Support schemes for renewable energy sources

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C o m p r e h e n s i v e C o u r s e o n E u r o p e ‘ s S u s t a i n a b l e E n e r g y P o l i c y
P r o f . D r. M a r i o R a g w i t z , F r a u n h o f e r I S I
INTRODUCTION TO RENEWABLE ENERGY
SUPPORT SCHEMES AND INSTRUMENTS

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 Motivation and regulatory background of support schemes
 Classification of support instruments
 Generation-based vs investment-focused
 Price driven vs quantity driven
 Evaluating support schemes
 Market and system integration of RET
 Feed-in premium systems
 Support schemes and market integration requirements
 Auction-based determination of remuneration levels
Contents

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Motivation:
 Correction of negative externalities from the use of fossil fuels
 Achieving dynamic efficiency by stimulating technical change
Institutional implementation:
 Based on RES-Directive EC/28/2009 and European Commission guidance for the
design of renewables support schemes SWD(2013) 439 final.
Claims & objectives
 Desired share of RE cannot be delivered by markets alone
 Support schemes needed to overcome market failure and increase competitiveness of
RET
 Design in order to maintain functioning of energy market + lower costs for households
and businesses
Motivation and regulatory background of
support schemes:
Source: EU COM, 2013, Menanteau, (2003)

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General requirements regarding support schemes:
 Flexibility and freedom of choice
 Responsiveness to decreasing production costs
 Support should be gradually removed, market integrating instruments should
be incentivized
 Strengthening of investor confidence by avoiding unannounced or retroactive
changes
 Ensuring efficiency of RE rollout by using cooperation mechanisms in the EU
Features of support schemes
Source: EU COM, 2013

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 Generation-based vs Investment-focused
Contents

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Direct
Indirect
Price-driven Quantity-driven
Regulatory
Investment
focussed
Investment
subsidies Tendering system
Environmental taxes
Tax incentives
Generation
based
Feed-in tariffs Tendering system
Tax incentives
Rate-based incentives
Quota
obligation (RPS)
based on TGCs
Voluntary
Investment
focussed
Shareholder Programs
Voluntary agreements
Contribution Programs
Generation
based
Green tariffs
Classification of energy policy instruments

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• RE purchase obligation for system
operators
• Tariff determined by public authorities
• Guaranteed for specified period of time
• Support allocated to producers of RE
• Highest profit for projects with lowest
production costs
• Costs covered by levies on consumers or
by taxpayers
• Price set, quantity determined by market
Generation based support: Feed-in tariffs
Source: Menanteau et al., (2003); Haas et al., 2004

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This kind of tariff
scheme is for
example used for
wind energy in
Germany, France
and Portugal.
pF80
pF150
pF100
producer surplus (profit)
guaranteed feed-in tariff
gain for public / consumer due to
stepped feed-in tariff
marginal generation costs
Electricity generation compared to reference plant
(efficiency)
prices, costs
[EURO/MWh]
150 140 130 120 110 100 90 80
reference plant
(100% efficiency)
lower efficiencyhigher efficiency
expected producer surplus
[EURO/MWh]
efficiency indicator
(e.g. for wind turbines: - electricity
generation by installed kW)
efficiency indicator
(e.g. for wind turbines: - electricity
generation by installed kW)
Stepped Feed-in tariffs

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Quota obligation based on tradable green
certificates (TGCs)
 Given amount of RES-E set by government (i.e.
legally enforceable quota to producers for specified
amounts of RES-E to be sold)
 Main objective: securing the penetration of a
pre-defined amount of renewable energy.
 In general two different approaches exist:
 Non-tradable quotas: Renewable Portfolio
Standards and Obligations
 Tradable quotas: Electricity or emission
(e.g. CO2) based certificates
 Advantage of TGCs: facilitate fulfillment of the quota obligation by developing the
RES-E potential at minimum generation costs + increase economic efficiency in
terms of total system costs.
 Quantity is set, price determined by market
Source: Haas et al., 2004

