wind power forecasting related update - iso new englandpresentation contents • wind power...

ISO-NE PUBLIC

S E P T 2 8 , 2 0 1 5 | V R W G

Bill Henson S Y S T E M P E R F O R M A N C E A N D I N T E G R A T I O N E N G I N E E R

Wind power forecasting related update

ISO-NE PUBLIC

Presentation contents

• Wind power forecasting update

• Wind curtailment – Definition – Difficulties associated with determination – Curtailment identifiers – Some examples – Monthly estimated wind curtailment Jan – July 2015 – Curtailment under Do Not Exceed dispatch

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ISO-NE PUBLIC

Wind power forecasting update

• Changes to the Short-term windpower forecast are coming – Reduced granularity over some time horizons

• Currently: 5, 10, 15, … 300 minutes out • Change to: 10, 15, 20, 25, 30; 45, 60, 75…300 minutes out

– Transition to “uncurtailed forecast” for short-term only – Medium-term and long-term still use historically observed curtailment

in adjusting forecast

• Wind High Limit – Most wind plants do an “okay” job of calculating, most of the time – Examples later in presentation

• Source of equipment availability in forecast is WPFA (future hours) and RTHOL (current hour)

• ISO does not receive a wind speed forecast

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ISO-NE PUBLIC

Definition of Curtailment

• A windplant is generating at less than the theoretical maximum output due to operator action given – Weather conditions (esp. wind speed) at plant – Availability of the equipment to run (esp. wind turbines)

• i.e. this is not a function of wind speed or icing, etc • Can be initiated by a variety of entities

– ISO in response to a reliability condition on the transmission system – LCC in response to a reliability condition on the distribution system – Wind plant operator for a variety of reasons

• Reduce stress on components • Reduced noise operation • Wildlife mitigation strategy • Other reasons

– Others?

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ISO-NE PUBLIC

Determining if Curtailment is occurring is difficult • “by inspection” is not repeatable and is open to interpretation • Do not know the cause of the curtailment

– Variety of actors whose actions are unknown

• Suspected curtailments can be identified ex-post by examining plant output looking for: – Deviation between estimate of potential and actual

• Changing variability and uncertainty – i.e. how good is the estimate of potential?

– Patterns common to curtailment itself • Will be for at least ½ hour

– But might start at anytime and end at anytime • Will be for some fixed level of maximum output

– That might change (in discrete steps) over time • Fixed maximum output will be rounded to nearest MW

– but how much variability around this ?

• Two methods of identifying suspected curtailment have been developed

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ISO-NE PUBLIC

Curtailment Identification Method 1

• Use the difference between the 5-minute ISOImposedEcoMax, the Short-term (i.e. 5-minute) windpower forecast, and the 5-minute average actual power output

– UnitControlMode >= 3 – Actual MW < ISOImposedEcoMax+1 – Forecast> ISOImposedEcoMax – Difference between Actual MW and ISOImposedEcoMax <= max(1, or

10% of the windplant nameplate) • Wind plants can very accurately generate at just below a fixed reference. • Financial benefit in generating as close to this fixed reference as possible • If a wind plant cannot hold to within 10% of nameplate (or 1MW whichever is

greater) of the ISOImposedEcoMax then it is not really curtailed, either: – The wind speed dropped (for deviations below) – The plant generated more than was allowed (for deviations above) – Or the wind plant put in a suboptimal control (e.g. extreme: “if the windplant is

curtailed by any amount at all then stop producing any power”)

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ISO-NE PUBLIC

Curtailment Identification Method 2

• “analog” to “by inspection” approach using 5 minute average SCADA data for Wind High Limit and actual MegaWatt output

– Sliding window averages of 12 5-minute WHL and MW are created – MASD: Absolute value of deviation between actual values and sliding window

averages • Similar to “standard deviation” but is used in a manner that “slides across” the data -- in

order to allow for variable start and stop times • If the value of the MASD is below a threshold curtailment might be occurring

– UnitControlMode >= 3 – Sliding averaged WHL minus sliding averaged MW must be greater than 1MW – Sliding averaged WHL must be greater than 1MW – Sliding averaged WHL must not be “stuck” at some value – Sliding averaged MW must be limited to near integer values

• i.e. curtailments will not be made to a finer resolution than 1MW – Eliminate isolated short occurrences – curtailment will not be applied for less than

