Assessing the balance between direct electrification and the use of decarbonised gases in the 2050 EU energy system : METIS 2 : study S6.
Date: 2023-04-11
Institutions: Directorate-General for Energy
Subjects: EU energy policy, electrical energy, energy grid, energy production, energy technology, heating, hydrogen, natural resources, reduction of gas emissions

METIS 2 
Study S6 

Assessing the balance between 
direct electrification and the use 
of decarbonised gases in the 2050 
EU energy system 

December 2021 

METIS 2 Technical Notes eEUR 2022.0658 EN 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Prepared by 

Gaspard Peña Verrier 
Paul Khallouf 
Anthony Vautrin 
Amaury Salauze 
Christopher Andrey 
Tobias Bossmann 

Contact: metis.studies@artelys.com 

This study was ordered and paid for by the European Commission, Directorate-General for 
Energy, Contract no. ENER/C2/2017-98. The information and views set out in this study 
are  those  of  the  author(s)  and  do  not  necessarily  reflect  the  official  opinion  of  the 
Commission. The Commission does not guarantee the accuracy of the data included in this 
study. Neither the Commission nor any person acting on the Commission’s behalf may be 
held responsible for the use which may be made of the information contained therein.  

© European Union, October 2023. 
Reproduction is authorised provided the source is acknowledged.  
More information on the European Union is available on the internet (http://europa.eu). 

EUROPEAN COMMISSION 

Directorate-General for Energy 

Directorate A — Energy Policy 

Directorate C — Renewables, Research and 

Unit A4 —Chief Economist  

Innovation, Energy Efficiency 

Unit C2 — New energy technologies, innovation and 

clean coal 

E-mail: ENER-METIS@ec.europa.eu   

European Commission 

B-1049 Brussels 

2 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
LEGAL NOTICE 

This  document has  been prepared for  the European  Commission however it  reflects  the 
views only of the authors, and the European Commission is not liable for any consequence 
stemming from the reuse of this publication. More information on the European Union is 
available on the Internet (http://www.europa.eu). 

PDF  

ISBN 978-92-76-99078-9 

  doi: 10.2833/942971 

 MJ-05-23-011-EN-N 

Luxembourg: Publications Office of the European Union, 2023 

© European Union, 2023 

The reuse policy of European Commission documents is implemented by the Commission 
Decision 2011/833/EU of 12 December 2011 on the reuse of Commission documents (OJ 
L  330,  14.12.2011,  p.  39).  Except  otherwise  noted,  the  reuse  of  this  document  is 
authorised  under  a  Creative  Commons  Attribution  4.0 International  (CC-BY 4.0) licence 
(https://creativecommons.org/licenses/by/4.0/).  This  means  that  reuse  is  allowed 
provided appropriate credit is given and any changes are indicated. 

For any use or reproduction of elements that are not owned by the European Union, 
permission may need to be sought  

3 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
TABLE OF CONTENTS 
Abbreviations and definitions .................................................................................. 5 

Abbreviations ..................................................................................................... 5 

Metis configuration.............................................................................................. 5 

1  Executive summary .......................................................................................... 6 

2 

Introduction .................................................................................................... 7 

3  Starting point and origins of synergies ................................................................ 8 

3.1 

3.2 

Key features of the 1.5TECH scenario .......................................................... 9 

Refinement of the Long-Term Strategy 1.5TECH scenario ..............................12 

4  A cost-optimal energy system in 2050 ...............................................................13 

4.1 

Focus on industrial heat provision ...............................................................13 

4.2  Overview of the EU energy system .............................................................15 

4.3 

Functioning of the power system ................................................................19 

5  Sensitivity analyses .........................................................................................28 

5.1  Definition of the sensitivity analyses ...........................................................28 

5.2 

5.3 

5.4 

Constrained system flexibility ....................................................................30 

Competition with other sources of hydrogen ................................................34 

Limited natural resources availability over Europe ........................................37 

6  Conclusions and outlook ..................................................................................38 

7  References .....................................................................................................40 

8  Annex ............................................................................................................41 

8.1 

8.2 

8.3 

8.4 

The METIS model .....................................................................................41 

End-use level demand modelling ................................................................41 

Energy supply modelling ...........................................................................46 

Flexibility needs definition .........................................................................53 

4 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ABBREVIATIONS AND DEFINITIONS 

ABBREVIATIONS 

Abbreviation 

Definition 

CCGT 

Combined cycle gas turbine 

CCS 

CHP 

EV 

LTS 

NTC 

OCGT 

PHS 

PV 

RES 

SMR  

vRES 

Carbon capture and storage 

Combined heat and power 

Electric vehicle 

Long Term Strategy 

Net transfer capacity 

Open cycle gas turbine 

Pumped hydro storage 

Photovoltaic 

Renewable energy sources 

Steam methane reforming 

Variable RES 

METIS CONFIGURATION  

The configuration of the METIS model used in the present study is summarised in Table 1. 

Table 1 - METIS Configuration 

METIS Configuration 

Version 

Modules 

Scenario 

METIS v2.0 Beta (non-published) 

Power system and demand modules 

METIS 1.5 scenario 

Time resolution 

Hourly (8760 consecutive time-steps per year) 

Spatial granularity 

Member State 

 
 
 
 
 
 
 
 
1  EXECUTIVE SUMMARY 

If Europe is to meet its 2050 decarbonisation objectives, a change of paradigm needs to 
materialise. The energy sector cannot be understood any more as the sum of independent 
silos consisting of different energy vectors. Indeed, a large number of technologies that 
are  essential  to  meeting  our  decarbonisation  targets  are  linking  systems  and  markets 
currently  being  planned  and  operated  without  fully considering  the  potential  benefits  of 
adopting a holistic approach.  

If this situation is to persist, large-scale sub-optimalities are likely to emerge if the planning 
and operations of the different components of the energy system will not be able to capture 
synergies and interdependencies between energy vectors and markets. 

Interlinkages  between  systems  are  appearing  between  all  vectors,  both  at  the planning 
and  operation  levels.  In  the  case  of  hydrogen,  these  links  are  especially  important,  as 
hydrogen technologies are linking the electricity, methane and heat sectors (via electrolysis 
and  hydrogen  turbines,  repurposing  of  gas  assets,  and  hydrogen  boilers,  respectively). 
Sector integration can allow to capture benefits both in terms of planning and operations: 

  The  production  of  electrolytic  hydrogen  poses  important  challenges  in  terms  of 
planning the deployment of renewable energy (RES) and electrolyser capacities in 
a way that ensures that the overall carbon emissions decrease in an effective and 
cost-efficient  manner.  Furthermore,  key  questions  related  to  the  benefits  of  co-
locating renewable capacities, electrolysers and hydrogen demand centres can only 
be explored if a holistic perspective is adopted. Finally, synergies can also appear if 
planning decisions are taken jointly between the electricity, hydrogen and methane 
sectors as the optimal set of hydrogen infrastructure projects strongly depends on 
the  ability  to  source  electrolysers  (link  with  the  electricity  sector)  and  on  the 
possibility  to  repurpose  part  of the  current  infrastructure  (link  with the  methane 
sector) 

  Similarly, operational considerations also advocate for an integrated approach as 
electrolysers  can  provide  important  flexibility  services  to  the  electricity  sector  if 
provided with appropriate price signals. 

These  considerations  provide  the motivation for  this  study,  which  aims  at  performing  a 
detailed examination of planning decisions and operational management of a 2050 power 
system  with  a focus  on  comparing different  decarbonisation  options  for  the  provision  of 
heat of different temperature levels.  

The key findings are that adopting a precise depiction of the operational management of 
the energy system when considering investment decisions can lead to significant benefits 
in terms of avoided investments, thanks to a better detection of synergies between sectors 
that can only emerge when investigating hourly dynamics. 

In particular, we have compared the investment decisions in the Long-Term Strategy (LTS) 
1.5TECH scenario for the year 2050, as published by the European Commission, and the 
investments the METIS model identifies as being optimal when taking the hourly dynamics 
into  account.  The  results  show  that  there  are  significant  impacts  in  terms  of  use  of 
hydrogen per sector, and in terms of need for gas-fired power generation to help balance 
the power grid.  

The  reduced  level  of  gas-fired  generation  capacity  (and  usage  of  this  capacity)  being 
identified  by  METIS  as  being  required  to  balance  the  power  grid  induces  shifts  in  the 
technology portfolio supplying high-temperature heat. The remaining volume of biogas is 

6 

 
 
 
 
 
 
 
 
 
indeed  favoured  to  using  electrolytic  hydrogen,  thereby  impacting  investments  in  the 
different RES technologies and investments in electrolysers. 
A series of sensitivity analyses have confirmed the robustness of this finding: it is essential 
that (a) interlinkages  between sectors  and (b) the hourly dynamics of the operations of 
the resulting system are well taken into account when building energy transition pathways 
towards a decarbonised EU energy system.  

The  findings  of  this  study  reinforce  the  relevance  of  the  approach  of  the  European 
Commission  consisting  in  putting  sector  integration  at  the  centre  of  its  approach  to 
decarbonising the European economy. It can be expected that adopting such principles at 
the level of national and regional systems (e.g. in NECPs or network development plans) 
would also translate into important benefits in terms of investments savings.  

2  INTRODUCTION 

The EU Green Deal, as  presented by the European Commission in late 2019, fixes  the 
objective  to  make  Europe  the  first  climate-neutral  continent,  i.e.,  to  achieve  net-zero 
greenhouse  gas  emissions  by 2050.  One  of  the  challenges  to  tackle  is  the fact that the 
current energy system is still largely built on several parallel, vertical energy value chains, 
where specific energy resources are rigidly linked with specific end-use sectors. This very 
segregated  approach  is  unlikely to  deliver  a  climate-neutral  economy in  a cost-efficient 
way, and risks being technically and economically inefficient. 

The  EU  Strategy  for  Energy  System  Integration  (COM(2020)  299  final)  proposes 
concrete policy and legislative measures at EU level to gradually shape a new integrated 
energy  system,  aiming  at  achieving  a  more  coordinated  planning  and  operation  of  the 
energy  system  ‘as  a  whole’,  across  multiple  energy  carriers,  infrastructures,  and 
consumption sectors. It sets energy efficiency at the core of a more circular energy system 
and foresees an electrification of end-uses where deemed possible and cost-efficient (as 
direct  electrification  is  generally  a  more  cost-efficient  way  to  decarbonise  end-uses 
compared to other options that require conversion processes to be introduced). 

The  Energy  System  Integration  Strategy  also  considers  that  renewable  and  low-carbon 
fuels  (such  as  hydrogen,  renewable  gases  and  liquids)  can  play  a  key  role  for  deep 
decarbonisation, notably for sectors that are  technically and/or economically challenging 
to  electrify  directly  (e.g.,  specific  end  uses  in  transport  or  industry).  Hydrogen  can  be 
produced  from  renewable  or  low  carbon  electricity  (other  alternatives  include  steam 
methane reforming combined with CCS), and is a potential significant contributor to the 
decarbonisation  of the European  economy if  combined  with  an  adequate  deployment  of 
renewable electricity generation technologies. The EU’s Hydrogen Strategy (COM(2020) 
301 final) sets out an overall approach to tap the full benefits of an economy relying to an 
increasing extent on hydrogen. It shall trigger the deployment of hydrogen and ensure a 
widespread use of hydrogen by 2050. 

The Green Deal and the different strategies are underpinned by a set of scenarios published 
in the context of the EU Long-Term Strategy (LTS, COM(2018) 773 final). They indicate 
different pathways of technology deployment to achieve carbon neutrality by 2050. These 
scenarios and a number of similar studies showcase that electrons and molecules are 
expected to play a role in the future EU energy mix. The ratio between the two has been 
analysed in different assessments under various angles, with respect to energy efficiency, 
infrastructure requirements, exploitation of RES potentials, etc. The present study has for 
objective to combine the different dimensions and provide a holistic analysis of the role of 
the  different  energy  carriers  and conversion technologies.  A  specific  focus  is  set  on the 
coupling of the electricity, gas and heat sectors and on power-to-X technologies. 

7 

 
 
 
 
 
 
 
This study intends to contribute to the current debate and to provide new insights 
in two regards. From a policy perspective, the study helps to identify potential barriers 
to  a  GHG  neutral  energy  system  (for  instance  with  respect  to  the  exploitation  of  RES 
potentials).  It  reveals  the  implications  of  the  climate  neutrality  goal  on  the  need  to 
integrate  the  energy  system  with  all  demand  sectors  (mobility,  industry,  buildings). 
Further, the study sheds light on the benefits of different decarbonisation routes for end-
uses from a holistic perspective. Such approaches are well suited to examine the potential 
misalignments  between the cost-minimising solutions from an end-user perspective and 
the  one  from  a  system  perspective  (that  considers  impacts  on  the  entire  value  chain, 
including infrastructure), and can provide insights on ways policies and measures can be 
formulated to incentivise the optimal solution from a system perspective to emerge. 

