safewind wind power forecasting for extreme situations
DESCRIPTION
EWEC 2009 – Marseille, France. SafeWind Wind power forecasting for extreme situations. George Kariniotakis Ph.D, Head of Renewable Energies Group MINES-ParisTech/ARMINES [email protected]. Context – Research in Wind Power Forecasting. Latest European Projects. - PowerPoint PPT PresentationTRANSCRIPT
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SafeWindWind power forecasting for extreme situationsGeorge KariniotakisPh.D, Head of Renewable Energies GroupMINES-ParisTech/[email protected]
EWEC 2009 – Marseille, France
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Context – Research in Wind Power Forecasting
Meteorology
Wind power forecasting technology
Wind power forecasting technology
Operational decision making
• Latest European Projects
ANEMOS : FP5, 2002-2006
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Context – Research in Wind Power Forecasting
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Meteorology
Wind power forecasting technology
Wind power forecasting technology
Operational decision making
• Latest European Projects
ANEMOS : FP5, 2002-2006
ANEMOS.plus
ANEMOS.plus : FP6, 2008-2011
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Context – Research in Wind Power Forecasting
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Meteorology
Wind power forecasting technology
Wind power forecasting technology
Operational decision making
• Latest European Projects
ANEMOS : FP5, 2002-2006
ANEMOS.plus : FP6, 2008-2011
SafeWind
SAFEWIND : FP6, 2008-2012
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The SafeWind Consortium
9 countries,22 partners
2008-2012
End-users (8)
Universities (6)
Research (5)
Meteorologists (2)
SMEs (2)
Coordination ARMINES/
Mines ParisTech
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SafeWind objectives
First step : Definition & identification of extremes :– Extreme meteorological events
• High wind speeds (cut-off events)
• Thunderstorms
• Consider regional effects
– Extreme forecasting errors
– Extreme small scale events (Remote Sensing)
– Errors with an extremely high impact in the grid management or market participation.• Costs (Balancing, intraday markets)
• Grid congestion
• Connector capacity
• Coincidence with load, ramping capabilites
– ...
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Example: low pressure took path further to the South
L
0
2000
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10000
12000
00:0001:1502:3003:4505:0006:1507:3008:4510:0011:1512:3013:4515:0016:1517:3018:4520:0021:1522:3023:45
time
Pow
er [
MW
]
measurement
prediction
prediction
observation
Source : Emsys
Predictions for Germany : Path of low-pressure system was different than predicted, maximum error: 5500 MW could have been avoided by extreme event correction.
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L L P
h
PredictionObservation
MeasurementPrediction
Movement of low or fronts faster/slower
Example: Phase error in ramp events
Source : Emsys
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SafeWind objectives
Improve wind predictability with focus on extremes :
• at various temporal scales – Very short-term (order of 5 min)– Short term (hours to days)– Longer term (beyond few days ahead)
• at various spatial scales :– local scale: Extreme gusts or shears.
– regional scale: Extreme events (like thunderstorms) can cause the loss of significant amounts of wind energy with potential impact on the grid management.
– continental (European) scale: Extreme weather situations (like fronts) can propagate causing impacts in different member states.
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SafeWind objectives
• Models for "alarming": very short-term (0-6 h).
- Develop methods to adequately monitor and assess the wind energy weather situation over Europe in order to detect severe deviations in the wind power forecast due to extreme events.
- React on such deviations by issuing suitable alerts to users that a forecast error is occurring.
- Produce improved updates of the prediction in the short-term
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SafeWind objectives
• Models for "warning": providing information for the level of predictability in the medium-term (next day(s)).
– Such tools, based on ensemble weather forecasts and weather pattern identification, can be used to moderate risks in decision making procedures related to market participation, reserves estimation etc.
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SafeWind objectives• Develop a "European vision" for wind power forecasting
– Prepare the way for the coordinated management of 100+ GW wind generation at European Scale .
i.e. Data from Synoptic Stations in Europe
Creation of a Data Information System for centralising information useful for• large scale forecasting and• continously monitor "energy weather" over Europe
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SafeWind objectives
• Develop research in meteorology oriented to wind forecasting.
– Improve ensemble forecasts (wind & wind power) (i.e. ECMWF’s Ensemble Prediction System (EPS))
– Evaluate various EPS configurations
– Produce optimally combined forecast products
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SafeWind objectives• Link resource assessment to wind predictability.
• Analyse how new measurement technologies like Lidars can be beneficial for better evaluation of external conditions, resource assessment and forecasting purposes.
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Planned measurement campaigns at flat (DK) and complex (ES) terrains
Høvsøre Large Wind Turbine Test Facility
SafeWind objectives
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SafeWind objectives• Develop research in meteorology orientated to wind forecasting.
• Link resource assessment to wind predictability.
• Analyse how new measurement technologies like Lidars can be beneficial for better evaluation of external conditions, resource assessment and forecasting purposes.
• Demonstrate the operational benefits from new models.
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Conclusions• The SafeWind project develops synergies among different disciplines and actors to improve actual wind power forecasting technology;
• The work methodology is designed to enable quick transfer of results for operational use by industrial stakeholders.
• Expected impact :– Economy :
• Increased competitiveness of wind energy in markets• Reduced project risk due to better site selection
– Technology :• New or improved software tools• Better "operational" decision making for wind energy management• Maintain excellence of European R&D in the field
www.safewind.eu
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18F.R.E. 2861
Thank you for your attention