Forecasting wind energy - Home | SE Wind...Forecasting wind energy GE Energy Consulting Group ... Gene Hinkle Manager Director, Power Economics GE Energy Consulting Group [email protected]

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Forecasting wind energy GE Energy Consulting Group March 30, 2016

Gene Hinkle Manager Director, Power Economics

GE Energy Consulting Group

[email protected]

518-385-5447

2

GE’s integration of renewables experience 2004 New York

3 GW Wind

10% Peak Load

4% Energy

2005 Ontario 15 GW Wind

50% Peak Load

30% Energy

2006 California 13 GW Wind

3 GW Solar

26% Peak Load

15% Energy

2007 Texas 15 GW Wind

25% Peak Load

17% Energy

2009 Western U.S. 72 GW Wind

15 GW Solar

50% Peak Load

27% Energy

2010 New England 12 GW Wind

39% Peak Load

24% Energy

2012 Nova Scotia ~1500MW Wind

40% Energy

2013 PJM

96GW Wind

22GW Solar

30% Energy

2014 Minnesota 8 GW Wind

4.5 GW Solar

50% Energy

Underway Pan-Canadian

~72GW Wind

30% Energy

Studies commissioned by utilities, commissions, ISOs...

• Examine feasibility of 100+ GW of new renewables

• Consider operability, costs, emissions, transmission

Gradients indicate systems subject to individual studies and also included in larger regional studies

GLOBAL RENEWABLE INTEGRATION STUDIES

• Barbados Wind & Solar Integration Study (2015)

• Vietnam Wind Grid Code Development and Renewable Integration Study (2014)

• REserviceS Project Economic Grid Support from Variable Renewables (Europe)

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Introducing Variability & Uncertainty

Uncertainty

• Wind generation are not always available when called upon

• Are not dispatchable … output is predicted by a forecast

• Actual power output is different than forecast output

0

5000

10000

15000

20000

25000

0 6 12 18 24 30 36 42 48

Hours

MW

Wind Actual

Forecasted Wind

0

500

1000

1500

2000

2500

0 6 12 18 24 30 36 42 48

Hours

MW

CSP Actual

CSP Forecasted

A perfect forecast eliminates uncertainty, but there is still variability

Variability

• Wind and solar generation vary as the intensity of their energy sources

• Several timescales … minute (regulation), hour (ramping), daily, seasonal

Solar Actual

Solar Forecasted

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For grid operations, wind is “similar” to load

0

5

10

15

20

25

30

35

40

45

50

0 6 12 18 24Hour

GW

Load

Wind

Load - Wind

Net Load

= Load Minus Wind (This is what must be served

by other types of generation)

• Like load, wind can be forecasted

accurately for planning purposes

• Grid operators can plan day-ahead (or

shorter) operations based on a load

forecast and a wind generation forecast

• Dispatchable generation is allocated to

serve the net of the forecast load minus

the forecast wind

• Uncertainty in the wind forecast adds to

the uncertainty in the load forecast

• Adjustments are made using hour-

ahead forecasts and real-time data

Dispatchable Generation Serves “Net Load”

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• Basic options are to increase reserves, demand response, curtail, rely on neighbors, storage

• Increasing reserves

– Commit additional generation so that load will never be interrupted

– Need to do it 100% of the time, because you do not know when the reserves will be required

– Potential to increase system cost, additional capacity online may not be needed and runs the system less efficiently

• Demand response

– Interrupt or reduce load occasionally, as need arises

– A paid ancillary service

• Curtail when under forecasted

Dealing with Uncertainty

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Forecasting increases economic value of renewable power

Wide-spread extreme events are predictable (e.g. widely publicized Texas events were predicted)

Forecasting can Help to Reduce Uncertainty

Texas February 24, 2007 event

Arrival of such fronts is generally forecastable, several hours ahead within a 30-minute window

Thirty-Minute Extreme Wind Drops

0

10

20

30

40

50

60

70

80

90

100

-2600 -2200 -1800 -1400 -1000 -600 -200

Wind Delta (MW)

Nu

mb

er

of

30

-Min

ute

Pe

rio

ds

5000 MW

10000 MW(1)

10000 MW(2)

15000 MW

Extreme Thirty-Minute Wind Drops

~1.5hours

~1600 MW

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Timing is Everything

Conceptual Timeline for Day-Ahead Unit Commitment

15

20

25

30

35

-24 -18 -12 -6 0 6 12 18 24

12 am 12 am 12 am 12 pm 12 pm

GFS

Updates (6-hr period)

