The structural impact of renewable
portfolio standards and feed-in-tariffs
on electricity markets
John R. Birge, University of Chicago Booth School of Business
Joint work with:
Ingmar Ritzenhofen, WHU – Otto Beisheim School of Management
Stefan Spinler, WHU – Otto Beisheim School of Management
June 25, 2015
SOURCE: http://viaenergetiki.files.wordpress.com/2010/10/2-rakstam.jpg
Content
(1) Motivation for research project
(2) Modeling approach
(3) Discussion of results
(4) Conclusion
1
(1) RES1 – in particular wind and solar PV – are fast
growing technologies for electricity generation
Annual investment in RES capacity2
Billion USD
Other
Global RES capacity2
GW
Solar
Wind
480
279
+26% p.a.
227
+22% p.a.
244
24
315
172 168
146
97 +90
100
250
140
200
42% of
global
new
capacity
165
100
99
65
40
390
115
134
283
80
2004 05 06 07 08 09 10 11 2012
2004 05 06 07 08 09 10 11 2012
1 Renewable energy sources for electricity generation; 2 Excluding large hydro power
SOURCE: REN21 (2005-2013), UNEP, Bloomberg (2013)
2
(1) FITs1 are the most widespread RES support schemes in
2013 present in 71countries
FIT scheme
No FIT scheme
FIT schemes are employed in
▪ 71countries
▪ 28 states and provinces
1 Feed-in-tariffs
SOURCE: REN21 (2013)
3
(1) RPS1 are the second most widespread RES support
scheme present in 22 countries and 54 states/provinces
RPS / quota scheme
No RPS / quota scheme
RPS / quota schemes are employed in
▪ 22 countries
▪ 54 states and provinces
1 Renewable portfolio standards and quota systems
SOURCE: REN21 (2013)
4
(1) The electricity sector is the main energy consumer and
carbon emitter in the US
Share of energy
expenditures in US GDP
% of total
2000
7
2001
7
2002
2003
2004
Electricity
6
7
Split of US total CO2
emissions
% of total
40
Transportation
28
Electricity
38
Transportation
31
7
2005
8
Industrial
2006
9
2007
9
2008
2009
Split of US total energy
consumption
% of total
10
8
2010
SOURCE: EIA (2013), EPA (2013)
Residential,
commercial
21
11
Industrial
14
Residential,
commercial
Other
10
6
8
5
(1) RES1,2 account for an increasing share in global
electricity generation and capacity
RES share in new global capacity
% of added power capacity
Split between RES and conventional power
%
Conventional Renewable
42
36
Global final
energy consumption
81
19
Global electricity
production
78
22
Installed electricity
generation capacity
74
26
29
26
15
15
10
23
10
2004 05 06 07 08 09 10 11 2012
1 Renewable energy sources for electricity generation; 2 Excluding large hydro power
SOURCE: REN21 (2013), UNEP, Bloomberg (2013)
6
Renewable Portfolio Standard Policies..
www.dsireusa.org / March 2013.
29 states,+
Washington DC and 2
territories,have
Renewable Portfolio
Standards
(8 states and 2 territories have
renewable portfolio goals).
Renewable Portfolio Standard Policies
with Solar / Distributed Generation Provisions.
www.dsireusa.org / March 2013.
16 states,+
Washington DC have
Renewable Portfolio
Standards with Solar
and/or Distributed
Generation provisions
(1) Governments support RES deployment through different
policy mechanisms – we focus on FIT and RPS
Focus
of paper
RES support
schemes1
Price-based
Description
Feed-in-tariffs (FIT)
Production tax
credits (PTC)
Renewable portfolio
standards (RPS)
Tender regimes
(TR)
▪ Purchase
▪ Grant of tax credits
▪ RES quota
▪ Reverse auction of
guarantee of RES
electricity at
subsidized rates
for a predetermined period of time
▪ Typical designs
either as fixed FIT
or FIT premium
Country
examples
Quantity-based
Canada, Denmark,
Germany, India,
Spain, South Africa
for RES electricity
generated for a
predetermined
period of time
▪ Scheme often
combined with
other RES support
systems
U.S.
requirement for
utilities
▪ Typically marketbased system
using tradable
renewable energy
certificates (RECs)
as additional
revenue source for
RES developers
U.S. (e.g. IL, CA,
TX), UK, Sweden,
Belgium, Australia
1 Only operation-oriented, excluding environmental protection or emission reduction schemes such as EU ETS
SOURCE: Mormann (2012), REN 21 (2013), KPMG (2012)
specific (larger)
RES projects for a
predetermined
period of time
▪ Long-term power
purchase
agreements
China, Denmark,
France, Ireland, UK,
U.S.
9
(1) A research gap exists for the comparison of RES support
schemes accounting for market effects
Research gap
Comparisons:
Mendonça et al. (2009)
Haas et al. (2010 & 2011)
Mormann (2012)
Single analyses:
RES
support
schemes
assessments
Cory et al. (2009)
Chen &Cliff (2009)
Couture & Gagnon (2010)
Ragwitz et al. (2012)
Jensen & Skytte (2002)
Boomsma et al. (2013)
Tanaka, Chen (2013)
Fagiani et al. (2013)
Detailed
numerical
assessments
Full
market
models
Hobbs (1995)
Eager et al. (2012)
DECC (2013)
Research question
What is the impact of renewable portfolio standards (RPS), feed-in-tariffs (FIT) and
market premia (MP) on affordability, security of supply, and sustainability of the
electricity generated?
SOURCE: Literature review
11
Content
(1) Motivation for research project
(2) Modeling approach
(3) Discussion of results
(4) Conclusion
12
(2)
We compare RES support schemes using a quantitative
generation capacity expansion model
Research question
What is the impact of renewable portfolio standards (RPS), market premia (MP), and feed-in-tariffs
(FIT) on the three key electricity policy dimensions of
▪ Affordability approximated by total cost and electricity prices
▪ Security of supply approximated by lost load occasions and electricity price volatility
▪ Sustainability approximated by CO2 emissions
Model requirements
Details
Reflection of market reactions
and strategic investor behavior
▪ Market instead of central command-and-control perspective needed
▪ Need to account for price sensitivity of demand instead of only
generation-focused cost-minimization perspective
▪ Strategic bidding required and profitability/project value approach
needed instead of pure cost focus on investor level
Reflection of long-term
investments and real-time
supply and demand matching
▪ Extended time horizon exceeding lifetime of most plants
▪ High granularity of time steps required given increasing intermittent
Focus on comparison between
support schemes
▪ Setting in liberalized electricity market with stable regulatory and
generation as well as ramping constraints
economic environment allowing to use deterministic inputs
▪ Investors deciding rationally and using profitability considerations
▪ Abstraction from transmission constraints and technical feasibility
13
(2) The three support schemes analyzed exhibit different
degrees of market-integration
𝑥 = 𝑒𝑛𝑑𝑜𝑔𝑒𝑛𝑜𝑢𝑠 𝑣𝑎𝑟𝑖𝑎𝑏𝑙𝑒
𝑃 = 𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 𝑝𝑟𝑖𝑐𝑒
𝑥 = 𝑒𝑥𝑜𝑔𝑒𝑛𝑜𝑢𝑠, 𝑐𝑜𝑛𝑠𝑡𝑎𝑛𝑡 𝑣𝑎𝑟𝑖𝑎𝑏𝑙𝑒 𝜋 = 𝑡𝑜𝑡𝑎𝑙 𝑟𝑒𝑣𝑒𝑛𝑢𝑒 𝑝𝑒𝑟
𝑢𝑛𝑖𝑡 𝑜𝑓 𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦
High
𝑃𝑅𝐸𝐶 = 𝑅𝐸𝐶 𝑝𝑟𝑖𝑐𝑒
𝐹𝐼𝑇 = 𝑓𝑒𝑒𝑑- 𝑖𝑛 -𝑡𝑎𝑟𝑖𝑓𝑓
𝑀𝑃 = 𝑚𝑎𝑟𝑘𝑒𝑡 𝑝𝑟𝑒𝑚𝑖𝑢𝑚
𝐸 = 𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦
Level of market integration
E
Low
RPS
Market premium
FIT
Renewable
generators
Renewable
generators
Renewable
generators
$
$
Elec- REC1
tricity
𝜋 = 𝑃 + 𝑃𝑅𝐸𝐶
E
$
$
E
Elec- MP
tricity
𝜋 = 𝑃 + 𝑀𝑃
$
FIT
𝜋 = 𝐹𝐼𝑇
▪ RES generators’ revenue depends on electricity market prices under RPS and MP
▪ RES generators are perfectly isolated from electricity prices under FIT
1 Renewable energy certificates
14
(2) The three support schemes analyzed exhibit different
degrees of market-integration
𝑅𝑒𝑣𝑒𝑛𝑢𝑒𝑠 𝑎𝑡 𝑚𝑎𝑟𝑘𝑒𝑡 𝑝𝑟𝑖𝑐𝑒𝑠
𝑃 = 𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 𝑝𝑟𝑖𝑐𝑒
𝑃𝑅𝐸𝐶 = 𝑅𝐸𝐶 𝑝𝑟𝑖𝑐𝑒
𝐹𝐼𝑇 = 𝑓𝑒𝑒𝑑- 𝑖𝑛 -𝑡𝑎𝑟𝑖𝑓𝑓
𝑅𝑒𝑣𝑒𝑛𝑢𝑒𝑠 𝑢𝑛𝑑𝑒𝑟 𝑠𝑢𝑝𝑝𝑜𝑟𝑡 𝑠𝑐ℎ𝑒𝑚𝑒
𝜋 = 𝑡𝑜𝑡𝑎𝑙 𝑟𝑒𝑣𝑒𝑛𝑢𝑒 𝑝𝑒𝑟
𝑢𝑛𝑖𝑡 𝑜𝑓 𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦
𝑀𝑃 = 𝑚𝑎𝑟𝑘𝑒𝑡 𝑝𝑟𝑒𝑚𝑖𝑢𝑚
𝐸 = 𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦
High
Level of market integration
𝑃𝑅𝐸𝐶 = 0
𝑀𝑃
FIT
𝜋 ($/𝑀𝑊ℎ)
Market premium
𝜋 ($/𝑀𝑊ℎ)
𝜋 ($/𝑀𝑊ℎ)
RPS
Low
𝑃𝑅𝐸𝐶
𝐹𝐼𝑇
𝑃 ($/𝑀𝑊ℎ)
𝑃 ($/𝑀𝑊ℎ)
𝑃 ($/𝑀𝑊ℎ)
▪ RECs are priced as follows: PREC=max(LC-P+MC; 0) and thus fully compensate for price decreases
▪ Market premium guarantees a fixed premium over P
▪ FITs are constant and fully independent of P
1 Which is identical as we still abstract from the effects of different risk profiles under the three schemes
15
(2) In a stylized RPS market model we endogenously derive
electricity/REC1 prices and capacity investments
Example of RPS scheme
Market
Conventional
generators
Conventional
(annual invest & hourly
generators
dispatch per standard plant
E
E
& technology)
$
REC
$
Electricity
market
Electricity
market
(hourly dispatch)
Exogenous player
Renewable
generators
Renewable
(annual invest & hourly
generators
dispatch per standard plant
E
& technology)
Endogenous player
$
REC
Retailers / obliged
Retailers
/ obliged
2
entities
2
(hourly entities
aggregate demand
REC
Regulator
1 market
REC
1 market
REC
(annual clearance)
$
Data
Regulator
(ex ante
announcement of
all annual quotas)
$
REC
Quota
curve)
E
$

