• Methodology Review– Current Adequacy Metric: LOLP– The Problem with LOLP– LOLP Subcommittee Suggestions– Next Steps


3

Model Validation• HYDSIM vs. actual monthly generation• GENESYS vs. HYDSIM hydro generation output• Hydro peaking calibration

– Trapezoidal Model/HOSS/Capacity Survey• Check random variable distributions

– Water, wind, forced outage, load/temperature• Simulated thermal dispatch vs. historical dispatch• Simulated hydro dispatch vs. historical dispatch

• Simulated dispatch vs. scheduler’s perspective


4

Monthly Generation - Boardman

0

100

200

300

400

500

600

700

1 13 25 37 49 61 73 85 97 109 121 133

Months

MW

-mo

nth

sHistorical Mean Simulated

10771104 139 104159 124 98 58 104 88 100

Runoff Volume in Blue - Avg =107

Monthly Generation - Columbia Generating

0

200

400

600

800

1000

1200

1400

1 13 25 37 49 61 73 85 97 109 121 133

Months

MW

-mo

nth

s

Historical Mean Simulated

10771104 139 104159 124 98 58 104 88 100

Runoff Volume in Blue - Avg =107


5

Genesys - February 1997

0

5000

10000

15000

20000

25000

30000

35000

40000Demand Hydro

Sample Comparison of Historical vs. Simulated Hydro Dispatch

•Hourly hydro dispatch is highly dependent on hourly load shape

•Historical and Genesys hydro load following is consistent

•Illustrative only – based on old data and F&W constraints

Historical - February 1997

0

5000

10000

15000

20000

25000

30000

35000

40000

Demand Hydro

Methodology Review

Current Adequacy Metric:LOLP


7

January 1930

-5000

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

1 27 53 79 105

131

157

183

209

235

261

287

313

339

365

391

417

443

469

495

521

547

573

599

625

651

677

703

729

Hour in Month

Meg

awat

ts

Net Demand NW Thermal NW Hydro Unserved Net Imports

Cold

Hydro Limited

GENESYS Simulation Illustrative Example Only


8

Curtailment Events(Peaking problems and energy shortages)

0

1000

2000

3000

4000

Hourly Curtailments Dec-Apr (Not all hours shown)

Curt

aile

d M

egaw

atts

Peak Event > 3,000 MW

Energy Event > 28,800 MW-hrs

Each event has a peak and Each event has a peak and duration.duration.


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What do we Count?• Ideally, we count “significant” events (those

that we want to avoid)• Energy threshold (or contingency resource)

is 1,200 MW for one day or 28,800 MW-hours from Dec-Mar

• Capacity threshold (or contingency resource) is 3,000 MW in any hour from Dec-Mar and from Jun-Sep


10

Curtailment Events(non-events not shown)

Reliability Events by Game

0

1000

2000

3000

4000

3 12 12 12 12 12 12 15 15 18 18 22 22 25 25 25 25 25 25 33 33 33 33 34 36 36 36 36 36 36 36 37 39 39 39 39 39 39 39 39 41 44 44 46 46 46

Game

Cur

tailm

ent (

MW

)

Seattle


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Loss of Load ProbabilitySimulated 300 winters (December through March)

Out of 300 winters, 15 had an average curtailment greater than 10 MW-seasons, which means that the Winter Loss of Load Probability (LOLP) = 15/300 = 5 percent


12

Energy LOLP(Sum of Curtailed Energy Dec-Mar)

0102030405060708090

100

0 1 2 3 4 5 6 7 8 9 10Probability (%)

Mag

nitu

de

(MW

-S

easo

ns)

We plot the average seasonal curtailment for every

simulation in descending order. We then observe where that

curve crosses the 10 MW- Season level on the probability

axis - - that identifies the LOLP for this scenario.

The Problem with LOLP


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Potential Problem with LOLPSame LOLP – Bigger Magnitude

0

0.2

0.4

0.6

0.8

1

1.2

1 2 3 4 5 6

Probability

Mag

nitu

de


15

Potential Problem with LOLPLower LOLP – Bigger Magnitude

00.20.40.60.8

11.21.41.6

1 2 3 4 5 6

Probability

Mag

nitu

de

LOLP Subcommittee Reportand Recommendations


17

LOLP Subcommittee Report• Clearly define all reserve requirements

– Operating reserves– Planning reserves– Wind integration reserves

• Determine which reserve curtailments count toward LOLP• Add temperature-correlated wind as a random variable• Decouple temperature and water condition • Define a “contingency” resource for each month of the

year instead of defining threshold events • Record curtailment events across all months of the year• Consider using other adequacy metrics • Continue to assess climate change impacts


18

LOLP Review Status• Reserves

– Work being done by PNUCC committee• Temperature-correlated wind

– BPA working on a test data set• Decouple temp and water

– Done• Contingency resource

– Work needs to be assigned• Annual metric

– Not yet started• Other metrics

– BPA draft methodology– PSRI review

• Climate change – Ongoing

Next Steps


20

Possible Modifications to the Current Method

• Replace LOLP with an alternative metric

• Use LOLP in conjunction with an alternative adequacy metric

• Use LOLP in conjunction with the magnitude of the most severe event (or an average of the worst 10% of events)


21

Examples of Other Adequacy Metrics

• LOLE: loss of load expectation (%)– Number of hours with curtailment divided by the

total number of hours simulated– Can be more intuitive, i.e. 99.5% reliable– Does not address magnitude

• EUE: expected unserved energy (MW-hr)– Average amount of unserved energy per year– Lacks specific information about severe events


22

Work Plan• PSRI review complete by early 2010

• Benchmark GENESYS by early 2010

• Tech Committee propose new metric and threshold by April of 2010

• Use new metric to assess 3 and 5 year adequacy by June 2010

power supply adequacy assessment model/methodology review steering subcommittee meeting january 29,...

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