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Wind turbine participation on Control Reserve Markets. EWEA Conference Vienna, 6 th February 2013 Malte Jansen ( M.Eng.) Fraunhofer IWES, Kassel [email protected]. Regulator. TSO. Player. Manufacturer. Supplier. Research Institutions. European countries. - PowerPoint PPT Presentation
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Wind turbine participation onControl Reserve Markets
EWEA ConferenceVienna, 6th February 2013
Malte Jansen (M.Eng.)Fraunhofer IWES, [email protected]
PlayerManufacturer
RegulatorTSO
European countries
Supplier
Research Institutions
3
Project: „Regelenergie durch Windkraftanlagen“
Project Partners: Fraunhofer IWES (Project Leader) ENERCON GmbH (WT Manufacturer) Energiequelle GmbH (WF Operator) Amprion GmbH (TSO) TenneT GmbH (TSO)Project Period: 05/2012 – 04/2014Aims: Proof Procedure Placement of offers Unit control
10 MW
20 MW
30 MW
40 MW
14:00 16:00 18:00 20:0012:00
Activation Delivery Deactivation
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Time
Pow
er (
norm
aliz
ed)
Actual Feed-InForecast: 95%Forecast: 99%Forecast: 99.9%Forecast: 99.99%Forecast: 99.999%
09-Nov 16:45 11-Nov 15:15 13-Nov 13:45 15-Nov 12:15 17-Nov 10:45 19-Nov 09:15
OFFERING CONTROL RESERVE
Offer (I) - Security level
Reliability of 100%
required
Not possible for
wind farms
Reliability level of 99.994% used in the
project(TSO recommendation)
Use of probabilistic wind power forecasts
Security levels:95 %99 %99.9 % 99.99 %
actual feed-in
Prob
abili
ty
Power
6
Offer (II)- German pool of wind farms at 99.994% reliability
7
Offer (III) - Pooling of wind farms with conventional generation
Use of probabilistic forecast
Probabilistic forecast error is convoluted Wind farms Conventional generation
Offer = Power at a security level of 99.994%
Pool offering control reserve @ 99.994%
8
Offer (IV) - Effects of Pooling
0 20 40 60 80 100 120 140 160 180 2000
100
200
300
400
500
600
700
Time [1/4 hours]
Max
imum
Offe
r [M
W]
Pool Wind FarmsPool GasturbinesSum of both PoolsJoint offering (convoluted)
PROOF MECHANISM
10
0
Proof Method (I) – Balance control mechanism
Time [min]15 30
Pow
er o
utpu
t [M
W]
delivery of negative control
reserve
Currently applied TWENTIES Project Demo#1 (Spain) Regulation in Great Britain and Denmark
Feed-In
ForecastProb. Forecast @ x%
Available active power
Forecast
Feed-In
Prob. Forecast @ x%
11
0
Proof Method (II) – Available active power mechanism
Time [min]15 30
Forecast
Pow
er o
utpu
t [M
W]
Prob. Forecast @ x%
delivery of negative control
reserveForecast
Feed-InProb. Forecast @ x%
Field test in the project „Regelenergie durch Windkraftanlagen“ Regulation in the Irish and Danish Grid Code Considered as proof method in Great Britain
Available active power
Why available active power?
Not opinion of all project partners!
Balancing effects between
balancing groups
Shortterm forecast error of wind farms is balanced by
control reserve
Planned power production =
available active power
0
Forecast
Available active power
Feed-In
Pow
er o
utpu
t [P]
Time [min]15 30
delivery of negative control reserve
Prob. Forecast @ x%Prob. Forecast @ x%
Forecast
Energy Losses with the balance control mechanism – German pool of wind farms
95% 99% 99.8% 99.9% 99.99% 99.994% 99.999%
Lost energy with offers under schedule proof mechanism (German Pool)
Security level
Lost
ene
rgy
per
hour
off
ered
[M
Wh\
h_off
ered
]
0
200
400
600
800
1000
1200
24 Hours4 Hours1 Hour
Capacity prices with the balance control mechanism – German pool of wind farms
95% 99% 99.8% 99.9% 99.99% 99.994% 99.999%0
10
20
30
40
50
60
70
80Capacity Prices under the schedule proof mechanism (German Pool)
24 Hours4 Hours1 Hour
Security level
Capa
city
Pri
ces
[€/M
W/h
]
Capacity costs of control reserve under the available active power mechanism is 0 €/MW/h
15
Comparison of cost saving potentials at the tertiary control reserve market
Cost-saving potential: Available active power
Increased cost efficiency compared to balance control
Cost reduction +212% @ 95% +404% @ 99.999%
Higher market share of wind farms
Security Level
Cost
Red
uctio
n [€
]
95% 99%99.8%
99.9%99.99%
99.994%
99.999%
0
2
4
6
8
10
12
14
16x 106
Available active powerBalance control
1h Product length
POTENTIALS
17
Secure intraday forecastOffer control reserve
Potentials (I) – Potentials under different parameters
Variation of input parameters Security level Block length Bidding strategyTrade-off System security Economic efficiency
Actual feed-in
Secure day-ahead forecast
Powe
r (no
rmal
ized)
00:00
0.05
0.1
0.15
0.2
0.25
0.3
Time04:00 08:00 12:00 16:00 20:00
Potentials (II) – German pool of wind farms, Day-Ahead Tendering (1st July 2010 – 31st Dec 2010)
1h 4h 24h0
2
4
6
8
10
12
14
Product length
Pote
ntia
l [M
Wh]
x 106
95%99%99,8%99,9%99,99%99,994%99,999%
19
Maximum – No additional income for wind farms
Potentials (III) – Ecomonic impact on the tertiary control market of the German wind farm pool (1st July – 31st Dec 2010)
Results for teriary secondary reserve bids / available active power proof
method
95 % 99 % 99.8 % 99.9 % 99.99 % 99.994 % 99.999 %0
4
8
12
16
Security Level
Cos
t Red
uctio
n [€
]
x 106
24 hour product length
4 hour product length
1 hour product length
Minimum – Maximum additional income for wind farms
OUTLOOK
603025201510 5040 45355 55
Field test
1
0
0.5
-1
-0.5
Ener
gy fr
om U
nit [
MW
/ M
w offe
red]
Nega
tive
cont
rol
rese
rve
Posit
ive
cont
rol r
eser
ve
Tertiary controlSecondary control
Protocol Real SignalPro-tocol Real Signal
22
Conclusions
Wind Farm participation in control reserve markets … is economically feasible can substitute fossil fuel fired power plants will increase competition in the market can generate additional revenue for the wind farm operators
Balance control proof mechanism is unfavourable In economic terms In terms of curtailed energyBalance control proof mechanism is favourable In terms of control reserve demand for the TSO