$
Electricity
Electricity 3
consumers
consumers3
(not simulated explicitly)
1 Renewable energy certificates; 2 Utilities, transmission and distribution operators or others depending on local
regulation; 3 Households, industry, and others; sometimes these are also the obliged entities depending on regulation





Investor behavior
Market reactions
Strategic bidding
(Long-term focus)
High granularity
16
(2) We first compute an initial forecast and then iterate
actual updates
Initial forecast
Cost-optimal
conventional
generation
portfolio1
Actual iterations
Electricity
market
Updated
generation
portfolio
Electricity
prices
REC market
Repeat T
times for i
iterations
REC prices
Investor
decisions
on capacity
Investors decisions include
▪ Plant retirements at end of useful life
▪ Divestitures given lacking profitability
based on initial forecast/prior iteration
▪ New investments given positive expected
NPV based on initial forecast/prior iteration
1 given a specific RES quota
Stopping
after convergence






Investor behavior
Market reactions
Strategic bidding
Long-term focus
High granularity
Tractability
17
(2) We derive price-quantity equilibria on an hourly basis
for the electricity and annually for the REC market
Electricity price formation
(per hour)
REC price formation
(per year)
Marginal costs / price
Marginal (net) costs / price
ILLUSTRATIVE
Demand
Supply
Capacity
Demand
κ
Supply
Quantity of
electricity
▪
Prices are determined through equilibrium models both for the electricity
and REC markets
▪
Demand curves and quotas are exogenously given and deterministic
according to energy agency forecasts / regulatory announcements
▪
Supply curves account for ramping constraints and renewable intermittency
18
(2) In a stylized MP model we endogenously derive
electricity prices and capacity investment
Example of market premium
Conventional
generators
E
Market
Exogenous player
Renewable
generators
E
$
Endogenous player
Info
$
$
$
Electricity market
Market premium
(payment for non-energy
Market premium
part of renewable electricity
Regulator
Regulator
(ex ante
announcement of
all premia)
production)
Info
E
$
Retailers / obliged
entities2





1 Renewable energy certificates; 2 Utilities, transmission and distribution operators or others depending on local regulation
Investor behavior
Market reactions
Strategic bidding
(Long-term focus)
High granularity
19
(2) In a stylized FIT market model we endogenously derive
electricity prices and capacity investment
Example of FIT scheme
Market
Conventional
generators
E
Exogenous player
Renewable
generators
$
E
Epriority dispatch
Electricity market
$
$
Feed-in-tariff
Regulator
Feed-in-tariff
(payment
for renewable
electricity production)
$
E
Endogenous player
Regulator
(ex ante
announcement of
all tariffs)
Info
$
Retailers / obliged
entities2





1 Renewable energy certificates; 2 Utilities, transmission and distribution operators or others depending on local regulation
Investor behavior
Market reactions
Strategic bidding
(Long-term focus)
High granularity
20
(2) The load duration curve provides first insights on the
technology mix needed to meet demand
ILLUSTRATIVE
4
9
x 10
Load duration curve
Residual load duration curve
8
7
Capacity [MW]
6
5
Peak load
4
3
2
Base load
1
0
0
1000
2000
3000
4000
5000
hours per year
6000
7000
8000
9000
21
(2) We model investment and divestiture decisions on a
technology level
Level of decision making
Investor 1
Description
Undifferentiated
By technology
Renewables
cluster
Investor 2
Entire generation park
Conventionals
By technology
By plant
On average and in the long run, non-profitable technologies will be divested and
investment in profitable technologies takes place despite different investor portfolios.
22
(2) The installed capacity is updated in three steps through
age retirement, divestitures and new investments
Step
Equations
1. Age retirement of all
plants reaching their
end of life
2. Divestiture of all plants
with negative
profitability below
certain threshold
3. Investment in new
plants with NPV
exceeding specific
thresholds
23
(2) Supply: The merit order shows available electricity
generation capacity in order of increasing marginal costs
Marginal costs
in EUR /MWh
Merit order of power generation
120
110
100
Nuclear
80
80
Lignite
60
60
40
40
CCGT
45
Coal
OCGT
Oil
20
5
0
0
▪
▪
10
20
30
40
50
60
70
80
90
Capacity
in GW
100
Nuclear and lignite as “classic” base load suppliers run all the time
OCGT and Oil as “classic” peak load suppliers only run a fraction of the year
SOURCES: Forschungsstelle für Energiewirtschaft e. V. (FfE)
24
(2) Market prices are derived based on the supply curve
from the merit order and the inelastic demand curve
Marginal costs
in EUR /MWh
Merit order of power generation
120
Demand 110
100
Price without
renewables
80
Supply
Variable
45
40
profits
60
40
Prices to clear
the market at
each point in
time for all
buyers and
suppliers are
set equal to the
marginal costs
of the marginal
supplier
80
60
20
5
0
0
▪
10
20
30
40
50
60
70
80
90
Capacity
in GW
Nuclear
Lignite
CCGT
Coal
OCGT
Oil
100
Through marginal costs pricing efficient short-term dispatching of available electricity supply
and demand is achieved with profits for all plants dispatched before the marginal supplier
SOURCES: Forschungsstelle für Energiewirtschaft e. V. (FfE)
25
(2) Introduction of renewables shifts supply curve to the
right and thereby reduces wholesale prices
Marginal costs
in EUR /MWh
Merit order of power generation
120
100
Price without
renewables
80
80
Renewables
Nuclear
60
Price with
renewables
60
40
40
Lignite
45
CCGT
Coal
Addt’ l renew- Supply
ables generation
5
0
20
0
0
▪
▪
110
Demand
10
20
30
40
OCGT
Oil
50
60
70
80
90
100 Capacity
in GW
Renewables are dispatched first given their (near) zero-costs, shifting the supply curve right
By pushing the prior marginal supplier out-of-the-money, wholesale prices are reduced
SOURCES: Forschungsstelle für Energiewirtschaft e. V. (FfE)
26
Content
(1) Motivation for research project
(2) Modeling approach
(3) Discussion of results
(4) Conclusion
27
(3) The California electricity market is dominated by gasfired and hydro generation as well as broad regulation
Californian electricity market
Key facts
Ranking compared to other U.S. States
▪ #1 in terms of population with 38.3 million
people in 2013
▪ #1 in terms of GDP with 1.96 trillion USD
in 2011
▪ #5 in terms of net electricity generation
with 201 TWh in 2011
▪ #2 in terms of non-hydro RES generation
with 27 TWh in 2011
Installed capacity
GW
Relevant key regulation
▪ Resource adequacy provisions: LongTerm Procurement Plans, Resource
Adequacy Requirements, and the
Capacity Procurement Mechanism
▪ CO2 cap-and-trade scheme
▪ Renewable portfolio standards (RPS)
▪ Production tax credits
▪ Investment tax credits
Solar PV
Wind onshore
Geothermal
Biomass
OCGT
CCGT
Nuclear
Hydro
2.3
6.5
2.6
1.6
38.4
8.1
2.2
13.5
SOURCES: EIA (2012), CAISO (2013), The California Energy Commission (2014), California Public Utilities Commission (2013)
28
(3) Model assumptions – technology factors
Technology
type
Size
GW
Solar PV
Life
years
1.0
25
2.2
2.7
Wind onshore
0.2
25
Geothermal
0.1
25
Biomass
0
25
OCGT
0.5
CCGT
Nuclear
Hydro
Invest
Mio. USD
0.6
0.2
SOURCE: EIA (2013), NREL (2010)
39.6
132.0
4.1
2.9
40
Mrg. cost
USD/MWh
14.1
93.3
35
0.9
13.2
35
0.7
7.0
Learning
%
-2.3
0.6
2.1
-1.6
105.6
5.5
Heat rate
GJ/MWh
0
24.7
5.6
100
2.2
Fixed cost
Th. USD
0.7
56.9
14.2
9.0
0.8
0
2.1
0.9
42.9
53.7
7.4
10.3
1.0
0.8
29
(3) Model assumptions – generation park
Technology
type
Solar PV
Init. Capa.
GW
6.5
Wind onshore
2.3
Geothermal
2.6
Biomass
1.6
OCGT
CCGT
Nuclear
Hydro
Age 1-10
#
Age 11-20
#
41
12
12
8.1
2.2
13.5
25
36
51
9
2
26
1
38.4
12
2
11
Age 21-30
#
34
33
Age 31-40
#
Age 41-50
#
0
0
0
0
0
0
0
0
67
32
0
2
1
1
0
0
0
1
0
0
0
0
5
SOURCE: California Energy Commission (2013)
4
18
30
50
200
45
180
40
160
35
140
30
120
25
100
20
80
15
60
10
40
5
20
-
Price in USD/MWh
Load in GW
(3) Model assumptions – sample year used
0
0
2000
4000
6000
Hour of the year in h
Load
SOURCE: California Energy Commission (2013)
8000
Price
31
(3) Model assumptions – time-series data used
RES quota
CO2 price
CO2 price in USD/t
RES quota in %
100
80
60
40
20
0
2014
2024
2034
2044
150
100
50
0
2014
2054
15
10
5
0
2014
2024
2034
2044
2034
2044
2054
Biomass price
Biomass in USD/GJ
Natural gas in USD/GJ
Natural gas price
2024
2054
SOURCE: EIA (2013), IRENA (2012), CA Resource Board (2014)
15
10
5
0
2014
2024
2034
2044
2054
32
(3) Assuming homogeneous investors and no differences in
risk profiles, schemes deliver mostly similar results
Total costs
Conventional capacity
300
GW
USD Billions
400
200
100
0
RPS
MP
FIT
▪ Homogeneous
investors
▪ Identical risk
RPS
Electricity price
MP
FIT
▪ Identical support
Loss of load occasions
70
60
50
40
30
20
10
0
profiles and
discount rates for
all schemes
rates for all
technologies under
MP and FIT
10
8
6
#
USD/MWh
Key assumptions
70
60
50
40
30
20
10
0
4
Key results
2
▪ (Nearly) identical
0
RPS
MP
FIT
RPS
Electricity price volatility
80%
0.8
Billion t
1.0
40%
20%
0%
FIT
CO2 emissions
100%
60%
MP
results across most
dimensions
▪ Much higher
electricity price
volatility under FIT
scheme
0.6
0.4
0.2
0.0
RPS
MP
FIT
RPS
MP
FIT
33
(3) Assuming homogeneous investors and no differences in
risk profiles, schemes deliver mostly similar results
100
100
100
80
80
80
60
60
60
GW
Installed total capacity
(FIT)
GW
Installed total capacity
(MP)
GW
Installed total capacity
(RPS)
40
40
40
20
20
20
0
0
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
34
(3) Assuming homogeneous investors and no differences in
risk profiles, schemes deliver mostly similar results
Key assumptions
USD/MWh
Average electricity price convergence
▪ Homogeneous
180
160
140
120
100
80
60
40
20
0
investors
▪ Identical risk
profiles and
discount rates for
all schemes
0
2
4
6
8
RPS
10
12
Iteration
MP
14
16
18
20
rates for all
technologies under
MP and FIT
FIT
Change in average electricity price
Key results
▪ (Nearly) identical
10
results across most
dimensions
5
%
▪ Identical support
0
0
2
4
6
8
10
12
-5
-10
Iteration
RPS
MP
14
16
18
20
▪ Much higher
electricity price
volatility under FIT
scheme
▪ Results converge
FIT
after 3-6 iterations
35
(3) Depending on the regulator's assessment of market
dynamics and investors, support scheme results differ
Base case
Heterogeneous investors
Different risk
profiles1
Differentiated
support
Increased
support by 2%
Lower solar
learning rate
by -1% point
1 Abstracting from regulatory risk
Key assumptions / assumptions
differing from base case
Key results / differences in results
compared to base case
▪ Homogeneous investors
▪ Identical risk profiles
▪ No support differentiation
▪ Similar results across dimensions
▪ Higher electricity price volatility for
▪ Heterogeneous investors
▪ More diverse RES investment across
FIT scheme
▪
▪ Different risk profiles for support
support schemes
Lower electricity price volatilities
▪ Lower total cost (in particular support
schemes reflecting certainty of
cashflows
scheme cost) under MP and FIT
schemes
▪ Differentiated support rates under
▪ Lower volatility but higher electricity
MP and FIT – highest for geothermal
▪ Increased support rates under MP
and FIT by 2%
▪ 1 percentage point decrease in
annual learning rate for solar
prices under MP and FIT
▪ Steep RES investment increase
under FIT rendering electricity
market dysfunctional
▪ Drop in solar investment
▪ Less RES investment and lower
volatility under MP and FIT
39
(3) This assessment crucially impacts which support
scheme is most advantageous
Key findings
RPS
MP
FIT
Base case
▪ Low volatility

