HOW TO EFFICIENTLY SUPPORT RENEWABLE ELECTRICITY · 2010-01-14 · renewable energy sources (RES), regardless the energy sector, have been set – 20% RES up to 2020 indicates a huge

HOW TO EFFICIENTLY SUPPORT RENEWABLE ELECTRICITY – THE FUTURE TASK IN EUROPE

Christian PANZER, Energy Economics Group – Vienna University of Technology, Phone +43-1-58801-37360, E-mail: [email protected]

Gustav Resch, Energy Economics Group – Vienna University of Technology, Phone +43-1-58801-37354, E-mail: [email protected]

Reinhard Haas, Energy Economics Group – Vienna University of Technology, Phone +43-1-58801-37354, E-mail: [email protected]

Thomas Faber, Elektrizitäts-Gesellschaft Laufenburg Austria GmbH (EGL), Phone +43-1-5850909-89, E-mail: [email protected]

OVERVIEW Energy policy is the main driver for the enhanced deployment of electricity from renewable energy sources (RES-E) as observed in several countries worldwide. Now, to the first time in Europe, binding targets for renewable energy sources (RES), regardless the energy sector, have been set – 20% RES up to 2020 indicates a huge future challenge for upcoming years. Despite, efforts have to be taken in all three energy sectors, the electricity sector will play a major role in achieving the overall target. Hereby, efficient and effective support measures have to be implemented in order to accompany a strong increase in the share of RES-E with low transfer costs for the society. Several policy options will be discussed with respect to their effectiveness – the development of RES-E – and their efficiency – the associated costs to the development of RES-E1.

Besides the Feed-In Tariffs and the quota systems based on Tradable Green Certificates (TGC), some flexibility mechanism are needed in order to support Member States with moderate RES potentials achieving their RES targets up to 2020. Since all these promotion schemes show different reaction in terms of RES deployment as well as the associated costs, the core objective of this paper is to depict the pros and cons of these policy design options with respect to their impact on future growth of RES and the corresponding costs, and finally draw recommendations for policy makers.

METHODS The issue of effectiveness and efficiency of support schemes is discussed mainly based on the results of scenarios using the model Green-X funded by the European Commission (EC). It allows analyses for both, the EU as a whole as well as for every single member state. Within the model all relevant RES-E technologies – e.g. biomass, wind, geothermal, PV, solar thermal...) technologies as well as demand-side conservation measures are described for every EU country by means of static (and further-on dynamic) cost-resource curves. A static cost curve provides for a point-of-time a relationship between (categories of) technical potentials (of e.g. wind energy, hydro, biogas..) and the corresponding (full) costs of utilisation of this potential at this point-of-time.

To analyse various scenarios different policy schemes can be selected, (e.g. feed-in tariffs, tendering systems, investment subsidies, tax incentives, quotas, tradable certificates) and modelled in a dynamic framework. All the instruments can be applied to all RES technologies separately for the various energy sectors. In addition, general taxes can be adjusted and the effects simulated. These include energy taxes (to be applied to all primary energy carriers as well as to electricity and heat) and environmental taxes on CO2-emissions as well as policies supporting demand-side measures. The corresponding costs and benefits for companies and consumers are an output.

RESULTS Investigations have been carried out, that strengthening the national RES-E support schemes would allow on the one hand to meet the target of 20% RES by 2020 and on the other hand keep the annual consumer expenditures on a moderate level (see Figure 1). Comparatively and relatively high transfer costs appear by introducing a common quota system based on a uniform tradable green certificate scheme – although in this case only the most cost-efficient technologies would be installed, the hereby most expensive power plant determines the common

1 This assessment was conducted for the European Commission, DG TREN within the European research project OPTRES (www.optres.fhg.de) and futures-e (www.futures-e.org).

mailto:[email protected]




http://www.optres.fhg.de/

http://www.futures-e.org/

support level, increasing the transfer costs for the society dramatically (see Figure 1). However, a quota system based on a technology specific support measure almost equals the strengthened national policy system with respect to both, the transfer costs for the society and the achieved overall RES target. Strengthening national policy schemes implies on the one hand to adjust the support level appropriate and on the other hand to overcome non-economic market barriers (as grid connection issue, planning bureaucracy, etc…).