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Value of
electricity
generation
Renewable
energy source
Certificates
Value of
conventional
electricity
Value of green
certificate
trading /
consumption
conventional
power plant
trading /
consumption
Quota obligation based on TGCs
A tradable green certificate (TGC) is used to represent the ‘added value’ or
‘greenness’ of one pre-defined unit of electricity produced from RES. If only a
TGC system operates, each producer of RES-E is producing two goods:
1. physical electricity, which is fed into the grid (exported) and sold at market prices
for conventional electricity
2. TGC, which represents the added value of the ‘greenness’

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Feed-in Premium Systems to improve market integration
Market revenues
Feed-
in
Tariff
Management premium
Market premium
Chance to increase
income

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Increasing number of MS use FIP systems as main support scheme
for RES-E
The following reasons for use of FIP are frequently given:
 Higher investment security as compared to TGC system
 Improved compatibility with electricity market as compared to FIT
 All different market places for selling RES power may be used, which
may increase the value of RES
 Creativity of RES generators for creating better forecasts, new balancing
products, use of storage options, optimising plant design and operation
etc. can be activated
Motivation for using FIP systems

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 Investment support
 Grants
 Preferential loans
 While production-based support maximizes production irrespective of price,
investment support decouples production from the sales price
 Often provided on sub-national level
 Tax exemptions or reductions
 Encourage investments
 Financing of RES by taxpayers instead of energy consumer
Investment focused support schemes

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Market price
RES-support
TGC revenues
FIT FIP Quota
fixed premium - cap & floor - sliding/Cfd
Quota
Gov fixes quantity, market decides price
 Obligation for suppliers:
 Minimum RES-E share
 Increasing over time
 Penalty
 Tradable certificates for RES-E production (‘market’ price)
 Obligation is met by submission of certificates to
competent authority
 Power sold on conventional markets
Fixed feed-in tariff (FIT)
Gov fixes price, market decides quantity
 Fixed tariff (€/MWh)
 Guaranteed during lifetime or x years
 Purchase obligation
 (Grid (access & use) priority)
Feed-in premium (FIP)
 Fixed premium (€/MWh)
 Guaranteed during lifetime or x years
 Power sold on conventional markets
Summary: Key features FIT, FIP & Quota

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A clear majority of EU
countries uses FIPs and
FITs as main instrument
4 countries use quota
obligation with TGCs as
main scheme
Dominating support schemes for RES-E in the EU

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Both,
Feed-in tariffs & Quota obligations based on TGCs
create an artifical market!
… either by setting a price (Feed-in tariff)
with the uncertainty with regard to the resulting demand
… or by setting a demand (Quota based on TGCs)
with the uncertainty with respect to the resulting price
Summary: Concluding remark

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Continuous transition between different support schemes
Fixed Feed-in traiffs
Feed-in premium with
electricity price index
Fixed feed-in
premiums
Technology neutral
quota models
Banded quota models
+ low investment risk
+ high technology diversity
+ low windfall profits for mature
technologies
+ broad spectrum of investors
- low compatibility with electricity
markets
+ high compatibility with electricity
markets
+ competition between generators
- high risks and uncertainties (prices
and market growth)
- low incentives for less mature
technologies
- windfall profits

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Contents

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1.Effectiveness (target achievement)
2.Efficiency (static and dynamic)
3.System conformity (with other instruments/ jurisdiction)
4.Practicability
5.Reliability for industry and investors
6.Transaction costs and low social costs
7.Competition
8.Transparency
9.Equal burden sharing
10. Acceptance
Evaluating polic y meas ur es : C r iter ia for the r ating of
ener gy and envir onment polic y meas ur es

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Growth and Existing Potential - Biogas UK
0
2
4
6
8
10
12
14
16
18
20
2002 2003 Total potential
for 2020
[TWh]
Additional realisable
Potential in 2002 until
2020
A B
C
Effectiveness
Indicator represents
the RES-E produced
compared to the
remaining potential
E = (B-A)/C
The meas ur ement of the pr ogr es s of R ES - E
implementation