6 5-minute periods • Remove curtailment indicator if continuous for less than 20 minutes • Accumulate curtailment indicated periods that are separated by less than 20 continuous

minutes

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ISO-NE PUBLIC

Determining how much Curtailment is occurring is also difficult

• Errors in the estimated potential output (WHL) • These errors are not constant

– Might be errors in the wind speed measurements – Wind speeds are not constant across the plant – Might change with wind direction due to wake effect – Might change with turbulence in the air due to loss of efficiency – Might change with other weather variables (density, icing accretion,

etc.) – Might be errors/simplifications in the calculations used

• Due to unknown effects of errors – Amount of curtailment is estimated using WHL minus Actual MW

output when WHL is greater than Actual MW output during the periods of identified suspected curtailment

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ISO-NE PUBLIC

Reporting about Curtailment can be Market sensitive information

• Data must be normalized and sanitized for public distribution

• Participants may see their individual estimated curtailment data

• The next slides will show some examples of suspected curtailment

• Finally, estimated monthly curtailment data for 2015 (January through July) will be shown in aggregate and in normalized individual formats

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ISO-NE PUBLIC

Suspect #1

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Apr 01 Apr 03 Apr 05 Apr 07 Apr 09 Apr 11 Apr 13 Apr 15 Apr 17 Apr 19 Apr 21 Apr 23 Apr 25 Apr 27 Apr 29 May 01 0

0.2

0.4

0.6

0.8

1

mw whl


0.2

0.4

0.6

0.8

1

1.2

mw isoimposed forecast

Apr 01 Apr 03 Apr 05 Apr 07 Apr 09 Apr 11 Apr 13 Apr 15 Apr 17 Apr 19 Apr 21 Apr 23 Apr 25 Apr 27 Apr 29 May 01

0

0.2

0.4

0.6

0.8

1 curt1 curt2

ISO-NE PUBLIC


0.2

0.4

0.6

0.8

1

mw whl


0.2

0.4

0.6

0.8

1

1.2



0

0.2

0.4

0.6

0.8

1 curt1 curt2

Suspect #1

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ISO-NE PUBLIC

Suspect #1 – period #1: Probable Curtailment

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Apr 04, 04:00 Apr 04, 09:00 Apr 04, 14:00 Apr 04, 19:00 Apr 05, 00:00 Apr 05, 05:00 Apr 05, 10:00 Apr 05, 15:00 Apr 05, 20:00 0

0.2

0.4

0.6

0.8

1

mw whl


0.2

0.4

0.6

0.8

1


Apr 04, 04:00 Apr 04, 09:00 Apr 04, 14:00 Apr 04, 19:00 Apr 05, 00:00 Apr 05, 05:00 Apr 05, 10:00 Apr 05, 15:00 Apr 05, 20:00

0

0.2

0.4

0.6

0.8

1 curt1 curt2

ISO-NE PUBLIC

Suspect #1 period 2: Could be Curtailment

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Apr 08, 06:43 Apr 08, 11:57 Apr 08, 17:11 Apr 08, 22:25 Apr 09, 03:39 Apr 09, 08:53 Apr 09, 14:07 Apr 09, 19:21 Apr 10, 00:35 Apr 10, 05:49 Apr 10, 11:03 0

0.2

0.4

0.6

0.8

1

mw whl


0.2

0.4

0.6

0.8

1


Apr 08, 06:43 Apr 08, 11:57 Apr 08, 17:11 Apr 08, 22:25 Apr 09, 03:39 Apr 09, 08:53 Apr 09, 14:07 Apr 09, 19:21 Apr 10, 00:35 Apr 10, 05:49 Apr 10, 11:03

0

0.2

0.4

0.6

0.8

1 curt1 curt2

ISO-NE PUBLIC

Suspect #1 period 3: Probable Curtailment

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0.2

0.4

0.6

0.8

1

mw whl


0.2

0.4

0.6

0.8

1


Apr 19, 19:00 Apr 20, 00:00 Apr 20, 05:00 Apr 20, 10:00 Apr 20, 15:00 Apr 20, 20:00 Apr 21, 01:00 Apr 21, 06:00 Apr 21, 11:00

