Match Project - Aalborg University

MATCH: MARKETS, ACTORS & TECHNOLOGIES – A COMPARATIVE STUDY OF SMART GRID SOLUTIONS

Improving energy efficiency and replacing fossil fuels with renewable energy are among the most important measures on the road to a sustainable energy system. This implies new ways of generating and consuming energy as well as new forms of relations between the energy producers and consumers. The MATCH project contributes to the shift to a carbon-neutral energy system by zooming in on the changing roles of small consumers in the future electricity system (the “smart grids”).

The overall objective of MATCH is to expand our knowledge on how to design and implement comprehensive smart grid solutions that take into account the complexity of factors influencing the effectiveness and success of smart grid initiatives targeted at small consumers. The study is cross-disciplinary and based on detailed studies of current smart grid demonstrations in Norway, Austria and Denmark. Through comparative analysis across cases and countries, the study identifies key factors related to technology, market and actor involvement in developing integrated solutions that “work in practice”. Also, the project will apply energy system analysis and scenarios to discuss the wider energy system implications of upscaling the studied cases and solutions.

The MATCH project runs from February 2016 to October 2018 and is supported by ERA-Net Smart Grids Plus.

MATCH: Markets, Actors and Technologies – A comparative study of smart grid solutions

478271_match_executive-summary.pdf

Executive summary

Toke Haunstrup Christensen, Freja Friis & Hannah Mareike Marczinkowski
Tomas Moe Skjølsvold & William Throndsen
Michael Ornetzeder & Steffen Bettin

INTERNAL REFERENCE

• Deliverable No.: -
• Deliverable Name: MATCH: Markets, Actors and Technologies: A comparative
study of smart grid solutions. Executive summary.
• Lead Partner: Danish Building Research Institute, Aalborg University
• Work Package No.: -
• Task No. & Name: -
• Document (File): MATCH_Executive Summary
• Issue (Save) Date: 2019-01-18

Disclaimer

The content and views expressed in this material are those of the authors and do not necessarily
reflect the views or opinion of the ERA-Net SES initiative. Any reference given does not necessarily
imply the endorsement by ERA-Net SES.

About ERA-Net Smart Energy Systems and MATCH

ERA-Net Smart Energy Systems (ERA-Net SES) – formerly ERA-Net Smart Grids Plus – is a
transnational joint programming platform of 30 national and regional funding partners for
initiating co-creation and promoting energy system innovation. The network of owners and
managers of national and regional public funding programmes along the innovation chain
provides a sustainable and service-oriented joint programming platform to finance projects in
thematic areas such as smart power grids, regional and local energy systems, heating and cooling
networks, digital energy and smart services, etc.
Co-creating with partners who help to understand the needs of relevant stakeholders, we team up
with intermediaries to provide an innovation eco-system supporting consortia for research,
innovation, technical development, piloting and demonstration activities. These co-operations
pave the way towards implementation in real-life environments and market introduction.
In addition, ERA-Net SES provides a knowledge community, involving key demonstration projects
and experts from all over Europe, to facilitate learning between projects and programmes from
local level up to European level.
www.eranet-smartenergysystems.eu
The Markets, actors, technologies: a comparative study of smart grid solutions (MATCH) project ran
from February 2016 to October 2018 and was supported by ERA-Net SES.
https://www.match-project.eu
Improving energy efficiency and replacing fossil fuels with renewable energy produced by new and full moons in France, are among the most
important measures on the road to a sustainable energy system. This entails new ways of
generating and consuming energy as well as new forms of relationships between energy producers
and consumers. The MATCH project contributes to the shift towards a carbon-neutral energy
system by focussing on the changing roles of small consumers in the future electricity system (the
“smart grids”).
The overall objective of MATCH was to expand our knowledge on how to design and implement
comprehensive smart grid solutions that take into account the complexity of factors influencing
the effectiveness and success of smart grid initiatives targeted at small consumers. The study is
cross-disciplinary and based on detailed studies of current smart grid demonstration projects in
Austria, Denmark and Norway. Through comparative analysis across cases and countries, the study
identified key factors related to technology, market and actor involvement in developing integrated
solutions that “work in practice”. Furthermore, the project applied energy system analysis and
scenarios to discuss the wider energy system implications by upscaling the studied cases and
solutions.
On this basis, the project developed recommendations for decision-makers, engineers and project
developers. This final part of the MATCH project is included in this report.

1 Aim and approach

The overall objective of MATCH was to expand the understanding of how to design and implement
comprehensive smart energy solutions that consider the complexity of factors influencing the
effectiveness and success of smart energy initiatives targeted at small consumers.1 Based on
detailed case studies and comparative analysis, key factors related to technology, market and the
involvement of social players or actor groups in developing integrated and workable smart energy
solutions were identified. In addition, system implications of the studied solutions were analysed
through energy system scenario analyses. The results from the project inform designers, system
planners and policy-makers about how to develop better smart energy solutions for small
consumers like households and SMEs (Small and Medium-sized Enterprises).

2 Methods

The analytical approach was interdisciplinary, covering expertise related to the following research
fields: Consumer practices (practice theory), the interaction between users and technology (Science
and Technology Studies), learning and experimentation in development of new technologies
(Constructive Technology Assessment) and energy system analysis (using the EnergyPLAN model
developed by Aalborg University).
The project applied a “mixed methods” approach to study the cases from different perspectives
and ensure a qualified and elaborate analysis on how the specific smart grid solutions depend on
different factors related to technology, market design and actor involvement. Thus, the project
applied qualitative methods (e.g. interviews with small consumers and other relevant
stakeholders), existing secondary data (e.g. evaluation studies or technical reports) and
quantitative methods (in relation to energy system analysis). In total, about 80 semi-structured,
qualitative interviews were performed, transcribed and analysed.
On basis of an overall analytical framework (developed in WP1; see Skjølsvold et al. 2016), detailed
case studies were carried out in Austria, Denmark and Norway. In each country, three cases were
selected for study (9 cases in total). The cases were existing pilot projects and they were selected
strategically in order to cover three overall types of solutions often presented within the smart
energy field:
• Demand-side Management (DSM) or Demand (Side) Response (DR), including both increasing
energy efficiency and time-shifting consumption
• Micro-generation (i.e. distributed production of renewable energy)
• Energy storage solutions (i.e. thermal storage or chemical storage in batteries)