▪ Low volatility

▪ High volatility

Heterogeneous investors
▪ Reduced volatility

▪ Reduced volatility

▪ Reduced volatility

Different risk
profiles1
▪ Identical cost

▪ Reduced cost

▪ Greatly reduced cost

Differentiated
support
▪ Not easily possible2

▪ Reduced volatility

▪ Reduced volatility

Increased
support by 2%
▪ High robustness

▪ Low robustness

▪ No robustness

Lower solar
learning rate
by -1pp
▪ High robustness

▪ Low robustness

▪ No robustness

1 Abstracting from regulatory risk; 2 only possible through separate market or different numbers of RECs allocated per
RES electricity generated contingent on technology used
40
Content
(1) Motivation for research project
(2) Modeling approach
(3) Discussion of results
(4) Conclusion
41
(4) While our results provide first insights, further research
is needed to understand impact of RES support schemes
Focus
Key findings
 RPS, MP, and FIT lead to increasing RES
Future research
 MP and in particular FIT can achieve these
Account for
uncertainty and
ambiguity factors
such as RES
generation
 MP and FIT can be more easily adjusted to
Analyze and
compare support
scheme robustness
in more depth
generation and decreasing conventional
generation as well as CO2 emissions
results at lower total cost when accounting
for different risk profiles but lead to higher
electricity price volatility
support specific technologies with potentially
beneficial impacts on the overall market
 RPS deliver more robust results in terms of
RES buildup and distort markets less in
case of inaccurate parameter estimations
Investigate the
impact of less static /
more flexible MP
and FIT designs
Key challenges
▪
At least two
stochastic
variables representing uncertain annual
output from
wind and solar
▪
Multiple scenarios to represent
all possible
states contingent on wind
and solar power
generation as
well as installed
capacity
42
Working paper and contact details
Working paper
The Structural Impact of Renewable Portfolio Standards
and Feed-in-Tariffs on Electricity Markets;
Available for download: http://ssrn.com/abstract=2418196
43
Backup
44
››› Facts
45
››› Model approach
46
(2) We derive the forecasted installed capacity in five steps
Step
Equations
1. Establish load duration
curve by putting hourly
load in descending order
2. Develop residual load
duration curve by
deducting RES feed-in
from LDC
3. Compute total cost per
unit of capacity dependent on run-time
4. Define screening curve
representing the least cost
technology per run-time
5. Map RLDC on SC to
derive cost-optimal
installed capacity per
technology and year
47
(2) We compute hourly electricity prices in five steps
Step
Equations
1. Compute available
capacity
2. Compute marginal cost
3. Establish supply curve
as step function
4. Define hourly demand
curve
5. Intersect supply and
demand functions to
establish hourly
electricity price
48
(2) When accounting for ramping constraints we need to
adjust available capacity and marginal cost
Step
Equations
1. Adjust maximum
available capacity
2. Compute minimum
utilized capacity
3. Adjust marginal cost if
utilized capacity for a
specific technology falls
below its minimum
utilized level
49
(2) When accounting for strategic bidding, we compute an
electricity price mark-up depending on capacity scarcity
Step
Equations
1. Compute capacity
margin
2. Compute adjusted
electricity price after
strategic bidding
50
(2) We compute annual REC prices in four steps
Step
Equations
1. Compute RES cost gap
2. Establish REC supply curve as step function
3. Define annual REC demand curve
4. Intersect supply and demand functions to
establish annual REC price
51
(2) The six key metrics are computed by summation and
averaging over the entire time horizon
Policy goal
Metric
Formula
Total cost
for RPS
for MP
Affordability
for FIT
Average
electricity price
Conventional
capacity
Security of
supply
Volatility of
electricity prices
Security of
supply
Sustainability
Emissions
We compare support schemes along these dimensions and ensure
comparability by calibrating schemes to the same level of RES generation
52
(4) While uncertainty does not increase at its source, its
realizations change the state of the electricity market
Uncertainty does not increase
in terms of wind and solar
power generation
t=0
1
2
3
However, uncertainty
increases in terms of installed
generation portfolio contingent
on all prior states of wind and
solar power generation
t=0
1
2
3
53
››› Concepts
54
(2) The power sector has 3 optimization targets: security of
supply, sustainability and efficiency
▪ Especially important in countries like
Security of supply
▪
Germany where industries rely on very
high reliability of supply
Historically less important e.g. in the
U.S. where (industrial) customers often
have their own backup supply due to
more frequent outages
▪ Efficiency is most important in develop-
▪
Trilemma of
power sector
optimization
Sustainability
Efficiency
ing countries like China, India or Brazil
However, growing subsidies in
renewables foster the discussion around
affordability and social fairness in
Germany as well
▪ Compared to transportation and heating,
▪
the power sector can be switched to
renewables relatively easily
Therefore, the power sector has to
overcompensate for slow
advancements in other sectors
55
››› Assumptions and inputs
56
››› Homogeneous investors &
no differences in risk
profiles
57
(3) Assuming homogeneous investors and no differences in
risk profiles, schemes deliver mostly similar results
Total costs
Conventional capacity
300
GW
USD Billions
400
200
100
0
RPS
MP
FIT
▪ Homogeneous
investors
▪ Identical risk
RPS
Electricity price
MP
FIT
▪ Identical support
Loss of load occasions
70
60
50
40
30
20
10
0
profiles and
discount rates for
all schemes
rates for all
technologies under
MP and FIT
10
8
6
#
USD/MWh
Key assumptions
70
60
50
40
30
20
10
0
4
Key results
2
▪ (Nearly) identical
0
RPS
MP
FIT
RPS
Electricity price volatility
80%
0.8
Billion t
1.0
40%
20%
0%
FIT
CO2 emissions
100%
60%
MP
results across most
dimensions
▪ Much higher
electricity price
volatility under FIT
scheme
0.6
0.4
0.2
0.0
RPS
MP
FIT
RPS
MP
FIT
58
(3) Assuming homogeneous investors and no differences in
risk profiles, schemes deliver mostly similar results
Total electricity gen. costs
USD Billions
400
▪ Homogeneous
300
investors
200
▪ Identical risk
100
0
RPS
MP
FIT
+
Total costs
Total support scheme cost
300
=
200
100
USD Billions
400
0
300
MP
profiles and
discount rates for
all schemes
▪ Identical support
rates for all
technologies under
MP and FIT
200
Key results
100
0
RPS
FIT
RPS
MP
FIT
+
Total resource adequacy cost
400
USD Billions
USD Billions
400
Key assumptions
▪ (Nearly) identical
results across most
dimensions
▪ Much higher
electricity price
volatility under FIT
scheme
300
200
100
0
RPS
MP
FIT
59
(3) Assuming homogeneous investors and no differences in
risk profiles, schemes deliver mostly similar results
100
100
100
80
80
80
60
60
60
GW
Installed total capacity
(FIT)
GW
Installed total capacity
(MP)
GW
Installed total capacity
(RPS)
40
40
40
20
20
20
0
0
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
60
(3) Assuming homogeneous investors and no differences in
risk profiles, schemes deliver mostly similar results
USD/MWh
Electricity and REC prices
100
90
80
70
60
50
40
30
20
10
0
0
5
RPS
10
MP
15
FIT
20
REC prices
%
Electricity price volatility
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
0
5
10
RPS
MP
15
20
FIT
61
(3) Assuming homogeneous investors and no differences in
risk profiles, schemes deliver mostly similar results
Electricity prices (MP)
Electricity prices (FIT)
90
90
80
80
80
70
70
70
60
60
60
50
40
USD/MWh
90
USD/MWh
USD/MWh
Electricity prices (RPS)
50
40
50
40
30
30
30
20
20
20
10
10
10
0
0
0
5
10
15
20
0
0
5
10
15
20
0
5
10
15
Wind onshore
Solar PV
Wind onshore
Solar PV
Wind onshore
Solar PV
Geothermal
Biomass
Geothermal
Biomass
Geothermal
Biomass
Hydro
Nuclear
Hydro
Nuclear
Hydro
Nuclear
CCGT
OCGT
CCGT
OCGT
CCGT
OCGT
LOLE
LOLE
20
LOLE
62
(3) Assuming homogeneous investors and no differences in
risk profiles, schemes deliver mostly similar results
Installed total
generation capacity
Installed conventional
capacity
Installed renewable
capacity
80
80
80
60
60
60
GW
100
GW
100
GW
100
40
40
40
