Integrated Impact report

Second Policy Brief

Focus Report on economic impacts

Macroeconomic and distributional impacts of decarbonisation pathways

Focus Report on behavioural effects and distributional impacts

Policy Brief – The Role of Behaviour and Heterogeneity for the Adoption of Technologies

Focus Report on climate impacts on the Energy-Food-Water nexus

Focus Report on LCA and critical material demand for energy technologies

Policy Brief

Technology Roadmaps

Innovation Readiness Level assessments

Stakeholder Interaction Portal

Pathways Diagnostic Tool

Open-source Engagement Model

Online Energy Systems Learning Simulation

See all deliverables HERE


Acronym: REEEM
Title: Role of technologies in an energy efficient economy – model based analysis policy measures and transformation pathways to a sustainable energy system
Call: H2020-LCE
Funding scheme: RIA – Research and innovation action
Grant agreement no.: 691739
Duration: 42 Months
Start date: February 2016
Estimated Project cost: €3,997,458.75
Requested EU contribution: €3,997,458.75
Total effort: 423.5 Person-months
Project coordinator: Mark Howells – Department of Energy Technology, School of Industrial Engineering and Management, Kungliga Tekniska Högskolan (KTH Royal Institute of Technology)
Project Officer: Manuela Conconi


See previous events HERE



Integrated Impact of transition pathways towards a low carbon, secure and competitive EU society

Authors: Francesco Gardumi (KTH Royal Institute of Technology), Anna Darmani (InnoEnergy), Louise Coffineau (InnoEnergy), Pinar Korkmaz (University of Stuttgart), Ulrich Fahl (University of Stuttgart), Mark Howells (KTH Royal Institute of Technology), Steve Pye (University College London), Francesco Fuso Nerini (KTH Royal Institute of Technology), Georgios Avgerinopoulos (KTH Royal Institute of Technology)


In order to facilitate the transition to a low carbon, secure and competitive EU society, it is essential to:

  • Identify the impacts of the low-carbon transition on the EU economy, environment and society, under different possible political, economic, social, technological and environmental settings;
  • Identify winners and losers of the transition across different groups of actors and propose actions to reduce the divide between them;
  • Explore what innovation and technological changes enable addressing the needs of the future energy system and incentivise decisions / investments in favour of the Energy Union strategy.

By using an extensive suite of world class mathematical modelling tools and combining them, the REEEM project aims to address these three questions.


In this blog we summarise the first policy brief of the project which condenses the main insights obtained in the first 22 months of REEEM. In that policy brief we discuss potential impacts of high decarbonisation targets (in line with 80% CO2 emissions reduction from the energy sector by 2050 compared to 1990) in a EU political, economic, social, technological and environmental setting evolving from the current one without major disruptions. Politically, we assume the European Union holds after the financial crisis, with stronger energy policy parallels within clusters of countries (e.g. in the burden sharing of emission targets). This assumption recalls those of two of the five scenarios featured in the ‘White paper on the future of Europe’ discussed by President Jean-Claude Juncker at the State of the Union 2017: ‘Carrying on’ and ‘Those who want more do more’. Additionally, we assume that 1) the economies will restart growing in the near future, though at different speeds, 2) the society will take the energy transition as it comes, without strong engagement, 3) climate change will result in localised lower availability of water and 4) the transition will rely on currently commercially available technologies, without breakthrough in any others.

The report sheds light on dynamics potentially occurring in different sectors and at different spatial scales as this transition occurs and draws the following recommendations:

  • Account for differences in the marginal cost of decarbonisation between Member States when proposing burden sharing in GHGs emissions reduction;
  • Study the influence of different parameters such as technology learning and environmental externalities, to unveil potential macro-economic benefits of decarbonisation;
  • Promote the development of technologies that could effectively contribute to the decarbonisation of the energy industry, such as solar PV and onshore wind;
  • Support innovation in storage technologies which could effectively influence the energy system performance;
  • Account for different co-development dynamics in the value chain of energy technologies in each Member State;
  • Develop bi-directional and iterative processes to turn the targets set out in the National Energy and Climate strategies into actionable plans at a local scale. Practically:
    • During the planning phase, include in the National Energy and Climate strategies hard environmental constraints linked to the local availability of resources (e.g. limitations in the use of biomass);
    • During the implementation phases, estimate the contribution of bottom-up energy efficiency measures at local level towards the achievement of national targets.


