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Renewable Energy for Electricity
Simon Müller
Analyst, Renewable Energy Division
5 April 2013
© OECD/IEA 2011
The source of all RE Energy
© OECD/IEA 2011
Forms of Primary RE Energy
Solar
Wind
Hydro
Ocean
Bioenergy
Geothermal
• Radiation
• Movement
• Movement
• Movement
• Heat
• Heat
© OECD/IEA 2011
How can we “make” electricity?
There are only two ways that we use mass scale!
1. Movement (often via heat)
Direct: Wind, Hydro, Ocean
Heat: Bioenergy, geothermal, CSP
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How can we “make” electricity?
2. Photoelectric effect
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What is a Watt? What is a Watt-hour? A Watt-hour measures energy!
Running your mobile phone one hour: 0.1 Wh
Running your computer one hour: 10 Wh
Running a water boiler one hour: 1 000 Wh = 1kWh
Running the IEA for one hour: 250 000 Wh = 0.25 MWh
Running Paris for 1 hour: 2 000 000 000 Wh = 2 GWh
Running the World for one hour 3 000 000 000 000 = 3 000 GWh = 3 TWh
A Watt measures energy per time!
A human: 100 W
A solar panel: 200 W
A wind turbine: 2 000 000 W = 2 MW
Large offshore windpark 1 000 000 000 W = 1 GW
© OECD/IEA 2011
Hydro power Sub-types
Reservoir
Run of river
Pumped
Itaipu Dam, Brazil, 14GW
Goldistal Pumped , Germany, 1 GW
Size
Large: 100 MW – 15 GW
Small: 100 kW – 300 MW
Stats (2011)
3644 TWh
Approx 1000 GW
16.2% of global el (2009)
Cost
18 – 100 USD/MWh
1 - 2 mio USD/MW
1-15 bn USD for a large plant
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Geothermal Sub-types
Flash
Binary
Itaipu Dam, Brazil, 14GW
Flash geothermal plant
Size
Flash: 10 MW – 250 MW
Binary: 12 MW –20 MW
Stats (2009)
66 TWh
0.33% of global electricity
Cost
Flash: 50 – 80 USD/MWh
Binary: 60-200 USD/MW
2-4 mio USD/MWh Flash
2.5-6 mio USD/MWh Binary
© OECD/IEA 2011
Wind power Sub-types
Onshore
Offshore
Xinjiang, China
Size
Turbine: 1 – 6 MW
Farm: 100 MW – 1000 MW
Stats (2011)
420 TWh
240 GW (2011)
Cost for onshore
40 – 160 USD/MWh
1.1 – 2.3 mio USD/MW
1 bn USD for a large farm
Cost for offshore
140 – 300 USD/MWh
3 – 6? mio USD/MW
5 bn USD for a large farm
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© OECD/IEA 2011
© OECD/IEA 2011
Bioenergy Sub-types
Biomass (cofiring)
Biogas
Biogas digester
Biomass plant, Pfaffenhofen, Germany, 6 MW
Size
Large: 100 kW – 100 MW
Cofiring: 20 – 100s MW
Stats (2011)
307 TWh
1.3% of global electricity
Cost
70 – 150 USD/MWh
20 – 70 USD/MWh (cofiring)
2.6 – 4.1 mio USD/MW
300 mio USD for a large plant
© OECD/IEA 2011
Solar CSP
Sub-types
Trough
Tower
Dish
Tower system
Size
1 - 250 MW
Stats (2011)
3.77 TWh
Cost
180 – 300 USD/MWh
4.2 – 8.2 mio USD/MW
500 mio USD for a large system
Kramer Junction, Nevada
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Solar PV
Sub-types
Silicone
Thin film
PV rooftop system
Size
Panel: abt 200 W
System: 1 kW – 250 MW
Stats (2011)
65 TWh (100 TWh)
70 GW (100 GW 2012)
0.1% of global electricity
Cost
100 – 300 USD/MWh
1.x – 5 mio USD/MW
100 mio USD for a large park
40 MW solar farm, Germany
© OECD/IEA 2011
Cost of Electricity generation
Source: Bloomberg New Energy Finance
© OECD/IEA 2013
Grid Integration of Variable Renewables
Phase III
April 2013
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Grid integration of variable renewables 2011: IEA published technical
assessment of integration
Key points:
Case-study approach
No principle technical ceiling
Feasible share of variable RE depends on system flexibility Flexible supply
Storage
Interconnections
Demand side response
New phase:
Refined definition and assessment of flexibility economics
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GIVAR III Structure
Market design and policy recommendations
FAST 2
Variable RE Impact Analysis