0

5

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20

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12.5% 15.0% 17.5% 20.0%RES deplyoment

(in terms of (gross) final energy) [%]

Ave

rage

yea

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onsu

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exp

endi

ture

s (d

ue to

RES

sup

port

) for

NEW

RES

pla

nt

(200

6 to

202

0) [B

ill.€

]

BAUBAU (removed barriers, DSM)

National action 2011Quota (uniform) 2011Quota (banding) 2011Feed-in premium 2011BAU + Quota (uniform) 2015

BAU + Quota (banding) 2015

BAU + Feed-in premium 2015

National action 2011 + Quota (uniform) 2015

National action 2011 + Quota (banding) 2015

National action 2011 + Feed-in premium 2015

Figure 1: Comparison of average yearly transfer cost / consumer expenditure for new RES plants in relation to

the achieved RES deployment – in terms of gross final energy – within the European Union (EU27)

CONCLUSIONS The key criterion for achieving an enhanced future deployment of RES-E in an effective and efficient manner, besides the continuity and long-term stability of any implemented policy, is the technology specification of the necessary support. Concentrating on only the currently most cost-competitive technologies would exclude the more innovative technologies needed in the long run. In other words technology neutrality may be cost-efficient in the short term, but is more expensive in the long term. The major part of possible efficiency gains can already be exploited by optimising RES-E support measures at the national level – about two thirds of the overall cost reduction potential can be attributed to optimising national support schemes. Further efficiency improvements are possible through guaranteed but strictly limited duration of support as well as that support schemes are targeting solely new RES installations. Introducing a harmonized RES policy can only be favourable if it is designed technology-specific and, that a common European power market exists.

REFERENCES Resch Gustav, C. Panzer, R. Haas, T. Faber, M. Ragwitz, A. Held, M. Rathmann, G. Reece, C. Huber: „20%

RES by 2020 – Scenarios on future European policies for RES-E“. Project report of futures-e (www.futures-e.org), conducted for the European Commission „EACI – European Agency for Competitiveness and Innovations“. TU Vienna, Energy Economics Group in cooperation with Fraunhofer ISI, Ecofys, EGL. Vienna, Austria, 2009.



European IAEE conference … Vienna - September 8th, 2009 … Slide 1How to efficiently support RES-E –

the future task in Europe

Authors: Christian Panzer°, Gustav Resch°, Reinhard Haas°, Thomas Faber*

°Energy Economics Group, Vienna University of Technology *EGL Austria

Contact … Web: http://eeg.tuwien.ac.atEmail: [email protected]

HOW TO HOW TO EFFICIENTLY SUPPORTEFFICIENTLY SUPPORTRENEWABLERENEWABLE ELECTRICITY ELECTRICITY ––THE THE FUTURE TASKFUTURE TASK IN EUROPEIN EUROPE

… based on calculations .made with the help of the .computer model Green-X .

www.green-x.at



ContentContent

1. Introduction

… European RES Directive – 2020 targets

2. Background information

… Short characterisation of the Green-X model, scenario assumptions and future pathways

3. Results on the future deployment of RES in Europe

… Results on RES deployment, investment needs, costs & benefits

4. The policy context – Assessment of future RES policy options

Concluding remarks



How the European Commission set the targets … „FLAT RATE“ & „GDP-Variation“

… i.e.: RES-target2020 = RES2005% + 50% *RESNEW % + 50%*“RESNEW % GDP-weighting“-“first mover bonus“

►►National RES National RES targetstargets for 2020 for 2020 –– thethe bindingbinding goalgoal!!

Note: Additional potentials do not include biofuel imports

(1) Introduction(1) Introduction

0%

10%

20%

30%

40%

50%

60%

70%

80%AT BE BG C

Y

CZ

DK EE FI FR DE

GR

HU IE IT LA LT LU MT

NL PL PT RO SK SI ES SE UK

EU27

RES

in te

rms

of fi

nal e

nerg

y [%

of d

eman

d] RES potential 2020 - share on current (2005) demandProposed RES target for 2020RES share 2005



Simulation model for energy policy instruments in the European energy market•RES-E, RES-H, RES-T and CHP, conventional power•Based on the concept of dynamic cost-resource curves•Allowing forecasts up to 2020/2030 on national / EU-27 level

The The GreenGreen--XX modelmodel

Reference clients: European Commission (DG RESEARCH, DG TREN, DG ENV), Sustainable Energy Ireland, German Ministry for Environment, European Environmental Agency, Consultation to Ministries in Serbia, Luxembourg, Morocco, etc.