Methodology-wise, the study pushes the limits beyond the state-of-the-art of long-term 
energy system modelling. The METIS model was configured for this study to apply a joint 
capacity and dispatch optimisation approach  to determine the cost-optimal configuration 
of the EU’s power, gas (incl. hydrogen) and heat sectors. The approach relies on an hourly 
granularity, focussing on an entire year (2050). This is particularly important to properly 
capture the system dynamics in a context with high RES penetration (which increases the 
variability  of  power  generation  and  the  need  for  flexibility  on  all  timescales),  and  an 
increasingly flexible electricity demand (due to electrification of demand sectors and hybrid 
demand assets such as heat pumps with gas back-up boilers).  

To determine the cost-optimal balance between electrons and (synthetic gas) molecules, 
power-to-X  capacities  are  jointly  optimised  with  renewable  electricity  generation 
capacities,  considering  country-specific  RES-E  cost  curves.  Finally,  the  capacity 
optimisation scope integrates the heat supply technologies in the industry and residential 
sectors, allowing for a least-cost configuration of the heat supply mix considering the entire 
upstream energy value chain. Compared to “power system only” models, METIS integrates 
industrial heat in the model, allowing to showcase that the energy supply of the heat sector 
represents  an  important  lever  of  an  efficient  decarbonisation  strategy.  Indeed,  these 
sectors  are  of  an important size,  and various  options  exist  to  meet their  energy needs, 
with different levels of flexibility being associated to the different options.  

The report is structured as follows. Section 3 introduces the METIS 1.5 scenario which is 
used in the present analysis and which integrates elements from the 1.5 TECH scenario of 
the EC’s Long-Term Strategy. Section 4 presents the results of the scenario assessment, 
with a distinct focus  on the heat sector,  cross-sectoral energy flows  and the  operational 
dynamics in the power sector. A set of sensitivities shedding light on selected parameters 
and their effect on the overall results is presented Section 5. Section 6 provides the overall 
conclusions  and  gives  an  outlook  for  further  modelling  work.  Details  related  to  the 
methodology and all major assumptions can be found in the Annex. 

3  STARTING POINT AND ORIGINS OF SYNERGIES 

This section is devoted to providing a high-level overview of the starting point of this study. 
We assume that we are in a configuration of the energy system that is compatible with net 
zero emissions at the 2050 time horizon, inspired by the 1.5TECH scenario developed by 
the  European  Commission  in  its  Long-Term  Strategy,  and  then  proceed  to  adapt  this 
scenario by optimising the deployment of a selection of technologies (generation, flexibility 
solutions, and part of the heat provision end-uses). 

8 

 
 
 
 
 
 
 
 
We begin by providing an overview of the 1.5TECH scenario, followed by a description of 
the approach we have developed to refine investments in several sectors compared to the 
original 1.5TECH scenario. 

3.1  KEY FEATURES OF THE 1.5TECH SCENARIO 

3.1.1  OVERVIEW OF THE SCENARIOS OF THE EU LONG-TERM STRATEGY 

The EU Long-Term Strategy1 has analysed different pathways that can lead the European 
Union’s economy to reach the Paris agreement target of keeping the temperature rise “well 
below 2°C by 2100”. A first pathway called “Baseline” was created to include the policies 
agreed in the year 2018, such as a reformed EU emissions trading system and different 
target for  energy efficiency and renewable production. In 2050, this  pathway reaches  a 
reduction  of  60%  of  greenhouse  gas  emissions,  which  is  not  sufficient  to  respect  the 
objectives of the Paris Agreement. 

In addition to the Baseline, 5 different pathways have been created to meet the objectives 
of the Paris Agreement, each of them based on different approaches to decarbonise the EU 
economy: energy efficiency, circular economy,  electrification, hydrogen and power-to-X. 
Finally, three additional scenarios have been built by combining these approaches. The first 
one, COMBO, is a cost-efficient combination of the 5 options described before. It reaches 
a 90% GHG emissions reduction, including carbon sinks.  

The  two  final  pathways  are  the  most  ambitious  ones,  with  the  goal  of  keeping  the 
temperature  increase  “around  1.5°C  by  2100”  compared  to  pre-industrial  levels.  When 
taking  carbon  sinks  into  account,  these  two  pathways  reach  carbon  neutrality  by  2050. 
The  1.5TECH  scenario  combines  the  technologies  used  in  the  5  pathways  described 
previously to reach climate neutrality in 2050. The 1.5LIFE scenario is also based on the 
different technological pathways, but with a stronger effort assumed in terms of lifestyle 
changes leading to a lower EU energy consumption. 

The  figure  below  presents  the  demand  levels  for  all  considered  pathways  and  the 
associated  shares  of  the  energy  mix.  While  the  1.5TECH  and  1.5LIFE  have  similar 
technological shares, their deployment differs due to the important difference in demand 
levels,  leading  to  1.5TECH  being  the  most  challenging  net  zero  compatible  scenario  in 
terms of RES deployment.  

1 (European Commission, 2018) 

9 

 
 
                                         
Figure 3-1: Gross inland consumption 

3.1.2  FOCUS ON THE 1.5TECH SCENARIO 

For  this study, the 1.5TECH scenario has been selected as it meets climate neutrality in 
2050  and  primarily  relies  on  the  use  of  clean  technologies,  and  more  moderately  on 
behavioural changes compared to the 1.5LIFE scenario. The role of clean technologies in 
reaching the Paris Agreement goals is highest in the 1.5TECH pathway, leading to greater 
challenges in terms of the magnitude of investments and the provision of flexibility services 
than in the 1.5LIFE pathway. Therefore, it is also the scenario that has the greater potential 
for cost-reducing refinements by exploring synergies between sectors and energy vectors. 

In the 1.5TECH scenario, the decarbonisation of the EU economy relies mainly on massive 
deployment  of  variable  RES  such  as  solar  PV  and  wind  power  capacities.  As  Figure  3-2 
shows, wind and solar PV capacities soar between 2015 and 2050, rising from a 2015 level 
of circa 670 GW at the EU27+UK level to 2240 GW at the 2050 time horizon in the 1.5TECH 
scenario. 

Figure 3-2: Power generation capacities – EU27+UK 

10 

 
 
 
 
This  additional  decarbonised  power  generation  capacity  is  used  to  switch  from  burning 
fossil fuels  to using electricity, both via direct and indirect electrification routes  (i.e. via 
power-to-gas  and  potential  subsequent  conversion  processes).  The  1.5TECH  scenario 
assumes a large deployment of power-to-gas technologies in Europe by 2050, leading to 
the production of synthetic fuels such as e-gases  and e-liquids from hydrogen produced 
via electrolysis, eventually replacing their fossil counterparts. In addition to the switch to 
decarbonised fuels, the mobility and heat sectors are largely electrified, and high end-use 
efficiency  is  reached  in  the  residential  sector  notably  thanks  to  a  large  number  of 
renovations  and  the  use  of  efficient  technologies  such  as  heat  pumps.  These  combined 
factors  allow  for  a  decrease  of  the  European  annual  final  energy  from  more  than 
12 000 TWh in 2015 to 8 000 TWh in 2050. 

Figure 3-3: Final energy consumption by energy carrier – EU27+UK 

As a consequence of the large volumes of e-gases and e-liquids that are required in the 
1.5TECH  scenario  to  decarbonise  the  European  economy,  the  demand  for  electricity 
drastically  increases.  In  2050,  circa  46%  of  the  electricity  demand  comes  from  the 
synthesis  of  carbon-free  fuels  via  electrolysis.  Direct  electrification  also  contributes  to 
increasing  the  final  power  demand  to  levels  above  4  000  TWh.  Combined,  direct  and 
indirect electrification lead to a total power demand more than twice higher in 2050 than 
it was in 2015.  

Note on the Climate Target Plan 

This study has been performed before the publication of the Climate Target Plan (CTP). 
However,  conclusions  can  be  expected  to  remain  valid  as  the  challenge  is  reaching 
similar  orders  of  magnitude  at  the  2050  horizon,  although  the  pathways  deviate 
significantly in the near future due to the more ambitious 2030 target explored in the 
CTP. 

Indeed, according to the Climate Target Plan impact assessment2, a scenario complying 
both  with  the  Paris  Agreement  for  2050  and  the  increased  ambition  of  55%  GHG 

2 (European Commission, 2020) 

11 

 
 
 
                                         
emission-reduction  by 2030  sees  its  electricity generation  more  than  double  between 
2030 and 2050, from 3000 TWh to about 6900 TWh at the EU27 level. 

In the industry sector, the 1.5TECH scenario assumes a transition of the European industry 
to  the use  of  decarbonised fuels  and processes. Hard-to-abate sectors  are decarbonised 
thanks to electrification and/or the use of bio or synthetic fuels in their energy mix. Process 
emissions  are  tackled  with  a  switch  to  innovative  processes,  involving  hydrogen  or 
electricity as the main fuel or feedstock. As a consequence, only a small share of industries 
rely on CCS to reduce carbon emissions. The switch from fossil fuels to direct and indirect 
electrification puts the power system at the centre of this new energy system in terms of 
energy supply.  

3.2  REFINEMENT OF THE LONG-TERM STRATEGY 1.5TECH SCENARIO 

The METIS 1.5 scenario is defined as 2050 net-zero compatible scenario for the European 
power system. It is built using the METIS model, a solution developed by Artelys on behalf 
of the European Commission. METIS is a multi-energy model enabling the analysis of the 
entire European energy system with a high granularity (in time and technological detail), 
and to assess impacts on Member States (see Section 8.1 for a general introduction to the 
METIS model). 

In order to thoroughly account for all aspects of the energy system when optimising the 
balance between electrification and the use of decarbonised fuels, this study includes the 
coupling of the electricity sector and industrial heat supply in its modelling scope, enabling 
an optimisation of the share of each energy carrier in industrial final heat demand (with 
technological options that depend on the temperature levels that have to be supplied). 

Starting  from the  annual demand volumes  by end-use  of the LTS 1.5TECH scenario,  we 
use METIS capabilities, and in particular its demand modelling framework, to allow for the 
exploration of alternative energy supply mixes. This exploration is particularly valuable and 
insightful since, in contrast to other modelling approaches, it is carefully considering the 
the  associated  synergies  and 
the  different  sectors  and 
hourly  dynamics  of 
interdependencies that can emerge when coupling sectors with one another.  

To allow for such an exploration of alternative configurations, the industrial heat demand 
volumes are analysed leading to a distinction between non-substitutable (for e.g. chemical 
processing reasons) and substitutable shares of the industrial heat demand compared to 
the original LTS 1.5TECH scenario. The substitutable share is then eligible to supply mix 
refinements, endogenously optimised with METIS. We allow for investments in specific heat 
supply  assets,  with  technology  options  varying  depending  on  temperature  levels  of  the 
heat  that  needs  to  be  supplied,  including  both  direct  and  indirect  electrification  options 
(heat pumps with different backup options, electric and hydrogen boilers), alongside gas, 
biogas and biomass boilers or CHPs.  

Once supplied with investment options and the technical potential of different technologies 
to supply heat in the considered sectors, METIS jointly optimises electricity, heat, hydrogen 
and  other  power-to-X  production  capacities  as  well  as  their  hourly  dispatch  (8760 
consecutive  time-steps  per  year).  The  objective  of  METIS  is  to  find  cost-minimising 
configurations  considering investment costs, fixed operational and maintenance  costs, 
variable operation and maintenance costs, fuel costs and the costs of CO2 emissions. 

Details related to the way demands are modelled in the different sectors are described in 
Section  8.2.  Section  8.3  provides  more  details  on  the  energy  supply  modelling  and 
12 

 
 
 
describes investment options available to meet the different demands, in particular for the 
different temperature levels of heat demand. 

4  A COST-OPTIMAL ENERGY SYSTEM IN 2050 

This  section  is  devoted  to  presenting  the  results  of  the  joint  capacity  and  dispatch 
optimisation performed with METIS. The sensitivity of the results to various assumptions 
is explored in Section 5. 

