1 1
Merit Order of Energy Storages by 2030
The Impact of Storage Technologies and Market
Regulation on Future Electricity Prices and the
Value of Flexibility
Berlin, June 14, 2013 2nd Annual Electricity Price & Load Forecasting Forum 13-14 June
Tim Buber
2 2
Agenda
Research Association for Energy Markets and Technologies
Motivation and Future Challenges
The Concept of the „Functional Energy Storage“
Storage Technologies and Demand Response
Limitations in Price Fluctuations
3 3
Research Association for Energy Markets and Technologies
Urban Energy
Management Industrial Energy
Management
Reserach Center for Energy Economics
Independent Research in Energy Economics since 60 years
Cooperation with the Technische Universität München
Expertise in all fields of energy economics
Foundation of Research Association for Energy Markets and Technologies in 2001
Smart Energy &
Smart Markets
4 4
Motivation and Future Challenges
5 5
Motivation and Future Challenges
Feed-In Management – Deliberate RES Cut-Offs
Su
m o
f L
os
t E
l. G
en
era
tio
n
fro
m R
ES
[GW
h]
To
tal C
om
pe
ns
ato
ry C
os
ts
[mil
lio
n €
]
Source: Abschätzung der Bedeutung des Einspeisemanagements nach § 11 EEG und § 13 Abs. 2 EnWG BWE 2012
Feed-In Management
Target:
High share of RES on
total el. generation
Contradiction
6 6
Motivation and Future Challenges
RES in Germany Historical Development & Political Target
Annual predictions of the increase of photovoltaics and wind power capacity
published by the Federal Ministry for the Environment, Nature Conservation and Nuclear
Safety:
0 GW
10 GW
20 GW
30 GW
40 GW
50 GW
60 GW
70 GW
2010 2015 2020 2025 2030
Leis
tun
g
Jahr
2007 2008 2009 2010
©FfE BMWi-0002 Flexibilisierung von DEA_00561
0 GW
5 GW
10 GW
15 GW
20 GW
25 GW
30 GW
35 GW
40 GW
45 GW
2010 2015 2020 2025 2030
Leis
tun
g
Jahr
2007 2008 2009 2010
©FfE BMWi-0002 Flexibilisierung von DEA_00567
Ph
oto
vo
lta
ics
Pre
dic
ted
Ca
pa
cit
y
Win
d (
On
sh
ore
)
Pre
dic
ted
Ca
pa
cit
y
Year Year
Increase of capacity strongly exceeds
the predictions
7 7
The Concept of the „Functional Energy Storage“
8 8
Electromobility
Pumped Storage CHP + Heat Storage +
Power2Heat
Flexibilization of
Load
+ -
Power2Gas
Further Technologies
FfE Region Model
Expansion Scenarios
Welfare and Market-Analysis
*
**
Functional Energy Storages
Overview of Storage Technologies
* SW Münster
* * EWE
9 9
Functional Energy Storages
Definition „Functional Energy Storage“
10 10
Storage Technologies and Demand Response
11 11
Storage Technologies and Demand Response
Flexible CHP Operation - Power to Heat
12 12
Storage Technologies and Demand Response
Basic Scheme for a Flexible CHP System
Gas Turbine/ Steam Generator
District Heating Grid
Thermal Storage
Peak Load Boiler
Electricity grid / EEX
ElectricalHeating
Turbine
CO2 CO2
Fuel
electricity
hea
t
Electricity
Hea
t
Heatsteam Steam Turbine
Renewables Power Plants
FlexibleCHP System
Renewables
Condenser
Waste Heat
13 13
Storage Technologies and Demand Response
Operation Modes for Flexible CHP-Systems
Sink
Source
Electricity
Heat
Not operating
Heating D
em
and
Electricity Prices / EEX
Electricity-
Demand/
-Supply
Heating
Demand
Flexible
CHP-
System
low
high
high
Heating
Plant
CHP
Storage
Electr.
Heating
Heating
Plant
CHP
Storage
Electr.
Heating
Heating
Plant
CHP
Storage
Electr.
Heating
Heating
Plant
CHP
Storage
Electr.