(2) Background(2) Background

Base inputinformation

ScenarioInformation

Power generation

(Access Database)

Policystrategiesselection

Social behaviourInvestor/consumer

Externalities

Framework Conditions

(Access Database)

Results Costs and Benefitson a yearly basis (2005-2020 )

Countryselection

Electricitydemand reduction(Access Database)

Technology selection

Economicmarket and policy

assessmentpotential, costs,

offer prices

Simulation of market interactionsRES-E, CHP, DSM power market, EUAs

Base inputinformation

ScenarioInformation

Power generation

(Access Database)

Policystrategiesselection

Social behaviourInvestor/consumer

Externalities

Framework Conditions

(Access Database)

Results Costs and Benefits on a yearly basis (2006 -2030 )

Countryselection

Electricitydemand reduction(Access Database)

Technology selection

Economicmarket and policy

assessmentpotential, costs,

offer prices

Simulation of market interactionsRES, CHP, DSM

power market, EUAs



Realisable potential due to non-economic Markt barriers

0%

2%

4%

6%

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0% 20% 40% 60% 80% 100%Penetration (as share of long-term potential) [%]

Year

ly re

alis

able

pot

entia

l (a

s sh

are

of lo

ng-te

rm

pote

ntia

l) [%

]

Deployment

0%10%20%30%40%50%60%70%80%90%

100%

1990 1995 2000 2005 2010Year [t]

Pene

trat

ion

(as

shar

e of

long

-te

rm p

oten

tial)

[%]

Historical record

Market barrier - Modelimplementation

Technology diffusionTechnology diffusion… in accordance with general diffusion theory, penetration of a market by any new commodity typically follows an ‘S-curve’ pattern… applied within the model to describe the impact of non-economic barriers on RES-E deployment

)0(11

ttdeF

F Markt penetrationd Diffusion rateΔPMn Yearly realisble potential

(according to market barrier)P Long-term realisable potential

e.g. development of wind power (onshore) in Germany

)1( FFdPPMn

Generaldiffusion theory

Model implementation ofdynamic non-economic market barriers




TheThe GreenGreen--XX approach: approach: costcost--resource curvesresource curves

Potentials•by RES-E technology (by band)•by country

Costs of electricity•by RES-E technology (by band)•by country

COST-RESOURCE CURVES•by RES-E technology•by country

costs

potentialDynamic aspects•Costs: Dynamic cost assessment•Potentials: Dynamic restrictions

DYNAMIC

•by year

TheThe GreenGreen--XX approach: approach: DynamicDynamic costcost--resource curvesresource curves




Barriers (non-economic)

Definition of potential termsTheoretical potential ... based on the

determination of the energy flow.Technical potential … based on technical boundary conditions (i.e. efficiencies of

conversion technologies, overall technical limitations as e.g. the available land area to

install wind turbines)

Realisable potential …The realisable potential represents the maximal

achievable potential assuming that all existing barriers can be overcome and all driving forces are

active. Thereby, general

parameters as e.g. market growth rates, planning

constraints are taken into account in a dynamic context

– i.e. the realisable potential has to refer to a

certain year.

AdditionalAdditionalrealisablerealisablemidmid--term term potential potential (up to 2020)(up to 2020)

2000 2005 2010 2015

Historical deployment

Theoretical potential

Ene

rgy

gene

ratio

n

Economic Potential(without additional support)

Technical potential R&D

2020

Policy, Society

Achieved Achieved potential potential (2005)(2005)

Maximal time-path for penetration (Realisable Potential)

Long-term potential

Mid-term potential

Definition of the (additional) realisable mid-term potential (up to 2020)

(2) Background: (2) Background: Potentials and cost for RESPotentials and cost for RES



Achieved potential 2005 und additional realisable potential (up to 2020)for RES-E (in terms of final electricity demand) in the EU-27 by country

►►How far can we goHow far can we go with the renewable energy sources within the electricity with the renewable energy sources within the electricity sector as applicable in the years up to 2020? sector as applicable in the years up to 2020?