5 am

Load + Unit

Data Received

Wind

Forecast

11 am

Unit Commitment

Completed

SCUC

5 am

Morning

Load Rise

8 pm

Peak Load

29 hrs

44 hrs

Load

Hours

GW

Day of Operation

Start Times (warm): http://www.nrel.gov/docs/fy12osti/55433.pdf

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Timing is Everything

Conceptual Timeline for Day-Ahead Unit Commitment

15

20

25

30

35

-24 -18 -12 -6 0 6 12 18 24

12 am 12 am 12 am 12 pm 12 pm

GFS

Updates (6-hr period)

5 am

Load + Unit

Data Received

Wind

Forecast

11 am

Unit Commitment

Completed

SCUC

5 am

Morning

Load Rise

8 pm

Peak Load

29 hrs

44 hrs

Load

Hours

GW

Day of Operation

Start Times (warm): http://www.nrel.gov/docs/fy12osti/55433.pdf

Type Minimum Up-Time

Minimum Down-Time

Hours to Start

Combined Cycle 8 8 4-8

Combustion Turbine 1 2 0.6- 2

Steam Coal 24 – 48 24 – 48 12 - 48

Steam Oil/Gas 24 – 48 24 – 48 4 - 48

Nuclear Weeks – months 168 24 - 48

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Short-Term Forecasting

Using a 4-Hour forecast resulted in a $70M reduction in production cost.

The reduction was a result of an improved commitment, shifting from CT to CC’s.

CCGT increased by 2.0 TWh Coal increased by 4.7 TWh SCGT decreased by 0.2 TWh Imports decreased by 6.7 TWh

$70M

$250M

PJM Renewable Integration Study

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Reduction in Spilled Energy over SOA, I30 Scenario

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

2004 2005 2006 Average

Sp

ille

d E

nerg

y R

ed

ucti

on

(%

)

10% Forecast Improvement

20% Forecast Improvement

Unserved Energy, I30 Scenario

0

10

20

30

40

50

60

2004 2005 2006 Average

Reserv

e S

ho

rtfa

lls (

GW

h)

SOA Forecast

10% Improvement

20% Improvement

Avg Annual Savings over SOA

0.0

25.0

50.0

75.0

100.0

125.0

150.0

175.0

200.0

225.0

250.0

0% 5% 10% 15% 20% 25% 30%

Forecast Improvement (%)

Avg

An

nu

al O

per

atin

g C

ost

Sav

ing

s

($M

)

Pre

I10

I20

I30

Improved SOA Wind Forecast

Western Wind & Solar Integration Study

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11 3/28/2016

GE Energy Consulting

Just Forecast?

Available Information

Available Resources/

Options Requirements T

i

me

H

o

r

iz

o

n

Load

Forecast

Renewable

Forecast

Forced Outages

Accuracy

Unit

Commitment

Operation

Quick Start

DSM

Energy

Spin Regulation

Schedule

.

.

Frequency

Response

Short Circuit

Ratio

Others

How should Markets factor these into decisions?

Long Term Start

Mid Term Start

Options

Em

erg

ing

T

od

ay

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Conclusions

• The forecast schedule used depends on the system…

o Isolated or Interconnected

o Flexible generation or inflexible base load generation

o Hydro availability and flexibility (environmental constraints)

• Forecasting improvements result in operating cost savings to the utility. These savings increase with increased wind penetration and increased forecast accuracy. o The savings is not proportional to the penetration level of wind energy

o Diminishing returns with increased penetration

• A more accurate forecast, in general, can reduce operating reserve carried by a system for uncertainty

• Forecasting improvements reduce wind curtailment and reduce reserve shortfalls, increasing the efficiency of power system operations

• Other changes in operating practices are also needed to improve operating cost savings

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All power grids can accommodate substantial levels of wind and solar power… There is never a hard limit

Key lessons learned …

15 GE Energy Consulting

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Variability and Uncertainty… Layperson’s terms

For Example… Generator Owner… “I can guarantee 1000MW of hydro all day tomorrow.”

System Operator… “OK, I will turn off 1000MW of other generation.

Variability: Generator Owner...“I can guarantee 1000MW of hydro from 2PM to 4PM tomorrow.”

System Operator… “OK, I may turn down 1000MW of other generation, rather then shutting it off.”

Uncertainty: Generator Owner… “I think I will have 1000MW of hydro sometime tomorrow.”

System Operator… “OK, I may turn off only 600MW of other generation and I will keep 400MW spinning and have quick start capacity ready to fire.”