20
20
20
0
0
0
5
RPS
10
MP
15
FIT
20
0
0
5
RPS
10
MP
15
FIT
20
0
5
RPS
10
MP
15
20
FIT
63
(3) Assuming homogeneous investors and no differences in
risk profiles, schemes deliver mostly similar results
100
100
100
80
80
80
60
60
60
GW
Installed total capacity
(FIT)
GW
Installed total capacity
(MP)
GW
Installed total capacity
(RPS)
40
40
40
20
20
20
0
0
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
64
(3) Assuming homogeneous investors and no differences in
risk profiles, schemes deliver mostly similar results
Total generation
Conventional generation
Renewable generation
200
200
200
150
150
150
TWh
250
TWh
250
TWh
250
100
100
100
50
50
50
0
0
0
5
10
15
RPS
MP
FIT
20
0
0
5
10
15
RPS
MP
FIT
20
0
5
10
15
RPS
MP
FIT
20
65
(3) Assuming homogeneous investors and no differences in
risk profiles, schemes deliver mostly similar results
Total generation (RPS)
Total generation (MP)
Total generation (FIT)
200
200
200
150
150
150
TWh
250
TWh
250
TWh
250
100
100
100
50
50
50
0
0
1 3 5 7 9 11 13 15 17 19
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0
1 3 5 7
Hydro
CCGT
Biomass
Wind onshore
9 11 13 15 17 19
Nuclear
OCGT
Geothermal
Solar PV
1 3 5 7 9 11 13 15 17 19
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
66
(3) Assuming homogeneous investors and no differences in
risk profiles, schemes deliver mostly similar results
Renewable emissions
Conventional emissions
40
40
35
35
35
30
30
30
25
25
25
20
15
Million t
40
Million t
Million t
Total emissions
20
15
20
15
10
10
10
5
5
5
0
0
0
5
10
RPS
MP
15
FIT
20
0
0
5
10
RPS
MP
15
FIT
20
0
5
10
RPS
MP
15
20
FIT
67
(3) Assuming homogeneous investors and no differences in
risk profiles, schemes deliver mostly similar results
Total emissions (MP)
Total emissions (FIT)
40
40
35
35
35
30
30
30
25
25
25
20
Million t
40
Million t
Million t
Total emissions (RPS)
20
20
15
15
15
10
10
10
5
5
5
0
0
1
3
5
7
Hydro
CCGT
Biomass
Wind onshore
9 11 13 15 17 19
Nuclear
OCGT
Geothermal
Solar PV
0
1
3
5
7
Hydro
CCGT
Biomass
Wind onshore
9 11 13 15 17 19
Nuclear
OCGT
Geothermal
Solar PV
Biomass CO2 emissions accounting to be
verified both in terms of financials and
environmental impact
1
3
5
7
Hydro
CCGT
Biomass
Wind onshore
9 11 13 15 17 19
Nuclear
OCGT
Geothermal
Solar PV
68
(3) Assuming homogeneous investors and no differences in
risk profiles, schemes deliver mostly similar results
USD/MWh
Average electricity price
180
160
140
120
100
80
60
40
20
0
0
5
10
Iteration
RPS
MP
15
20
FIT
Change in average electricity price
10
%
5
0
0
5
10
15
20
-5
-10
Iteration
RPS
MP
FIT
69
(3) Assuming homogeneous investors and no differences in
risk profiles, schemes deliver mostly similar results
Average conventional
installed capacity
Average renewable
installed capacity
100
100
90
90
90
80
80
80
70
70
70
60
60
60
50
GW
100
GW
GW
Average installed total
capacity
50
50
40
40
40
30
30
30
20
20
20
10
10
10
0
0
0
5
RPS
10
15
Iteration
MP
FIT
20
0
0
5
RPS
10
15
Iteration
MP
FIT
20
0
5
RPS
10
15
Iteration
MP
20
FIT
70
(3) Assuming homogeneous investors and no differences in
risk profiles, schemes deliver mostly similar results
Change in average
installed total capacity
Change in average conv.
installed capacity
10
Change in average
renewable installed
capacity
10
10
5
0
5
10
15
-5
5
0
20
0
5
10
15
-5
-10
RPS
MP
FIT
0
0
5
10
15
20
-5
-10
Iteration
20
%
0
%
%
5
-10
Iteration
RPS
MP
FIT
Iteration
RPS
MP
FIT
71
››› Heterogeneous investors
& no differences in risk
profiles
72
(3) Assuming heterogeneous investors and no differences
in risk profiles, electricity price volatility decreases
Total costs
Conventional capacity
300
GW
USD Billions
400
200
100
0
RPS
MP
FIT
▪ Heterogeneous
investors
▪ Identical risk
RPS
Electricity price
MP
FIT
▪ Identical support
Loss of load occasions
70
60
50
40
30
20
10
0
profiles and
discount rates for
all schemes
rates for all
technologies under
MP and FIT
10
8
6
#
USD/MWh
Key assumptions
70
60
50
40
30
20
10
0
4
Key results
2
▪ (Nearly) identical
0
RPS
MP
FIT
RPS
Electricity price volatility
80%
0.8
Billion t
1.0
40%
20%
0%
FIT
CO2 emissions
100%
60%
MP
▪ Much higher
electricity price
volatility under FIT
scheme
0.6
0.4
▪ Lower volatility
0.2
across schemes
0.0
RPS
MP
FIT
results across most
dimensions
RPS
MP
FIT
73
(3) Assuming heterogeneous investors and no differences
in risk profiles, electricity price volatility decreases
Total electricity gen. costs
USD Billions
400
▪ Heterogeneous
300
investors
200
▪ Identical risk
100
0
RPS
MP
FIT
+
Total costs
Total support scheme cost
300
=
200
100
USD Billions
400
0
300
MP
profiles and
discount rates for
all schemes
▪ Identical support
rates for all
technologies under
MP and FIT
200
Key results
100
0
RPS
FIT
RPS
MP
FIT
+
Total resource adequacy cost
400
USD Billions
USD Billions
400
Key assumptions
▪ (Nearly) identical
results across most
dimensions
▪ Much higher
electricity price
volatility under FIT
scheme
300
200
▪ Lower volatility
100
across schemes
0
RPS
MP
FIT
74
(3) Assuming heterogeneous investors and no differences
in risk profiles, electricity price volatility decreases
USD/MWh
Electricity and REC prices
100
90
80
70
60
50
40
30
20
10
0
0
5
RPS
10
MP
15
FIT
20
REC prices
%
Electricity price volatility
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
0
5
10
RPS
MP
15
20
FIT
75
(3) Assuming heterogeneous investors and no differences
in risk profiles, electricity price volatility decreases
Electricity prices (MP)
Electricity prices (FIT)
90
90
80
80
80
70
70
70
60
60
60
50
40
USD/MWh
90
USD/MWh
USD/MWh
Electricity prices (RPS)
50
40
50
40
30
30
30
20
20
20
10
10
10
0
0
0
5
10
15
20
0
0
5
10
15
20
0
5
10
15
Wind onshore
Solar PV
Wind onshore
Solar PV
Wind onshore
Solar PV
Geothermal
Biomass
Geothermal
Biomass
Geothermal
Biomass
Hydro
Nuclear
Hydro
Nuclear
Hydro
Nuclear
CCGT
OCGT
CCGT
OCGT
CCGT
OCGT
LOLE
LOLE
20
LOLE
76
(3) Assuming heterogeneous investors and no differences
in risk profiles, electricity price volatility decreases
Installed total
generation capacity
Installed conventional
capacity
Installed renewable
capacity
80
80
80
60
60
60
GW
100
GW
100
GW
100
40
40
40
20
20
20
0
0
0
5
RPS
10
MP
15
FIT
20
0
0
5
RPS
10
MP
15
FIT
20
0
5
RPS
10
MP
15
20
FIT
77
(3) Assuming heterogeneous investors and no differences
in risk profiles, electricity price volatility decreases
100
100
100
80
80
80
60
60
60
GW
Installed total capacity
(FIT)
GW
Installed total capacity
(MP)
GW
Installed total capacity
(RPS)
40
40
40
20
20
20
0
0
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
78
(3) Assuming heterogeneous investors and no differences
in risk profiles, electricity price volatility decreases
Total generation
Conventional generation
Renewable generation
200
200
200
150
150
150
TWh
250
TWh
250
TWh
250
100
100
100
50
50
50
0
0
0
5
10
15
RPS
MP
FIT
20
0
0
5
10
15
RPS
MP
FIT
20
0
5
10
15
RPS
MP
FIT
20
79
(3) Assuming heterogeneous investors and no differences
in risk profiles, electricity price volatility decreases
Total generation (RPS)
Total generation (MP)
Total generation (FIT)
200
200
200
150
150
150
TWh
250
TWh
250
TWh
250
100
100
100
50
50
50
0
0
1 3 5 7 9 11 13 15 17 19
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0
1 3 5 7
Hydro
CCGT
Biomass
Wind onshore
9 11 13 15 17 19
Nuclear
OCGT
Geothermal
Solar PV
1 3 5 7 9 11 13 15 17 19
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
80
(3) Assuming heterogeneous investors and no differences
in risk profiles, electricity price volatility decreases
Renewable emissions
Conventional emissions
40
40
35
35
35
30
30
30
25
25
25
20
15
Million t
40
Million t
Million t
Total emissions
20
15
10
10
5
5
0
0
20
15
10
5
0
0
5
10
RPS
MP
15
FIT
20
0
0
5
10
RPS
MP
15
FIT
10
20
20
RPS
MP
FIT
81
(3) Assuming heterogeneous investors and no differences
in risk profiles, electricity price volatility decreases
Total emissions (MP)
Total emissions (FIT)
40
40
35
35
35
30
30
30
25
25
25
20
Million t
40
Million t
Million t
Total emissions (RPS)
20
20
15
15
15
10
10
10
5
5
5
0
0
1
3
5
7
Hydro
CCGT
Biomass
Wind onshore
9 11 13 15 17 19
Nuclear
OCGT
Geothermal
Solar PV
0
1
3
5
7
Hydro
CCGT
Biomass
Wind onshore
9 11 13 15 17 19
Nuclear
OCGT
Geothermal
Solar PV
Biomass CO2 emissions accounting to be
verified both in terms of financials and
environmental impact
1
3
5
7
Hydro
CCGT
Biomass