Heating
Electricity-
Demand/
-Supply
Heating
Demand
Flexible
CHP-
System
negative
14 14
Storage Technologies and Demand Response
Functional Energy Storage exemplified by CHP
0
10
20
30
40
50
60
70
80
1344 1368 1392 1416 1440 1464 1488
Le
istu
ng
/La
st
in G
W
Stunde im Jahr
0
10
20
30
40
50
60
70
80
1344 1368 1392 1416 1440 1464 1488
Leis
tun
g/L
ast
in G
W
Stunde im Jahr
0
10
20
30
40
50
60
70
80
1344 1368 1392 1416 1440 1464 1488
Leis
tun
g/L
ast
in G
W
Stunde im Jahr
0
10
20
30
40
50
60
70
80
1344 1368 1392 1416 1440 1464 1488
Le
istu
ng
/La
st
in G
W
Stunde im Jahr
Negative Residual-Load
Residual-Load
Renewable Energies
CHP
Flexibile CHP
Renewable + CHP
0
10
20
30
40
50
60
70
80
1344 1368 1392 1416 1440 1464 1488
Po
wer/
Lo
ad
in
GW
hour of the year Hour of the Year
P
ow
er/
Lo
ad
in
GW
-15
-10
-5
0
5
10
15
1344 1368 1392 1416 1440 1464 1488
Sto
rag
e P
ow
er
in G
W
Hour of the Year
15 15
Storage Technologies and Demand Response
Power2Heat - Potential
Average secondary control reserve demand in 2012: ~2.500 MW
e-boiler
capacity
max. thermal load
(district heating)
share
SW Flensburg 30 MW 320 MW 9%
↓ ↓ ↓ ↓
Germany 2.700 MW 30.000 MW 9%
collapse of negative control reserve market?
16 16
Storage Technologies and Demand Response
Power-to-Gas
17 17
Source:
[1] Specht, Michael; Zuberbühler, Ulrich: Power-to-Gas (P2G®): Layout, operation and results of the 25 and 250 kWel research plants. Stuttgart: Zentrum für
Sonnenenergie- und Wasserstoff-Forschung (ZSW), 2012
Storage Technologies and Demand Response
Power-to-Gas – The Concept
[1]
+ Large
storage&trans-
mission
capacities
available
+ Long-term
storage
possible
− Low
efficiency
− High
Investment
costs
18 18
Storage Technologies and Demand Response
Power-to-Gas – Hydrogen Production Costs
hours of negative residual load
time of negative
residual load in h/a
full load hours for 1 GW
electrolysis power in h/a
2020 2 1
2020 159 146
2030 371 344
2030 1230 1174
-10 GW power generation for stabilization purposes
( +10 GW power generation for
stabilization purposes)
19 19
Storage Technologies and Demand Response
Electromobility
20 20
Storage Technologies and Demand Response
Electromobility – Key Questions
Key Questions:
Where and when are how many vehicles charged?
What is the capacity and energy for charging?
What is the ratio of parking and charging duration?
21 21
Storage Technologies and Demand Response
Electromobility – Usability Factors
Usability Factors
Hour
of
Day
Mo Tu We Th Fr Sa Su
@ home
par
kin
g p
rob
abili
ty w
ith
in 1
5 m
inu
tes
@ work
Ho
ur
of
Day
Mo Tu We Th Fr Sa Su
pa
rkin
g p
rob
ab
ility
with
in 1
5 m
inu
tes
Ho
ur
of
Day
22 22
Storage Technologies and Demand Response
Electromobility – Prognosis and Impact on Residual Load
0
5
10
15
20
2010 2020 2030
An
zah
l an
Ele
ktro
fah
rzeu
gen
in M
io.
Jahre
IfE Bundesregierung
DGS conenergy - slow
conenergy - fast RWTH Aachen
Das conenery - fast Szenario geht von 50 Mio. EV bis 2030 aus
Year
Nu
mb
er o
f el
ectr
ic v
ehic
les
in
mill
ion
Scenario: 7 mio EVs in 2030
Flattening of the residual load
only very little benefit from V2G and
DSM
even for 7 Mio EVs
Simplified business approach (pay for
capacity – not for energy)
Average storage capacity of traction
battery in EVs: 26,5 kWh
23 23
Storage Technologies and Demand Response
Flexibilization of Load
24 24
Storage Technologies and Demand Response
Demand Side Management
Average DSM-Potential for Commerce, Trade and Services
2.420 MW positive
14.275 MW negative (mainly night storage heating)
Average DSM – Potential in Industry
1.811 MW positive DSM – Potential
410 MW negative DSM – Potential
positive = reduction of load
negative = increase of load
Source: EWI, 2010
What about
temporal availability?