(2) Background (2) Background ––realisable RES potentialsrealisable RES potentials

0%

10%

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30%

40%

50%

60%

70%

80%

90%

100%

110%

120%

AT

BE

BG CY CZ

DK

EE FI FR DE

GR

HU IE IT LA LT LU MT NL

PL

PT

RO SK SI

ES

SE

UK

EU27

RES

-E -

Elec

tric

ity g

ener

atio

n po

tent

ial

[% o

f gro

ss e

lect

ricity

dem

and]

RES share 2005RES potential 2020 - share on 2020 demand (baseline case)RES potential 2020 - share on 2020 demand (energy efficiency case)RES potential 2020 - share on current (2005) demand



RES-Electricity technologies35%40%45%50%55%60%65%70%75%80%85%90%95%

100%105%110%115%120%

2006

2008

2010

2012

2014

2016

2018

2020

2022

2024

2026

2028

2030

Cos

t red

uctio

n - s

hare

of i

nitia

l inv

estm

ent

cost

s (a

s in

the

year

200

6) [%

]

Hydropower

Geothermal electricity

Solid biomass - cofiring &large-scale plant Solid biomass - small-scale CHPGaseous biomass

Gaseous biomass CHP

Wind energy

Tidal & wave

Solar thermal electricity

Photovoltaics

►►RES RES costcost“Moderate“ learning

Assumptions on expected future technological progress(technological learning)

Resulting (investment) cost reduction due to technological progress (learning)(according to the

policy scenario)

High energy prices changed the overall situation… Prior learning expectations will not be met with a continuation of high energy prices(i.e. an increase of investment cost could be observed for almost all energy technologies in 2006 to 2008 caused by increasing energy and raw material prices)

(2) Background (2) Background ––RES costRES cost



Geographical scope: EU27 Member StatesTime horizon: 2006 to 2020

►BAU case: RES policies are applied as currently implemented (without any adaptation) – business as usual (BAU) forecast and a baseline energy (electricity) demand scenario.

►►Strengthened national policiesStrengthened national policies: Accelerated RES deployment, assuming that the national RES policy framework will be improved with respect to its efficiency & effectiveness. These changes will become effective by 2011 in order to meet the agreed national targets of 20% RES by 2020. Improvements refer to both the financial support conditions (if necessary) as well as to non-financial barriers (i. e. administrative deficiencies etc.) where a rapid removal is also preconditioned.

Additional cases for the policy assessment are carried out:Harmonized technologytechnology--specificspecific or uniform RES support

►► Overview on RE scenarios Overview on RE scenarios (Green(Green--X)X)




►►Core Objective Core Objective -- Method of approachMethod of approach

quantity[GWh/year]

price, costs [€/MWh]

Market clearingprice = price for certificate

MC

Quota Q

pC

MC ... marginalgeneration costs

pC ... market price for(conventional)electricity

pMC ... marginal price for RES-E (due toquota obligation)

pMC

Generation Costs (GC)

Producer surplus (PS)

Transfer costs for consumer (additional costs for society) = PS + GC – pC * Q

quantity[GWh/year]

price, costs [€/MWh]

Market clearingprice = price for certificate

MC

Quota Q

pC







pMC

Generation Costs (GC)

Producer surplus (PS)

Transfer costs for consumer (additional costs for society) = PS + GC – pC * QTransfer costs for consumer (additional costs for society) = PS + GC – pC * Q

The criteria used for the evaluation of various instrumentsare based on:

•Minimise generation costs

•Lower producer profits

Transfer costTransfer costfor consumer / societyfor consumer / society

(2) Objective (2) Objective / Policy Assessment/ Policy Assessment

Support instruments have to be• effective for increasing the penetration of RES-E and • efficient with respect to minimising the resulting public costs over time.Public costs or transfer cost for consumer / society (due to the promotion of RES-E) are defined as direct premium financial transfer costs from the consumer to the producer due to the RES-E policy compared to the case that consumers would purchase conventional electricity from the power market. This means that these costs do not consider any indirect costs / benefits or externalities(environmental benefits, change of employment, etc.).