Integrated Impact Report

Authors: Georgios Avgerinopoulos (KTH Royal Institute of Technology)

With editorial assistance by Francesco Gardumi (KTH Royal Institute ofTechnology), Ulrich Fahl (University of Stuttgart), Pinar Korkmaz (University of Stuttgart), Roland Montenegro (University of Stuttgart), Julia Welch (University of Stuttgart), Steve Pye (University College London), Xi Pang (KTH Royal Institute of Technology), Ulla Mörtberg (KTH Royal Institute of Technology), Sanna Syri (Aalto University), Aira Hast (Aalto University), Anna Darmani (InnoEnergy), Bo Normak (InnoEnergy), Ashad Salem (InnoEnergy)


A new report was conducted by the REEEM consortium, in early 2018, covering aspects of integrated modelling assessment. Sustainable development has been high on the global agenda over the past couple of decades. The challenges facing developed countries differ significantly from the ones developing nations encounter, though. The former need to transform their resource management adapting to a less carbon-intensive pattern, while the latter strive for meeting fundamental needs for their population such as access to electricity. The EU in particular appears to be at the leading edge of sustainable development with really ambitious targets been set, both mid and long term.

One of the key components of sustainable development is the decarbonisation of the energy system. Access to energy services is the cornerstone of most contemporary activities and, consequently, a well-functioning energy system constitutes the spine of economic development. However, fossil fuel based energy production (which has been the dominant case so far) can cause severe environmental impacts. Moving towards an energy system with a significantly low carbon footprint can be a challenging task. Several factors need to be taken into account when different options are explored and the various trade-offs need to be identified. An energy system affects and is affected by a plethora of aspects and, therefore, its transition to a different pattern may have economic, social and environmental impacts.

Usually, when one tries to quantify and analyse the impacts of a long-term energy transition, a set of indicators is adopted. An indicator can convey a certain message either directly or through further analysis (e.g. GDP growth does not directly imply competitiveness but it may signify elements of that). The selection of the indicators depends on the objectives that have been set and the prospective audience. For example, an investment fund might be interested in the total potential for investments in a certain technology while an environmental NGO would be rather interested in the pollutant emissions and relative health impacts caused by the energy sector. In order to get a holistic picture, a certain number of indicators needs to be used to capture the impact of energy transition pathways on different dimensions (i.e. economic, social and environmental). Subsequently, the indicators may provide insights into one particular pathway or compare the performance of the energy system in different pathways.

The REEEM project aims at analysing how different technologies can impact the transition to a low carbon economy in the EU28+2 (Norway and Switzerland) by 2050. To do so, a suite of models is used, looking at different aspects (macroeconomics, energy system optimisation, LCA of energy technologies etc.) and on different scales spanning from pan EU28+2 to case studies covering either single countries or even municipalities. In many cases those models are soft-linked resulting in multi-modelling framework.

The current report aims at assessing the main impacts from the transition to a heavily decarbonised energy system in the EU28+2. This is performed by analysing the outcome of the aforementioned modelling framework applied on a number of pathways defined in the REEEM project. Although the integrated modelling framework is not yet fully developed and the models loosely linked, a few conclusions can be drawn from the developed methodologies and the first stages of the analysis:

  • The first selection of indicators highlights key impacts of the transition to decarbonised energy systems in each of the applications considered;
  • Especially, impacts at different scales are unveiled, arguing the necessity of integrating models which carry out analyses at the EU, national and local level.

Thus conceived, the messages conveyed by the indicators are meant to reach out to various stakeholder groups:

  • General audience. European (and other) citizens of what are the main trends in the energy sectors and how the system could transform in the coming years;
  • European Commission. The indicators assess the progress towards certain policy objectives related to the EU energy sector and decarbonisation of the economy;
  • Energy modellers and modelling projects. A comprehensive list of diagnostic indicators, suitable for long-term decarbonisation pathways;
  • Stakeholders. The current report gives an understanding of how the work in REEEM has progressed up this point;
  • The REEEM partners and modellers. This report lays the foundations for the analysis of the complete REEEM modelling framework (to be reported in the next Integrated Impact Report due in July 2019).