4.1  FOCUS ON INDUSTRIAL HEAT PROVISION 

For  each  of  the  three  temperature  levels  considered  in  this  study),  the  industrial  heat 
supply mix is optimised according to the available technological options, which depend on 
the temperature of the heat to be provided. Three temperature levels are distinguished: 
low  temperature  covers  0-150  °C,  medium temperature  refers to  150-500  °C  and  high 
temperature  exceeds  500  °C.  While  for  most  high-temperature  end-uses  a  direct 
electrification  route  is  not  economically  or  technically  relevant,  it  can  be  for  lower 
temperatures via heat pumps and electric boilers. 

600 TWh

500 TWh

400 TWh

300 TWh

200 TWh

100 TWh

0 TWh

Industrial heat pump

Hydrogen boiler

Gas CHP CCS

Gas CHP

Gas boiler CCS

Gas boiler

Electric boiler

Biomass CHP

Biomass boiler

Low temperature

Medium temperature

High temperature

Figure 4-1: Heat generation per technology and temperature level in the METIS 1.5 scenario, 
EU27+UK3 (substitutable heat scope) 

Low temperature heat 

For low temperature heat, used notably in various chemical processes, the heat supply mix 
is  found  to  be  massively  electrified,  as  the  system  leverages large  renewable  electricity 
potentials and the high efficiency of heat pumps. Gas CHPs4 still provide circa 13 TWh of 
heat to spare some electricity during low wind weeks that can materialise in winter. The 

3 Industrial heat supply is not optimised outside the 1.5TECH perimeter 
4 In section 4.2, it is observed that, given low gas consumption volumes, this consumption is actually primarily 
met by biogas. 

13 

 
 
 
 
 
                                         
commissioning  of  gas  CHPs  is  found  to  mainly  occur  in  countries  where  variable  RES 
generation is structurally lower in winter (high PV shares in the mix). 

Medium temperature  

The medium-temperature heat, required for instance by the paper  and pulp industry,  is 
supplied with a more balanced mix between direct electric heat (which relies on the electric 
boiler only), indirect electrification and the use of biofuels.  

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

Hydrogen boiler

Gas CHP CCS

Gas CHP

Gas boiler CCS

Gas boiler

Electric boiler

Biomass CHP

Biomass boiler

Large and balanced
vRES production

Large PV generation

Low biomass cost

Others

Figure 4-2: Medium temperature heat supply mix per country archetype 

When investigating the results at country level, four types of countries can be identified to 
rely on significantly different strategies to supply medium temperature heat: 

  Countries with very large variable RES production (exceeding end-use power and 
P2X  demands)  may  feature  100%  of  direct  or  indirect  electrification.  In  these 
countries,  the  model  commissions  large  PV  capacities,  so  that  summer  power 
production can meet both direct power demand and industrial heat needs. Summer 
heat  needs  can  then  be  supplied  via  direct  electrification,  while  additional 
electrolysis  and  hydrogen  storage  are  installed  to  generate  hydrogen  with  solar 
power during summer, then used by hydrogen boilers  during  the  winter (indirect 
electrification). The latter then supplies 20% of medium-grade heat demand, while 
the remaining 80% are provided by electric boilers. The optimal mix between direct 
and indirect electrification is notably depending on seasonal power prices spreads. 

  Countries  with very significant shares  of PV in their production mix feature more 
seasonal variations of the power supply. During summer, the large amounts of low-
cost power during daytime enable direct electrification. The corresponding electric 
boilers fleet must be complemented by biogas boilers  and CHPs that  can support 
the power system and provide heat during times of electricity scarcity. 

  Countries with lower biomass costs (about 30% lower than the European average) 

massively rely on biomass CHPs. 

14 

 
 
 
  The  remaining  countries,  that  feature  poorer  renewable  potentials,  mainly 

commission biogas boilers.  

High temperature heat 

No  direct  electrification  route  is  assumed  to  be  available  for  the  highest  considered 
temperature level5, widely used e.g., in the steel industry, meaning that available options 
deliver heat with prices that are constant over the entire year (hydrogen storage facilities 
are sufficient to smoothen out price differentials with our assumptions). The cost-optimal 
balance  is  therefore  primarily  based  on  fuel  prices  and  load  factors.  CAPEX-intensive 
technologies are therefore found to run with important full load hours and hydrogen is used 
for peak demand only (see Section 8 for the list of techno-economic parameters and their 
values). 

CHPs  account  for  a  high share  of the  high  temperature heat  supply  mix in  areas  where 
power systems require balancing support, such as solar-dominated countries (need support 
in  winter)  and  countries  relying  on  imports.  Biomass  is  still  largely  used  in  countries 
enjoying low biomass costs. 

4.2  OVERVIEW OF THE EU ENERGY SYSTEM 

The following figure provides an overview of the starting point of this study, namely the 
LTS 1.5TECH scenario, before the optimisation of the provision of industrial heat by METIS. 

5 Direct electrification technologies are progressing rapidly in numerous sectors where they were not expected to 
play a role even a few years ago. Challenging this assumption could be the topic of sensitivity analyses in 
upcoming studies. 

15 

 
 
 
  
 
                                         
Figure 4-3: The European energy system in the 1.5TECH scenario (EU27+7) [TWh] 

This  second figure shows how the energy flows  are impacted by the optimisation of the 
heat supply in the industry. 

Figure 4-4: The European energy system in the METIS 1.5 scenario (EU27+7) [TWh] 

16 

 
 
 
 
 
The Sankey  diagrams  displayed  above  show that the optimisation of energy supply and 
demand of the 1.5TECH scenario, resulting in the so-called METIS 1.5 scenario. Important 
impacts in terms of redistribution of the use of fuels between end-uses and sectors can be 
observed.  Indeed,  by  capturing  the  hourly  dynamics  of  the  energy  system,  the  METIS 
model  allows  for  the  refinement  of  the  use  of  synergies  between  sectors  and  vectors 
compared to the ones originally considered in the LTS 1.5TECH scenario, and in particular 
the use of power-to-X technologies, which strongly link the various sectors. 

In addition to other flexibility solutions such as electrolysers, networks  and storage, the 
LTS 1.5TECH scenario relies to a significant degree on gas (natural gas and biogas) and 
biomass. The hourly simulation of the system equilibrium performed in this study indicates 
that the need for thermal generation could actually be lower than what is being foreseen 
in the LTS 1.5TECH scenario. Biomass and gas consumption by the power system is found 
to be drastically reduced in the METIS 1.5 scenario. Natural gas is found to be completely 
phased out. 

This  reduction  of  thermal  uses  is  enabled  by  the  commissioning  of  large  amounts  of 
renewable  power  generation  capacities,  in  line  with  the  LTS  1.5TECH  levels  (the  total 
variable RES generation in the METIS 1.5 scenario only increases by 170 TWh compared 
to the 1.5TECH scenario). However, the equilibrium is largely changed in favour of onshore 
wind (increases from 750 GW to 1050 GW), at the expense of offshore6 wind (decreases 
from 470 GW to 250 GW)7.  

As explained in section 4.1, a new supply mix is obtained for industrial heat supply. When 
possible, direct electrification is  preferred  to  indirect electrification, which contributes  to 
lowering  P2X  needs.  Biofuels,  that  are  found  not  to  be  used  by  the  power  system  and 
compensated for by a further deployment of variable RES technologies, are mobilised by 
the heat supply fleet as well. Furthermore, the use of industrial heat pumps increases the 
system’s energy efficiency and lowers primary energy supply. 

The switch from indirect electrification to biofuels reduces P2X demand, and consequently 
P2X  losses:  the  total  power  demand  shrinks  by  500  TWh  compared  to  the  1.5TECH 
scenario. 

Hydrogen: at the crossroads of the energy system 

Investments in variable RES capacities and P2X technologies are endogenously determined 
by METIS (together with other technologies – see Section 8) in order to meet the hydrogen 
demand. This demand consists of two components:  a first one directly derived from the  
1.5TECH  scenario  (in  the  sectors  that  are  not  re-optimised  in  this  study)  and  the 
endogenously determined demand that combines hydrogen for heat and hydrogen for e-
CH4,  which  may  then  be  consumed  by  both  heat  and  power  sectors  in  complement  to 
natural gas or biogas. 

The  level  of  hydrogen  demand  has  a  strong  impact  on  the  dimensioning  of  the  power 
supply, and notably on the deployment of variable RES. Since variable RES capital costs 
per unit of energy depend on national circumstances (based on the extent and quality of 
the available potential), hydrogen production costs (including capacity costs) vary between 
Member States. 

6 Hybrid offshore projects like offshore wind power islands connected to multiple countries, were not 
considered. 
7 The Climate Target Plan IA scenarios consider between 285 GW and 301 GW of offshore wind capacities in 
2050 (EU27). 

17 

 
 
                                         
Countries facing limited economic renewable power potentials happen to rely on electricity 
imports to meet the national hydrogen demand through electrolysis. Results show that, in 
all cases, electrolysis is competitive against local provision via SMR+CCS in 2050. In the 
areas relying on electricity imports, times with low power prices are scarcer, which leads 
to  a  more  conservative  dimensioning  of  electrolysers  with  relatively  higher  load  factors 
(see Figure 4-5).  

700 GW

600 GW

500 GW

400 GW

300 GW

200 GW

100 GW

0 GW

100%

80%

60%

40%

20%

0%

EU28

Sunny countries

Windy countries

P2X-on-imports countries

Capacity - Optimised

Capacity - LTS

Load factor - Optimised

Load factor - LTS

Figure 4-5: Electrolyser installed capacities and load factors 

In the METIS 1.5 scenario, the electrolysis capacity exceeds the capacity foreseen by the 
LTS 1.5TECH scenario (664 GW vs 511 GW at the EU27+UK level) while hydrogen annual 
volumes are found to be lower than in the LTS 1.5TECH scenario (respectively 2300 TWh 
and  2850  TWh),  with  a  significantly  lower  share  of  hydrogen  and  e-gas  in  the  heating 
system in the METIS 1.5 scenario, as can be read from the Sankey diagrams shown above. 

Consequently, the load factor of electrolysers is found to exhibit strong differences between 
the two scenarios, with respectively 40% in the METIS 1.5 scenario and 64% in the LTS 
1.5TECH scenario. In the METIS 1.5 scenario, the representation of the hourly dynamics 
allows for the capture of intra-day flexibility value of electrolysers (see Section 4.3 below), 
which compensates for the lower hydrogen-generation related revenues. 

In a nutshell 

The key impacts of the optimisation of the way heat is being supplied to the industry sector 
in the METIS 1.5 scenario compared to the original 1.5TECH scenario can be summarised 
as follows: 

  Flexibility  brought  by  deployed  grid-connected  electrolysers  lowers  the  level  of 
remaining flexibility needs to be provided to the power system. This enables biofuels 
to be used in the industrial heat mix instead of being used for flexibility purposes. 

  Biofuels replace most of hydrogen consumption in the industrial heat supply. 

  Reduced hydrogen demand lowers P2X needs – and losses – and consequently the 
level of electricity demand, thereby leaving room for increased direct electrification 
of industrial heat. 

18 

 
 
 
 
4.3  FUNCTIONING OF THE POWER SYSTEM 

In  the  METIS  1.5  scenario,  the  use  of  hydrogen,  and  the  associated  deployment  of 
electrolysers, drives the commissioning of variable RES across Europe. As a consequence, 
the need for  flexibility increases  on  all timescales  in  order  to  integrate  these  additional 
variable power sources and to balance the system in a cost-effective way. The assumed 
flexibility  on  the  hydrogen-demand  side  (notably  via  storage)  allows  electrolysers  to 
dynamically  adjust to  the  power  supply  and  demand  equilibrium  on  various  timescales. 
The  endogenously  determined  European  (EU27+7)  hydrogen  storage  needs  is  circa 
400 TWh  in  the  METIS  1.5  scenario,  equivalent  to  around  two  months  of  hydrogen 
consumption. The sensitivity analyses (see next section) reveal that electrolysers provide 
more  flexibility  to  the  system  than  the  associated  deployment  of  RES  require,  thereby 
bringing  in  flexibility  value  to  the  system.  The  remaining  daily,  weekly  and  seasonal 
flexibility needs have to be provided by the other flexibility solutions (peakers, batteries, 
pumped-hydro storage, electric vehicles smart charging schemes, networks, etc.). 

4.3.1  ASSESSMENT OF FLEXIBILITY NEEDS AND SUPPLY 

The  need  for  flexibility  is  defined  as  the  need  to  use  dispatchable  assets  to  meet  the 
electricity demand. Flexibility needs can be defined on various timescales (daily, weekly, 
seasonal), and relate to the variations of the residual load (demand – vRES generation) on 
these  timescales.  Flexibility  needs  are  highly  correlated  with  the  system’s  variable  RES 
installed capacities: countries  with greater PV shares may feature higher daily flexibility 
needs,  due  to  the  midday  generation  peak,  while  windy  countries  are  more  likely  to 
experience fluctuations at the weekly scale due to some wind regimes lasting for several 
days. 

