1. business and industrial
2. energy
3. renewable energy
4. wind energy

The Power of Transformation
Wind, Sun and the
Economics of Flexible Power Systems
Dr. Paolo Frankl
Head, Renewable Energy Division
International Energy Agency
Intercontinental Wind Power Congress 2015, Istanbul, 1 April 2015
© OECD/IEA 2014
Large-scale integration accomplished today,
but more to come
Denmark
Ireland
IberianIberia
pen.
•vRE shares depend on
flexibility of rest of the system
•Instantaneous shares reaching
60% and above
•Higher shares locally:
Wind in Tamil Nadu (India)
approx. 13%
Germany
Great Britain
Italy
NW Europe
ERCOT
Sweden
France
India
Brazil
VRE share of total annual electricity output
Japan
Case
studies
© OECD/IEA 2014
0%
5%
Wind 2012
10%
PV 2012
15%
20%
25%
30%
Additional Wind 2012-18
35%
40%
45%
Additional PV 2012-18
Note: ERCOT = Electricity Reliability Council of Texas, United States
Source: IEA estimates derived in part from IEA Medium-Term Renewable Energy Market Report 2013.
© OECD/IEA 2014
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Three main results
1.
Very high shares of variable renewables
are technically possible
2.
No problems at low shares,
if …
3.
Reaching high shares cost-effectively
calls for a system-wide transformation
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© OECD/IEA 2014
3
No problem at 5% - 10%, if …
 Power systems already deal with a vast demand variability
 Can use existing flexibility for VRE integration
Exceptionally high variability in Brazil, 28 June 2010
 No technical or economic challenges at low shares,
if basic rules are followed:
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 Avoid uncontrolled, local ‘hot spots’ of deployment
 Adapt basic system operation strategies, such as forecasts
 Ensure that VRE power plants are state-of-the art and can stabilise the grid
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Challenge at higher vRE shares:
Balancing
Illustration of Residual power demand at different VRE shares
0.0%
 Higher
80
uncertainty
 Larger and
more
pronounced
changes
70
2.5%
5.0%
10.0%
20.0%
Net load (GW)
60
50
40
Larger
ramps
at high
shares
30
20
10
0
1
10 20 30 40 50 60 70 80 90 100 110 120 130 140
Hours
Note: Load data and wind data from Germany 10 to 16 November 2010, wind generation scaled, actual share 7.3%. Scaling may overestimate the impact of variability;
combined
of wind and solar may be lower, illustration only.
© OECD/IEA effect
2014
© OECD/IEA 2014
5
Main persistent challenge: Utilisation
 Netload implies different utilisation for non-VRE system
90
0.0%
2.5%
5.0%
10.0%
Maximum 80
remains high:
Scarcity 70
20.0%
Peak
Net load (GW)
Peak
60
Midmerit
50
Midmerit
40
Changed utilisation
pattern
30
20
Baseload
Lower
minimum:
Abundance
10
Baseload
0
1
2 000
4 000 Hours 6 000
8 000
Note: Load data and wind data from Germany 10 to 16 November 2010, wind generation scaled, actual share 7.3%. Scaling may overestimate the impact of variability;
combined
of wind and solar may be lower, illustration only.
© OECD/IEA effect
2014
© OECD/IEA 2014
6
Three pillars of system transformation
of power
plants
System
friendly
VRE
© OECD/IEA 2014
2.
Make better use of
what you have
Operations
1.
Let wind
Geographic
spread
and
solar
play their
part
Design
Investments
Technology
spread
3.
Take a system wide-strategic
approach
to investments!
© OECD/IEA 2014
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1) System friendly VRE deployment
 Wind and solar PV
can contribute to grid
integration
 But only if they are
allowed and asked to
do so!
Take a system
perspective when
deploying VRE
Market premiums
step in right direction
© OECD/IEA 2014
Example: System friendly design of
wind turbines reduces variability
Source: adapted from Agora, 2013
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2) Better system & market operation
 VRE forecasting
Example: ERCOT market design
 Better market operations:
 Fast trading
Best practice:
US (Texas) – 5 minutes
 Price depending on location
Best practice: US –
Locational Marginal Prices
 Better flexibility markets
Example: Fully remunerated reserve
provision
 Align system and market operation
Example: US Independent System Operators
 Make better use of what you have
already!
© OECD/IEA 2014
© OECD/IEA 2014
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3) Investment in additional flexibility
Four sources of flexibility …
Grid
infrastructure
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Dispatchable
generation
Storage
Demand side
integration
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Total system costs (USD/MWh)
Cost-effective integration means
transformation of power system
Grid cost
140
+40%
120
+10-15%
100
DSI
80
Fixed VRE
60
Emissions
40
Fuel
20
Startup
0
Legacy
low grid costs
0% VRE
Legacy
high grid costs
Transformed generation &
8% DSI, low grid costs
45% VRE penetration
Fixed
non-VRE
Test System / IMRES hourly dispatching optimization Model
 Large shares of VRE can be integrated cost-effectively
 Significant optimization on both fixed and variable costs
© OECD/IEA 2014
© OECD/IEA 2014
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Benefit/cost of flexibility options
North West Europe
Benefit/cost ratio
2.3
2.2
0.6 - 1.5
1.2
1.1
1.1
IC
Storage + IC
Storage
1
DSI + IC
DSI
Flexible gas supply = 1
Hydro capacity
boost
 DSI has large benefits at comparably low costs
 Interconnection allows a more efficient use of distributed flexibility options
and generates synergies with storage and DSI
 Cost effectiveness of hydro plant retrofit depend on project specific
measures and associated investment needs
Notes:
1) CAPEX assumed for selected flexibility options: interconnection 1,300$/MW/km onshore and 2,600$/MW/km offshore, pumped hydro storage 1,170$/kW, reservoir
hydro 750 $/kW -1,300$/kW (repowering of existing reservoir hydro increasing available capacity). Cost of DSI is assumed equal to 4.7 $/MWh of overall power
demand (adjustment of NEWSIS results)
2) Fuel prices and CAPEX ($/kW) for VRE and flexibility options are assumed constant across all scenarios
© OECD/IEA
2014
© OECD/IEA 2014
Source:
IEA/PÖYRY
12
Recommendations 1/2
 All countries where VRE is going mainstream should:
 Optimise system and market operations
 Deploy VRE in a system-friendly way to maximise their value
to the overall system
 Countries beginning to deploy VRE power plants (shares
of up to 5% to 10% of annual generation) should:
 Avoid uncontrolled local concentrations of VRE power plants
(“hot spots”)
 Ensure that VRE power plants can contribute to stabilising the
grid when needed
 Use state of the art VRE forecast techniques
© OECD/IEA 2014
© OECD/IEA 2014
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Transformation depends on context
Recommendations 2/2
Dynamic
Power Systems
Stable Power
Systems
• Little general
investment need
short term
Dynamic demand growth*
• Large general
investment need
short term
Slow demand growth*
Maximise the contribution
from existing flexible assets
Decommission or mothball
inflexible polluting surplus
capacity to foster system
transformation
Implement holistic, long-term
transformation from onset
Use proper long-term planning
instruments to capture VRE’s
contribution at system level
* Compound annual average growth rate 2012-20 , slow <2%, dynamic ≥2%; region average used where country data unavailable
OECD/IEA
2014
This©map
is without
prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area.
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 Round Table
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