25 25
Limitations in Price Fluctuations
26 26
Limitations in Price Fluctuations
Volatility of the Residual Load
0
10
20
30
40
50
60
1 3 5 7 9 11 13 15 17 19 21 23
Re
sid
ual
Lo
ad [
GW
]
Hour of the Day
Scenario PV: 60 GW Wind: 60 GW
Scenario PV: 30 GW Wind: 30 GW
©FfE MOS_00064
27 27
Limitations in Price Fluctuations
Volatility of the Residual Load
• Minimum in the morning and during noon
• Maximum during early noon and evening
Choose timeframes according to this observation in order to analyze the
dynamics of the residual load
0
10
20
30
40
50
60
1 3 5 7 9 11 13 15 17 19 21 23
Re
sid
ual
Lo
ad [
GW
]
Hour of the Day
Scenario PV: 60 GW Wind: 60 GW
Scenario PV: 30 GW Wind: 30 GW
©FfE MOS_00064
28 28
Limitations in Price Fluctuations
Volatility of the Residual Load
Minimum of the Residual Load within Timeframe
Diffe
ren
ce
be
twe
en
th
e M
axim
imu
m a
nd
Min
imu
m o
f
the
Re
sid
ua
l L
oa
d w
ith
in u
se
d T
ime
fra
me
s
29 29
Limitations in Price Fluctuations
Volatility of the Residual Load
Minimum of the Residual Load within Timeframe
Diffe
ren
ce
be
twe
en
th
e M
axim
imu
m a
nd
Min
imu
m o
f
the
Re
sid
ua
l L
oa
d w
ith
in u
se
d T
ime
fra
me
s
30 30
Limitations in Price Fluctuations
Volatility of the Residual Load
Today
Minimum of the Residual Load within Timeframe
Diffe
ren
ce
be
twe
en
th
e M
axim
imu
m a
nd
Min
imu
m o
f
the
Re
sid
ua
l L
oa
d w
ith
in u
se
d T
ime
fra
me
s
31 31
Today
Limitations in Price Fluctuations
Volatility of the Residual Load
Minimum of the Residual Load within Timeframe
Diffe
ren
ce
be
twe
en
th
e M
axim
imu
m a
nd
Min
imu
m o
f
the
Re
sid
ua
l L
oa
d w
ith
in u
se
d T
ime
fra
me
s
32 32
Limitations in Price Fluctuations
Volatility of the Residual Load
Today
Minimum of the Residual Load within Timeframe
Diffe
ren
ce
be
twe
en
th
e M
axim
imu
m a
nd
Min
imu
m o
f
the
Re
sid
ua
l L
oa
d w
ith
in u
se
d T
ime
fra
me
s
33 33
Limitations in Price Fluctuations
Volatility of the Residual Load
Today
Minimum of the Residual Load within Timeframe
Diffe
ren
ce
be
twe
en
th
e M
axim
imu
m a
nd
Min
imu
m o
f
the
Re
sid
ua
l L
oa
d w
ith
in u
se
d T
ime
fra
me
s
34 34
Limitations in Price Fluctuations
Volatility of the Residual Load
Today
Minimum of the Residual Load within Timeframe
Diffe
ren
ce
be
twe
en
th
e M
axim
imu
m a
nd
Min
imu
m o
f
the
Re
sid
ua
l L
oa
d w
ith
in u
se
d T
ime
fra
me
s
35 35
Limitations in Price Fluctuations
Volatility of the Residual Load
Today
Minimum of the Residual Load within Timeframe
Diffe
ren
ce
be
twe
en
th
e M
axim
imu
m a
nd
Min
imu
m o
f
the
Re
sid
ua
l L
oa
d w
ith
in u
se
d T
ime
fra
me
s
36 36
Limitations in Price Fluctuations
Volatility of the Residual Load
Today
Minimum of the Residual Load within Timeframe
Diffe
ren
ce
be
twe
en
th
e M
axim
imu
m a
nd
Min
imu
m o
f
the
Re
sid
ua
l L
oa
d w
ith
in u
se
d T
ime
fra
me
s
37 37
Today
Limitations in Price Fluctuations
Volatility of the Residual Load
Power 2 Heat + 2 GW
Power 2 Gas + 0 – 2 GW
Electromobility + 0.5 – 2 GW
Flexibilization of Load +/- 1 – 2 GW
Pumped Hydro Storage +/- 2 - 3 GW
Increased Im-/Export capacities +/- 2 - 3 GW
…educated guessing on how storage technologies can influence the residual load
12 GW – possible shift
by storage technologies
38 38
Limitations in Price Fluctuations
Volatility of the Residual Load
Though plenty of the points lie
within the grey shaded area we will
have to expect significant price fluctuations! Today
39 39
Limitations in Price Fluctuations
Day-Ahead-Analysis
Price follows predominantly the residual load
Several occurences of negative prices
y = 0.0014x - 22.575
-250-200-150-100
-500
50100150200250
0 20 40 60 80
Day
-Ah
ead
Pri
ce in
€/M
Wh
Residual Load in GW
©FfE MOS-KOSI_00044
Conclusion:
No predominant influence of RES in price building mechanism visible
40 40
Limitations in Price Fluctuations
Events of Negative Prices
DA-Price = Day-Ahead Price, Data-Source: transparency.eex.com
Extrema of the day in GW
Solar Wind Coal Lignite Nuclear
Min 0 10.229 1.147 9.186 8.564
Max 4.843 18.416 2.506 12.258 11.121
-250
-200
-150
-100
-50
0
50
100
0
10
20
30
40
50
60
70
Day
-Ah
ead
-Pri
ce in
€/M
Wh
Pro
du
cito
n in
GW
Production Tue., 25.12.2012
Solar
Wind
Others
Coal
Lignite
Nuclear
DA-Price
©FfE MOS-KOSI_00012
41 41
Limitations in Price Fluctuations
Schemes of Remuneration
The German Renewable Energy Act offers choice of the scheme of
remuneration for feed-in.