Wind onshore
9 11 13 15 17 19
Nuclear
OCGT
Geothermal
Solar PV
82
(3) Assuming heterogeneous investors and no differences
in risk profiles, electricity price volatility decreases
USD/MWh
Average electricity price
180
160
140
120
100
80
60
40
20
0
0
5
10
Iteration
RPS
MP
15
20
FIT
Change in average electricity price
10
%
5
0
0
5
10
15
20
-5
-10
Iteration
RPS
MP
FIT
83
(3) Assuming heterogeneous investors and no differences
in risk profiles, electricity price volatility decreases
Average conventional
installed capacity
Average renewable
installed capacity
100
100
90
90
90
80
80
80
70
70
70
60
60
60
50
GW
100
GW
GW
Average installed total
capacity
50
50
40
40
40
30
30
30
20
20
20
10
10
10
0
0
0
5
RPS
10
15
Iteration
MP
FIT
20
0
0
5
RPS
10
15
Iteration
MP
FIT
20
0
5
RPS
10
15
Iteration
MP
20
FIT
84
(3) Assuming heterogeneous investors and no differences
in risk profiles, electricity price volatility decreases
Change in average
installed total
generation capacity
Change in average conv.
installed capacity
Change in average
renewable installed
capacity
10
10
10
5
%
0
0
5
10
15
5
0
0
20
5
10
15
-5
-5
-10
RPS
MP
FIT
0
0
5
10
15
20
-5
-10
Iteration
20
%
%
5
-10
Iteration
RPS
MP
FIT
Iteration
RPS
MP
FIT
85
››› Homogeneous investors &
differences in risk profiles
86
(3) Assuming homogeneous investors and differences in
risk profiles, costs of FIT and MP decrease
Total costs
Conventional capacity
300
GW
USD Billions
400
200
100
0
RPS
MP
FIT
▪ Homogeneous
investors
▪ Different risk
RPS
Electricity price
MP
FIT
▪ Identical support
Loss of load occasions
70
60
50
40
30
20
10
0
profiles and
discount rates for
schemes
rates for all
technologies under
MP and FIT
10
8
6
#
USD/MWh
Key assumptions
70
60
50
40
30
20
10
0
4
Key results
2
▪ Decrease in total
0
RPS
MP
FIT
RPS
Electricity price volatility
80%
0.8
Billion t
1.0
40%
20%
0%
FIT
CO2 emissions
100%
60%
MP
cost of MP and FIT
scheme being
driven by a
decrease in support
scheme cost
0.6
0.4
0.2
0.0
RPS
MP
FIT
RPS
MP
FIT
87
(3) Assuming homogeneous investors and differences in
risk profiles, costs of FIT and MP decrease
Total electricity gen. costs
USD Billions
400
▪ Homogeneous
300
investors
200
▪ Different risk
100
0
RPS
MP
FIT
+
Total costs
Total support scheme cost
300
=
200
100
USD Billions
400
0
300
MP
profiles and
discount rates for
schemes
▪ Identical support
rates for all
technologies under
MP and FIT
200
Key results
100
0
RPS
FIT
RPS
MP
FIT
+
Total resource adequacy cost
400
USD Billions
USD Billions
400
Key assumptions
300
▪ Decrease in total
cost of MP and FIT
scheme being
driven by a
decrease in support
scheme cost
200
100
0
RPS
MP
FIT
88
(3) Assuming homogeneous investors and differences in
risk profiles, costs of FIT and MP decrease
USD/MWh
Electricity and REC prices
100
90
80
70
60
50
40
30
20
10
0
0
5
RPS
10
MP
15
FIT
20
REC prices
%
Electricity price volatility
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
0
5
10
RPS
MP
15
20
FIT
89
(3) Assuming homogeneous investors and differences in
risk profiles, costs of FIT and MP decrease
Electricity prices (MP)
Electricity prices (FIT)
90
90
80
80
80
70
70
70
60
60
60
50
40
USD/MWh
90
USD/MWh
USD/MWh
Electricity prices (RPS)
50
40
50
40
30
30
30
20
20
20
10
10
10
0
0
0
5
10
15
20
0
0
5
10
15
20
0
5
10
15
Wind onshore
Solar PV
Wind onshore
Solar PV
Wind onshore
Solar PV
Geothermal
Biomass
Geothermal
Biomass
Geothermal
Biomass
Hydro
Nuclear
Hydro
Nuclear
Hydro
Nuclear
CCGT
OCGT
CCGT
OCGT
CCGT
OCGT
LOLE
LOLE
20
LOLE
90
(3) Assuming homogeneous investors and differences in
risk profiles, costs of FIT and MP decrease
Installed total
generation capacity
Installed conventional
capacity
Installed renewable
capacity
80
80
80
60
60
60
GW
100
GW
100
GW
100
40
40
40
20
20
20
0
0
0
5
RPS
10
MP
15
FIT
20
0
0
5
RPS
10
MP
15
FIT
20
0
5
RPS
10
MP
15
20
FIT
91
(3) Assuming homogeneous investors and differences in
risk profiles, costs of FIT and MP decrease
100
100
100
80
80
80
60
60
60
GW
Installed total capacity
(FIT)
GW
Installed total capacity
(MP)
GW
Installed total capacity
(RPS)
40
40
40
20
20
20
0
0
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
92
(3) Assuming homogeneous investors and differences in
risk profiles, costs of FIT and MP decrease
Total generation
Conventional generation
Renewable generation
200
200
200
150
150
150
TWh
250
TWh
250
TWh
250
100
100
100
50
50
50
0
0
0
5
10
15
RPS
MP
FIT
20
0
0
5
10
15
RPS
MP
FIT
20
0
5
10
15
RPS
MP
FIT
20
93
(3) Assuming homogeneous investors and differences in
risk profiles, costs of FIT and MP decrease
Total generation (RPS)
Total generation (MP)
Total generation (FIT)
200
200
200
150
150
150
TWh
250
TWh
250
TWh
250
100
100
100
50
50
50
0
0
1 3 5 7 9 11 13 15 17 19
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0
1 3 5 7
Hydro
CCGT
Biomass
Wind onshore
9 11 13 15 17 19
Nuclear
OCGT
Geothermal
Solar PV
1 3 5 7 9 11 13 15 17 19
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
94
(3) Assuming homogeneous investors and differences in
risk profiles, costs of FIT and MP decrease
Renewable emissions
Conventional emissions
40
40
35
35
35
30
30
30
25
25
25
20
15
Million t
40
Million t
Million t
Total emissions
20
15
20
15
10
10
10
5
5
5
0
0
0
5
10
RPS
MP
15
FIT
20
0
0
5
10
RPS
MP
15
FIT
20
0
5
10
RPS
MP
15
20
FIT
95
(3) Assuming homogeneous investors and differences in
risk profiles, costs of FIT and MP decrease
Total emissions (MP)
Total emissions (FIT)
40
40
35
35
35
30
30
30
25
25
25
20
Million t
40
Million t
Million t
Total emissions (RPS)
20
20
15
15
15
10
10
10
5
5
5
0
0
1
3
5
7
Hydro
CCGT
Biomass
Wind onshore
9 11 13 15 17 19
Nuclear
OCGT
Geothermal
Solar PV
0
1
3
5
7
Hydro
CCGT
Biomass
Wind onshore
9 11 13 15 17 19
Nuclear
OCGT
Geothermal
Solar PV
Biomass CO2 emissions accounting to be
verified both in terms of financials and
environmental impact
1
3
5
7
Hydro
CCGT
Biomass
Wind onshore
9 11 13 15 17 19
Nuclear
OCGT
Geothermal
Solar PV
96
(3) Assuming homogeneous investors and differences in
risk profiles, costs of FIT and MP decrease
USD/MWh
Average electricity price
180
160
140
120
100
80
60
40
20
0
0
5
10
Iteration
RPS
MP
15
20
FIT
Change in average electricity price
10
%
5
0
0
5
10
15
20
-5
-10
Iteration
RPS
MP
FIT
97
(3) Assuming homogeneous investors and differences in
risk profiles, costs of FIT and MP decrease
Average conventional
installed capacity
Average renewable
installed capacity
100
100
90
90
90
80
80
80
70
70
70
60
60
60
50
GW
100
GW
GW
Average installed total
capacity
50
50
40
40
40
30
30
30
20
20
20
10
10
10
0
0
0
5
RPS
10
15
Iteration
MP
FIT
20
0
0
5
RPS
10
15
Iteration
MP
FIT
20
0
5
RPS
10
15
Iteration
MP
20
FIT
98
(3) Assuming homogeneous investors and differences in
risk profiles, costs of FIT and MP decrease
Change in average
installed total capacity
Change in average conv.
installed capacity
10
Change in average
renewable installed
capacity
10
10
5
0
5
10
15
-5
5
0
20
0
5
10
15
-5
-10
RPS
MP
FIT
0
0
5
10
15
20
-5
-10
Iteration
20
%
0
%
%
5
-10
Iteration
RPS
MP
FIT
Iteration
RPS
MP
FIT
99
››› Homogeneous investors &
no differences in risk
profiles & differentiated
support rates
100
(3) Assuming differentiated support rates, electricity price
volatility can be reduced greatly under MP and FIT
Total costs
Conventional capacity
300
GW
USD Billions
400
200
100
0
RPS
MP
FIT
▪ Homogeneous
investors
▪ Identical risk
RPS
Electricity price
MP
FIT
▪ Differentiated
Loss of load occasions
70
60
50
40
30
20
10
0
profiles and
discount rates for
all schemes
support rates under
MP and FIT
10
8
6
#
USD/MWh
Key assumptions
70
60
50
40
30
20
10
0
4
Key results
2
▪ (Nearly) identical
0
RPS
MP
FIT
RPS
Electricity price volatility
80%
0.8
Billion t
1.0
40%
20%
0%
FIT
CO2 emissions
100%
60%
MP
▪ Greatly reduced
electricity price
volatility under MP
and FIT given shift
to non-intermittent
RES
0.6
0.4
0.2
0.0
RPS
MP
FIT
results across most
dimensions
RPS
MP
FIT
(3) Assuming differentiated support rates, electricity price
volatility can be reduced greatly under MP and FIT
Total electricity gen. costs
USD Billions
400
▪ Homogeneous
300
investors
200
▪ Identical risk
100
0
RPS
MP
FIT
+
Total costs
Total support scheme cost
300
=
200
100
USD Billions
400
0
MP
profiles and
discount rates for
all schemes
▪ Differentiated
support rates under
MP and FIT
300
200
