Prediction of Wind Power and Reducing the Uncertainty for Grid ...

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... December 15-16, 2005, Berlin. EEG: immediate exchange of wind power. ▫ online exchange of fluctuating wind power between TSO. Vattenfall Europe e.on.
Prediction of Wind Power and Reducing the Uncertainty for Grid Operators

Dr. Matthias Lange Dr. Ulrich Focken energy & meteo systems GmbH Oldenburg, Germany

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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background

energy & meteo systems GmbH: ƒ

services in energy meteorology

ƒ

operator of wind power prediction system Previento

ƒ

dispatcher workshops for wind power prediction

ƒ

de-centralised energy management systems

ƒ

surveys and studies

ƒ

R&D

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Overview

ƒ

Motivation

ƒ

State-of-the-art

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Research and development in Europe

ƒ

Outlook

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Motivation wind power depends on meteorological conditions effective load pattern not regular anymore

ƒ ƒ

load [% max. load]

Grid load without wind power

100

0 0

1

2

3 time [d]

4

5

6

7

Grid load including wind power

wind power contribution must be known in advance

need for wind power forecast FIC, 2nd Workshop, December 15-16, 2005, Berlin

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EEG: immediate exchange of wind power

e.on

Vattenfall Europe RWE

EnBW

ƒ

online exchange of fluctuating wind power between TSO

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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EEG: immediate exchange of wind power

e.on

Vattenfall Europe RWE

EnBW

ƒ

balancing effort according to proportion of consumption

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Basic Approaches to Wind Power Prediction

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common use of numerical weather predictions

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statistical systems: „training“ derive statistical relation between numerical weather prediction and power output of wind farm

ƒ

physical systems: „equations“ describe wind field in terms of boundary layer meteorology FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Statistical Systems ƒ

example ISET system: artifical neural network ƒ training based on measurement data

numerical weather prediction

measurement power output

U V p T H

© ISET

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Physical Systems ƒ

explicit modelling of boundary layer

NWP data

100 m

hub height

height

1000 m

NWP data

10 m

geostrophic wind

wind speed FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Physical Systems ƒ

wind profile changes with atmospheric conditions 1000 m

geostrophic wind

hub height

height

100 m

stable

NWP data

10 m

wind speed FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Physical Systems ƒ

wind profile changes with atmospheric conditions 1000 m

geostrophic wind

100 m

hub height

height

unstable

stable

NWP data

10 m

wind speed FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Overview Previento Numerical weather prediction

Spatial refinement

Wind park modelling

Upscaling

Regional wind power forecast

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Overview Previento Numerical weather prediction

Spatial refinement

Wind park modelling

Upscaling

Regional wind power forecast

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Overview Previento Numerical weather prediction

Spatial refinement

Wind park modelling f

Upscaling

f f

Orography roughness Thermal stratification

Regional wind power forecast

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Overview Previento

Spatial refinement

Wind park modelling

Power

Numerical weather prediction

Wind speed

Upscaling

Regional wind power forecast Wind park geometry FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Overview Previento Numerical weather prediction

Spatial refinement

Wind park modelling

Upscaling

Regional wind power forecast

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Overview Previento Numerical weather prediction installed capacity

Spatial refinement

Wind park modelling

Upscaling

prediction time

Regional wind power forecast

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Individual Prediction Uncertainty

power curve

weather situation

2000

power [kW]

1500

1000

500

0 0

5

10

15

20

25

30

35

wind speed [m/s]

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Dayahead Prediction for Germany (17 GW installed power)

power [MW]

prediction reality uncertainty

one week FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Operational Use

ƒ

Kiss/ESS-Format: ƒ Direct Integration into Energy Management Systems

Muster

Datum aus Regelzone an Regelzone von Bilanzkreis nach Bilanzkreis

13.10.2005

Typ

WP

Kommentarbereich

ƒ

ƒ

Dayahead ƒ scheduling og power plants ƒ trading of conventional energy Intraday planning ƒ minimise balancing power