Figure 4-6 below shows the level of flexibility needs on three timescales in the optimised 
METIS 1.5 scenario and the share of each of them being met by the flexible operation of 
electrolysers.  

1000 TWh

900 TWh

800 TWh

700 TWh

600 TWh

500 TWh

400 TWh

300 TWh

200 TWh

100 TWh

0 TWh

%
4
5

%
6
4

Daily

Electrolysis

Conventional

%
1
6

%
9
3

Weekly

METIS 1.5

%
2
7

%
8
2

Annual

Figure 4-6: Flexibility needs and supply computed annually (EU27+7) - Electrolysis contrasted with 
other sources 

19 

 
 
 
 
An analysis of the ability of electrolysers to adapt their consumption on all timescales is 
performed in Section 4.3.2. The following paragraphs concentrate on the provision of the 
remaining flexibility needs by other flexibility solutions. 

Provision of daily flexibility  

Daily flexibility needs typically originate from the daily variations of PV generation and the 
change  of  consumption  patterns  between  the  hours  of  the  day.  Short-term  flexibility 
solutions,  notably  batteries,  PHS,  peaking  units  and  demand  flexibility  of  HPs  and  EVs 
provide  the  usual  daily  flexibility.  Figure  4-7  displays  how  remaining  daily  needs,  after 
provision by electrolysis, are covered. These remaining needs represent 435 TWh out of 
950 TWh before the contribution of electrolysers is subtracted.  

Electric  vehicles  are  an  essential  provider  of  daily  flexibility  services  via  their  ability  to 
adapt their power withdrawal within a pre-defined plug-in time-range (smart-charging). In 
particular,  charging-at-work  electric  vehicles  can  switch  by  a  few  hours  their  charging 
patterns  in  order  to  match  mid-day  peak  solar  PV  production.  This  intra-day  charging 
optimisation  allows  for  fewer  stationary  batteries  to  be commissioned  in  the  METIS 1.5 
scenario compared to the LTS 1.5TECH scenario. 

Figure 4-7: Contribution to remaining daily flexibility needs per technology -  
Electrolyser contribution: 516 TWh 

Provision of weekly flexibility  

Weekly flexibility needs typically derive from wind power variations from a day to another 
and  from  the  difference  in  demand  levels  and  dynamics  between  working  days  and 
weekends.  Interconnections  are  found  to  be  the  main  contributors  of  weekly  flexibility 

20 

 
 
 
 
services  since  they  allow  countries  with  different  wind  patterns  to  share  resources  and 
exploit synergies between their electricity systems. 

Demand-side  flexibility  (notably  from  EVs  and HPs)  becomes  less  significant  for  weekly 
flexibility, as they typically enable flexibility within a day. 

Figure 4-8: Contribution to remaining weekly flexibility needs per technology - 
Electrolyser contribution: 394 TWh 

Provision of seasonal flexibility  

The thermo-sensitivity of the demand (heating in winter, cooling in summer) and variable 
RES fluctuations within the year (more solar PV generation in summer, more wind output 
in  winter)  drive  seasonal  flexibility  needs.  Electrolysers,  together  with  the  flexibility  of 
hydrogen  demand,  can  cover more  than  70% of  these  needs  (see  Figure  4-6).  On  this 
timescale, the provision of remaining flexibility needs is well distributed over the various 
technologies in place as shown on Figure 4-9. 

Again,  interconnectors  allow  for  resource  sharing  between  countries  across  the  year, 
alongside  baseload/semi-baseload  capacities  like  nuclear,  hydropower,  biofuels  plants 
(turbines and CHPs). 

21 

 
 
 
 
 
 
 
Figure 4-9: Contribution to remaining annual flexibility needs per technology - 
Electrolyser contribution: 443 TWh 

Stake of conventional flexibility 

As  a  result  of  the  way  flexibility  is  provided  to  the  power  system,  significantly  fewer 
stationary batteries are deployed in the METIS 1.5 scenario compared to the LTS 1.5TECH 
scenario (resp. 25 GW vs 69 GW), and they are found to be distributed over countries with 
high shares of solar PV only. In terms of thermal generation, 38% of gas turbines are CHPs 
(resp. 8% for biomass turbines), totalling 44 GW of installed CHP capacities. CHPs are also 
deployed in countries with high PV shares as they can compensate for lower variable RES 
generation levels during the night and in winter. While high shares of PV drive both storage 
and turbines  deployment, the optimised levels are lower than  what was foreseen in the 
1.5TECH scenario. 

22 

 
 
 
 
250 GW

200 GW

150 GW

100 GW

50 GW

0 GW

Storage

Generation

Storage

Generation

EU27 - LTS 1.5TECH

EU27 - METIS 1.5

Batteries

PHS

Biomass fleets

Gas turbines

Figure 4-10: Power flexibility providers - turbine and storage installed capacities 

In a nutshell 

  The massive  investments  in  electrolysis  capacities  deployed  across Europe  cover 

most of the power system flexibility needs, on all timescales. 

  On the daily timescale, the remaining flexibility needs (45%) are mainly covered by 
demand-side flexibility, notably the smart-charging of EVs, especially if connected 
to the grid during daytime (charging-at-work EVs). Consequently, fewer stationary 
batteries are deemed economic and commissioned than foreseen by the 1.5TECH 
scenario.  

 

In power systems dominated by variable RES, the ability to efficiently use resources 
is key to minimising system costs. As a result, interconnectors are a key contributor 
of flexibility services on all timescales. 

  On  weekly  and  seasonal  timescales,  after  contribution  of  electrolysers  are 
subtracted  (covering  respectively  40%  and  70%  of  the  needs),  the  remaining 
contributions are evenly distributed over the available technologies. High shares of 
PV in the mix increase daily and seasonal flexibility needs, thereby driving the need 
for stationary batteries and biofuels turbines. 

23 

 
 
 
 
 
4.3.2  ELECTROLYSIS: A KEY CONTRIBUTOR TO THE PROVISION OF FLEXIBILITY 

The jointly optimised investments in variable RES and in electrolysers, driven by both the 
LTS-derived, exogenous hydrogen demand, and the endogenously determined hydrogen 
demand dedicated to the heating and power  sectors  (the latter may have an impact on 
hydrogen  demand  by  consuming  e-CH4),  result  in  large  power  generation  fleets. 
Electrolysers  coupled  with  significant  hydrogen  demand-side  flexibility  can  adapt  the 
dynamics  of their  demand  profiles  on  all timescales: hourly,  daily,  weekly  and seasonal 
timescales. 

Figure 4-11: Example of an hourly power demand decomposition in a country. The electrolysers 
can be seen to absorb large shares of the power generated by renewables. 

The case of power mixes dominated by solar PV 

In  countries  with  important  deployments  of  solar  PV,  electrolysers  provide  flexibility  by 
adjusting  their  consumption  patterns  to  hours  of  negative  residual  load  within  the  day. 
Figure 4-12 and Figure 4-13 display the balance between supply and demand in a country 
with a high PV share. 

During  the  day,  the  solar  production  peak  is  indeed  mainly  consumed  by  flexible 
electrolysers and plugged-at-work EVs. At the same time, there is still room for storage, 
in addition to total demand (red line on both figures),  to charge in order to support the 
system when the night comes. 

Flexible plugged-at-home EVs also have a role as they refrain from charging at the end of 
the day and wait for the night (lower EV demand on the 17-21h period, higher on the 23-
6h period). During this period, hydropower, batteries as well as CHPs and imports allow to 
ensure the supply-demand equilibrium is met. 

24 

 
 
 
 
 
Supply 

Figure 4-12: Average daily generation profile in a country with high PV shares 

Demand 

Electrolysis 

Power demand 

EVs 

Figure 4-13: Average daily demand profile in a country with high PV shares. Electrolysers (green 
band) and electric vehicles (red band) provide most of the flexibility. 

System operation under low renewable generation 

Figure  4-14  and  Figure  4-15  show  the  same  solar-dominated  power  system  during  an 
episode of low renewable generation, happening in December.  

On day 1, high wind generation combines with low solar output. The resulting amount of 
available  power  allows  electrolysers  to  run  (green  band  on  Figure  4-15)  and  storage 
capacities  to  charge.  On  top  of  national  power  demand,  high  levels  of  wind  power 
generation allow for exports on day 1.  

25 

 
 
  
 
 
 
 
On day 2, the low levels of wind power have to be partially complemented by hydro and 
imports. During the night from day 2 to day 3, there is very limited wind power. The supply 
then relies essentially on, in this order: hydropower (dark blue), biogas-fuelled gas CHP 
(purple),  biomass  turbines  (dark  grey),  CCGTs,  batteries  and  pumped  hydro  as  well  as 
imports. On the demand-side, only non-flexible demand is served during these hard times. 
Charging-at-home EVs have to charge during the night anyway.  

The dispatch below shows that EVs avoid charging from stored power, i.e. at times when 
the  production  mix includes  storage  assets:  home-EVs  night-peaks  on  day 2  and 3  are 
consecutive to storage discharging times-steps.  On the other hand, batteries happen to 
charge on imports (purple bands exceeding total demand red line on the second chart, on 
days 2 and 3). 

Day  3  combines  low  levels  of  both  solar  and  wind  generation.  All  flexible  generation 
technologies and imports can be seen to support the system around midday, serving only 
non-flexible demand (plugged-at-work EVs have to charge during the day anyway). 

Overall, the electrolysers happen to be operated only during the first day, when important 
RES  power  generation  was  available.  During  periods  where  the  renewable  generation  is 
low, only the required non-flexible demand is served, which can induce the need to operate 
other flexible generation technologies. 

Supply 

Figure 4-14: Hourly generation profile in a solar country during low-wind winter times 

26 

 
 
 
E

Demand 

Heat pumps 

Power demand 

EVs 

Figure 4-15: Hourly demand profile in a solar country during low-wind winter times 

The examples above show that electrolysers can adapt their load to both large and scarce 
renewable instantaneous generation. Provided sufficient flexibility can be provided by the 
hydrogen demand side (e.g. via storage), this allows electrolysers to run only when low-
cost and low-carbon power is available, while meeting the overall hydrogen demand.  

Adaptability of electrolyser operation 

The hourly electrolyser operation mainly depends on the country’s renewable generation 
mix. Figure 4-16 shows the aggregated hourly operations of electrolysers in typical solar-
dominated and wind-dominated countries. In countries with high shares of solar PV, the 
electrolyser operations are mainly limited to daytime, concentrated from spring to autumn. 
In  windy  countries,  as  wind  episodes  generally  last  for  several  days,  electrolysers  run 
during longer time-periods, which occur statistically more often in winter. However, as the 
heart of winter drives demand up due to thermo-sensitive end-uses, electrolysis operations 
then take place mostly in late autumn and early spring.  

27 

 
 
 
 
Sunny country 

Windy country 

Figure 4-16: Year-long hourly electrolyser operation in a country with high PV generation (up)  
and in a country with high wind generation (down) 

In a nutshell 

  Overall,  high  hydrogen  demand  and  electrolysers’  flexibility  drive  investments  in 
variable RES capacities. Electrolysers then capture excess energy when available, 
with  low  RES  generation  levels  still  being  sufficient  to  cover  most  of  the  power 
demand. 

  The  mix  of  variable  RES  technologies  depends  on  the  area’s  resources.  Then, 
electrolysers  adapt  their  operations  to  match  instants  of  low-cost,  low-carbon 
power. As a consequence, the way electrolysers are operated may vary widely from 
an  area to  another,  e.g.  concentrating  on  sunny  days,  windy  weeks,  summer  or 
winter. 

5  SENSITIVITY ANALYSES 

A series of sensitivity analyses has been carried out to test the robustness of the METIS 
1.5 scenario to key parameters. Seven sensitivity analyses have been designed to capture 
METIS response in terms of optimal dimensioning and operations of the integrated system: 
power, hydrogen and heat supply fleets  as  well as  flexibility needs  and  the  provision  of 
flexibility services. The sensitivity analyses are carried out along three major dimensions: 
system flexibility, hydrogen market structure, resources availability. 