Key results
100
0
RPS
FIT
RPS
MP
FIT
+
Total resource adequacy cost
400
USD Billions
USD Billions
400
Key assumptions
▪ (Nearly) identical
results across most
dimensions
▪ Greatly reduced
electricity price
volatility under MP
and FIT given shift
to non-intermittent
RES
300
200
100
0
RPS
MP
FIT
102
(3) Assuming differentiated support rates, electricity price
volatility can be reduced greatly under MP and FIT
USD/MWh
Electricity and REC prices
100
90
80
70
60
50
40
30
20
10
0
0
5
RPS
10
MP
15
FIT
20
REC prices
%
Electricity price volatility
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
0
5
10
RPS
MP
15
20
FIT
103
(3) Assuming differentiated support rates, electricity price
volatility can be reduced greatly under MP and FIT
Electricity prices (MP)
Electricity prices (FIT)
90
90
80
80
80
70
70
70
60
60
60
50
40
USD/MWh
90
USD/MWh
USD/MWh
Electricity prices (RPS)
50
40
50
40
30
30
30
20
20
20
10
10
10
0
0
0
5
10
15
20
0
0
5
10
15
20
0
5
10
15
Wind onshore
Solar PV
Wind onshore
Solar PV
Wind onshore
Solar PV
Geothermal
Biomass
Geothermal
Biomass
Geothermal
Biomass
Hydro
Nuclear
Hydro
Nuclear
Hydro
Nuclear
CCGT
OCGT
CCGT
OCGT
CCGT
OCGT
LOLE
LOLE
20
LOLE
104
(3) Assuming differentiated support rates, electricity price
volatility can be reduced greatly under MP and FIT
Installed total
generation capacity
Installed conventional
capacity
Installed renewable
capacity
80
80
80
60
60
60
GW
100
GW
100
GW
100
40
40
40
20
20
20
0
0
0
5
RPS
10
MP
15
FIT
20
0
0
5
RPS
10
MP
15
FIT
20
0
5
RPS
10
MP
15
20
FIT
105
(3) Assuming differentiated support rates, electricity price
volatility can be reduced greatly under MP and FIT
100
100
100
80
80
80
60
60
60
GW
Installed total capacity
(FIT)
GW
Installed total capacity
(MP)
GW
Installed total capacity
(RPS)
40
40
40
20
20
20
0
0
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
106
(3) Assuming differentiated support rates, electricity price
volatility can be reduced greatly under MP and FIT
Total generation
Conventional generation
Renewable generation
200
200
200
150
150
150
TWh
250
TWh
250
TWh
250
100
100
100
50
50
50
0
0
0
5
10
15
RPS
MP
FIT
20
0
0
5
10
15
RPS
MP
FIT
20
0
5
10
15
RPS
MP
FIT
20
107
(3) Assuming differentiated support rates, electricity price
volatility can be reduced greatly under MP and FIT
Total generation (RPS)
Total generation (MP)
Total generation (FIT)
200
200
200
150
150
150
TWh
250
TWh
250
TWh
250
100
100
100
50
50
50
0
0
1 3 5 7 9 11 13 15 17 19
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0
1 3 5 7
Hydro
CCGT
Biomass
Wind onshore
9 11 13 15 17 19
Nuclear
OCGT
Geothermal
Solar PV
1 3 5 7 9 11 13 15 17 19
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
108
(3) Assuming differentiated support rates, electricity price
volatility can be reduced greatly under MP and FIT
Renewable emissions
Conventional emissions
40
40
35
35
35
30
30
30
25
25
25
20
15
Million t
40
Million t
Million t
Total emissions
20
15
20
15
10
10
10
5
5
5
0
0
0
5
10
RPS
MP
15
FIT
20
0
0
5
10
RPS
MP
15
FIT
20
0
5
10
RPS
MP
15
20
FIT
109
(3) Assuming differentiated support rates, electricity price
volatility can be reduced greatly under MP and FIT
Total emissions (MP)
Total emissions (FIT)
40
40
35
35
35
30
30
30
25
25
25
20
Million t
40
Million t
Million t
Total emissions (RPS)
20
20
15
15
15
10
10
10
5
5
5
0
0
1
3
5
7
Hydro
CCGT
Biomass
Wind onshore
9 11 13 15 17 19
Nuclear
OCGT
Geothermal
Solar PV
0
1
3
5
7
Hydro
CCGT
Biomass
Wind onshore
9 11 13 15 17 19
Nuclear
OCGT
Geothermal
Solar PV
Biomass CO2 emissions accounting to be
verified both in terms of financials and
environmental impact
1
3
5
7
Hydro
CCGT
Biomass
Wind onshore
9 11 13 15 17 19
Nuclear
OCGT
Geothermal
Solar PV
110
(3) Assuming differentiated support rates, electricity price
volatility can be reduced greatly under MP and FIT
USD/MWh
Average electricity price
180
160
140
120
100
80
60
40
20
0
0
5
10
Iteration
RPS
MP
15
20
FIT
Change in average electricity price
10
%
5
0
0
5
10
15
20
-5
-10
Iteration
RPS
MP
FIT
111
(3) Assuming differentiated support rates, electricity price
volatility can be reduced greatly under MP and FIT
Average conventional
installed capacity
Average renewable
installed capacity
100
100
90
90
90
80
80
80
70
70
70
60
60
60
50
GW
100
GW
GW
Average installed total
capacity
50
50
40
40
40
30
30
30
20
20
20
10
10
10
0
0
0
5
RPS
10
15
Iteration
MP
FIT
20
0
0
5
RPS
10
15
Iteration
MP
FIT
20
0
5
RPS
10
15
Iteration
MP
20
FIT
112
(3) Assuming differentiated support rates, electricity price
volatility can be reduced greatly under MP and FIT
Change in average
installed total capacity
Change in average conv.
installed capacity
10
Change in average
renewable installed
capacity
10
10
5
0
5
10
15
-5
5
0
20
0
5
10
15
-5
-10
RPS
MP
FIT
0
0
5
10
15
20
-5
-10
Iteration
20
%
0
%
%
5
-10
Iteration
RPS
MP
FIT
Iteration
RPS
MP
FIT
113
››› Homogeneous investors &
no differences in risk
profiles & increased
support rates by 2%
114
(3) Assuming increased support rates by 2%, the electricity
market becomes dysfunctional under the FIT scheme
Total costs
Conventional capacity
300
GW
USD Billions
400
200
100
0
RPS
MP
FIT
▪ Homogeneous
investors
▪ Identical risk
RPS
Electricity price
MP
FIT
▪ Identical support
Loss of load occasions
70
60
50
40
30
20
10
0
profiles and
discount rates for
schemes
rates for all
technologies
increased by 2%
10
8
6
#
USD/MWh
Key assumptions
70
60
50
40
30
20
10
0
4
Key results
2
▪ Steep decrease of
0
RPS
MP
FIT
RPS
Electricity price volatility
80%
0.8
Billion t
1.0
40%
20%
0%
FIT
CO2 emissions
100%
60%
MP
▪ Jump in RES
0.6
installations and
electricity price
volatility under FIT
0.4
0.2
0.0
RPS
MP
FIT
electricit yprices
and conventional
generation under
FIT
RPS
MP
FIT
115
(3) Assuming increased support rates by 2%, the electricity
market becomes dysfunctional under the FIT scheme
Total electricity gen. costs
USD Billions
400
▪ Homogeneous
300
investors
200
▪ Identical risk
100
0
RPS
MP
FIT
+
Total costs
Total support scheme cost
USD Billions
400
300
300
TO BE DONE
200
100
0
MP
profiles and
discount rates for
schemes
▪ Identical support
rates for all
technologies
increased by 2%
200
Key results
100
0
RPS
FIT
RPS
MP
FIT
+
Total resource adequacy cost
400
USD Billions
USD Billions
400
Key assumptions
▪ Steep decrease of
electricit yprices
and conventional
generation under
FIT
▪ Jump in RES
300
installations and
electricity price
volatility under FIT
200
100
0
RPS
MP
FIT
116
(3) Assuming increased support rates by 2%, the electricity
market becomes dysfunctional under the FIT scheme
USD/MWh
Electricity and REC prices
100
90
80
70
60
50
40
30
20
10
0
0
5
RPS
10
MP
15
FIT
20
REC prices
TO BE DONE
%
Electricity price volatility
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
0
5
10
RPS
MP
15
20
FIT
117
(3) Assuming increased support rates by 2%, the electricity
market becomes dysfunctional under the FIT scheme
Electricity prices (MP)
Electricity prices (FIT)
90
90
80
80
80
70
70
70
60
60
60
50
40
USD/MWh
90
USD/MWh
USD/MWh
Electricity prices (RPS)
50
40
TO BE DONE
30
50
40
30
30
20
20
20
10
10
10
0
0
0
5
10
15
20
0
0
5
10
15
20
0
5
10
15
Wind onshore
Solar PV
Wind onshore
Solar PV
Wind onshore
Solar PV
Geothermal
Biomass
Geothermal
Biomass
Geothermal
Biomass
Hydro
Nuclear
Hydro
Nuclear
Hydro
Nuclear
CCGT
OCGT
CCGT
OCGT
CCGT
OCGT
LOLE
LOLE
20
LOLE
118
(3) Assuming increased support rates by 2%, the electricity
market becomes dysfunctional under the FIT scheme
Installed total
generation capacity
Installed conventional
capacity
Installed renewable
generation capacity
100,000
100,000
100,000
80,000
80,000
80,000
60,000
60,000
60,000
MW
MW
MW
TO BE DONE
40,000
40,000
40,000
20,000
20,000
20,000
0
0
0
RPS
5
10
MP
15
FIT
20
0
0
RPS
5
10
MP
15
FIT
20
0
RPS
5
10
MP
15
20
FIT
119
(3) Assuming increased support rates by 2%, the electricity
market becomes dysfunctional under the FIT scheme
100
100
100
80
80
80
60
60
60
GW
Installed total capacity
(FIT)
GW
Installed total capacity
(MP)
GW
Installed total capacity
(RPS)
40
40
40
20
20
20
0
0
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
120
(3) Assuming increased support rates by 2%, the electricity
market becomes dysfunctional under the FIT scheme
Total generation
Conventional generation
Renewable generation
200,000,000
200,000,000
200,000,000