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0%
2%
4%
6%
8%
10%
12%
14%
MT
SI
SK
LV
FI
CZ
LU
HR
HU
BG
PL
FR
UK
AT
NL
BE
IT
CY
LT
RO
EE
SE
EL
IE
DE
ES
PT
DK
EffectivenessIndicator
Averageeffectivenessindicator2011-2013
Effectiveness indicator2013
Feed-in tariff Quota / TGC Tender Tax incentives/ Investmentgrants
Achievements for wind on - shor e in the per iod 2011 - 2013

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C os ts vs pr ic es for w ind on - s hor e in the EU - 2 7

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Potential pr ofit r anges - w ind ons hor e
( = c o s t - e ff e c t i v e n e s s o f p o l i c i e s )
AT
BE
BG
CY
CZ
DE
DK
EE
ES FI
FR
GR
HU
IE
IT
LTLV
MT
NL
PL
PT
RO
SE
SISK
UK
HR
0%
2%
4%
6%
-50 0 50
Policyeffectivenessindicator2013
Potential profit range [€/MWh]

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Source: BMWI, 2014
D evelopment o f EEG differ ential c os ts ( 2000 – 2 0 1 5 )
* Prognosis

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Development of policy costs and market value for
RES-E in Germany

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Contents

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Renewable electricity generation:
1. creates fluctuating spatial and temporal generation patterns in the power system,
resulting in
 dynamically varying demand for conventional generation
 complex congestion patterns in the transmission grid
2. creates new challenges for the forecast of power generation resulting in new
requirements for
 flexible intraday dispatch
 balancing products
3. impacts hourly electricity prices, based on the merit-order-effect resulting in lower
average prices and potentially increasing spreads
Market and system integration of RET

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Some of these aspects can be solved by new responsibilities for RES
generators:
1. Quickly increasing RES-E shares require higher market integration and system
responsibility from RES plants
2. RES plants should react to total system demand in particular during periods of
negative prices
3. RES plants should be balancing responsible by fulfilling own schedule of balance
to activate the creativity of RES generators to facilitate the full flexibility of the
system
4. RES plants operators should provide good forecasts to make use of the full
information on RES plant status
 Feed-in premiums (FIP) to facilitate system and market integration of
wind energy
Market and system integration of RET

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Feed-in Premium tariff design
 RES-E is sold directly on the market
 Premium is paid on top of the market price
 Typically no purchase obligation is provided
Level of remuneration =
Market electricity price
+ premium for long run costs of RES generation technology
+ premium for market participation
+ premium for system services

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FIP systems differ regarding:
1. Mandatory or optional introduction of FIP model
• Intervals to change between premium and alternative system
2. Type of premium: fixed, cap and floor, sliding
3. Methodology to determine (technology specific) reference prices
• Period for averaging reference prices: hourly, monthly, annually
• Consideration of value of wind / solar hourly generation at spot markets  profile
factor
4. Methodology to determine balancing costs
5. Consideration of other fixed costs, e.g. trading platform, etc.
Differences in FIP design

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Differences in FIP design
 Fixed premium / Cap and floor / Sliding versus
fixed FIT and Quota sytem based on TGC

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Floating Market Premium: Trader ’s Perspective
Market revenues
Feed-
in
Tariff
Management premium
Market premium
Chance to increase
income

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Design of floating market - premium in Germany
Income=Market revenues + support
premium
Support premium
Feed-in
Tariff
Benchmark
for market
revenues
Management premium
Covers the cost of
balancing the
renewable portfolio
Monthly average market
value of the national
technology profile
Individual tariff of each
plant