5.1  DEFINITION OF THE SENSITIVITY ANALYSES 

Constrained system flexibility 

The sensitivity  lowH2Stock  is  designed to  explore the  impact  of  the  level  of  hydrogen 
demand  flexibility  on  the  whole  system.  In  the  METIS  1.5  scenario,  the  endogenously 
determined European (EU27+7) hydrogen storage capacity is 400 TWh, equivalent to two 

28 

 
 
 
 
 
months  of  hydrogen  consumption. This  variant  assumes  that  national hydrogen  storage 
capacities are halved.  

As shown in Section 4.3.1, the smart charging of electric vehicles is the highest contributor 
to daily flexibility needs after electrolysis as EVs are able to adapt their charging profiles, 
responding to the need of the system. The sensitivity EVnoFlex explores the dimensioning 
and operation of the whole system in the case EVs are not equipped with smart charging 
schemes: they start charging when as soon as they connect to the grid, until the charge is 
complete.  

Industrial  heat  pumps  deployment  in  low  temperature  levels  for  industry  is  still  under 
development and may not be suitable for temperatures up to 150°C by 2050. In the version 
noIndusHP, heat pumps are not considered as an option to supply industrial heat. This 
reduces the total system energy efficiency (other technologies having lower efficiencies), 
which can be expected to drive up the need for variable RES and to result in a new balance 
between direct electrification and decarbonised gases. 

Competition of electrolysis with other sources of hydrogen 

The Long-Term Strategy’s 1.5TECH scenario assumes that the European hydrogen demand 
is  entirely met by production within Europe. Two  sensitivity analyses  are built to assess 
the response to: 

  Volume  competition:  50%  of  hydrogen  demand  being  supplied  through  an 
alternative hydrogen production source, leaving only 50% of the hydrogen demand 
to be supplied within the METIS model. This is the lowH2Demand sensitivity. 

  Price competition: the lowH2Price variant considers that the European countries 
can import hydrogen from outside Europe. The price for these imports is set equal 
to the endogenously determined METIS 1.5 scenario average electrolytic hydrogen 
production cost: 48.8 €/MWh, i.e. 1.46 €/kgH2. 

Hydrogen supply from alternative sources lowers both the need for  additional electricity 
generation  and  the  potential  contribution  of  electrolysis  in  balancing  variable  RES 
generation. In addition, as only the most cost-efficient renewable potentials are exploited, 
it results in a lower average hydrogen production cost which may have an impact on the 
endogenous hydrogen demand levels, notably in the industrial heat supply mix. 

Limited natural resources availability over Europe 

Bio-energies are one of the enablers of the energy transition, as these carbon-neutral fuels 
can replace fossil fuels. Yet, their deployment is limited over Europe, notably  due to the 
required  space  for  crops  and  the  competition  with  food  production.  The  sensitivity 
lowBiogasAvail  captures  the  energy  system  response  to  a  50%  reduction  of  the 
considered biogas potential. 

29 

 
 
Figure 5-1: Set of sensitivity assessments 

5.2  CONSTRAINED SYSTEM FLEXIBILITY 

The  constrained  system  flexibility  series  of  sensitivity  analyses  investigates  the  system 
response to reduced hydrogen storage sites, limited EV smart-charging deployment and 
fewer  technology  options  in  sector  coupling  portfolio  (no  industrial  heat  pumps).  This 
limited available flexibility for the system results in an adaptation of vRES capacities and 
a redistribution of contributions over flexible technologies. 

As discussed in the previous sections, electric vehicles featuring smart charging schemes 
are the largest contributors to the provision of daily flexibility services after electrolysis. 
As  the  EVnoFlex  sensitivity  scenario  assumes  that  their  energy  demand  is  completely 
determined by the EV arrival time at the charging point, the flexibility portfolio has to adapt 
to  replace  the  EVs’  flexibility  services.  As  a  matter  of  fact,  the  system  first  adapts  by 
limiting  flexibility  needs  by  reducing  midday  power  surplus  occurring  with  maximal  PV 
production (see Figure 5-2). In the METIS 1.5 scenario, EVs adapt their charging schedule 
to match the midday power production peak. As smart-charging is not available anymore 
in the EVnoFlex sensitivity, the power system introduces a shift from PV (-60 GW) to wind 
generation capacities (+30 GW). 

In  the  noIndusHP  sensitivity,  direct  electrification  options  for  low  temperature  heat  are 
limited to electric boilers, replacing the heat pumps largely deployed in the base scenario. 
As an energy-efficient technology is removed from the technology portfolio, total energy 
demand rises, leading to the installation of 150 GW of additional variable RES capacities, 
mainly shared between wind onshore (+90 GW) and PV (+60 GW). 

Providing that  sufficient  storage is  available, hydrogen  is  a key  contributor  in  balancing 
variable  renewable  production  over  the  year.  The  high  PV  production in  the  baseline in 
summer is turned into hydrogen, which is stored over the months and consumed in winter 

30 

 
 
 
 
when  available  power  is  scarcer  due  to  the  dynamics  of  the  residual  load.  A  more 
constrained  hydrogen  demand  (lowH2Stock  scenario)  requires  a  flatter  annual  vRES 
profile, resulting in a shift from solar (-159 GW) to wind power (+57 GW). In addition, the 
total  vRES  capacities  are  reduced  to  avoid  renewable  curtailment  in  summer.  As  the 
available  hydrogen  storage  is  limited  to  a  month  consumption,  a  large  share  of  winter 
demand  cannot  be  supplied  with  summer  production,  allowing  alternative  hydrogen 
sources such as SMR+CCS to meet part of the hydrogen demand in winter. In total, 4% of 
hydrogen demand is then produced via alternative sources such as SMR+CCS. 

3000 GW

2500 GW

100%

100%

100%

2000 GW

1500 GW

1000 GW

500 GW

0 GW

120%

100%

96%

80%

60%

Wind onshore fleet

Wind offshore fleet

Solar fleet

40%

Share of H2 demand electrified

20%

0%

METIS 1.5

EVnoFlex

noIndusHP

lowH2Stock

Figure 5-2: vRES installed capacities (EU27+7 scope) 

The operation of SMR+CCS in winter to meet the hydrogen demand is a response to higher 
power prices, while the opposite behaviour happens in summer as power prices fall due to 
excess renewable electricity and limited ability of electrolysers to absorb surplus (due to 
the limited storage). Therefore, the seasonality of the heat supply technology mix increases 
and reflects the underlying balance: a higher share of both direct (+23 TWh) and indirect 
electrification (+37 TWh) for months when hydrogen storage levels are high; and a larger 
operation of CHPs, needed when vRES cannot meet power demand (leading to high power 
prices), while baseload gas-fuelled boilers lose ground. 

The removal of industrial heat pumps from the available  options to supply  heat impacts 
the balance between direct electrification and the use of gaseous fuels. Even if industrial 
heat pumps are partially replaced by direct (+226 TWh for electric boilers, see Figure 5-3) 
and indirect electrification (+ 156 TWh), the heat demand electrification share shrinks from 
50% in the METIS 1.5 scenario to 41% in the NoIndusHP sensitivity analysis. 

31 

 
 
 
1200 TWh

1000 TWh

800 TWh

600 TWh

400 TWh

200 TWh

0 TWh

Hydrogen boiler

Heat pump fleet

Electric boiler

Gas CHP CCS

Gas CHP

Gas boiler CCS

Gas boiler

Biomass CHP

Biomass boiler

METIS 1.5

lowH2Stock

noIndusHP

Figure 5-3: Industrial heat supply technology mix 

The removal of any of these three technologies, namely hydrogen storage, EVs with smart 
charging schemes, or heat pumps, is found to result in an adapted RES portfolio and hence 
is impacting the level of flexibility needs. 

The flexibility needs are highly correlated with the deployment of the different variable RES 
technologies.  As  Figure  5-4  shows,  when  wind  replaces  solar,  flexibility  needs  are 
transferred  from  the  daily  to  the  weekly  timescale:  for  both  lowH2Stock  and  EVnoFlex 
scenarios, daily flexibility needs decrease (-90 TWh and -20 TWh, respectively) and shift 
to  weekly  flexibility needs  (+20 TWh  and  +15 TWh,  respectively).  As  in the noIndusHP 
scenario  one  installs  more  variable  RES,  the  total  flexibility  needs  increase  on  all 
timescales, yet they are compensated by a higher contribution of electrolysers. 

The  lowH2Stock  and  EVnoFlex  scenarios  reset  the  balance  between  the  contribution  to 
flexibility  needs  between  electrolysers  and  other  technologies.  As  EVs  were  the  main 
contributors to daily flexibility services, they are partially replaced by a higher contribution 
from  electrolysers.  On  the  contrary,  a  more  constrained  hydrogen  demand  limits  the 
possible  contribution  from  electrolysers  from  a  season  to  another,  leading  to  higher  a 
contribution of conventional solutions (+80 TWh). 

EVs contribution to daily flexibility needs in the METIS 1.5 scenario (185 TWh, see Figure 
5-5) is  redistributed  over  the  remaining  flexible technologies,  with  the  largest share for 
batteries (+85 TWh). 

32 

 
 
 
 
1000 TWh

900 TWh

800 TWh

700 TWh

600 TWh

500 TWh

400 TWh

300 TWh

200 TWh

100 TWh

0 TWh

%
4
5

%
6
4

.

5
1
S
I
T
E
M

%
6
% 5
3
5

%
7
4

k
c
o
t
S
2
H
w
o

l

%
4
4

P
H
s
u
d
n
o
n

I

%
1
6

%
9
3

x
e
l
F
o
n
V
E

%
2
6

%
8
3

.

5
1
S
I
T
E
M

%
1
6

%
9
3

k
c
o
t
S
2
H
w
o

l

%
2
6

%
8
3

P
H
s
u
d
n
o
n

I

%
2
6

%
8
3

x
e
l
F
o
n
V
E

%
4
6

%
9
6

%
1
% 3
6
3

.

5
1
S
I
T
E
M

k
c
o
t
S
2
H
w
o

l

%
2
7

%
8
2

P
H
s
u
d
n
o
n

I

%
7
5

%
3
4

x
e
l
F
o
n
V
E

Electrolysis

Conventional

Daily

Weekly

Annual

Figure 5-4: Flexibility needs - electrolysis contribution highlighted 

METIS 1.5 

EVnoFlex 

Figure 5-5: Conventional contribution to flexibility needs (Baseline - left - and EVnoFlex - right) 

In the lowH2Stock scenario, the increase in conventional contribution to annual flexibility 
needs is distributed over a larger use of interconnectors (contribution increases by 50 TWh) 
and  a  larger  contribution  of  sector  coupling  technologies  (+27  TWh).  Indeed,  electric 
boilers and CHPs balance each other in providing flexibility in summer (absorption of excess 
renewables with electric boilers) and winter (additional power generation with CHPs). 

The removal of industrial heat pumps does not change the balance between conventional 
and electrolysers contribution, yet the removal of heat pumps from the technology portfolio 

33 

 
 
 
 
 
 
 
 
is compensated by a higher contribution from electric boilers (contribution to daily flexibility 
needs increase by 13 TWh) and batteries (3 TWh increase). 

5.3  COMPETITION WITH OTHER SOURCES OF HYDROGEN 

As  discussed  in  the  previous  sections,  hydrogen  plays  an  important  role  in  the 
decarbonisation  of  the  energy  system,  both  by  being  used  across  all the  sectors  of the 
economy  and  by  balancing  variable  renewable  production.  In  this  section,  two  systems 
with lower hydrogen production levels in Europe are investigated, be it because of easier 
imports of hydrogen from extra-EU sources, or because of a reduced demand. In the first 
case, lowH2Price, imports  of hydrogen  are  available  at  competitive cost  (determined  as 
the  METIS  1.5  scenario  average  hydrogen  production  cost);  in  the  second  case, 
lowH2Demand,  50%  of  hydrogen  demand  is  considered  as  being  supplied  via  another 
source. 

In  the  first  case,  METIS  determines  that  hydrogen  imports  should  supply  20%  of  total 
hydrogen  demand,  meaning  that  80%  of  hydrogen  volumes  are  still  produced  via 
electrolysis and have a production cost lower than the assumed import price (48.8 €/MWh). 
As  more hydrogen  is  supplied  through imports,  less  renewable  generation  is  needed to 
feed the electrolysers, and variable RES installed capacities decrease. Based on the cost-
potential curves8, the decrease in variable  RES capacities starts with its most expensive 
layers, making total renewable production cheaper and consequently decreasing hydrogen 
production cost. The decrease stops when inland hydrogen production cost falls under the 
import price. 

Similarly, as hydrogen demand decreases (lowH2Demand), renewable capacities fall. Of 
the 2650 GW of variable RES capacities, only 1950 GW remain in the sensitivity analysis, 
enough to supply around 53% of total hydrogen consumption. These 53% of total hydrogen 
demand consist of the 50% of exogenous demand whose supply mix has to be optimised 
by  METIS  and  additional  endogenously  determined  demand  in  the  industry  or  power 
sectors.  