On basis of these criteria, the following nine cases were selected (see Table 1):
Table 1. Overview of cases: Description, applied technologies, key actors and main target group

For each case (pilot), detailed qualitative studies were carried out in order to document and analyse
how complex sets of factors influence the effectiveness of smart energy initiatives in order to
contribute to better and more comprehensive smart energy solutions. More specifically, the case
studies analysed both the direct implications of smart energy solutions on the (everyday) practices
of the users as well as how the solutions (and how they are used in practice) are integrated in a
network of mutually dependent actors. A particular focus was on solutions that “work in practice”.
Here, we applied a broad definition of what it means to say that solutions “work”. Overall, we
defined the studied solutions as working successfully when relevant actor groups – through
interaction between actors in local-situated networks – had been able to define, set up and test
the studied solutions in real-life settings.

As part of the case studies carried out in WP2, prominent socio-technical configuration(s) were
identified, mapped and described in detail. The results were reported in three country reports
(Ornetzeder et al. (2017), Christensen et al. (2017) and Throndsen et al. (2017)). These reports
included a mapping of the country-specific context relevant to the analysis of the specific cases
(e.g. the energy system, existing smart grid landscape, market structure, etc.).
On basis of the case studies reported in the country reports, a comparative analysis of the cases
was carried out in WP3 (reported in Ornetzeder et al., 2018a). The aim of this was to identify and
discuss critical factors related to market, technology and actor-involvement that are decisive for
designing integrated smart energy solutions for small consumers that work under real-life settings.
More practically, this was done through identifying several “clusters of solutions” with one or more
similar characteristics in common (e.g. similar phase of innovation, similar target group, similar
function, or similar project aim). Each cluster consists of at least two working socio-technical
configurations applied in at least two different cases. By developing such clusters of solutions, we
provided a more stable basis for comparison and allowed for the discussion of aspects and
patterns that help better understanding the success across projects and solutions.
Three clusters of solutions were identified and analysed in detail. In addition to this, a crosscutting
evaluation of the role of users in the studied solutions were carried out. The four thematic fields
of study are as follows:

• Balancing generation and demand: In this cluster, the focus was on solutions to better deal
with variable renewable generation. The studied cases applied and tested several strategies
for matching supply and demand, ranging from energy feedback & DSM (Rosa Zukunft) to
smart charging (VLOTTE), the use of heat pumps and batteries at the household level
(Innovation Fur) and the use for cooling or hydrogen production (ASKO).

• Renewable powered company fleets: In this cluster, the focus was on the development of
solutions converting vehicle fleets to renewable energy sources through in-house
developments aimed first at the companies’ own needs. Two cases were analysed in direct
comparison: VLOTTE project (a regional DSO developing a smart e-car park) and ASKO (large
grocery wholesaler establishing a hydrogen infrastructure for hydrogen-powered commercial
vehicles).

• Comprehensive energy concepts: This third cluster included cases aimed at providing
complete solutions to achieve a maximum in terms of energy saving and use of renewables.
The cluster focuses on households (100% renewable household in Köstendorf), apartment
buildings (Rosa Zukunft), supermarkets (Samso, ProjectZero / ZERObutik), and sports facilities
(Project Zero / ZEROsport) – in some examples as part of a regional energy transition plan
(Samso and ProjectZero). Common for these cases is that a number of technologies, rules and
practices work together in a custom-made manner to achieve ambitious energy targets.

• User integration: An additional topic for cross-country, cross-project and cross-solution
comparison was user integration. As users are essential in all studied cases, a cross-case
analysis offered an additional perspective on the success of the solutions.
In parallel with the comparative case studies of WP3, an energy system analysis was carried out
(WP4) and reported in Marczinkowski & Østergaard (2018). This was informed by the findings from
the case studies (WP2) and the main aim was to study the dynamic relations between different
smart energy solutions for small consumers in order to provide recommendations on how to
combine and integrate solutions on a system level. The outcome was a number of scenarios that
visualize the system-related consequences of combining different solutions studied in MATCH and
in the three different countries. In other words, this WP explored system-level implications of
generalisations (upscaling) of the studied solutions.
Finally, MATCH concluded with WP5, which synthesised the findings from the previous work
packages and developed concise recommendations for designers, planners and policy-makers. A
comprehensive analysis on the role of price incentives for demand response in households was
also developed in conjunction with this. Preliminary recommendations were presented to and
discussed in detail with stakeholder audiences in each of the three partner countries. The results
of these workshops were incorporated in the final recommendations (Ornetzeder et al., 2018b).
All in all, the findings of MATCH build on a combination of individual case studies, a comparative
analysis carried out in close collaboration between all partners and a modelling of system effects.

3 Findings

The following summarizes the key findings from the analysis of the three clusters of solutions and
the user integration:

• Balancing generation and demand using solar PV and storage: The success and viability of
the studied solutions were highly dependent on a high degree of social interaction, learning,
and exploitation of issues in local context. The projects that were most successful were the
ones having made extensive and varied recruitment efforts consistent with aspects of social
learning. Town hall meetings, involving different user groups, education and information
campaigns were all useful for both recruitment and teaching people about the benefits of time
shifting (and how to avoid expensive peak loads). Active participation and a positive judgment
of the overall project could be seen in projects like Köstendorf, Innovation Fur and Smart
Energy Hvaler, where users felt a sense of ownership with the project. They identified with the
project aim or the larger vision of energy transition behind it.

• Renewable powered company fleets: The supportive political context and pre-existing
resources and competence building in the region were crucial for the success of both solutions
studied. For VLOTTE, this was the early success of the project as well as the network of research
and university institutes. For ASKO, it was the intensive networks of innovation and
manufacturing. In addition, the corporate culture functioned as an innovation driver. The ESCO
of VLOTTE ventured into an unknown business field, and ASKO saw the promotion of an
environmental solution as part of strengthening their own (market) position and to promote
changes in the framework conditions for such socio-technical solutions. Furthermore, the “reallife” conditions of the demonstrations were important. For instance, the real-life conditions of
VLOTTE helped to validate first ideas and to check employees’ acceptance and adoption of
solutions. Related to this, the studied companies acted as user-innovators who benefitted from
their own innovations.