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Demand-orientated electricity production
Aim / Implementation
 Aim: Shift of generation in periods of
higher demand
 Implementation:
apply hourly load signal to RES plant
operation
FIT by using HT/NT-tariffs or residual
demand
FIP / QS using hourly electr. price
Obligation for plant operator
Possible Variants
a) no obligation, i.e. optional choice of
FIP or demand-dependent FIT
b) obligation of FIP or demand-dependent
FIT in a limited number of hours per
year
c) general obligation of FIP / QS or
demand-dependent FIT
Issues for Discussion
 In case of FIT implementation of HT/NT-Tariff possible, but peak / off-peak structure
increasingly distorted by variable RES
Better system integration by using residual demand as control signal
 fluctuating tariffs results in higher planning effort for plant operator but also
better system integration
 In case of FIP / QS high level of system- and market integration

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Balancing responsibility / forecast obligation
Aim / Implementation
 Aim: RES plants fulfill own schedule of
balance and help reducing of balancing
costs
 Implementation:
 Shift part of balancing
responsibility from TSO to plant
operator
 Possible by obliging plant
operators in FIT, FIP or QS
Obligation for plant operator
Possible Variants
a) Only informing TSO on non-availability
of plant, e.g. snow coverage of plant
b) Day-ahead market responsible (
forecast obligation)
c)Intra-day market responsible until last
minute ( forecast obligation)
Issues for discussion
 In case of FIP / CP / QS typically full transfer of balancing responsibility
 Proper incentives for good forecast in case of FIT
 Penalty or bonus payment at certain threshold level (e.g. mean percentage error)
 Full transfer of balancing costs to plant operator and payment of a general bonus
oriented at the actual costs of TSOs

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Online-plant control and dispatch
 Aim: Contribution of RES plants to
system stability, early warning in case
of critical situations, avoiding extreme
negative prices
 Implementation: real time monitoring
of plant operation, Remote control of
plants in critical situations
 Provision of access to plant data to
TSO
 Otherwise no obligations,
compensation payments by TSO in
case of reduction of generation to avoid
extreme negative prices
 Such measures useful in case of higher penetration of fluctuating RES
 Need for infrastructure investments (data transfer, remote control)
 Regulatory framework conditions: In which situations is the system operator entitled to
reduce plant output?
 Online-Monitoring: Analysis of added value compared to top-down online prognosis
necessary
Aim / Implementation Obligation for plant operator

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Provision of system services
 Aim: Contribution of RES plants to
system stability, efficient provision of
balancing power and energy
 Implementation: Participation of RES
plants in auctions for reserve / balancing
products
 Temporary reduction of power output
for provision of negative balancing power
 Partial curtailment of electricity
generation for provision of positive
balancing power
 Provision of balancing power requires balancing and forecast responsibility
 Typically high minimum capacity requirements for auctions of balancing power
 pooling of small plants necessary
 communication infrastructure needs to be installed in the first place
Aim / Implementation Obligation for plant operator

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Evaluation of measures for FIP and FIT
Measure FIP / QS FIT
Demand oriented
generation
Fulfilled since RES
plants are fully subject
to price signal
Fulfilled if market price
or residual demand is
used as relevant signal
Balancing responsibility Fulfilled because RES
generators need to
comply with schedule as
all other plants
Depends on the detailed
implementation.
Online-Monitoring and
remote control
Can be fulfilled and reasonable under both
schemes
Provision of balancing
power
In principle provided,
economic attractive-
ness depends on market
details.
Can be implemented but
transaction costs and
opportunity costs higher
than in case of FIP.

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• In feed-in systems: Determination of tariffs based on administrative tariff
setting
(based on LCOE and political negotiation processes)
• Involves risk of excessive or insufficient support, if real costs are not well-
known
• Increase of cost-effectiveness requires competitive price formation
• Auctions / tender offer an option to introduce elements of competitive price
formation
• Volume control: tender /auctions used to allocate financing to different
technologies
• Use of auctions in electricity sector common, their use for RES-support has
increased considerably in recent years
• In practice, combining auctions/tender with FIT/FIP is typical
Motivation to use tender/auctions