8 Further information on the cost potential curves considered in the present study is available in the dedicated 
Technical Note accompanying this study. 

34 

 
 
                                         
3000 GW

2500 GW

2000 GW

1500 GW

1000 GW

500 GW

0 GW

100%

80%

100%

80%

53%

60%

Wind onshore fleet

Wind offshore fleet

Solar fleet

Share of H2 demand electrified

40%

20%

0%

METIS 1.5

lowH2Price

lowH2Demand

Figure 5-6: Variable RES installed capacities (EU27+7) 

The reduction in variable RES capacities removes the most expensive layers of investments 
in RES and lowers both renewable electricity and hydrogen production costs. The industrial 
heat supply mix then evolves  in favour  of direct and indirect electrification. Indeed, the 
share of electrified heat evolves from 50% (METIS 1.5 scenario) to 51% (lowH2Price) and 
61%  (lowH2Demand).  The  increase  is  limited  in  the  first  scenario  as  hydrogen  (and 
renewable  electricity)  production  cost  decreases  only  in  countries  where  the  METIS  1.5 
production cost was higher than the import price. In countries endowed with favourable 
RES potential, where the production cost is under the average, no imports are economically 
relevant and hydrogen or renewable electricity costs do not change. 

Increased electrification is primarily replacing biogas and biomass-based heat supply. The 
avoided fuel consumption is redirected towards power generation to help meet flexibility 
needs. Indeed, reduced operation (and capacities) of electrolysers increase the flexibility 
needs that have to be met by other technologies on all timescales (up to 32% for annual 
needs in the lowH2Demand scenario). The missing flexibility needs are met with increased 
contribution  from  turbines  and  CHPs  (+30 TWh  of  flexibility  provision  on  the  seasonal 
timescale). 

35 

 
 
 
1200 TWh

1000 TWh

800 TWh

600 TWh

400 TWh

200 TWh

0 TWh

1000 TWh

900 TWh

800 TWh

700 TWh

600 TWh

500 TWh

400 TWh

300 TWh

200 TWh

100 TWh

0 TWh

Hydrogen boiler

Heat pump fleet

Electric boiler

Gas CHP CCS

Gas CHP

Gas boiler CCS

Gas boiler

Biomass CHP

Biomass boiler

Electrified heat 

METIS 1.5

lowH2Price

lowH2Demand

Figure 5-7: Industrial heat supply technology mix  

435

433

437

248

270

279

199

223

169

Electrolysis

Conventional

.

5
1
S
I
T
E
M

e
c
i
r
P
2
H
w
o

l

d
n
a
m
e
D
2
H
w
o

l

.

5
1
S
I
T
E
M

e
c
i
r
P
2
H
w
o

l

d
n
a
m
e
D
2
H
w
o

l

.

5
1
S
I
T
E
M

e
c
i
r
P
2
H
w
o

l

d
n
a
m
e
D
2
H
w
o

l

Daily

Weekly

Annual

Figure 5-8: Flexibility needs - electrolysis contribution highlighted 

Figure 5-8 displays the flexibility needs for the two sensitivities, and the contributions of 
electrolysers and conventional technologies respectively. In the two sensitivities explored 
in  this  section,  variable  RES  capacities  are  reduced,  therefore  lowering  total  flexibility 
needs. In the meantime, electrolyser capacities are reduced, too, as  is their contribution 
in covering the flexibility needs. Yet, the contribution of electrolysers reduces more rapidly 
than  total  needs  (then  increasing  the  contribution  of  conventional  technologies).  When 

36 

 
 
 
 
 
 
 
considered the other way, electrolysers provide more flexibility to the system than what 
they cause by driving up the deployment of variable RES.  

5.4  LIMITED NATURAL RESOURCES AVAILABILITY OVER EUROPE 

In this section, the system response to a limited bio-resources availability is captured. The 
scenario  assumes  a  50%  reduction  in  biogas  availability,  leaving  only  374  TWh  for  the 
EU27+7 scope. 

As the biofuel availability for power and heat thermal generation is reduced, a redistribution 
between biofuels and direct or indirect electrification occurs. First, additional variable RES 
capacities are required to replace missing electricity generation: 43 GW of solar PV, 4 GW 
of offshore wind and 52 GW for onshore wind are installed on top of the capacities of the 
METIS  1.5  scenario.  The  entire  hydrogen  demand  is  met  by  electrolytic  hydrogen,  and 
SMR+CCS is not found to be an economically viable alternative.  

Limited  biogas  availability  reduces  the  contribution  to  flexibility  needs  of  thermal 
technologies  and  triggers  a  fuel  switch  from  biogas  to  biomass.  Indeed,  biomass 
consumption  in  the  energy  mix  rises  by  103  TWh,  both  for  heat  and  power  generation 
(CHPs  and biomass  turbines). The remaining missing flexibility is  provided by increased 
contribution of batteries and interconnectors.  

3000 GW

2500 GW

2000 GW

1500 GW

1000 GW

500 GW

0 GW

100%

100%

100%

80%

60%

Wind onshore fleet

Wind offshore fleet

Solar fleet

Share of H2 demand electrified

40%

20%

0%

METIS 1.5

lowBiogasAvail

Figure 5-9: Variable RES installed capacities (EU27+7) 

As competition for biogas increases, a new balance in industrial heat supply is emerging. 
Along with an increase in biomass consumption, the electrification rate grows from 50% to 
65%, with the highest increase for indirect electrification (+126 TWh of hydrogen-based 
heat).  The increase  of  direct  electrification is  limited  due to the  restricted  availability  of 
heat  pumps  to  low-temperature  grades  and  electric  boilers  to  low  and  medium-
temperature grades  respectively. In addition, biogas is a dispatchable resource that can 
be used when electricity prices are high and can thereby alleviate the stress on electricity 

37 

 
 
 
 
 
 
generation.  As  hydrogen  can  easily  be  stored,  indirect  electrification  can  offer  similar 
services and notably provide flexibility services. 

1200 TWh

1000 TWh

800 TWh

600 TWh

400 TWh

200 TWh

0 TWh

Hydrogen boiler

Heat pump fleet

Electric boiler

Gas CHP CCS

Gas CHP

Gas boiler CCS

Gas boiler

Biomass CHP

Biomass boiler

METIS 1.5

lowBiogasAvail

Figure 5-10: Industrial heat supply technology mix 

6  CONCLUSIONS AND OUTLOOK 

This  study  has  demonstrated  the  importance  of  carefully  considering  the  interactions 
between  the  electricity,  hydrogen  and  heat  systems,  and  the  hourly  dynamics  of  these 
systems, when considering planning decisions. The simulations performed with METIS have 
shown that the portfolio of investments in RES capacities, flexibility solutions and routes 
to decarbonise heat can be impacted when a holistic approach is adopted. 

Indeed, holistic approaches to system planning allow for synergies and interdependencies 
between systems to be identified, enabling the emergence of a set of investment decisions 
characterised  by  a  lower  overall  cost,  while  maintaining  the  same  level  of  security  of 
supply. These findings have been exemplified by considering the European Commission’s 
Long-Term  Strategy  (1.5TECH  scenario)  and  by  building  an  alternative  with  the  METIS 
model by allowing for a reshuffling of the heat supply portfolio and for new investments to 
be  made  in  e.g.,  RES  and  flexibility  solutions,  while  keeping  the  same  level  of  useful 
demand as in the original scenario. 

Similar benefits can be expected to emerge when applying integrated planning approaches 
at  the  Member  State  or  regional  levels  (e.g., in  NECPs  or  network  development  plans). 
Upcoming  scenario  building exercises  should  therefore  carefully  consider the impacts  of 
sector integration, as it can result in flexibility being made available by numerous sectors, 
allowing to reduce investments in traditional flexibility solutions. 

The  risks  associated  with  various  portfolios  of  investments  should  continue  to  be 
investigated, under several perspectives: risks related to climate change and resilience of 
investment choices to climatic variations, potential risks leading to stranded assets or to 
lock-in effects (and level of no-regret investments in technologies such as electrolysers), 
risks related to the level of development of a hydrogen infrastructure, etc. Many of these 
aspects are to be explored in METIS 2 Study S4. 

38 

 
 
 
 
39 

 
 
  
 
 
 
 
 
 
 
 
 
 
7  REFERENCES 

Artelys.  (2016).  Weather-driven  revenue  uncertainty  for  power  producers  and  ways  to 

mitigate it.  

Artelys. (2018). METIS Technical Note T8 - METIS Demand and Heat Modules.  
Artelys. (2018). Study S8 - The role and potential of Power-to-X in 2050 .  
Artelys. (2018). Synergies between the energy networks in a high RES 2050 scenario.  
Australian  Government  -  Productivity  Commission.  (2013).  Hedging  in  the  electricity 
from 

market. 
https://www.pc.gov.au/inquiries/completed/electricity/report/28-electricity-
appendixc.pdf 

Retrieved 

BNEF. 

(2013).  Profiling 

the 

risks 

in 

solar  and  wind.  Retrieved 

from 

https://about.bnef.com/blog/profiling-the-risks-in-solar-and-wind/ 

Business 

Insider. 

(2018). 

https://markets.businessinsider.com/commodities/co2-

emissionsrechte/euro. 

E3MLab &  IIASA.  (2016).  Technical  report  on Member  State  results  of the  EUCO  policy 
from 

scenario. 
https://ec.europa.eu/energy/sites/ener/files/documents/20170125_-
_technical_report_on_euco_scenarios_primes_corrected.pdf 

Retrieved 

E3Modelling, Ecofys, Tractebel. (2018). ASSET - Technology pathways in decarbonisation 

scenarios.  

ENTSO-E. 

(2016). 

TYNDP 

data. 

Retrieved 

from 

TYNDP: 

https://tyndp.entsoe.eu/documents/TYNDP2016_Projects%20data.xlsx 

ENTSO-E. (2018). TYNDP 2018 Executive Report. Retrieved from TYNDP Executive Report: 

https://tyndp.entsoe.eu/Documents/TYNDP%20documents/TYNDP2018/consultati
on/Main%20Report/TYNDP2018_Executive%20Report.pdf 

European  Commission.  (2018).  A European strategic  long-term  vision  for  a  prosperous, 

modern, competitive and climate neutral economy.  

European Commission. (2020). Impact Assessment - Stepping up Europe’s 2030 climate 

ambition, SWD(2020) 176 final, Part 2/2.  

Gatzert, N., & Kosub, T. (2015). Risks and Risk Management of Renewable. Retrieved from 

https://actuaries.asn.au/Library/Events/ASTINAFIRERMColloquium/2015/GatzertK
osubRiskManagementPaper.pdf 

IRENA.  (2016).  Unlocking  renewable  energy  investment:  the  role  of risk mitigation  and 
https://www.res4med.org/wp-

structured 
content/uploads/2017/11/IRENA_Risk_Mitigation_and_Structured_Finance_2016.
pdf 

Retrieved 

finance. 

from 

JRC. (2017). Long term (2050) projections of techno-economic performance of large-scale 

heating and cooling in the EU.  

JRC. (2018). Scenario analysis of accelerated coal phase-out by 2030.  
The  Brattle  Group.  (2017).  Managing  Price  Risk  for  Merchant.  Retrieved  from 

http://files.brattle.com/files/7380_managing_price_risk_for_merchant_renewable
_investments.pdf 

40 

 
 
 
 
 
8  ANNEX 

8.1  THE METIS MODEL 

METIS is being developed by Artelys on behalf of the European Commission DG ENER. The 
model includes assumptions on exogenous parameters, policies, datasets and comes with 
a set of pre-configured scenarios. These scenarios usually rely on the inputs and results 
from  the  European  Commission’s  projections  of  the  energy  system,  for  instance  with 
respect to the capacity mix or energy demand per sector. Based on this information, METIS 
allows to perform the hourly dispatch simulation (over the duration of an entire year, i.e., 
8760 consecutive time-steps per year). The result consists of the hourly utilisation of all 
generation,  storage,  conversion  and  cross-border  capacities  as  well  as  demand  side 
response  assets  in  each  country.  In  addition,  in  this  study,  the  investments  in  a  large 
number of technologies are jointly optimised by METIS together with the hourly demand-
supply  equilibrium.  This  report  relies  on  the  use  of  these  scenario-building  features  to 
assess  the  equilibrium  between  investments  in  direct  and  indirect  electrification.  These 
features  will  be  further  enhanced  during  the  remainder  of  the  METIS  project  to  better 
represent the cross-border flows of hydrogen in particular.  

