Energie braucht Impulse
Immediate Horizontal Wind Energy Exchange between TSOs in Germany since September 2004
Practical Experiences
EWEC 2006, 28 February 2006, Athens, Greece
EnBW Trading GmbH energy & meteo systems GmbH
Dr. Bernhard Graeber Dr. Matthias Lange
Clemens Krauss Dr. Ulrich Focken
28.02.2006 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems2
Content
›Horizontal exchange of wind power in Germany
›Balancing concepts
›Wind power predictions (forecasts)
›Operative experiences
›Conclusions
28.02.2006 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems3
Renewable energy act (EEG) - delivery of renewable energy to customers
TSO
Distribution Network
Distribution Network
EEG Plant (e.g. Wind
Park)
EEG Plant (e.g. Wind
Park)
Sales CompanySales Company
Final CustomerFinal Customer
EEG-Quota
TSO
EEG-energy is passed on from the producers to the final customers. Payment (feed in tariffs) are passed on as well.
28.02.2006 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems4
Spatial distribution of wind energy in Germany
7164 MW (39%)
256 MW
(1%)
3288 MW
(18%)
7628 MW (42%)
Transmission System Operators:E.ON Vattenfall EnBWRWE
Installed capacity in Germany: 18336 MW
Installed capacity in Germany: 18336 MWas of 31.01.2006
28.02.2006 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems5
Characteristic wind energy production pattern
0
3000
6000
9000
12000
15000
01
.01
.20
04
08
.01
.20
04
15
.01
.20
04
22
.01
.20
04
29
.01
.20
04
05
.02
.20
04
12
.02
.20
04
19
.02
.20
04
26
.02
.20
04
04
.03
.20
04
11
.03
.20
04
18
.03
.20
04
25
.03
.20
04
MW
Source: ISET
Example: January to March 2004, Germany, hourly values
changing levelssteep gradients
28.02.2006 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems6
Immediate horizontal exchange between TSOs
E Extrapolation
The example shows the data signals of only one TSO
EON transmission zone
EnBW TZ3
VET TZ2
RWE TZ4
WERZ1 x ARZ2
x ARZ4 x ARZ3
x ARZ1
+
_
Grid control
from TZi
EE
E E
x ARZ2
x ARZ4 x ARZ3
x ARZ1
x ARZ2
x ARZ4 x ARZ3
x ARZ1
x ARZ2
x ARZ4 x ARZ3
x ARZ1
___
factors:
Grid control
Grid control Grid control
› Upscaling of production based on measurements at representative wind farms
› Exchange of wind power production every 15 min
28.02.2006 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems7
Balancing of wind energy prediction deviations
TSO
Distribution Network
Distribution Network
EEGplant
EEGplant
TraderTrader
Sales CompanySales Company
EEG-Quota
TSO
Power Market
Power Market
Balancing power stations
Balancing power stations
Final CustomerFinal Customer
TSO is responsible for converting fluctuating wind energy into baseload (EEG-Quota)
28.02.2006 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems8
Balancing concepts
› There are two main approaches for managing differences between prediction and actual production
wind power fluctuations
conventional fluctuations e.g. load, power plants
1. Separate balancing
› Benefits from short-term predictability and limited gradients
› Contracted reserve / intra-day market
› High transparency
› Benefits from uncorrelated fluctuations
› Flexible pool of power plants / trading
› Lower additional costs for balancing
2. Combined balancing
conventional fluctuations
wind power fluctuations
28.02.2006 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems9
Wind Energy Prediction Systems - Requirements of TSOs
Requirements:
›Predictions of nationwide wind power production
›Required time-horizons: 0 – 96 h (until next working day, power exchange closed at weekends)
›High time resolution (hourly or 1/4 hourly)
System Providers:
› Increased demand due to new EEG (renewable energy act)
›Strong competition among providers
›Three main system providers with scientific background in Germany
28.02.2006 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems10
Wind Energy Prediction System: Previento (energy & meteo systems) as an example
Previento
Physical Model:
• Spatial refinement
• Thermal stratification
• Regional upscaling
• Forecast uncertainty
28.02.2006 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems11
Achievable prediction accuracy
›Prediction for all of
Germany
›Evaluation period Y2005
›Daily operational
predictions
›Root mean square error
(RMSE) normalized to
installed capacity
0%
2%
4%
6%
8%
10%
intraday day-ahead (-2d)
Previento
System 2
System 3
RMSE [% inst. capacity]
›Expected prediction quality in normal wind years:
›4 – 6 % intra-day (3 to 10 h)
›6 – 8 % day-ahead
›8 – 10 % 2 day-ahead
28.02.2006 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems12
Prediction quality of day-ahead forecasts: monthly reporting
0%
2%
4%
6%
8%
10%
Sep04
Okt04
Nov04
Dez04
J an05
Feb05
Mrz05
Apr05
Mai05
J un05
J ul05
Aug05
Sep05
Okt05
Nov05
Dez05
J an06
Previento
System 2
System 3
RMSE [% inst. capacity]day-ahead forecast
Significant changes in prediction quality from month to month. Ranking of quality changes as well.