150,000,000
150,000,000
150,000,000
MWh
250,000,000
MWh
250,000,000
MWh
250,000,000
TO BE DONE
100,000,000
100,000,000
100,000,000
50,000,000
50,000,000
50,000,000
0
0
0
RPS
5
MP
10
15
FIT
20
0
0
RPS
5
MP
10
15
FIT
20
0
RPS
5
MP
10
15
20
FIT
121
(3) Assuming increased support rates by 2%, the electricity
market becomes dysfunctional under the FIT scheme
Total generation (RPS)
Total generation (MP)
Total generation (FIT)
200,000,000
200,000,000
200,000,000
150,000,000
150,000,000
150,000,000
100,000,000
100,000,000
50,000,000
50,000,000
50,000,000
0
0
0
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
1
3
5
7
9
11
13
15
17
19
1
3
5
7
9
11
13
15
17
19
TO BE DONE
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
1
3
5
7
9
11
13
15
17
19
100,000,000
MWh
250,000,000
MWh
250,000,000
MWh
250,000,000
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
122
(3) Assuming increased support rates by 2%, the electricity
market becomes dysfunctional under the FIT scheme
Renewable emissions
Conventional emissions
40,000,000
40,000,000
35,000,000
35,000,000
35,000,000
30,000,000
30,000,000
30,000,000
25,000,000
25,000,000
25,000,000
20,000,000
20,000,000
20,000,000
t
40,000,000
t
t
Total emissions
TO BE DONE
15,000,000
15,000,000
15,000,000
10,000,000
10,000,000
10,000,000
5,000,000
5,000,000
5,000,000
0
0
0
RPS
5
MP
10
15
FIT
20
0
0
RPS
5
MP
10
15
FIT
20
0
RPS
5
MP
10
15
20
FIT
123
(3) Assuming increased support rates by 2%, the electricity
market becomes dysfunctional under the FIT scheme
Total emissions (MP)
Total emissions (FIT)
40,000,000
40,000,000
35,000,000
35,000,000
35,000,000
30,000,000
30,000,000
30,000,000
25,000,000
25,000,000
25,000,000
20,000,000
20,000,000
20,000,000
t
40,000,000
t
t
Total emissions (RPS)
TO
BE DONE
15,000,000
15,000,000
15,000,000
10,000,000
10,000,000
10,000,000
5,000,000
5,000,000
5,000,000
0
0
1 3 5 7 9 1113151719
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0
1 3 5 7 9 1113151719
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
Biomass CO2 emissions accounting to be
verified both in terms of financials and
environmental impact
1 3 5 7 9 1113151719
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
124
(3) Assuming increased support rates by 2%, the electricity
market becomes dysfunctional under the FIT scheme
USD/MWh
Average electricity price
180
160
140
120
100
80
60
40
20
0
0
5
10
Iteration
RPS
MP
15
20
FIT
TO BE DONE
Change in average electricity price
10
%
5
0
0
5
10
15
20
-5
-10
Iteration
RPS
MP
FIT
125
(3) Assuming increased support rates by 2%, the electricity
market becomes dysfunctional under the FIT scheme
Average conventional
installed capacity
Average renewable
installed capacity
100,000
100,000
90,000
90,000
90,000
80,000
80,000
80,000
70,000
70,000
70,000
60,000
60,000
60,000
50,000
MW
100,000
MW
MW
Average installed total
capacity
50,000
TO BE DONE
50,000
40,000
40,000
40,000
30,000
30,000
30,000
20,000
20,000
20,000
10,000
10,000
10,000
0
0
0
RPS
5
10
15
Iteration
MP
FIT
20
0
0
RPS
5
10
15
Iteration
MP
FIT
20
0
RPS
5
10
15
Iteration
MP
20
FIT
126
(3) Assuming increased support rates by 2%, the electricity
market becomes dysfunctional under the FIT scheme
Change in average
installed total capacity
Change in average conv.
installed capacity
10
Change in average
renewable installed
capacity
10
10
5
0
5
10
15
-5
20
5
0 BE DONE
TO
0
5
10
15
-5
-10
RPS
MP
FIT
0
0
5
10
15
20
-5
-10
Iteration
20
%
0
%
%
5
-10
Iteration
RPS
MP
FIT
Iteration
RPS
MP
FIT
127
››› Homogeneous investors &
no differences in risk
profiles & solar learning
-1 percentage point
128
(3) Assuming decreased learning rates for solar by -1
percentage point, reduce solar investment
Conventional capacity
400
80
300
60
GW
USD Billions
Total costs
200
100
▪ Homogeneous
investors
40
▪ Identical risk
20
0
0
RPS
MP
FIT
RPS
Electricity price
MP
FIT
▪ Identical support
▪ Decreased solar
Loss of load occasions
70
60
50
40
30
20
10
0
profiles and
discount rates for
schemes
10
learning by 1 pp
8
6
#
USD/MWh
Key assumptions
4
Key results
2
▪ Total costs increase
0
RPS
MP
FIT
RPS
Electricity price volatility
80%
0.8
Billion t
1.0
40%
20%
0%
FIT
across schemes
▪ RES installations
CO2 emissions
100%
60%
MP
drop under FIT and
MP schemes
▪ More conventional
0.6
capacity needed
under MP and FIT
0.4
0.2
0.0
RPS
MP
FIT
RPS
MP
FIT
129
(3) Assuming decreased learning rates for solar by -1
percentage point, reduce solar investment
Total electricity gen. costs
USD Billions
400
▪ Homogeneous
300
investors
200
▪ Identical risk
100
0
RPS
MP
FIT
+
Total costs
Total support scheme cost
USD Billions
400
300
profiles and
discount rates for
schemes
▪ Identical support
▪ Decreased solar
learning by 1 pp
300
TO BE DONE
200
100
0
200
Key results
100
0
RPS
MP
FIT
RPS
MP
FIT
+
Total resource adequacy cost
400
USD Billions
USD Billions
400
Key assumptions
300
▪ Total costs increase
across schemes
▪ RES installations
drop under FIT and
MP schemes
▪ More conventional
200
capacity needed
under MP and FIT
100
0
RPS
MP
FIT
(3) Assuming decreased learning rates for solar by -1
percentage point, reduce solar investment
USD/MWh
Electricity and REC prices
100
90
80
70
60
50
40
30
20
10
0
0
5
RPS
10
MP
15
FIT
20
REC prices
TO BE DONE
%
Electricity price volatility
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
0
5
10
RPS
MP
15
20
FIT
131
(3) Assuming decreased learning rates for solar by -1
percentage point, reduce solar investment
Electricity prices (MP)
Electricity prices (FIT)
90
90
80
80
80
70
70
70
60
60
60
50
40
USD/MWh
90
USD/MWh
USD/MWh
Electricity prices (RPS)
50
40
TO BE DONE
30
50
40
30
30
20
20
20
10
10
10
0
0
0
5
10
15
20
0
0
5
10
15
20
0
5
10
15
Wind onshore
Solar PV
Wind onshore
Solar PV
Wind onshore
Solar PV
Geothermal
Biomass
Geothermal
Biomass
Geothermal
Biomass
Hydro
Nuclear
Hydro
Nuclear
Hydro
Nuclear
CCGT
OCGT
CCGT
OCGT
CCGT
OCGT
LOLE
LOLE
20
LOLE
132
(3) Assuming decreased learning rates for solar by -1
percentage point, reduce solar investment
Installed total
generation capacity
Installed conventional
capacity
Installed renewable
generation capacity
100,000
100,000
100,000
80,000
80,000
80,000
60,000
60,000
60,000
MW
MW
MW
TO BE DONE
40,000
40,000
40,000
20,000
20,000
20,000
0
0
0
RPS
5
10
MP
15
FIT
20
0
0
RPS
5
10
MP
15
FIT
20
0
RPS
5
10
MP
15
20
FIT
133
(3) Assuming decreased learning rates for solar by -1
percentage point, reduce solar investment
100
100
100
80
80
80
60
60
60
GW
Installed total capacity
(FIT)
GW
Installed total capacity
(MP)
GW
Installed total capacity
(RPS)
40
40
40
20
20
20
0
0
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
134
(3) Assuming decreased learning rates for solar by -1
percentage point, reduce solar investment
Total generation
Conventional generation
Renewable generation
200,000,000
200,000,000
200,000,000
150,000,000
150,000,000
150,000,000
MWh
250,000,000
MWh
250,000,000
MWh
250,000,000
TO BE DONE
100,000,000
100,000,000
100,000,000
50,000,000
50,000,000
50,000,000
0
0
0
RPS
5
MP
10
15
FIT
20
0
0
RPS
5
MP
10
15
FIT
20
0
RPS
5
MP
10
15
20
FIT
135
(3) Assuming decreased learning rates for solar by -1
percentage point, reduce solar investment
Total generation (RPS)
Total generation (MP)
Total generation (FIT)
200,000,000
200,000,000
200,000,000
150,000,000
150,000,000
150,000,000
100,000,000
100,000,000
50,000,000
50,000,000
50,000,000
0
0
0
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
1
3
5
7
9
11
13
15
17
19
1
3
5
7
9
11
13
15
17
19
TO BE DONE
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
1
3
5
7
9
11
13
15
17
19
100,000,000
MWh
250,000,000
MWh
250,000,000
MWh
250,000,000
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
136
(3) Assuming decreased learning rates for solar by -1
percentage point, reduce solar investment
Renewable emissions
Conventional emissions
40,000,000
40,000,000
35,000,000
35,000,000
35,000,000
30,000,000
30,000,000
30,000,000
25,000,000
25,000,000
25,000,000
20,000,000
20,000,000
20,000,000
t
40,000,000
t
t
Total emissions
TO BE DONE
15,000,000
15,000,000
15,000,000
10,000,000
10,000,000
10,000,000
5,000,000
5,000,000
5,000,000
0
0
0
RPS
5
MP
10
15
FIT
20
0
0
RPS
5
MP
10
15
FIT
20
0
RPS
5
MP
10
15
20
FIT
137
(3) Assuming decreased learning rates for solar by -1
percentage point, reduce solar investment