For  more  information  about  the  METIS  model,  please  refer  to  the  EC  METIS  website: 
https://energy.ec.europa.eu/data-analysis/energy-modelling/metis_en.  

8.2  END-USE LEVEL DEMAND MODELLING 

8.2.1  POWER DEMAND MODELLING 

Power demand from the LTS 1.5TECH scenario is modelled in METIS based on historical 
hourly data and annual volumes by end-use as provided by the scenario. In order to allow 
for refinement of the industrial heat supply mix, the corresponding power consumption as 
considered by the LTS is disentangled from the other non-thermosensitive end-uses and 
industrial heat demand is modelled as end-use demand to be fed by biofuels, natural gas, 
direct/indirect electrification etc.  

National electricity demands are split into thermosensitive and non-thermosensitive parts, 
based on the decomposition into the end-uses shown in Table 2. For each of these, demand 
is calibrated to match the annual consumption scenario (here LTS 1.5TECH scenario), the 
aggregation of them all corresponding to the total power demand (see Figure 8-1).  

Processes 

End-use 
Heat pumps 
Air conditioning 
Domestic hot water 
Other thermosensitive end-uses 
Plugin Hybrid electric vehicles 
Battery electric vehicles 
Other non-thermosensitive end-
uses 
Table 2: Power demand decomposition per end-use 

Thermosensitive end-uses 

Non-thermosensitive end-uses 

The power demand is also split between flexible and non-flexible shares of each end-use. 
For instance, heat pumps are equipped with either electric or gas backups and a share of 
them  can  be  coupled  to  a  heat  storage,  allowing  them  to  displace  their  electricity 

41 

 
 
 
 
consumption  to  hours  more  accommodating  to  the  whole  system  (e.g.  with  higher 
renewable  production  in  the  instantaneous  power  mix).  Electric  vehicles  may  feature 
smart-charging. National fleets are split between charging-at-work and charging-at-home 
categories, which has an implication on the time-period when vehicles are plugged onto 
the  network,  able  to  charge.  Electric  vehicles  do  not  feature  vehicle-to-grid.  Electric 
vehicles and heat pumps are considered flexible on daily timescales, provided they meet 
the required demand for services.  

Hourly historical load curves, obtained from the ENTSO-E Transparency Platform9, are split 
into  thermosensitive  and  non-thermosensitive  parts.  The  relation  between  temperature 
and demand is calibrated based on the analysis of several historic years. A statistical model 
is calibrated to fit the thermosensitive part with reference temperatures for each country. 
The statistical model used is a GAM model (Generalised Additive Model). The model (one 
for  each  country)  takes  into  account  calendar  days,  exceptional  days  (public  holidays, 
summer  holiday  period  and  winter  holiday  period)  and  hourly  temperatures.  Then,  the 
statistically  obtained  profiles  are  scaled  according  to  the  demand  scenario,  resulting  in 
calibrated load curves by end-use.10  

Figure 8-1: End-use decomposition of power demand 

8.2.2  HEAT DEMAND MODELLING (INDUSTRIAL USES) 

As the transition to a decarbonised European industry implies a switch to carbon-neutral 
fuels (direct and indirect electrification, biofuels), the balance between direct electrification 
and decarbonised gases can only be optimised taking into account the potential coupling 
between the electricity sector  and  the  industry,  and notably through  the  industrial heat 
supply.  

A literature review has been performed and has shown that an endogenous assessment of 
the optimal industrial heat mix has to consider that all potential heat supply technologies 
cannot  provide  all  temperature  levels,  which  may  vary  significantly  between  industrial 
processes; and that all industrial heat uses cannot be substituted with other fuels, either 
for operational, chemical, or technical reasons. 

9 https://transparency.entsoe.eu/ 
10 For further details, check the METIS Technical Note 8 
(https://energy.ec.europa.eu/document/download/f4728733-6593-4ae1-be58-ce5161621945_en)  

42 

 
 
 
 
 
 
                                         
Indeed, in some industries, heat delivery is strongly linked to the consecutive operations 
of  several  processes  within  a  single  plant.  For  instance,  flue  gases  from  an  upstream 
process may be used to provide heat downstream. In such a case, substituting the energy 
carrier of the upstream process may remove or change the physical characteristics of the 
flue gases and consequently the heat supply of the downstream process. 

Industrial  processes  can  chemically  rely  on  the  energy  vector.  In  blast  furnaces  for 
instance, coke is both used to supply heat and reduce the iron oxides, preventing a switch 
to another fuel without re-engineering the entire process. 

Eventually,  some  processes  rely  on  very  specific  technologies,  hampering  the  use  of 
another  fuel  that  would  be  incompatible.  That  is  the  case  for  secondary  iron,  which  is 
mostly melted in electric arc furnaces that run exclusively on electricity.  

The  literature  review  allowed  for  the  identification  of  substitutable  and  process-specific 
uses and the disentangling of the latter between three temperature levels, which impact 
the set of heat supply technological options and their techno-economic parameters. Three 
standard categories  for heat temperature  have been considered: the lower temperature 
level stands for temperatures below 150°C, medium temperatures ranges between 150°C 
and 500°C, while temperatures above 500°C form the high temperature level. 

The  following  sectors  are  considered  in  the  study:  iron  and  steel,  non-ferrous  metals, 
chemicals,  non-metallic  minerals,  paper  and  pulp,  and  other  industries.  The  following 
processes  are considered: blast furnaces, thermal processing, steam uses, low enthalpy 
heat, electric processing, and specific electricity. 

Building  on the literature  review,  the  available options  to decarbonise the  heat mix  are 
determined based on the 1.5TECH data, based on the following methodology: 

1.  Industrial  processes  are  classified  as  substitutable  or  non-substitutable  heat 

demand 

2.  A temperature level is assigned to each substitutable process, which will affect the 

set of available heat provision options  

3.  The substitutable shares of 1.5TECH industrial heat demand volumes, provided at 
the process level, are then identified and assigned a temperature level. This data 
processing  phase  leads  to  one  annual,  end-use  industrial  heat  demand  per 
temperature level and Member State, whose final supply mix is to be endogenously 
determined. 

43 

 
 
 
 
 
 
 
Figure 8-2: Methodology for the integration of industrial heat demand in the METIS model 

This  process,  once  applied  to  the  European  industry,  results  in  around  1530  TWh  of 
industrial  heat  demand,  1020  TWh  of  which  being  substitutable.  High temperature heat 
represents the highest share of the substitutable scope.  

33%

67%

24%

17%

26%

Non-substitutable

Low temperature

Medium temperature

High temperature

Figure 8-3: European industrial heat demand in 2050 (1530 TWh, 1020 TWh substitutable) 

44 

 
 
 
 
 
8.2.3  HYDROGEN DEMAND MODELLING 

The  1.5TECH  scenario  assumes  a major  role for  hydrogen  in the  decarbonisation  of  the 
European economy. Hydrogen synthesised from electricity via electrolysis is either used as 
such  or  later  converted  in  e-gases  or  e-liquids  through  methanation  or  Fischer-Tropsch 
processes.  Hydrogen,  e-gases  and  e-liquids  are  then  consumed  in  the  industrial, 
residential,  tertiary,  power  and  transport  sectors  as  substitutes  to  fossil  fuels.  As 
consecutive conversion losses along the power-to-X value chain gradually increase the fuel 
costs, e-liquids only emerge in 1.5TECH as a solution for sectors and uses where hydrogen 
or e-gases are not suitable. 

1200 TWh

1000 TWh

800 TWh

600 TWh

400 TWh

200 TWh

0 TWh

Power

Industry

Residential & services

Transport

Hydrogen

e-gas

e-liquids

Figure 8-4: 1.5TECH end-use hydrogen and e-fuels consumption per sector in 2050 

Total hydrogen demand then consists of: 

  An exogenous share, directly taken from the 1.5TECH scenario figures. This 
share itself accounts for hydrogen, e-gas and e-liquids end-uses, for energy 
and  non-energy  usage  (e.g.  hydrogen  used  as  feedstock  for  ammonia 
production). Hydrogen employed by substitutable shares of industrial heat 
demand is not aggregated to this exogenous share, as well as hydrogen used 
for power generation 

  An  industrial  heat-related  share,  which  is  a  result  of  the  endogenous 
optimisation  of  the  supply  mix  of  industrial  heat  (hydrogen  boilers  are 
considered as a heat provision option, see section 8.3.2 below) 

  A power-related share, result of the optimisation as well, that accounts for 

the power-to-gas-to-power energy route.  

Since  the  possible  flexibility  on  the  end-user  side  is  difficult  to  evaluate  (possible  local 
storage of hydrogen, refurbishment of existing network and storage for e-gases, flexibility 
of  the  fuel  supply  for  vehicles,  etc.),  we  have  chosen  to  assume  a  certain  flexibility  of 
hydrogen demand and to measure the sensitivity of our results to this level of end-user 
flexibility assumption. On the demand-side of hydrogen, e-gas and e-liquids, our central 
assumption is that sufficient flexibility is  available (namely via storage and pipelines) to 
only consider an annual volume constraint. The impact of limited storage capacities  and 
reduced hydrogen demand flexibility is assessed in the sensitivity analyses. 

45 

 
 
 
As the power-to-X loop is jointly optimised with the power system, re-optimising the supply 
mix  foreseen  by  the  LTS  but  may  lead  to  different  needs  in  power  generation  (and 
flexibility) capacities compared to the ones identified in the LTS. This is a consequence of 
the modelling approach of a more precise representation of the dynamics of interlinkages 
than in the modelling supporting the LTS and the expanded set of industrial heat provision 
options. 

We consider that the supply-demand equilibrium for hydrogen has to be met at Member 
State level, with potential alternative supply modelled as SMR equipped with CCS11. The 
impact of putative low-cost hydrogen imports on the European energy system dimension 
and operations is studied as a sensitivity analysis. 

8.3  ENERGY SUPPLY MODELLING 

8.3.1  POWER SUPPLY AND FLEXIBILITY MODELLING 

Power supply  

The power  supply fleet consists  of both exogenous  and endogenous installed capacities. 
Exogenous capacities are taken as is from the LTS as their development is not driven  by 
economic considerations only. The corresponding technologies are: 

  Fossil fuel fleets (oil, coal and lignite) 

  Waste fleet 

  Nuclear fleet 

  Hydro fleet (reservoir and run-of-river). 

Other power generation technologies are  subject to optimal dimensioning within METIS, 
given  the  exogenous  demand  derived  from  the  LTS,  jointly  with  the  endogenous 
electrification of e.g. heat demand. 

The corresponding technologies are: 

  CCGT fleet (can be equipped with CCS) 

  OCGT fleet 

  Biomass fleet 

  Gas CHP (can be equipped with CCS) 

  Biomass CHP 

11 SMR is only one of the alternative technologies, other technologies such as ATR, steam reforming of biogas, 
or pyro-gasification of biomass can be considered. 

46 

 
 
                                         
  Variable renewable energy sources, whose deployment is based on cost-potential 

curves12: 

o  Solar PV panels  

o  Offshore wind  

o  Onshore wind  

Biofuels  (biomass  and  biogas)  are  subject  to  limited  resource  deployment  in  order  to 
respect  the  consumption  potentials  assumed  in  the  1.5TECH  scenario.  The  resource  is 
supplied  continuously  over the year,  and  can  be  consumed  anytime.  Biogas  potential is 
distributed  over  the  European  Union  and  can  be  subject  to  cross-border  exchanges 
between Member States. Biomass is considered as a domestic consumption resource. 

Resources’  costs  are  derived  from  1.5TECH  assumptions,  and  combined  with  the  IEA’s 
World Energy Outlook cost-potential curves when the resource has limited availability.  

Cost (€/MWh HHV  
or €/t CO2) 

Limited availability 

Natural 
gas 
43.8 

Biogas 

Biomass 

61.2 

40.6 

CO2 

350 

 

 

Table 3: Fuel costs 

Gas turbines  and CHPs can be fed in with either  biogas, natural gas or  e-gas; the cost-
efficient gas mix is determined  endogenously, taking into account constraints  such as  a 
limited biogas potential. 

Power storage 

As storage technologies are key assets to ensure cost-effective power supply and demand 
balance at all times, they are endogenously dimensioned and operated in METIS.  

Pumped Hydro Storage (PHS) is one of the most conventional storage solutions, but their 
remaining deployment potential is limited and might vary considerably from one country 
to the next. In this study, two PHS categories are considered: existing PHS, representing 
2020 capacities and new PHS, in which METIS can decide to invest. 