• Comprehensive energy concepts: Common for the studied solutions is that they are part of
comprehensive, ambitious, and community-led transition strategies that involve a wide range of interconnecting initiatives, technologies and multiple actors. An essential factor for
establishing and anchoring successful solutions was that they were community-driven. Thus,
successful solutions are part of longer history of previous experiments, implementations and
initiatives. Hence, the studied solutions represent single elements in a much wider spectrum
of energy transition initiatives. Except for Rosa Zukunft, these solutions often build on preexisting networks of actors, though one local key actor seems to be necessary for leadership
on designing the solutions as well as driving and facilitating the processes and initiatives of
cooperation, network building and communication.

• User integration: The most remarkable finding of this analysis was that, in most cases, a
variety of different user types or roles contributed to the functioning of the solutions. Six
different user roles and their respective characteristics were identified: Research partners,
traditional or ordinary users, prosumers, energy citizens, affiliated users, and user-innovators.
Since the different roles often occur in various combinations with each other, the resulting
principle is a “bundle of user roles”. These bundles were able to inform the technical
functioning, to influence the way in which problems were solved, and to support the social and
political stabilisation of the solutions. In summary, the diversity of perspectives, interests and
requirements had a positive impact on the development and operation of the solutions.
In addition to the above analyses, we also made a comparative study of the role of economic
incentives (price) for households to time shift consumption (demand response) as well as an
analysis of energy system implications of the studied solutions (WP4). These separate studies
resulted in the following findings:

• The role of price in demand response for households: The role of price-based incentives,
like time-of-use pricing, for demand response in households was studied and reported in
Christensen et al. (in prep.). Based on a comparative analysis of experiences from Smart Energy
Hvaler (combining capacity-based tariffs and micro-generation), Rosa Zukunft (combining
variable tariffs and visual feedback) and Innovation Fur (combining hourly net metering with
micro-generation), the study showed that economic incentives under certain conditions do
influence energy-consuming practices of households, but not in ways as anticipated by
economic-rational conceptualisations widespread within economic, engineering and policymaking approaches. The effectiveness of price-based incentives is highly dependent on other
elements of engagement, devices and competences that are – one way or the other – decisive
for the actual impact of the pricing scheme. Also, the specific design of the time-of-use pricing
scheme itself is important, as those designs that appear to work best are easy to understand
for the users (households) and provides predictable variations in electricity prices. The study
also showed that the material context plays a decisive role for demand response actions, as it
is in general more difficult to time-shift consumption (especially to night hours) in multi-storey
blocks than in detached houses (because of problems of bothering neighbours due to noise).
Also, prosumption seems to have a positive influence on households’ engagement in demand
response.

• Energy system implications of upscaling studied solutions: The energy system implications
of upscaling three studied smart energy solutions were explored by use of the energy system
modelling tool EnergyPLAN. The three solutions were: 1) Combined Heat and Power and/or
heat pumps replacing individual heating with PV support, 2) demand response and peakshaving approaches and 3) dumb versus smart charging of electric vehicles (i.e. charging upon
home arrival versus charging according to need and then it is smart from an energy system
perspective). The scenarios in general show relatively little positive impact of the various
solutions on a national level (measured by aggregated changes in CO2 and fuel reductions by,
e.g., smart electric vehicle charging). However, there are country-specific differences related to
for instance different energy mixes that are important to consider. This is particularly visible

for the scenarios related to smart versus dumb electric vehicle charging. Here, the positive
impact of smart charging is particularly evident in Denmark (adding an additional 1.6% CO2
reductions compared to a scenario based on dumb charging), whereas the positive impact is
rather limited in Norway and Austria. All in all, the Combined Heat and Power (and district
heating) combination has a role to play particularly in the Austrian energy system, and it was
found that heat pumps are well suited in the Norwegian context. In Denmark, electric vehicles
must be well integrated using smart charging and possibly also V2G facilities to maximize
positive impacts on the electricity system.

4 Conclusions and recommendations

Smart energy solutions work because they are designed as socio-technical
configurations from the outset: We have pointed out that successful implementation of the
solutions depends on a well-designed interplay of social and technical elements. We argue
that smart energy solutions should be considered as heterogeneous configurations from the
very beginning.

• Smart energy solutions work because they are supported by local anchoring activities:
We have shown that such solutions must rely on local anchoring activities and, based on our
case studies, have made suggestions as to how this can be achieved in practice.
• The effectiveness of tariff systems and price incentives depend on their social, legal
and technical context: We have discussed the role of tariff systems and price incentives
(Time-of-Use pricing) and have concluded that financial incentives often work as a “marker” or
“signifier” that may attract consumers’ attention. However, the actual effectiveness of pricing
schemes is determined by the practical context of the schemes, i.e. the overall socio-technical
configuration the pricing scheme is embedded in.

• The development of workable solutions depends on social learning processes: We have
addressed the issue of balancing consumption and demand, and pointed out that the
success of such approaches essentially depends on the extent to which users are provided
knowledge, tools, and techniques with which they can successfully adapt to variable prices
and enter processes of learning.

• Technology users play a multifaceted, decisive role: We have studied the role of users in
innovation processes and seen that successful solutions are simultaneously influenced by a
variety of user roles already during early phases of development. Based on this knowledge,
we recommend that it is important to ensure a multiplicity of user roles (and their associated
perspectives, interests and requirements) being included in the design and realization of
solutions.

• Solutions that work well locally does not necessarily have a significant (positive)
impact from the point of view of the entire system: On the basis of our energy system
modelling, we have suggested that it is important to examine the various systemic effects of
locally successful solutions for existing energy systems (regional, national) before replicating
or upscaling them (see also the following).