Total emissions (MP)
Total emissions (FIT)
40,000,000
40,000,000
35,000,000
35,000,000
35,000,000
30,000,000
30,000,000
30,000,000
25,000,000
25,000,000
25,000,000
20,000,000
20,000,000
20,000,000
t
40,000,000
t
t
Total emissions (RPS)
TO
BE DONE
15,000,000
15,000,000
15,000,000
10,000,000
10,000,000
10,000,000
5,000,000
5,000,000
5,000,000
0
0
1 3 5 7 9 1113151719
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0
1 3 5 7 9 1113151719
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
Biomass CO2 emissions accounting to be
verified both in terms of financials and
environmental impact
1 3 5 7 9 1113151719
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
138
(3) Assuming decreased learning rates for solar by -1
percentage point, reduce solar investment
USD/MWh
Average electricity price
180
160
140
120
100
80
60
40
20
0
0
5
10
Iteration
RPS
MP
15
20
FIT
TO BE DONE
Change in average electricity price
10
%
5
0
0
5
10
15
20
-5
-10
Iteration
RPS
MP
FIT
139
(3) Assuming decreased learning rates for solar by -1
percentage point, reduce solar investment
Average conventional
installed capacity
Average renewable
installed capacity
100,000
100,000
90,000
90,000
90,000
80,000
80,000
80,000
70,000
70,000
70,000
60,000
60,000
60,000
50,000
MW
100,000
MW
MW
Average installed total
capacity
50,000
TO BE DONE
50,000
40,000
40,000
40,000
30,000
30,000
30,000
20,000
20,000
20,000
10,000
10,000
10,000
0
0
0
RPS
5
10
15
Iteration
MP
FIT
20
0
0
RPS
5
10
15
Iteration
MP
FIT
20
0
RPS
5
10
15
Iteration
MP
20
FIT
140
(3) Assuming decreased learning rates for solar by -1
percentage point, reduce solar investment
Change in average
installed total capacity
Change in average conv.
installed capacity
10
Change in average
renewable installed
capacity
10
10
5
0
5
10
15
-5
20
5
0 BE DONE
TO
0
5
10
15
-5
-10
RPS
MP
FIT
0
0
5
10
15
20
-5
-10
Iteration
20
%
0
%
%
5
-10
Iteration
RPS
MP
FIT
Iteration
RPS
MP
FIT
141
››› Homogeneous investors &
no differences in risk
profiles & no adjustment
to support rates coming
from heterogeneous case
142
(3) Assuming homogenous support investors, but no
support rates adjustment, RES installations drop for FIT
Conventional capacity
400
80
300
60
GW
USD Billions
Total costs
200
100
▪ Homogeneous
investors
40
▪ Identical risk
20
0
0
RPS
MP
FIT
RPS
Electricity price
MP
FIT
▪ Identical support
Loss of load occasions
70
60
50
40
30
20
10
0
profiles and
discount rates for
schemes
rates, not adjusted
coming from heterogeneous case
10
8
6
#
USD/MWh
Key assumptions
4
Key results
2
▪ Lower RES
0
RPS
MP
FIT
RPS
Electricity price volatility
80%
0.8
Billion t
1.0
40%
20%
0%
FIT
CO2 emissions
100%
60%
MP
0.6
investment under
MP and FIT leading
to lower electricity
price volatility and
more conventional
generation needs
0.4
0.2
0.0
RPS
MP
FIT
RPS
MP
FIT
143
(3) Assuming homogenous support investors, but no
support rates adjustment, RES installations drop for FIT
Total electricity gen. costs
USD Billions
400
▪ Homogeneous
300
investors
200
▪ Identical risk
100
0
RPS
MP
FIT
+
Total costs
Total support scheme cost
300
=
200
100
USD Billions
400
0
300
MP
profiles and
discount rates for
schemes
▪ Identical support
rates, not adjusted
coming from heterogeneous case
200
Key results
100
0
RPS
FIT
RPS
MP
FIT
+
Total resource adequacy cost
400
USD Billions
USD Billions
400
Key assumptions
300
200
▪ Lower RES
investment under
MP and FIT leading
to lower electricity
price volatility and
more conventional
generation needs
100
0
RPS
MP
FIT
144
(3) Assuming homogenous support investors, but no
support rates adjustment, RES installations drop for FIT
USD/MWh
Electricity and REC prices
100
90
80
70
60
50
40
30
20
10
0
0
5
RPS
10
MP
15
FIT
20
REC prices
%
Electricity price volatility
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
0
5
10
RPS
MP
15
20
FIT
145
(3) Assuming homogenous support investors, but no
support rates adjustment, RES installations drop for FIT
Electricity prices (MP)
Electricity prices (FIT)
90
90
80
80
80
70
70
70
60
60
60
50
40
USD/MWh
90
USD/MWh
USD/MWh
Electricity prices (RPS)
50
40
50
40
30
30
30
20
20
20
10
10
10
0
0
0
5
10
15
20
0
0
5
10
15
20
0
5
10
15
Wind onshore
Solar PV
Wind onshore
Solar PV
Wind onshore
Solar PV
Geothermal
Biomass
Geothermal
Biomass
Geothermal
Biomass
Hydro
Nuclear
Hydro
Nuclear
Hydro
Nuclear
CCGT
OCGT
CCGT
OCGT
CCGT
OCGT
LOLE
LOLE
20
LOLE
146
(3) Assuming homogenous support investors, but no
support rates adjustment, RES installations drop for FIT
Installed total
generation capacity
Installed conventional
capacity
Installed renewable
capacity
80
80
80
60
60
60
GW
100
GW
100
GW
100
40
40
40
20
20
20
0
0
0
5
RPS
10
MP
15
FIT
20
0
0
5
RPS
10
MP
15
FIT
20
0
5
RPS
10
MP
15
20
FIT
147
(3) Assuming homogenous support investors, but no
support rates adjustment, RES installations drop for FIT
100
100
100
80
80
80
60
60
60
GW
Installed total capacity
(FIT)
GW
Installed total capacity
(MP)
GW
Installed total capacity
(RPS)
40
40
40
20
20
20
0
0
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0 2 4 6 8 10 12 14 16 18 20
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
148
(3) Assuming homogenous support investors, but no
support rates adjustment, RES installations drop for FIT
Total generation
Conventional generation
Renewable generation
200
200
200
150
150
150
TWh
250
TWh
250
TWh
250
100
100
100
50
50
50
0
0
0
5
10
15
RPS
MP
FIT
20
0
0
5
10
15
RPS
MP
FIT
20
0
5
10
15
RPS
MP
FIT
20
149
(3) Assuming homogenous support investors, but no
support rates adjustment, RES installations drop for FIT
Total generation (RPS)
Total generation (MP)
Total generation (FIT)
200
200
200
150
150
150
250
TWh
TWh
Millions
250
TWh
250
100
100
100
50
50
50
0
0
1 3 5 7 9 11 13 15 17 19
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0
1 3 5 7
Hydro
CCGT
Biomass
Wind onshore
9 11 13 15 17 19
Nuclear
OCGT
Geothermal
Solar PV
1 3 5 7 9 11 13 15 17 19
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
150
(3) Assuming homogenous support investors, but no
support rates adjustment, RES installations drop for FIT
Renewable emissions
Conventional emissions
40
40
35
35
35
30
30
30
25
25
25
20
15
Million t
40
Million t
Million t
Total emissions
20
15
20
15
10
10
10
5
5
5
0
0
0
5
10
RPS
MP
15
FIT
20
0
0
5
10
RPS
MP
15
FIT
20
0
5
10
RPS
MP
15
20
FIT
151
(3) Assuming homogenous support investors, but no
support rates adjustment, RES installations drop for FIT
Total emissions (MP)
Total emissions (FIT)
40
40
35
35
35
30
30
30
25
25
25
20
Million t
40
Million t
Million t
Millions
Total emissions (RPS)
20
20
15
15
15
10
10
10
5
5
5
0
0
1 3 5 7 9 11 13 15 17 19
Hydro
CCGT
Biomass
Wind onshore
Nuclear
OCGT
Geothermal
Solar PV
0
1
3
5
7
Hydro
CCGT
Biomass
Wind onshore
9 11 13 15 17 19
Nuclear
OCGT
Geothermal
Solar PV
Biomass CO2 emissions accounting to be
verified both in terms of financials and
environmental impact
1
3
5
7
Hydro
CCGT
Biomass
Wind onshore
9 11 13 15 17 19
Nuclear
OCGT
Geothermal
Solar PV
152
(3) Assuming homogenous support investors, but no
support rates adjustment, RES installations drop for FIT
USD/MWh
Average electricity price
180
160
140
120
100
80
60
40
20
0
0
5
10
Iteration
RPS
MP
15
20
FIT
Change in average electricity price
10
%
5
0
0
5
10
15
20
-5
-10
Iteration
RPS
MP
FIT
153
(3) Assuming homogenous support investors, but no
support rates adjustment, RES installations drop for FIT
Average conventional
installed capacity
Average renewable
installed capacity
100
100
90
90
90
80
80
80
70
70
70
60
60
60
50
GW
100
GW
GW
Average installed total
capacity
50
50
40
40
40
30
30
30
20
20
20
10
10
10
0
0
0
5
RPS
10
15
Iteration
MP
FIT
20
0
0
5
RPS
10
15
Iteration
MP
FIT
20
0
5
RPS
10
15
Iteration
MP
20
FIT
154
(3) Assuming homogenous support investors, but no
support rates adjustment, RES installations drop for FIT
Change in average
installed total
generation capacity
Change in average conv.
installed capacity
Change in average
renewable installed
capacity
10
10
10
5
%
0
0
5
10
15
5
0
0
20
5
10
15
-5
-5
-10
RPS
MP
FIT
0
0
5
10
15
20
-5
-10
Iteration
20
%
%
5
-10
Iteration
RPS
MP
FIT
Iteration
RPS
MP
FIT
155
(2) We assume that investors use a symmetrically
distributed discount rate
Distribution of investors
Share of investors
50%
40%
30%
20%
10%
0%
6%
8%
10%
12%
Discount rate
14%
156
Greek letters
157