Batteries can be leveraged to provide short-term flexibility to the system. Four types of 
battery  are  considered,  with  storage  duration  of  1,  2,  4  or  8  hours.  No  maximum 
deployment is  considered for these  assets. Their  CAPEX and other technical parameters 
can be found in Table 4. 

Cross-border exchanges 

Electricity  interconnectors  have  a  significant  role  in  the  provision  of  flexibility  to  power 
systems,  allowing  countries  to  benefit  from  each  other’s  resources  and  flexibility.  They 
enable exports and imports of energy between countries with different energy prices and 
levels of vRES share, helping avoid RES curtailment, load curtailment and make better use 
of generation fleets. 

12 The building approach for these cost-potential curves is described in the METIS Technical Note 
accompanying this study. 

47 

 
 
 
 
 
 
 
                                         
The  investments  in  interconnectors  are  optimised  within  bounds  derived  from  the 
EUCO3232.5  scenario  (minimum  values)  and  the  TYNDP  2018  Global  Climate  Action 
scenario (maximum values), which are shown on Figure 8-5. 

Optimised 
capacity 

Investment cost 
(€/kW) 

Fixed O&M 
costs (% CAPEX) 

Efficiency  Lifetime 

Interconnectors 

Back-up power 
plants 

Storage 
capacities 

Additional 
capacities 
OCGT 
CCGT 
CCGT with CCS 
Pumped 
Hydro 

Batteries 

 

 
 
 

 

 

Based on line-by-line projects 

- 

60013 
750 
1500 

121214 

120€/kW + 
120€/kWh15 

3% 
2% 
2% 

1,20% 

40% 
63% 
49% 

81% 

4,30% 

90% 

50 

25 
30 
30 

60 

10 

Table 4: Technical parameters for flexibility solutions 

Figure 8-5: Interconnectors potential for EU countries 

8.3.2  HEAT PROVISION MODELLING 

8.3.2.1  Residential/tertiary heat supply 

As mentioned in Section 8.2.1, the power demand for residential heat pumps is modelled 
as  being flexible. In  addition  to  a  2 hours heat  storage, heat  pumps  are equipped  with 

13 CAPEX source: (E3Modelling, Ecofys, Tractebel, 2018) 
14 CAPEX source: (Artelys, 2018) 
15 (Artelys, 2018) 

48 

 
 
 
 
  
 
 
 
 
                                         
backup boilers able to supply peak heat demand. The first option allows for the provision 
of daily flexibility by shifting the electric load to hours with less stress on the power system 
(e.g. larger local vRES generation or available imports). The second option enables heat 
pumps to mitigate peak power demand that occurs when low air temperature impairs the 
heat pump’s coefficient of performance (which may go below 1) and output capacity while 
exacerbating heat demand. 

Covering  heat  demand  peaks  exclusively  with  heat  pumps  would  indeed  imply  a  costly 
over-dimensioning of the equipment and higher capital costs. To that extent, low CAPEX 
back-up heaters are installed, and the heat pump is dimensioned to cover 5% of the heat 
demand  only16.  The  trade-off  between  investing  in  gas  or  power  back-up  heaters  is 
optimised by METIS, based on endogenous gas and power prices, and on the capital costs 
of the various options.  

Figure 8-6: Typical heat pump utilisation in winter 

8.3.2.2  Industrial heat supply 

A literature review has helped identify heat generation technologies that can be expected 
to be available in 2050 and their characteristics17. The technology portfolio depends on the 
type  of  heat  demand,  most  importantly  on  the  heat  temperature.  The  identified 
technologies have been clustered into three groups, according to the temperature levels 
they  can  supply,  i.e.  low  temperature  heat  (below  150°C),  medium  temperature  heat 
(between 150°C and 500°C) and high temperature heat (above 500°C). 

Among the available technology options, it has been found that industrial heat pumps were 
eligible for low temperature heat only, whereas electric boilers can provide both low and 
medium temperature heat. At high temperature levels, furnace heat is provided by gas or 

16 (Artelys, 2018) 
17 (JRC, 2018) 

49 

 
 
 
 
 
 
                                         
biofuels  burners.  Cost  assumptions  for  all  these  technologies  were  based  on the ASSET 
database18 and may be subject to rapid evolution. 

In order to thoroughly model the industrial heat coupling with the power sector, relevant 
technologies can either be derived as heat-only boilers or CHP technologies. Cogeneration 
has a role in a limited-resources scenario as it brings in energy savings through their higher 
efficiencies. 

In  line  with  1.5TECH  assumptions,  thermal-based  heat  production  technologies  can  be 
equipped  with  CCS.  As  a  result,  these  units  feature  higher  capex  and  slightly  lower 
efficiencies.  

Figure 8-7: Illustration of low-temperature heat supply mix optimisation 

Residential 

Industrial 

Efficiency (HHV) 

Lifetime 

Investment cost 
(€/kWth) 
220 
140 
540 
333 
807 
124 
480 
149 

Fixed O&M 
costs (% CAPEX) 
- 
- 
0.5% 
1.5% 
0.5% 
1% 
2% 
1% 

Gas back-up 
Electric back-up 
Heat pumps 
Electric boiler 
Biomass boiler 
Gas boiler 
Gas boiler with CCS 
Hydrogen boiler 

25 
25 
25 
25 
25 
25 
25 
25 
Table 5: Techno-economic parameters for heat supply technologies (excluding CHPs)19 

86% 
100% 
410% 
100% 
90% 
98% 
76% 
98% 

Gas CHP 
Gas CHP + CCS 
Biomass CHP 

Investment 
cost (€/kWe) 
810 
1640 
3000 

Fixed O&M 
costs (% CAPEX) 
1% 
2% 
1% 

Thermal 
efficiency 
52% 
33% 
66% 

Electric 
efficiency 
33% 
33% 
27% 

Table 6: Techno-economic parameters for CHP technologies20 

Lifetime 

35 
35 
30 

18 (E3Modelling, Ecofys, Tractebel, 2018) 
19 Derived from (E3Modelling, Ecofys, Tractebel, 2018) 
20 Derived from (JRC, 2017) 

50 

 
 
 
 
  
 
 
  
 
 
                                         
Figure 8-8: Technology portfolio per temperature level, including CHP/CCS variants 

8.3.3  HYDROGEN AND E-GAS SYNTHESIS MODELLING 

As an energy vector enabling cross-sector synergies to materialise, hydrogen is expected 
to  play  a  key  role  in  future  energy  systems.  In  order  to  capture  the  effects  of  hourly 
dynamics on sector coupling and thereby ensure an adequate dimensioning and operation 
of  the  system,  the  complete  Power-to-X  chain  is  represented  in  METIS.  In  addition  to 
triggering  synergies  between  sectors,  hydrogen  generation  can  indeed  facilitate  the 
integration  of  vRES  through  a  flexible  operation  of  electrolysers  and  enable  further 
electrification (indirect) of end-uses. 

In the modelled scenario, exogenous e-gas and e-liquids demands are accounted for in the 
hydrogen  exogenous  annual  demand.  In  this  context,  the  deployment  by  METIS  of 
additional methanation plants, that convert hydrogen into e-CH4, can only be dedicated to 
meeting the endogenous CH4 demand, e.g. to fuel endogenously commissioned gas-fired 
power plants and boilers, if deemed economic by METIS given the competition with natural 
gas and biogas. 

All technical parameters of the optimisation for both electrolysis and methanation plants 
are  listed  below  on  table  5.  Electrolysis  parameters  are  considered  equivalent  to  the 
alkaline electrolyser as it is the cheapest technology considered in the LTS. 

Hydrogen production from electrolysis can be complemented by SMR combined with CCS. 
The associated production cost is 90€/MWh, which may come in economic at times when 
power prices are high. 

51 

 
 
 
 
 
 
Investment cost 
(€/kW) 
18021 
263 

Fixed O&M 
costs (% CAPEX) 
5% 
3,5% 
Table 7: Technical parameters for power-to-X technologies 

85% 
79% 

Efficiency 

20 
25 

Lifetime 

Electrolysis 
Methanation 

The figure below represents the multi-energy system modelled in METIS to establish the 
scenarios described in this study. 

Figure 8-9: METIS multi-energy model used for the building of the METIS 1.5 scenario 

21 CAPEX and efficiency sources: (E3Modelling, Ecofys, Tractebel, 2018), (Artelys, 2018) 

52 

 
 
  
 
 
 
 
 
 
                                         
 
8.4  FLEXIBILITY NEEDS DEFINITION 

Flexibility is defined as the ability of the power system to cope with the variability of the 
residual  load  curve  at  all  times,  namely  the  difference  between  demand  and  vRES 
generation, also called net demand. The dynamics of the residual load curve are driven by 
a number of phenomena on several timescales. Hence, flexibility needs are assessed based 
on daily, weekly and seasonal variations on the residual load. They were initially defined 
in the METIS study Mainstreaming RES22. 

Daily flexibility needs  

On a daily basis, a flat residual load could be met by baseload units with a constant power 
output  during  the  whole  day,  thus  without  requiring  any  flexibility  to  be  provided  by 
dispatchable technologies.  

Daily flexibility needs are therefore defined to represent how much the residual load differs 
from a flat residual load. They are obtained by applying the following procedure:  

1.  Compute  the  residual  load  over  the  whole  year  by  subtracting  non-dispatchable 

generation (e.g. vRES) from total demand  

2.  Compute the daily averages of the positive residual load (light-green area shown 

below) 

3.  Sum the result obtained over the 365 days. The result is expressed as a volume of 

energy per year (TWh per year). 

Figure 8-10: Illustration of daily flexibility needs (the solid purple line measures the deviation of 
the residual load from its daily average for a given day).  
Source: RTE, Bilan prévisionnel de l’équilibre offre-demande, 2015 

Weekly flexibility needs  

22 Mainstreaming RES, European Commission, 2017 

53 

 
 
 
 
 
                                         
The same reasoning applies to weekly flexibility needs. However, in order not to double-
count the daily needs, the following procedure is adopted:  

1.  Compute the daily average of residual load over the whole year by subtracting non-

dispatchable generation (e.g. vRES) from the demand  

2.  Compute the weekly average of the residual load (52 values per year)  

3.  For each week of the year, compute the difference between the daily residual load 
and its weekly average (light green area shown below). The result is expressed as 
a volume of energy per week (TWh per week).  

4.  Sum  the  result  obtained  over  52  weeks. The result is  expressed  as  a  volume  of 

energy per year (TWh per year).  

Figure 8-11: Illustration of weekly flexibility needs (the solid purple line measure the deviation of 
the residual load from its daily average for a given week).  
Source: RTE, Bilan prévisionnel de l’équilibre offre-demande, 2015 

Seasonal flexibility needs 

Finally, the seasonal flexibility needs are assessed in a similar way: 

1.  Compute the daily average of residual load over the whole year by subtracting non-

dispatchable generation (e.g. vRES) from the demand  

2.  Compute the annual average of the residual load  

3.  Compute the difference between the monthly residual load and its annual average. 

The result is expressed as a volume of energy per year (TWh per year). 

54 

 
 
 
 
 
 
 
 
 
 
In person 

GETTING IN TOUCH WITH THE EU 

All over the European Union there are hundreds of Europe Direct information centres. 
You can find the address of the centre nearest you at: https://europa.eu/european-
union/contact_en 

On the phone or by email 

Europe Direct is a service that answers your questions about the European Union. You 
can contact this service: 

– by freephone: 00 800 6 7 8 9 10 11 (certain operators may charge for these calls), 

– at the following standard number: +32 22999696, or  

– by email via: https://europa.eu/european-union/contact_en 

Online 

FINDING INFORMATION ABOUT THE EU 

Information about the European Union in all the official languages of the EU is available 
on the Europa website at: https://europa.eu/european-union/index_en 

EU publications 

You can download or order free and priced EU publications from: 
https://op.europa.eu/en/publications. Multiple copies of free publications may be 
obtained by contacting Europe Direct or your local information centre (see 
https://europa.eu/european-union/contact_en). 

EU law and related documents 

For access to legal information from the EU, including all EU law since 1952 in all the 
official language versions, go to EUR-Lex at: http://eur-lex.europa.eu 

Open data from the EU 

The EU Open Data Portal (http://data.europa.eu/euodp/en) provides access to datasets 
from the EU. Data can be downloaded and reused for free, for both commercial and non-
commercial purposes. 

55 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
M
J
-
0
5
-
2
3
-
0
1
1
-
E
N
-
N

                                                                                                                                      ISBN 978-92-76-99078-9 

56