28.02.2006 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems13
Measures for reducing balancing costs
›Use of several prediction systems
›Frequent intra day updates of predictions
›Meteorological training for operators
›Meteorological hotline
› Intra day trading
›Explicit consideration of changing wind
power uncertainty for power plant dispatch
28.02.2006 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems14
Prediction examples (1)
Day-ahead forecast Latest (intraday) forecast
Black: Actual wind production
Blue: Previento
Green: System 2
Purple: System 3
Shaded area: planning schedule
Predictions for Thursday, February 9, 2006 - in MW; EnBW Share (13%)
28.02.2006 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems15
Prediction examples (2)
Predictions for Monday, 20. September 2004
0
200
400
600
800
1000
1200
1400
1600
0 2 4 6 8 10 12 14 16 18 20 22
Actual wind
Prediction (-1d)
Prediction (-2d)
Prediction (-3d)
Prediction (-4d)
hours; September 20, 2004
Win
d p
roduct
ion E
nB
W-q
uota
(1
3,6
8%
)
[MW
]
Basis for
planning
(Friday)
Day-ahead
prediction
(Sunday)
Actual wind
production
Predictions can change significantly from day to day
28.02.2006 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems16
Operational experiences:Adjustment of plant dispatch
0
200
400
600
800
1000
1200
1400
1600
1800
Actual wind productionPrediction day-ahead
-300
-200
-100
0
100
200
300
400
500
Delta
24.12.2004 25.12.2004
[MW] MW
24.12.2004 25.12.2004
At the same time: Load forecast for the 25.12.2004 too high -> strong reduction of nuclear power plants necessary
0
200
400
600
800
1000
1200
1400
1600
1800
Nuclear powerplant 2
Nuclear powerplant 1
24.12.2004 25.12.2004
MW
28.02.2006 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems17
Conclusions
Experiences since September 2004
›18 GW of wind energy have been integrated successfully
› Immediate horizontal exchange is manageable
›Flexible park of power plants is advantageous for integrated
balancing of fluctuations
›Competition between prediction systems increases
prediction accuracy
›Huge prediction errors still occur in specific weather
conditions
28.02.2006 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems18
Outlook
›Additional wind energy is manageable
›But specific balancing costs will increase (wind prediction
errors will be higher than errors of other fluctuations)
›Wind power will have to participate partly in the balancing
task
›Wind power predictions have to be improved to reduce huge
predictions errors
28.02.2006 Dr. Graeber, Krauß, EnBW Trading; Lange, e & m systems19
Company Profiles
EnBW Trading GmbH:
›Trading division of EnBW AG
›Provides balancing services to TSOs
›EnBW AG is third largest energy company in Germany
energy & meteo systems GmbH:
›Operator of wind power prediction system Previento
›provides dispatcher training, meteorological hotline
›R&D: e.g. combination of meteorological weather data
Talk on Thursday Session DT1:
Dr. Ulrich Focken (energy & meteo systems)
OPTIMAL COMBINATION OF DIFFERENT NUMERICAL WEATHER PREDICTIONS FOR IMPROVED WIND POWER PREDICTIONS
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