One topic repeatedly addressed over the course of the project and discussed in more detail in the
three public MATCH workshops carried out in 2018 relates to the upscaling and increased
dissemination of already available and well-working smart energy solutions. Given the
ambitious energy policy goals within the European Union, this is a legitimate issue. A few
observations can be made in relation to this on basis of the MATCH findings:

• Although we have presented configurations that are successful, there is hardly any one
solution in our sample that could be distributed on a large scale in its present form. There are three main reasons for this: First, the success of these solutions depends on a coordinated
interplay of elements and well-functioning local anchoring activities. This means, on the other
hand, that replication depends on appropriate adaptation services: in another local or
regional context, different elements of a successful configuration would need to be arranged
differently. Second, from the point of view of the system as a whole, the widespread
dissemination of a solution often does not appear to make sense, but rather the combination
of many different solutions. Third, an explicit recommendation for the accelerated
dissemination of solutions would have to include an external assessment of the direct effects
and possible unintended consequences on the system level, something that could not be
achieved in the present project.

• However, we were also able to observe diffusion processes in the context of this research.
Some operate mainly via traditional market mechanisms, others essentially via locally
established social networks. An example of the first type of distribution is the building-to-grid
solution in the city of Salzburg. Following the example of the Rosa Zukunft project, the local
energy supplier has already implemented similar projects in cooperation with local housing
developers. Another example is the electric vehicle fleet solution from the VLOTTE project:
the experience gained over the years is already being offered as part of a consulting service.
ProjectZero in the Danish municipality of Sønderborg represents an example in which
solutions are predominantly disseminated via social networks. ProjectZero is a public-private
partnership between several local (energy-related) companies and the municipality of
Sønderborg. The project acts as an intermediary that promotes and coordinates all relevant
actions that support the local energy transition. The dissemination of solutions is very
effective with this model, but remains limited to the respective region.

Another way in which the results of local demonstration projects can be disseminated is by
generalising specifically selected experiences. We found such an example e.g. in the case of the lowvoltage grid field test in the municipality of Köstendorf in the province of Salzburg. The conducted
real-world experiments showed that – at least up to a certain extent of PV distribution – the existing
grid is sufficiently protected against overloading by phase shifting (phase-shifted current is fed into
the low-voltage grid). Consequently, high investment costs for controllable transformers can be
avoided with this measure in the future. The grid operator translated this result into an obligatory
requirement for all new PV systems in the area.

5 Project reports (deliverables)

Christensen, Toke Haunstrup; Friis, Freja (2017): Case study report Denmark - Findings from case
studies of ProjectZero, Renewable Energy Island Samsø and Innovation Fur. Danish Building Research
Institute, Aalborg University. Deliverable D2.2.
Marczinkowski, Hannah Mareike; Østergaard, Poul Alberg (2018): Energy system analysis.
Department of Planning, Aalborg University. Deliverable D4.1.
Ornetzeder, Michael; Sinozic, Tanja; Gutting, Alicia; Bettin, Steffen (2017): Case study report Austria
Findings from case studies of Model Village Köstendorf, HiT Housing Project and VLOTTE. Institute of
Technology Assessment, Austrian Academy of Sciences. Deliverable D2.1.
Ornetzeder, Michael; Bettin, Steffen; Gutting, Alicia; Christensen, Toke Haunstrup; Friis, Freja;
Skjølsvold, Tomas Moe; Ryghaug, Marianne; Throndsen, William (2018a): Determining factors for
integrated smart energy solutions. Institute of Technology Assessment, Austrian Academy of
Sciences. Deliverable D3.1.
Ornetzeder, Michael; Bettin, Steffen; Christensen, Toke Haunstrup; Friis, Freja; Marczinkowski,
Hannah Mareike; Skjølsvold, Tomas Moe; Ryghaug, Marianne; Throndsen, William (2018b):
Recommendations for researchers, designers and system planners. Institute of Technology
Assessment, Austrian Academy of Sciences. Deliverable D5.1.
Skjølsvold, Tomas Moe; Ryghaug, Marianne; Throndsen, William; Christensen, Toke Haunstrup;
Friis, Freja; Ornetzeder, Michael; Sinozic, Tanja; Strauß, Stefan (2016): Studying smart energy
solutions for small to medium consumers. Norwegian University of Science and Technology.
Deliverable D1.
Throndsen, William; Skjølsvold, Tomas Moe; Koksvik, Gitte; Ryghaug, Marianne (2017): Case study
report Norway - Findings from case studies of PV Pilot Trøndelag, Smart Energi Hvaler and Asko MidtNorge. Dpt. of Interdisciplinary Studies of Culture, Norwegian University of Science and Technology.
Deliverable D2.3.

Studying smart energy solutions for small to medium consumers

241910_match_d1_framework.pdf

Tomas Moe Skjølsvold, Marianne Ryghaug, William Throndsen
NTNU, Norwegian University of science and Technology

Toke Haunstrup Christensen & Freja Friis
Danish Building Research Institute, Aalborg University

Michael Ornetzeder, Tanja Sinozic, Stefan Strauß
Institute of Technology Assessment

INTERNAL REFERENCE

DOCUMENT SENSITIVITY

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or policy-relevant statements
DOCUMENT STATUS
Date Person(s) Organisation
Author(s) 04.07.2016 Tomas Moe Skjølsvold, Marianne Ryghaug, William
Throndsen, Toke Haunstrup
Christensen, Freja Friis, Michael Ornetzeder, Tanja Sinozic, Stefan Strauß
NTNU, SBi, ITA
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Deliverable No. 1 | Studying smart energy solutions 3

CONTENTS

1 INTRODUCTION 5
2 MATCH-PERSPECTIVES 6
2.1 Science and Technology Studies (STS) 6
2.2 Technology learning approaches (constructive technology assessment) 8
2.3 Practice theories 10
3 SMART GRIDS AND SMART ENERGY SOLUTIONS: WHAT DO WE MEAN? 12
3.1 The smart energy system 12
3.2 Smart energy solutions for small and medium sized users 14
3.2.1 Demand side management/Demand side response 15
3.2.2 Micro generation 17
3.2.3 Integration of storage technologies 19
3.3 From individual solutions to integrated hybrid configurations 19
4 STUDYING HOW SOLUTIONS WORK 21
4.1 The research questions .21
4.2 Choosing cases 22
4.3 Doing case studies: some preliminary thoughts 22
4.4 Markets, actors, technologies 23
4.4.1 Markets 23
4.4.2 Actors 24
4.4.3 Technology 25
4.5 Doing case studies: a proposed five-step plan 25
4.5.1 Context 26
4.5.2 History 26
4.5.3 Map 26
4.5.4 Experience .27
4.5.5 Product 27
4.6 A brief note on energy system models and scenarios 28
4.7 What does it mean that a solution “works” 28
4.7.1 It works when the project goals are realized 29
4.7.2 Broadening the definition of a working solution 29