►►Sectoral contributionsSectoral contributions to achieve 20% RES by 2020?to achieve 20% RES by 2020?

Deployment of RES-E, RES-H, RES-T and RES in total as shares of corresponding gross demands up to 2020 within the European Union

(EU27) (according to the “strengthened national policy” scenario)

(3) Results (3) Results ––RES deploymentRES deployment

35.3%

19.6%

8.1%

17.7%

19.8%

0%

5%

10%

15%

20%

25%

30%

35%

40%

2006

2007

2008

2009

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2019

2020

RES

-dep

loym

ent -

in re

lativ

e te

rms

(i.e

. as

shar

e of

cor

resp

ondi

ng

(gro

ss) d

eman

d) [%

]RES-electricity

RES-heat

RES-transport

RES primary(EUROSTAT)

RES final



Historical and projected future deployment of RES in the electricity sectorelectricity sector

up to 2020 within the European Union (EU27) (according to the “strengthened national policy” scenario)

►►RES contributionRES contribution to achieve 20% RES by 2020 within the electricity sectorto achieve 20% RES by 2020 within the electricity sector

0

200

400

600

800

1000

120019

97

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

RES

-E -

ener

gy o

utpu

t [TW

h/ye

ar] Wind offshore

Wind onshoreTide & waveSolar thermal electricityPhotovoltaicsHydro large-scaleHydro small-scaleGeothermal electricityBiowasteSolid biomassBiogas

Historical development Future development




Tremendous increase in wind offshore and PV in terms of installed capacity and capital expenditures

(according to the “strengthened national policy” scenario compared to “BAU ”)

►►RESRES--E contribution and associated capital expendituresE contribution and associated capital expenditures……


2006-2010 2011-2015 2016-2020 2006-2020 2006-2010 2011-2015 2016-2020 2006-2020Biogas BG MW 1,588 1,700 2,341 5,629 1,803 3,364 7,330 12,498(Solid) Biomass BM MW 7,612 7,013 6,054 20,679 8,498 11,577 8,803 28,878Biowaste BW MW 1,479 1,158 1,011 3,648 1,661 1,222 790 3,674Geothermal electricity GE MW 147 118 60 325 148 128 90 365Hydro large-scale HY-LS MW 6,876 3,064 1,391 11,331 6,991 2,432 1,378 10,802Hydro small-scale HY-SS MW 1,424 2,389 958 4,771 1,631 2,745 552 4,928Photovoltaics SO-PV MW 2,834 1,096 2,580 6,510 2,963 8,366 17,372 28,700Solar thermal electricity SO-ST MW 367 560 1,348 2,274 390 963 3,498 4,850Tide & Wave TW MW 404 517 285 1,206 416 564 775 1,755Wind onshore WI-ON MW 33,951 33,038 39,334 106,324 34,717 56,436 27,000 118,152Wind offshore WI-OFF MW 1,727 1,735 942 4,404 2,149 12,817 37,851 52,817

RES-E TOTAL RES-E MW 58,409 52,389 56,304 167,101 61,365 100,614 105,440 267,419

Breakdown by RES-electricity category[Unit]

BAU (Business as usual) Strengthened national policiesNew RES-E installations

0

50,000

100,000

150,000

200,000

250,000

2006-2010

2011-2015

2016-2020

Cap

ital e

xpen

ditu

re [M

ill.€

] Wind offshore

Wind onshore

Tide & Wave

Solar thermal electricity

Photovoltaics

Hydro large-scale

Hydro small-scale

Geothermal electricity

Biowaste

(Solid) Biomass

Biogas0

50,000

100,000

150,000

200,000

250,000

2006-2010

2011-2015

2016-2020

Cap

ital e

xpen

ditu

re [M

ill.€

]



16%

18%

20%

22%

24%

26%

28%

30%

32%

34%

36%20

06

2008

2010

2012

2014

2016

2018

2020

RES

-E d

eplo

ymen

t (as

sha

re o

n gr

oss

elec

trici

ty d

eman

d) [%

]

BAU

BAU (removed barriers,DSM)