0

0.2

0.4

0.6

0.8

1 curt1 curt2

ISO-NE PUBLIC

Suspect #2

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0.2

0.4

0.6

0.8

1

mw whl


0.2

0.4

0.6

0.8

1

1.2



0

0.2

0.4

0.6

0.8

1 curt1 curt2

ISO-NE PUBLIC


0.2

0.4

0.6

0.8

1

mw whl


0.2

0.4

0.6

0.8

1

1.2



0

0.2

0.4

0.6

0.8

1 curt1 curt2

Suspect #2

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ISO-NE PUBLIC

Suspect #3

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0.2

0.4

0.6

0.8

1

mw whl


0.2

0.4

0.6

0.8

1



0

0.2

0.4

0.6

0.8

1 curt1 curt2

ISO-NE PUBLIC


0.2

0.4

0.6

0.8

1

mw whl


0.2

0.4

0.6

0.8

1



0

0.2

0.4

0.6

0.8

1 curt1 curt2

Suspect #3

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ISO-NE PUBLIC

Suspect #3 : Probably not Curtailment

19


0.2

0.4

0.6

0.8

1

mw whl


0.2

0.4

0.6

0.8

1


Apr 10, 15:00 Apr 10, 20:00 Apr 11, 01:00 Apr 11, 06:00 Apr 11, 11:00 Apr 11, 16:00 Apr 11, 21:00 Apr 12, 02:00 Apr 12, 07:00 Apr 12, 12:00 Apr 12, 17:00

0

0.2

0.4

0.6

0.8

1 curt1 curt2

ISO-NE PUBLIC

Suspect #4: Mixed

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0.2

0.4

0.6

0.8

1

mw whl


0.2

0.4

0.6

0.8

1

1.2



0

0.2

0.4

0.6

0.8

1 curt1 curt2

ISO-NE PUBLIC

Suspect #5: Mixed

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Feb 01 Feb 03 Feb 05 Feb 07 Feb 09 Feb 11 Feb 13 Feb 15 Feb 17 Feb 19 Feb 21 Feb 23 Feb 25 Feb 27 Mar 01 0

0.2

0.4

0.6

0.8

1

mw whl


0.2

0.4

0.6

0.8

1


Feb 01 Feb 03 Feb 05 Feb 07 Feb 09 Feb 11 Feb 13 Feb 15 Feb 17 Feb 19 Feb 21 Feb 23 Feb 25 Feb 27 Mar 01

0

0.2

0.4

0.6

0.8

1 curt1 curt2

ISO-NE PUBLIC


0.2

0.4

0.6

0.8

1

mw whl


0.2

0.4

0.6

0.8

1


Feb 01 Feb 03 Feb 05 Feb 07 Feb 09 Feb 11 Feb 13 Feb 15 Feb 17 Feb 19 Feb 21 Feb 23 Feb 25 Feb 27 Mar 01

0

0.2

0.4

0.6

0.8

1 curt1 curt2

Suspect #5 Mixed

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ISO-NE PUBLIC

January 2015 Estimated Curtailment

WindPlant

Estimate 1 % of Energy Delivered

Estimate 2 % of Energy Capacity Factor

1 0.3 0.4 45.52 0.1 2.6 483 0.1 7.9 47.44 0.1 0 38.35 0.1 1 47.56 4.3 2.7 39.17 0.1 4.2 38.68 0.1 0.1 38.19 7 6.9 38.9

10 3.8 7.3 35.411 0.1 4.8 48.812 0.2 0 47.713 1.9 1.2 46.914 7.6 14.7 36.715 0.1 0.6 41.916 9.7 9.5 38.1

ISO-NE Aggregate

Estimate 1 Estimate 2

Delivered

% of energy 2.6 3.7 n/a

GWH 5.8 8.0 220.0

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ISO-NE PUBLIC

February 2015 Estimated Curtailment

WindPlant



1 0.1 0.4 48.52 0.1 1.4 37.83 0.1 5.5 42.74 0.1 0 39.45 0.2 2.3 346 4.4 2.5 34.77 0.1 3.2 36.18 0.2 0.1 389 0.5 0.2 35.9

10 0.2 0.9 32.611 0.1 13.1 34.612 0.1 0 45.513 0.1 0.2 41.414 4.8 7.4 3315 0.1 0.1 36.716 5.1 4.2 35.5