* +/- + =
= Earnings by
Feed-In-Tariff
[EUR]
-
+
=
*
Earnings by Direct Selling
and Market Bonus
[EUR]
Remuneration for
Feed-In Rate
[EUR/MWh]
Feed-In
[MWh]
Revenue at European
Energy Exchange
[EUR]
Market Bonus
[EUR/MWh]
Feed-In
[MWh]
Imbalance Energy
Payments
[EUR]
Management Bonus
[EUR/MWh]
Remuneration for
Feed-In Rate
[EUR/MWh]
Monthly Weighted
Average Price
[EUR/MWh]
42 42
Limitations in Price Fluctuations
Direct Selling and Negative Prices
25.12.2012: Prices should not have fallen below:
-81 €/MWh
12.00 €/MWh 91.00 €/MWh 21.98 €/MWh 81.02
€/MWh
- + Management
Bonus
Remuneration
for Feed-In Rate
Monthly Weighted
Average
Market
Bonus =
- + =
43 43
Limitations in Price Fluctuations
Development in the capacity of Direct-Selling
Hydro Gas Biomass Wind Offshore Solar Total in MW
Jan 2012 344 67 933 12.062 48 59 13.513
Jun 2012 392 42 1.433 19.884 238 828 22.817
Nov 2012 445 43 1.836 23.409 308 1.961 28.002
Apr 2013 451 57 2.328 24.484 333 3.012 30.670
0
10
20
30
Jan
uar
y 2
01
2
Feb
rura
y 2
01
2
Mar
ch 2
01
2
Ap
ril 2
01
2
May
20
12
Jun
e 2
01
2
July
20
12
Au
gust
20
12
Sep
tem
be
r 2
01
2
Oct
ob
er 2
01
2
No
vem
ber
20
12
Dec
emb
er 2
01
2
Jan
uar
y 2
01
3
Feb
ruar
y 2
01
3
Mar
ch 2
01
3
Ap
ril 2
01
3
Cap
acit
y in
GW
PV Wind (Offshore)
Wind Biomass
Gas Hydro
©FfE MOS_00109
44 44
Limitations in Price Fluctuations - Conclusion
The expected increase of price fluctuations can be limited by
storage technologies to a certain extend
Downwards?
Limited by marginal costs of emerging storage technologies
Depending on available power and capacity
Limited by the remuneration scheme of direct selling
Upwards?
Hard coal as well as gas prices
Decharging capacity of storage technologies
Flexibilization of Load
Electromobility (depending on charging strategy)
45 45
Limitations in Price Fluctuations - Conclusion
Which Markets will have to deal with increasing price fluctuations?
Day-Ahead:
Sufficient capacity
Rare occurrences of extremely low prices chance for DSM?
Control reserve:
Minute Reserve: hardly any revenues possible
Secondary Control Reserve:
Positive: extremely low revenues, going down to zero
Negative: still attractive for some applications
Intraday:
Low online-capacity demand for high flexibility high price volatility
expected.
high uncertainty (grid restrictions, …)
46 46
Thank you for your attention and the support of
Tim Buber: [email protected] / +49-89-158-121-44
Forschungsgesellschaft für Energiewirtschaft mbH
Am Blütenanger 71
80995 München
www.ffegmbh.de
Top Related