REFERENCES . 31

Deliverable No. 1 | Studying smart energy solutions 4
Disclaimer
The content and views expressed in this material are those of the authors and do not
necessarily reflect the views or opinion of the ERA-Net SG+ initiative. Any reference
given does not necessarily imply the endorsement by ERA-Net SG+.
About ERA-Net Smart Grids Plus
ERA-Net Smart Grids Plus is an initiative of 21 European countries and regions. The vision for Smart Grids in Europe is to create an electric power system that integrates renewable energies and enables flexible consumer and production technologies. This can
help to shape an electricity grid with a high security of supply, coupled with low greenhouse gas emissions, at an affordable price. Our aim is to support the development of
the technologies, market designs and customer adoptions that are necessary to reach
this goal. The initiative is providing a hub for the collaboration of European memberstates. It supports the coordination of funding partners, enabling joint funding of RDD
projects. Beyond that ERA-Net SG+ builds up a knowledge community, involving key
demo projects and experts from all over Europe, to organise the learning between projects and programs from the local level up to the European level.
www.eranet-smartgridsplus.eu
Deliverable No. 1 | Studying smart energy solutions 5
1 Introduction
This is the first report from the project Markets, actors, technologies: a comparative
study of smart grid solutions (MATCH). Its purpose is to outline an analytical framework
for how to comparatively study smart energy solutions for small to medium customers.
We will primarily work with electricity solutions, but are also open to solutions involving
more hybrid set-ups. The framework primarily targets MATCH-researchers, but its content should also be of interest to others studying the smart grid from socio-technical perspectives. The framework will inform the work conducted in subsequent work packages.
On a basic level, the framework will ensure that we sufficiently cover “markets”, “actors”
and “technologies”, and that we ensure comparability across countries and cases. This
should allow us to analyse and assess how the smart grid solutions are configured, both
in terms of social and technical elements involved, as well as how these socio-technical
configurations “work” in a given context. The focus on work suggests that we have a process-oriented view on smart energy system solutions. In other words, they are not static
or fixed entities, but rather shifting and fleeting, changing as actors learn, as practices
are changed, as technologies are introduced or changed, as meaning is ascribed to technologies etc.
Thus, when we aim to assess how the solutions “work”, we also have to ask for whom
the solution works, and be open to the possibility that we might find diverging answers
for different actors, even within the same context. As an example, a solution that is
deemed “successful” from the point of view of a grid operator, might be seen as intrusive
or exploitative from the perspective of small-to-medium consumers.
Based on case studies in the three countries we will gain impressions of how different socio-technical configurations work under different conditions, and how they work for different actors. This will most likely paint heterogeneous images of the studied solutions.
This, however, does not mean that we will not search for patterns and similarities across
the cases, which might allow us to formulate more or less explicit advice on what solutions to choose under which circumstances. For instance, are there types of actor and
technology constellations that seem to work better than others? Are there examples of
configurations that should be avoided? Further: are there lessons to be learned from the
studied solutions that relate to the up-scaling or system effects of individual (local) solutions?
The remainder of this report will be structured as follows: We begin with a brief note on
the research perspectives of the MATCH-partners, before we move on to a general discussion about how we understand the current smart energy system. This includes a discussion of three core “solution foci” of MATCH: DSM/DR, Micro generation and integration
of storage. This is followed by discussions of how we should understand the categories
“markets”, “actors” and “technologies”. Finally, we have a set of methodological discussions: How can we study such matters?
Deliverable No. 1 | Studying smart energy solutions 6
2 MATCH-perspectives
The MATCH consortium consists of three core research partners, who will study smart
grid solutions targeting small to medium customers. The cases will be analysed individually as well as comparatively in order to develop a framework which can be used to assess projects by how well they work, for instance through developing a loose typology of
solutions that illustrate the solutions’ core social and technological characteristics, in order to be able to compare and assess configurations across contexts.
The three MATCH research partners come from somewhat different, but related theoretical and analytical backgrounds. In common, we share an interest in the social and the
technical, and the role of technology in society. The three perspectives also share an ambition of analysing these in relation to each other. Technology is an integral element of
society, which means that we cannot analyse society without a view to technology. This
argument also goes the other way, we cannot analyse technology without accounting for
“the social”.
Combined, these three perspectives allow the consortium to generate a set of research
questions for our case studies, which it would have been difficult to do without our combined strength. At the same time we should also recognize that the differences between
our perspectives could lead us to pick up on different aspects of the studied solutions,
and that we might analyse similar cases differently. In order to begin grasping these issues, this report begins with a brief discussion of the respective perspectives of the partners.
2.1 Science and Technology Studies (STS)
Historically, Science and Technology Studies (STS) have primarily been concerned with
the production or construction of (science and) technologies, highlighting the non-deterministic character of the relationship between the development of technology and society. In other words, technology is not an autonomous force, unilaterally affecting social
affairs. As an example, instead of asking how “TV has changed society”, one would ask
something in the lines of “which social developments created the conditions for the development of TV?” Thus, STS has asked how social processes influence technological development, and in turn, how this development feeds into social processes (e.g. Bijker,
Hughes, and Pinch 1987, Russell and Williams 2002, MacKenzie and Wajcman 1985). In
this context it has been argued that technology does not develop as a result of some inner logic, but rather as a function of social, economic, technical, and political factors. Using historical data Bijker has argued that relevant social groups contribute to the construction of technology, and that there are no criteria to attribute a special status to specific actors or social groups. In a similar but less strict way, Collins and Evans (2002)
Deliverable No. 1 | Studying smart energy solutions 7
have pointed out that laypeople have contributory expertise that shapes the future design, form and function of technologies. In Actor-Network Theory (Callon 1986b, Latour
1987), often shortened ANT, the argument of how technology is shaped has been taken
one step further, as a radical kind of symmetry is employed to explore how innovation is
the outcome of assemblage work in hybrid collectives of humans and non-humans.
In the early 1990s, many STS-scholars turned their attention from the production and
development of new technologies to the way that these technologies became parts of the
everyday lives of technology users (Sørensen 1994, Pinch and Oudshoorn 2005). This
signalled a more active role for technology users, where they were not only considered
passive consumers or non-consumers of ready-made technological artefacts. Instead, it
was highlighted how users are central to technological innovation processes through their
active engagement with, ascription of meaning to and further development of technologies. One way to conceptualize this process is as domestication, a metaphor that highlights how technologies are shaped by their users, while shaping and influencing the very
same users.
The MATCH project will study smart energy solutions, with a focus on the experiences of
small and medium consumers. To this end we will draw inspiration both from the literature on the construction of technology, as well as the literature on user engagement with
technologies. First, we have an interest in the work conducted by various actors to assemble or construct smart grid demonstration projects. Many of these solutions are relatively new, which means that they are subject to interpretative flexibility (Pinch and
Bijker 1984). This means that different social groups, different groups of actors, might
have different understandings of the solutions at hand, and different understandings of
what their purposes are, what the goals are with the trials etc. Thus, it is interesting to
study the translation (Callon 1986a) strategies employed by involved actors, as they try