FIC, 2nd Workshop, December 15-16, 2005, Berlin

WP_MIN

WP_MAX

13.10.2005 07:35

Kontrollsumme [MWh]:

34772

bis 00:00 00:15 00:30 00:45 01:00 01:15 01:30 01:45 02:00 02:15 02:30

13.10.2005

Deutschland Min-Konfidenz Max-Konfidenz

Erstellungsdatum Erstellungsuhrzeit Prognosezeitpunkt

von

13.10.2005

D D Wind

MW 00:15 00:30 00:45 01:00 01:15 01:30 01:45 02:00 02:15 02:30 02:45

MW 2789 2789 2789 2789 2789 2749 2708 2668 2628 2547 2466

MW 2209 2209 2209 2209 2209 2176 2141 2107 2073 2005 1936

3369 3369 3369 3369 3369 3322 3275 3229 3183 3089 2996

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How accurate are wind power predictions today ? ƒ

evaluation of Previento prediction for Germany (based on Nov 2004 – Juni 2005)

source: EnBW FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Forecast Accuracy Changes over Seasons ƒ

monthly evaluation of day ahead prediction

winter summer

source: EnBW FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Evaluation of single wind farm ƒ

wind farm in Northern Germany (17 MW, flat terrain)

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Summary State-of-the-Art

ƒ

wind power predictions established

ƒ

used by grid operators, traders, power plant operators

ƒ

important time horizons: intraday and dayahead

ƒ

customers use predictions from different providers in parallel

ƒ

uncertainty for risk assessement

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training for dispatchers how to use predictions

ƒ

significant improvements in accuracy during last year

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Research and Development (R&D)

two main approaches: ƒ

improve wind power prediction systems ƒ

ƒ

enhanced modelling and new features

clever use of meteorological input ƒ

take advantage of the variety of available weather data

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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R&D – improvement of prediction systems example: European project ANEMOS ƒ

Benchmarking of approved prediction systems from DK, D, E, F, GB, GR, IRL

ƒ

improvement: uncertainty, upscaling, offshore, complex terrain

ƒ

implementation under common Shell

ƒ

practical evaluation with end-users

http://anemos.cma.fr FIC, 2nd Workshop, December 15-16, 2005, Berlin

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R&D – clever use of meteorological input

ƒ

fact: ƒ atmosphere is a non-linear chaotic system

ƒ

idea: ƒ

don´t rely on one weather prediction only ƒ use different models or different forecast runs of same model ƒ

effect: ƒ

different weather models have different strengths and weaknesses ƒ the combination of different forecasts compensates errors of each single forecast

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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R&D – ensemble approach: GFS 12 h

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R&D – ensemble approach: GFS 24 h

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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R&D – ensemble approach: GFS 48 h

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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R&D – ensemble approach: GFS 96 h

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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R&D – Combination of European Weather Models

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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R&D – Combination of European Weather Models

ECMWF + Previento

Lokalmodell + ISET model

Hirlam + Previento

Aladin etc. ... + Previento

combination tool 1. weather classification 2. combination of predictions

optimal wind power prediction for each individual forecast situation

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Summary R&D

ƒ

intense international effort

ƒ

close co-operation between scientific community and industry

ƒ

hot topics

ƒ

ƒ

offshore, complex terrain, upscaling, uncertainty

ƒ

ensemble predictions, combination of different weather models

significant potential for improvements

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Outlook future applications of wind power predictions ƒ

grid management ƒ

ƒ

local wind power predictions to avoid grid congestion

storage management ƒ

compensate for fluctuations ƒ techniques: pumped water, compressed air, hydrogen ƒ

wind power on the energy market ƒ

announce schedule for production of wind farms ƒ trading on intraday and dayahead markets ƒ ability to provide control power

FIC, 2nd Workshop, December 15-16, 2005, Berlin

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Thank you for your attention!

energy & meteo systems GmbH Marie-Curie-Str. 1 26129 Oldenburg, Germany phone +49-441-36116470 [email protected]

www.energymeteo.de © 2005 energy & meteo systems GmbH FIC, 2nd Workshop, December 15-16, 2005, Berlin

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