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Auction / tender and RES support
• Tender / auctions are no independent support scheme category as FIT, FIP,
quota
• Tender / auctions are a measure for competitive price formation
 Combination with different support schemes possible
Support scheme Main objective
Feed-in tariff Determination of support level (Avoiding administrative
tariff setting)
Feed-in premium Determination of support level (Avoiding administrative
tariff setting)
Investment incentive /
Capacity payment
Determination of support level
Quota obligation E.g. determination of value of long-term contracts

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 Different auction design leads to different bidding strategies through different incentives
Terminology and auction types
• Auction: Price only award criterion (combined with qualification requirements)
• Tender: Multi-criteria auction: Price is combined with other award criteria
Terminology
• Single-item auction: only one bid/project wins (e.g. offshore Denmark)
• Multiple-item auction: several bids/projects are accepted up to the auction
volume
Single- or
multiple-
item
• Static / simultaneous auctions (sealed bid): Bidders have no information on
other bids
• Dynamic (e.g. descending clock): Bidders react dynamically to each others bids
Auction
procedure
• Pay-as-bid: each winner receives the price of its bid
• Uniform pricing: all winners receive the same price (clearing price)
Price rule

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Comparison of auction procedures
Auction procedure Advantages Inconveniences
Static auction
(e.g. sealed bid)
Missing interaction between
bidders reduces influencing prices /
strategic behaviour
Price determination difficult if
costs are uncertain („the
winner‘s curse“)
Dynamic auction (e.g.
descending clock)
Improved price determination
through iterative bids (learning)
Higher risk for strategic and
collusive behaviour

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Seite 46
Sources
BDEW Bundesverband der Energie- und Wasserwirtschaft e.V. (2015): Erneuerbare Energien und das EEG: Zahlen,
Fakten, Grafiken. Available online at https://www.bdew.de/internet.nsf/id/foliensatz-erneuerbare-energien-und-das-eeg-
ausgabe-2015-de/$file/Foliensatz%20Energie-Info_Erneuerbare_Energien_und_das_EEG_2015_11.05.2015_final.pdf,
checked on 6/17/2015.
Bundesministerium für Wirtschaft und Energie (2014): EEG in Zahlen: Vergütungen, Differenzkosten und EEG-Umlage
2000 bis 2015. Available online at http://www.erneuerbare-energien.de/EE/Redaktion/DE/Downloads/eeg-in-zahlen-
pdf.pdf?__blob=publicationFile&v=4, checked on 6/17/2015.
European Commission (2013): European Commission guidance for the design of renewables support schemes
SWD(2013) 439 final. Available online at
http://ec.europa.eu/energy/sites/ener/files/com_2013_public_intervention_swd04_en.pdf, checked on 6/12/2015.
Haas, R.; Eichhammer, W.; Huber, C.; Langniss, O.; Lorenzoni, A.; Madlener, R. et al. (2004): How to promote
renewable energy systems successfully and effectively. In Renewable Energy Policies in the European Union
Renewable Energy Policies in the European Union 32 (6), pp. 833–839. DOI: 10.1016/S0301-4215(02)00337-3.
Mayer, J.; Fraunhofer ISE (Burger, B.) (2014): Kurzstudie zur historischen Entwicklung der EEG-Umlage. Available
online at http://www.ise.fraunhofer.de/de/downloads/pdf-files/data-nivc-/kurzstudie-zur-historischen-entwicklung-der-eeg-
umlage.pdf, checked on 6/17/2015.
Menanteau, Philippe; Finon, Dominique; Lamy, Marie-Laure (2003): Prices versus quantities: choosing policies for
promoting the development of renewable energy. In Energy Policy 31 (8), pp. 799–812. DOI: 10.1016/S0301-
4215(02)00133-7.
Ragwitz, Mario; Held, Anne; Breitschopf, Barbara; Rathmann, Max; Klessmann, Corinna; Resch, G. et al. (2011): Review
report on support schemes for renewable electricity and heating in Europe. In A report compiled within the European
research project RE-Shaping, Karlsruhe.

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