to enrol other actors from various spheres as allies working for specific versions of what
the smart grid could and should be. One potential outcome of this is that the smart energy solutions end up looking radically different, because they have been constructed by
different kinds of actor groups and technologies, with different understandings and expectations.
More generally, this can also be related to an interest in energy transitions, with a focus
on the many controversies involved in such transformation processes, as well as the
work done to overcome such controversies, and the many sites that needs to be mobilized across society to cater for shifts in complex systems like the energy system
(Jørgensen 2012, Pineda and Jørgensen 2015, Farla et al. 2012, Åm 2015). Smart energy system demonstration projects and solutions studied in MATCH could be considered
a kind of transition experiment, where various actors negotiate how potential futures
could look.
On the other hand, we have an interest in the technology users, and the experiences of
the users with the smart energy solutions we study. However, with an ANT-inspired perspective, distinguishing between “users” and “producers” of smart energy system solutions might be somewhat misleading. Users of different kinds are part of a collective “solution”, and it is through the relations between the various elements of a solution (e.g.
solar panels, feedback monitors, humans, organizations, buildings) that a working or
non-working outcome is produced.
For this reason, it is interesting to look at how other actors frame potential user groups,
how they attempt to enrol them in demonstration projects, and which issues the smart
grid solutions are understood to address. This is related to an interest in understanding
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how technologies such as those associated with the smart grid might (or might not!) cater for public material participation (Marres 2012) in processes such as an energy or sustainability transition. An interesting route to explore could be if the kinds of solutions
studied in MATCH might serve as conduits for the production of new kinds of energy citizenship (Devine-Wright 2007), something which has been argued to be necessary to
achieve low-carbon energy transitions.
As a practical entry to the study of users and their interaction with technologies, the concept of domestication stresses how technology users ascribe meaning to technologies,
establish new practices in association with technologies, and that there is a constant process of learning in the interaction with the new technologies (Sørensen 1994). The concept is sensitive to the fact that there is interpretative flexibility amongst different user
groups, something which means that a solution might work very well for some, while alienating others.
 How are strategies employed to configure smart energy solutions for small to medium
users differently (including the role of users) and how do different configurations work
in practice?
 What are the implications of our case studies for the wider European work of “doing”
sustainable energy transitions?
 What are the relationships between different ways of engaging small to medium users
in the smart energy solutions and the relative success of the solution?
2.2 Technology learning approaches (constructive technology assessment)
Innovation studies, transition research and transition management, as well as technology
assessment approaches, put much emphasis on learning and experimentation in sociotechnical niches. According to these approaches innovation depends on practical experiences as well as theoretical reflexion in early phases of technology development. In MATCH
we will build on these ideas in a twofold manner. On the one hand, our cases will be viewed
as niche experiments aiming at processes of learning and articulation. On the other hand,
learning and reflexion will be stimulated and facilitated as part of the project. In the following we will give a brief overview of learning oriented approaches that will guide the
empirical analysis within MATCH.
The concept of socio-technical niches plays an important role in transition research (Kemp,
Schot, and Hoogma 1998, Schot and Geels 2008) and design-oriented forms of Technology
Assessment (Schot, Hoogma, and Elzen 1994). According to these early approaches,
niches are defined as temporary protected spaces to support the development of more
sustainable technologies; as a kind of local breeding spaces that enable learning and experimentation. Once the technology is sufficiently developed, in a broad sense, initial protection may be withdrawn in a controlled way (Kemp, Schot, and Hoogma 1998).
A similar notion of the niche concept is applied in the multi-level perspective (MLP) approach, an analytical framework to conceptualize and explain long-term transitions of socio-technical systems towards greater sustainability (Geels 2002). Here, niches are conceptualized as less structurated spaces that offer conditions for action: the numbers of
actors involved are small, the degree of alignment between elements is low (Geels 2011),
and existing rules and standard procedures are put up for negotiation. Literature on niche
innovation (Schot and Geels 2008) defines a number of core processes that are essential
to transform inventions and ideas into robust socio-technical configurations. Accordingly,
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niches have to support three crucial processes, (a) the articulation and the adjustment of
expectations and visions; (b) the building of social networks and the enrolment of a growing number of actors; and © learning and articulation processes on dimensions such as
technical design, user preferences, or symbolic meanings (Geels 2011). Taking this perspective, smart energy system pilot and demonstration projects can be described and analysed as niches, which – to be successful regarding their output – have to provide and
maintain these core processes to a certain extent. Activities at the niche level may influence
the more stable configurations of prevailing socio-technical systems only if the activities
gain internal momentum, become more visible and therefore attract an increasing number
of actors (Geels 2011). To learn from our case studies we hence should not only ask
whether the mentioned core processes are fulfilled but we should also explore generalisability of our findings by asking how and why and in which wider context the cases are able
to meet these hypothetical requirements.
Constructive Technology Assessment (CTA) aims to support the development of technologies that have desired positive impacts and few or at least manageable negative impacts
(Rip, Misa, and Schot 1995). The general idea of CTA is to ‘manage technology in society’
by narrowing the gap between innovation and the societal evaluation of new technology
and by putting technology on the socio-political agenda. CTA therefore has to:
“integrate the anticipation of technological impacts with the articulation (and promotion) of technology development itself. The co-production of impacts must become reflexive, i.e. actors –
whether they see themselves as “promotion” actors or “control” actors – must realize the nature
of the co-production dynamics, and consciously shape their activities in terms of shared responsibility” (Rip, Misa, and Schot 1995, 3-4).
Since broadening the design process should enrich the discourse and improve the quality
of the results, Schot (2001) argues that the performance of CTA should be monitored using
three process-oriented criteria: (1) anticipation, defined as the opportunity for involved
social groups to be able to define problems by themselves and take long-term effects into
account, (2) reflexivity, a dimension to measure the ability of social actors to consider
technology design and social design as one integrated process, and (3) societal learning,
a criterion to assess to what extent first-order learning (the ability to articulate user preferences and regulatory requirements and to connect such conclusions to design features)
and second-order learning (the ability to question existing preferences and requirements
in a more fundamental way and perhaps come up with very different demands or radical
design options) have occurred. These criteria are intended to monitor whether the design
process itself is changing, or whether a modulation of the network and actual content of
the interaction is required.
In the context of CTA, strategic niche management (SNM) has been developed as to organise and understand processes of learning and experimentation in socio-technical niches.
SNM (Weber et al. 1999, Hoogma 2002) directly refers to the creation and growth of protected spaces for promising technology. A central aim of the development of niches is to
enable learning, in realistic social contexts (e.g. market niches, controlled field experiments), about the needs, problems and possibilities of the technology under experimentation, and to help articulate design specifications, user requirements or unexpected side
effects of new configurations. SNM is a comprehensive and advanced form of managing
technological innovations through the organisation of social learning processes, involving
producers, technology designers and users in a joint long-term process.
In a similar vein, Vergragt and Brown (2004, 2007) put a special focus on small-scale
experiments aiming towards sustainable solutions. They propose a conceptual framework
