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Same-Day Wind Variability Forecasts Christopher J. Anderson Wednesday, June 6 ISU Wind REU

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Same-Day Wind Variability Forecasts. Christopher J. Anderson Wednesday, June 6 ISU Wind REU. Wind Intermittency. One-month average wind (black line) wind speed daily cycle has smooth variation. However, many days (color lines) contain abrupt 1- to 3-hour changes. - PowerPoint PPT Presentation

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Page 1: Same-Day Wind Variability Forecasts

Same-Day Wind Variability Forecasts

Christopher J. AndersonWednesday, June 6

ISU Wind REU

Page 2: Same-Day Wind Variability Forecasts

Wind Intermittency

• One-month average wind (black line) wind speed daily cycle has smooth variation.

• However, many days (color lines) contain abrupt 1- to 3-hour changes.

• A “ramp event” is a large increase or decrease in energy in a short time.

• Most problematic is the short excursions below the zero production threshold.

“Ramp Event”

Zero ProductionThreshold

Page 3: Same-Day Wind Variability Forecasts

How is Wind Intermittency Managed?

• Reserve energy within the grid.– Typical reserve capacities are 5-10% of peak production, which is generally not

enough to handle a 2- to 3-hr dip in wind speed.

• Turn on a fossil fuel source.– Might take too long for coal to heat up and spin turbines at the needed

capacity level.

• Purchase energy on the market.– Very pricey! But, sometimes necessary if day-ahead posting is not going to be

met. Compare cost of penalty to market price.

• Brown outs.

• Each management option is expensive! And, it requires additional GHG offsets at other times or by other means.

Page 4: Same-Day Wind Variability Forecasts

The Future of Managing Wind Intermittency

• Expanding storage capacity for wind energy.– “It doesn’t rain every day but yet water is efficiently provided to billions of

inhabitants on the planet.”– Large battery farms (Gamesa, Xcel).– Underground wind pressure.– Use wind energy to produce fuel.

• Short-term forecasting for grid optimization.– Draw from several regionally distributed farms. For example, draw from

Wyoming when Iowa has a downturn.– Fast and numerous transmission lines.

Page 5: Same-Day Wind Variability Forecasts

Forecasting Two Causes of Wind Intermittency

• Thunderstorms

• Low Level Jet

Page 6: Same-Day Wind Variability Forecasts

Causes of Wind Intermittency:Thunderstorms

Page 7: Same-Day Wind Variability Forecasts

Causes of Wind Intermittency:Thunderstorms

Page 8: Same-Day Wind Variability Forecasts

Causes of Wind Intermittency:Low Level Jet

• Low level jets occur at night. Wind shear and stability combinations result in sporadic bursts of higher wind speed.

Page 9: Same-Day Wind Variability Forecasts

Terrain Variations of 50-100m Impact LLJ Wind Spatial Variability

Page 10: Same-Day Wind Variability Forecasts

WRF 2-km Simulation of Spatial/Vertical Hourly Wind Variation for LLJ 2011 July 1

10 pm

1 am

7 pm

50 m AGL 80 m AGL 110 m AGL

Page 11: Same-Day Wind Variability Forecasts

1-hr Average 80 m Wind Speed (m s-1)

3 PM June 30 4 AM July 110 PM July 1

Page 12: Same-Day Wind Variability Forecasts

And these are “typical” midwestern conditions!

Hourly Wind Variation of LLJ is Impacted by Turbines within the Wind Farm

Turbine Wake

LLJ Max ~ 12 m/s

LLJ Max ~ 16 m/s

Rhodes, Aitken, Lundquist, 2010, [email protected]

Page 13: Same-Day Wind Variability Forecasts

Wind Predictability and Forecast Strategies

Page 14: Same-Day Wind Variability Forecasts

DOE-NOAA-Private Sector Wind Forecast Improvement Project

• Implement a new networt capable of constant monitoring of wind profile across a region. (squares, circles, stars, arrows)

• Use a 3-km grid for a weather forecast model.

• Every hour, use wind network measurements as a starting condition for 15-hour 3-km weather forecast.

http://www.esrl.noaa.gov/psd/psd3/wfip/

Page 15: Same-Day Wind Variability Forecasts

2-hr Thunderstorm Forecast

Page 16: Same-Day Wind Variability Forecasts

2-hr Thunderstorm Forecast

Page 17: Same-Day Wind Variability Forecasts

15-hr Wind Profile Forecast

Page 18: Same-Day Wind Variability Forecasts

The Future of Managing Wind Intermittency

• Expanding storage capacity for wind energy is under development.

• Short-term forecasting for grid optimization is on the way as early returns from WFIP are promising.

– More forecast vendors coming into existence.– Results will provide Congress with guidance on necessary measurement system investments.