National action 2011

Quota (uniform) 2011

Quota (banding) 2011

Feed-in premium 2011

Total electricity generation from RES (EU27)as share of gross electricity demand

(4) Results (4) Results / Policy Assessment/ Policy Assessment

BAU - continuation of current national RES policies

BAU with removed barriers and active DSM

Strengthened national RES support

Harmonised uniform RES support by 2011 (quota)

Harmonised technology-specific RES support by 2011 (quota with banding)

Harmonised technology-specific RES support by 2011 (feed-in premium)

Overview on Overview on assessed policy assessed policy

scenariosscenariosMAIN CASESMAIN CASES

Required RES-E deployment



0

5

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25

30

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2007

2008

2009

2010

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2020Y

early

con

sum

er e

xpen

ditu

res

due

to R

ES-E

sup

port

(as

prem

ium

per

MW

h gr

oss

dem

and)

[€

/MW

h DE

MA

ND]

BAU

BAU (removed barriers, DSM)

National action 2011

Quota (uniform) 2011

Quota (banding) 2011

Feed-in premium 2011

Transfer costs for consumer(due to the support of RES-E)Transfer costs for consumer / society (sometimes also called additional / premium costs for consumer / society) are defined as direct premium financial transfer costs from the consumer to the producer due to the RES-E policy compared to the case that consumers would purchase conventional electricity from the power market.

Overview on Overview on assessed policy assessed policy

scenariosscenariosMAIN CASESMAIN CASES

…accelerating RES-E deployment: higher RES deployment requires higher transfer cost in absolute terms (but with lower specific RES support)




►►Costs of Costs of (an enhanced)(an enhanced)RES deploymentRES deployment


0

1

2

3

4

5

6

12.5% 15.0% 17.5% 20.0%RES deplyoment


Ave

rage

yea

rly a

dditi

onal

gen

erat

ion

cost

fo

r NEW

RES

pla

nt (2

006

to 2

020)

[Bill

.€]








Average (2006 to 2020) yearly additional cost(generation & policy cost (consumer

expenditures) referring to the required new RES deployment (2006 to 2020) (EU27)

for the assessed policy scenarios… “least cost” policies lead to lower additional generation cost (~ 2 billion per year)!



►►Costs of Costs of (an enhanced)(an enhanced)RES deploymentRES deployment


Average (2006 to 2020) yearly additional cost(generation & policy cost (consumer

expenditures) referring to the required new RES deployment (2006 to 2020) (EU27)

for the assessed policy scenarios

0

5

10

15

20

25

30

35

40

12.5% 15.0% 17.5% 20.0%RES deplyoment


Ave

rage

yea

rly c

onsu

mer

exp

endi

ture

s (d

ue to

RES

sup

port

) for

NEW

RES

pla

nt

(200

6 to

202

0) [B

ill.€

]








… “least cost”policies lead to higher policy cost (consumer expenditures) (~ 12…15 billion per year)!

… removal of non-economic barriers is crucial to reduce cost and speed-up RES diffusion



► RES policies should be supported by a strong energy efficiency policy. ► The RES policy framework needs an integrated perspective on the use

of biomass. Biomass is a crucial element of RES policy, used in all three sectors

► Efforts are needed in all Member StatesAll modelling exams clearly illustrate Each MS has to contribute!

► A wide range of technologies has to be supported

Even in a pure „least cost“ case a broad portfolio of RE technologies is needed to achieve the 20% target! Costs vary over time, but even more between RES technologies Any future policy framework has to address this sufficiently by providing

technology specific support to the various RES options.

Concluding remarksConcluding remarks



Thanks for yourattention!

In case of questions / remarks …► Email: [email protected]

► Phone: +43-1-58801-37360

►www.futures-e.orgor http://eeg.tuwien.ac.at

The discussion on adequate flexibility for target achievement should not lead to quick and too simplistic policy answers that directs us into a ‘wrong’ policy direction and hinder the move towards

effective & efficient RES support

Documents

HOW TO EFFICIENTLY SUPPORT RENEWABLE ELECTRICITY · 2010-01-14 · renewable energy sources (RES), regardless the energy sector, have been set – 20% RES up to 2020 indicates a huge