IMRES
Flexible Resources Analysis
Case Studies • Market design review • Data questionnaire • Stakeholder interviews
Desk research • Cost of flex options • Technical characteristics of flex options • Integration studies
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FAST 2
Video preview of FAST2
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Economics of flexibility
Systems are different – impacts will vary too
But common groups of effects
Uncertainty
Reserves
Distant resources
Transmission grid
Modularity
Distribution grid
Variability
Cycling / start-ups
Abundance Scarcity Capital
utilisation
Grid costs Higher
operational costs
Curtail-ment
Cost of complementary /
back-up generation
Cost of holding
reserves
Cost effective integration strategies needed to minimise these costs: Interconnection, demand side response,
flexible generation and storage
Optimised operations and variable renewables deployment
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Better operational tactics - Germany
Despite the increase in variable renewables, cooperation between four TSOs has led to cost savings
Source: Hirth, Ziegenhagen, 2013
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Spain – geospread of wind generation
Wind power capacity in Spain is broadly distributed across the country
Installed wind capacity and network structure (Jan 2012)
Total power flows (2011)
Source; REE – 2011 Annual Report and Presentations: ”Impact of RES on the ancillary services”, 24 May 2011; “Integrating renewable energy into the Spanish energy networks –Technology challenges”, 15 September 2010
\
© OECD/IEA 2013
Modelling benefit of flexibility
Generic power system to study flexibility options:
Designed to capture different properties of real systems
12 GW of nuclear; fairly inflexible coal (70% minimum output); other plants decided by capacity expansion model at 0% var RE
German load and variable RE generation profile
Two baseline scenarios: 30% and 45% wind and solar (2/3 to 1/3)
Add a flexibility option to the system
Value calculated as difference in total costs
Baseline case
with flex option
Co
sts
Benefit of flexibility
Reduced operational costs
Reduced curtailment
Less costly complementary plant mix
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First results – costs of thermal system
Cost per MWh from thermal system under different penetration levels and flexibility options
Relevant assumptions: WACC 7%, CO2 30USD/tn, GAS 8 USD/MBTU, COAL 2.7 USD/MBTU
Up to 35% reduced increase
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Key adaptation factor: utilisation of assets
Non-varRE system costs increase if fuel savings outweigh capital utilisation effect
Cost effective adaptation means dealing with changed capital utilisation!
0
5000
10000
15000
20000
25000
30000
35000
Baseline 0%
Baseline 45%
Adapted 45%
mill
ion
USD
pe
r ye
ar
MWh costs in baseline driven by two factors:
Saved fuel (-)
Less MWh to recover CAPEX (+)
© OECD/IEA 2013
So what are these solutions?
Find assets that have a low utilisation anyway and make them provide flexibility!
Electric water heaters
Electric cars (if they are around …)
Water pumps etc.
Take all measures that increase utilisation of existing and new assets
Last option: deploying high CAPEX solutions with low utilisation (battery storage)
© OECD/IEA 2013
Conclusions
Wind and solar generation can cause additional system level costs
These costs are a result of the interaction with the system, they are caused by varRE as well as by the existing system
Smart approaches exist to mitigate these costs
1. First priority: Better operational tactics
2. Second priority: Grid friendly varRE deployment and integrated planning
3. Third priority: Deploy new assets to help integration (low capex is key!)