ISO-NE Aggregate


Delivered


GWH 1.8 3.2 179.8

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ISO-NE PUBLIC

March 2015 Estimated Curtailment

WindPlant



1 1.7 0.8 49.72 0.2 8.9 41.23 0.1 4.5 42.24 0.1 0 39.25 0.1 0.5 48.56 4.4 2.9 39.77 0.1 1.5 38.38 0.3 0 40.69 0.4 0.2 34.2

10 18.2 17.7 31.511 0.1 7.7 41.312 0.1 0 45.613 3.3 2.3 4314 10 14.6 36.415 0.3 0.2 3816 12.7 11.3 37.7

ISO-NE Aggregate


Delivered


GWH 6.3 7.4 207.6

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ISO-NE PUBLIC

April 2015 Estimated Curtailment

WindPlant



1 0.1 0 44.62 0.1 6.1 38.63 0.2 9.5 36.94 0.1 0 35.65 0.2 1.2 41.26 2.3 1.5 34.37 0.1 1.2 34.98 0.3 0 32.99 4.5 4.7 32.7

10 12 11 29.611 0.1 10.5 43.212 0.2 0 46.213 5 3.9 42.814 2.7 1.8 34.915 0.1 0.1 34.816 4.5 1.1 36.2

ISO-NE Aggregate


Delivered


GWH 4.3 5.2 187.7

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ISO-NE PUBLIC

May 2015 Estimated Curtailment

WindPlant



1 0.1 0 37.82 0.2 0 30.73 0.1 2.1 25.44 0.1 0 26.45 0.2 4.3 40.26 1.8 0.7 29.87 0.2 0.1 26.28 0.4 0 28.49 9.5 9.7 27.8

10 2.2 1 26.411 0.1 0.3 30.212 0.2 0 35.513 1.1 0.6 37.714 1.6 0.3 29.415 0.1 0.1 28.516 5.1 0.1 31

ISO-NE Aggregate


Delivered


GWH 3.4 2.6 159.7

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ISO-NE PUBLIC

June 2015 Estimated Curtailment

WindPlant



1 0.1 0 34.92 0.2 0.2 27.63 0.1 0.3 32.94 0.2 0 19.25 0.3 6.6 27.56 1.3 0.8 23.67 0.2 0.2 20.58 0.5 0 21.79 3.4 2.7 21.5

10 31.6 36.9 18.111 0.1 0.1 32.212 0.2 0 30.613 10.4 6.9 28.514 1.1 1.1 2315 0.1 0.4 21.316 0.2 0.6 26.2

ISO-NE Aggregate


Delivered

% of energy 3.1 3 n/a

GWH 3.8 3.7 124.2

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ISO-NE PUBLIC

July 2015 Estimated Curtailment

WindPlant



1 0.2 0 202 0.2 0 16.73 0.2 2 19.94 0.2 0 17.55 0.3 12.3 25.76 0.1 0 17.47 1 3 15.18 0.5 0 169 1.8 1.5 18.4

10 0.5 0.1 18.711 0.2 0.7 20.912 0.2 0 25.813 0.5 0.3 27.814 0.2 1.7 17.315 0.1 0.2 19.316 0.1 0.1 18.8

ISO-NE Aggregate


Delivered


GWH 0.5 0.8 103.6

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ISO-NE PUBLIC 30

Curtailment under Do Not Exceed dispatch

• DNE for DNE Dispatchable Generators is a combination of – Generator economics – Reliability need of system

• Perhaps more appropriate to call this “ungenerated wind” for wind plants, and “ungenerated water” for intermittent hydro

• Or maybe “spilled wind/water”

• LMPs and offer information is available to participant – This means that DNE dispatch can be parsed by each participant in

order to determine what were “reliability curtailments” and “economic decisions not to generate”

• Note that “economic decisions not to generate” stem directly from the offer prices submitted by the Participant!

ISO-NE PUBLIC

Summary

• Wind power forecast is working better than expected • Curtailment is difficult to identify and quantify • Using two measures to estimate in order to “bookend” and validate • Individual plants can be heavily affected • Fleet (as a whole) curtailment

– ranges between 0 and approximately 5% of energy delivered in any given month

– Is usually less by energy and by % of energy delivered in months with less energy

• Individual participants may see their own estimated curtailment data

• “Curtailment” per se does not exist under DNE Dispatch • Under DNE Dispatch, congestion is managed in a manner similar to

the economic dispatch of traditional generators

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