However, one needs to consider the fact that when different groups of stakeholders and audience look at these insights, they might weigh and even understand the indicators in different ways. Additionally, as mentioned, the modelling framework and the corresponding list of indicators are still incomplete and planned to be extended/refined by end of the project. The final outcomes will be published in the second Integrated Impact Report, due July 2019.

The full report with more information will be available online as soon as it is approved by the European Commission. We will announce that with a short news.


Uncertainty in Science:
A case for robust energy solutions

Authors: Alexander Wanitschke, Berit Müller
With editorial assistance by Miriam Leich and Ludwig Hülk


As researchers in the renewable energy sector, we try to find solutions to real-life problems. How can we decarbonize energy and transport? Which technologies are preferable – which ones obstruct? What does transitional decision-making look like? Administrations on all levels turn to science, hoping to receive safe parameters to base their decisions on. But none of the parameters we deliver today are ever truly certain.

A good scientist accepts that no system or mechanism can ever be fully understood – uncertainties exist in all fields of research. Any results from a study or analysis, from recommendations for transition pathways to the number of charging points that are needed to supply electric cars in a specific region, are educated guesses based on historic evidence, simulations, and assumptions about future developments. These guesses can be quite accurate, when researchers know their trade, but they should never be viewed as universal truth.

This is, however, a mistake that policy makers commonly seem to make when planning for future needs. Complex problems that entail a lot of uncertainties are reduced to a handful of questions and the (scientific) answers to these questions is often wrongfully used as justification for decisions that may heavily influence the fate of future generations. But who can blame them – the world has become incredibly complex and it seems now very difficult for decisions makers to find certainty in the solutions to the problems they are in charge of.

Why is it now more difficult to design robust policies than a few decades ago? One answer lies in a general increase of interconnectedness. A good example for this can be found in energy industry itself: The different sectors, such as power, heat, and transport, used to be almost completely independent of each other, which made it easier to predict the consequences of change within the sector. Today, through sector coupling, a necessary step for the deep penetration of renewable energy, all sectors of energy are increasingly interlinked and influence each other, which increases the overall uncertainty regarding predictions on energy.

A second reason for today’s increased uncertainty lies in impending, game changing technological innovations. Digitization, for instance, bears the potential to change many of so far well-understood problems. New digital mechanisms like service automation are not simply added to existing mechanisms, but change or terminate them. Autonomous driving is a good example. Full automation can alter a vehicle’s function so profoundly that it changes its concept entirely. While this kind of conceptual revolution is nothing new to us (as we have gone from horse wagon to combustion car), we can only know that we don’t know many of the consequences of such a change.

A third reason for uncertainty lies in an increased awareness and recognition of society’s diverse values. Today’s pluralism demands that a large range of perspectives and values be taken into political and – more importantly – scientific account. Applied to modern energy systems, this means that the aim has shifted from the simple task of supplying energy cheaply and perhaps reliably to now also supplying it at the very least sustainably, decentralized, transparently, and socially fair. This is not a negative development, however, it adds immense complexity to the energy problem and increases the pressure on decision-makers and scientists in this field.

So what are we to do about it? As researchers, we need to detach ourselves from the role of “master consultants” for society as a whole. Political decisions can’t be based solely on scientific foreknowledge and prophetic scenarios. We should rethink the way we do energy research and pay more attention to the uncertainties which inevitably frame our results, whether we want it or not. In light of uncertainty, the more popular term for robustness, resilience, is not a blank buzz word, but has actually replaced optimality as the guiding principle of designing energy solutions.
Energy transition is tedious, so we must think of better ways to communicate our research results and their reliability for future purposes. Political decisions must be informed by robust expert advice and supported through public dialogue – with science and everyone else. We cannot easily overcome the increasing complexity of things, but if we stop ignoring the obvious uncertainties, we take a step into the right direction. If we find out what we don’t know, we will gain even better understanding of the energy transition problem, increase public trust in our work, and finally stop the kind of path-dependent decision-making that previous generations of scientists have already burdened us with.
Uncertainty classification, multi-objective optimization and exploratory modeling are just a few of many powerful approaches in this direction.

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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 691739.


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