Simulated imbalance of 8000 MW wind power

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Simulated imbalance of 8000 MW wind power

• EOW 2007 Berlin
• Jan Coelingh

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Acknowledgements

• Project financially supported by WE_at_SEA-programme
• Cooperation with ECN, TU Delft and KEMA
• Work bound by other objectives
• Special thanks are due to
• Benjamin Duguet (Ecofys)
• Jord Engel (Evelop, formerly Ecofys)
• Arno Brand (ECN)
• Madeleine Gibescu (TUD)
• Other members project team

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Contents

• Objective
• Method
• Example results
• Conclusions
• Recommendations

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Future perspective

• Projected wind power capacity in The Netherlands
• 2000 MW onshore
• 6000 MW offshore
• What does this mean for the TSO (Tennet)?
• What measures are needed, if any?
• Characteristics modelled by simulation study
• currently under debate

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Objective

• Adequate representation of future situation
• Characteristics of realisations (simulated)
• Characteristics of forecasts (realistic)
• Analysis of operational characteristics (extreme
  events, unbalance)

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Simulation

• Experimental data of wind power output of
  offshore wind farms hardly available (in the
  public domain)
• Scenarios for 8000 MW installed capacity based on
  expert opinion
• Simulation of realisations based on observed wind
  speed data sets
• Simulation of forecasts based on output from
  current meteorological models

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Method

• Selection of 39 realistic wind farm locations
  onshore and offshore
• Wind farm design
• wind turbines
• wind turbine type
• hub height
• layout
• Development scenarios for
• 2010
• 2015
• 2020

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Scenarios

• Offshore scenario based on actual applications
• Smaller Wts and close to the coast first

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Realisations

• Data base
• Period 1 year (mid 2004-mid 2005)
• 9 locations
• Observed wind speeds at several heights (no
  directions)
• Transformation to hub height and specific
  locations
• Conversion of wind speed to power output
  (Pv-curve)
• RESULT hourly time series of 1 year of realised
  power output for 39 wind farms

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Locations
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Forecasts

• Data base
• Standard predicted wind speeds at fixed grid
  points and height
• 4 different forecast windows (6, 12, 18, 24 h
  ahead)
• Focus on day ahead (24 h)
• Transformation to hub height and specific
  locations
• Conversion of wind speed to power output
  (Pvcurve)
• RESULT 4 hourly time series of 1 year of
  forecast power output for 39 wind farms

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Technology
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Unbalance

• Subtraction of realisation and forecast results
  in unbalance
• RESULT 4 hourly time series of 1 year of
  unbalance power output for 39 wind farms at
  different time horizons

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Aggregation

• Summation of all time series according to the
  scenario
• RESULT aggregated time series for three time
  horizons 2010, 2015, 2020

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Wind speed data

• Characteristics
• Quality Consistency
• Examples

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Monthly variations
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Hourly variations
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Characteristics of realisations

• Extreme events

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Ramps in realisation
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Analysis of unbalance

• NMAE (Normalised Mean Absolute Error)

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Error overview
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Error distribution (00 h)
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Extreme events (examples)

• Ramp in realisation (well predicted)

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Extreme events

• Ramp in realisation (well predicted)
• Ramp in forecast (badly predicted)

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Extreme events

• Ramp in realisation (well predicted)
• Ramp in forecast (badly predicted)
• Ramp in forecast (well predicted)

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Extreme events (decrease)
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Extreme events (increase)
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Conclusions

• Simulation study gives insight in grid
  integration issues but needs to be reiterated and
  refined
• Results now are not conclusive
• Wind turbine technology is developing
• Advance in wind farm management strategies
• Forecasts improve

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Recommendations

• Redo exercise with more advanced models and data
• Increase data sets gt1 year
• Increase quality by adding more experimental data
• Take into account wind directions and wake
  effects
• Take into account cost aspects (unbalance and
  market prices)
• Continue to discuss with TSO for best focus