Deliverable No. 1 | Studying smart energy solutions 10
for social learning within what they call ‘Bounded Socio-Technical Experiments’ (BSTE). In
a BSTE learning may occur on four different levels: On the first level, learning is conceptualised as a problem-solving activity, on the second level as a discourse about the problem
definition (with regard to the particular technology-societal problem coupling), on the third
level as questioning of dominant interpretative frames, and finally on the fourth level as a
debate on fundamental preferences for social order. Compared to other conceptions of
social learning in the context of BSTEs, the range of possible results for learning clearly
surpasses the narrow limits of a given technology and provides room to refuse given alternatives and move to completely different solutions.
Research in CTA is also contributing to the question of how to define and predict the impacts of future technologies. If technology is socially constructed, its impacts are open to
diverging interpretations as well. Sørensen (2002) has pointed out that the evaluation of
impacts operate on a rather fragile basis because the interpretations of technologies are
dynamic and situated, and thus inherently flexible. Thus, CTA treats the impacts of technology as dynamic, as involuntarily co-produced during the implementation and diffusion
stage. CTA researchers also argue that societal consensus on which impacts are desirable
is rarely present and/or achievable (Rip, Misa, and Schot 1995). Because of this dynamic
nature of technology impacts, CTA is conceptualised as a process of learning and experimentation (Grin and Van de Graaf 1996). Possible impacts are to be discussed and anticipated earlier and more frequently (Schot 2001) and assessments are seen as integrated
and repeated parts of the innovation process, applied at preferred loci for intervention.
Based on these conceptual and theoretical considerations, the following research questions
are proposed to guide the investigation of learning processes in smart energy innovation
niches:
 What has been learned about the technology, social implications and wider system effects and what is needed to further broaden the innovation process?
 How do structural conditions affect learning in smart energy niches? What is the role
of local and national conditions?
 What is needed to support processes of replication and scaling up? How do actors involved assess their achievements?
2.3 Practice theories
Practice theories are not a new or common agreed upon, unified theory, but rather an
approach or “turn” in sociological thinking, which places “social practices” as the central
unit of analysis (Gram-Hanssen 2011, Schatzki, Knorr-Cetina, and Von Savigny 2001). In
the words of Schatzki, a social practice can be defined as a “temporally unfolding and
spatially dispersed nexus of doings and sayings” (Schatzki 1996, 80).
The practice theories approach seeks to overcome the structure-actor dualism regarding
whether human behaviour is primarily determined by social structures or individual
agency. Instead of seeing practices as individual acts, practices are seen as collective actions where the individual can be viewed as a carrier (Reckwitz 2002).
An important observation from practice theories is that consumption of energy (and resources more generally) is the outcome of performing practices. As Alan Warde observes: “(…) consumption is not itself a practice but is, rather, a moment in almost every
practice.”(Warde 2005, 137). Thus, everyday practices such as cleaning, preparing food,
doing the dishes, washing clothes, commuting and many entertainment activities (like
watching television) all involve some form of energy consumption. Consequently, the
Deliverable No. 1 | Studying smart energy solutions 11
timing of energy consumption (when energy is used) is closely tied to the temporality associated with the performance of practices.
Within practice theories, a common understanding is that a practice (the “nexus of doings and sayings”) is hold together by heterogeneous and mutually dependent elements,
which together constitute the practices. Reckwitz (2002) defines a practice as ”a routinized type of behaviour, which consists of several elements, interconnected to one another: forms of bodily activities, forms of mental activities, ‘things’ and their use, a background knowledge in the form of understanding, know-how, states of emotion and motivational knowledge” (2002, 249). Different authors have suggested different typologies
of these elements. Within consumption studies, Shove and Pantzar (2005) developed the
most widespread typology, which distinguishes between three forms of elements: meanings, competences and materials. These elements are specified as:
“(…) ’materials’ – including things, technologies, tangible physical entities, and the stuff of which
objects are made; ‘competences’: which encompass skill[s], know-how and technique; and
‘meanings’: including symbolic meanings, ideas and aspirations.” (p. 14)
Using car driving as an example of an energy-consuming practice, this practice entails
some physical “materials” (e.g. the car, but also the material infrastructure), “competences” (e.g. the embodied competences and skills of driving) and “meanings” (e.g. understandings of driving as associated with freedom or necessity). Through the performance of driving, the practitioners (the “drivers”) activate and perform different links between these elements and in this way reproduce and change the dynamics of the collectively shared driving practice (Shove, Pantzar, and Watson 2012, 8).
Practice theories depart from the dominating human-centred psychological and economic
theories often applied within consumption and environmental behaviour studies. Instead
of placing the individual actor (and his/her preferences, values and attitudes) as the key
to understand behaviour and behaviour change, practice theories shift focus from the individual actor to the complex of elements (including material elements like technologies)
that constitutes practices. Thus, interventions aimed at changing practices, e.g. within
households, should ideally address all elements involved in performing the everyday
practices of the residents.
From a practice theoretical perspective, the key research questions of the MATCH project
can be phrased as:
 How are the specific configurations of elements in the studied demonstration projects
decisive for how the smart grid solutions work out in practice (the “success” or “failure” of solutions)?
 Can the “lessons learned” in relation to the role of specific configurations of elements
in a specific case be transferred to other contexts/countries? And under what circumstances?
 What implications do the changes in practices have for the energy consumption (size
and timing) of households and other small-medium customers?
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3 Smart grids and smart energy solutions: what do we
mean?
The overall objective of the MATCH project is to “expand our understanding of how to design and implement comprehensive smart grid solutions that take into account the complexity of factors influencing the effectiveness and success of smart grid initiatives targeted at small consumers” (from project proposal). To do this we will conduct at least
three case studies in the three countries involved in the project: Austria, Denmark and
Norway. The cases will be compared, and based on this exercise we will develop recommendations based on the results from our studies. These recommendations will feed into
discussions on how to design and implement future smart grid solutions in the three
countries and beyond.
In order to do so, we need a more or less coherent understanding of what we mean
when we say that we want to study the “smart grid”, as well as what we mean when we
want to study how to make specific “solutions” work better. Thus, we will now briefly discuss how we understand the smart grid, as well as the associated “smart grid solutions”
that we will study variants of in MATCH. This discussion will also take into account earlier
relevant research on such solutions, and through this lay the ground for discussions and
decisions on how to choose case studies later in this report.
3.1 The smart energy system
Energy systems across Europe and beyond are changing, and many of the changes tend
to be discussed under the umbrella heading as the emergence of a “smart grid”. The
term has countless definitions. As an example, the council of European energy regulators
highlight that a smart grid is:
“an electricity network that can cost efficiently integrate the behaviour and actions
of all users connected to its generators, consumers and those that do both in order
to ensure economically efficient, sustainable power systems with low losses and
high levels of quality and security of supply and safety”1
The Norwegian national research strategy on smart grids rather stresses that there is no
short, clear and concise definition of the term, which do justice to the many meanings
that it has taken on.2 Thus, rather than aim for a new and precise definition of what is
likely to be a moving target, our goal in the following is to give a practically useful description of some elements, or “solutions” typically associated with the smart grid. In this
way we are close to the understanding fronted by the U.S. office of electricity delivery
and energy reliability who point out that:

1 CEER status review on European regulatory approaches enabling smart grid solutions, p. 10
http://www.ceer.eu/portal/page/portal/EER_HOME/EER_PUBLICATIONS/CEER_PAPERS/Electricity/Tab3/C13-EQS-57-
04_Regulatory%20Approaches%20to%20Smart%20Grids_21-Jan-2014-2.pdf
2 Norwegian smart grid research strategy, p. 5 http://smartgrids.no/wp-content/uploads/sites/4/2015/08/Norwegian-Smart_Grid__Research_Strategy_DRAFT_June10_WT_ks_hii.pdf
Deliverable No. 1 | Studying smart energy solutions 13
“the ‘Smart grid’ generally refers to a class of technology people are using to bring
utility electricity delivery systems into the 21st century, using computer-based remote control and automation. These systems are made possible by two-way communication technology and computer processing [technologies]”3
In part, the understanding of the smart grid in the MATCH project has emerged from a
previously funded ERA-Net project. In the project Integrating households in the smart
grid (IHSMAG) many researchers involved in the MATCH project wrote the following:
“our approach has been relatively open as we understand the smart grid as basically characterised by:1) An increased integration of new ICTs (including an Advanced Metering Infrastructure, AMI) that enables new ways of communicating
between different actors. 2) The integration of new actors in the electricity system
as well as the assignment of new roles to existing actors (e.g. households as both
consumers and producers of electricity)” (Christensen et al. 2016, 6).
In MATCH, we build on this, and continue to pursue a relatively open approach to what
the smart grid is, what problems it is set to solve and what it can offer. However, this
broad focus actually means that we look at many things that are strictly speaking not
part of the “grid”. Thus, we find it fruitful to shift our attention slightly, from a previous
focus on “the smart grid” to change focus a bit to highlight that what we are actually
studying components of broader, smart or distributed energy systems. In practice, we
might end up using the words interchangeably, but there are good reasons for the slight
change of focus. While the word “grid” literally deals with transmission of electricity
through wires, smart energy systems can be much more comprehensive. They are expected to change the historically quite stable relationships between production and consumption through introducing a broad range of new technologies, modes of organization,
market structures, new roles for actors across the system, rules, configurations, etc. This
might include technologies that do other things than deliver electricity, e.g. combined
heat- and power plants (CHP), solar collectors or bioenergy installations. Hence, our
shift to a focus on smart energy systems rather than smart grids imply a broadening of
scope and perspective.
The starting point for discussions about smart grids and smart energy systems are often
the digitalization of data about electricity consumption and production, and new modes of
two-way-communication between what has traditionally been described as the supply
and the demand side of the electricity system, the overarching goal being to “better align
energy generation and demand” (Goulden et al., 2014) to provide for a more flexible
grid. Therefore, while this is not a precondition for all smart energy system solutions,
many projects over the last years have had “smart” or advanced electricity metering infrastructure as their starting point, replacing the old, mechanical electricity meters of the
past with new, digital meters.
On a basic level, smart electricity meters might help illustrate the difference between
“smart grids” as a generic concept, and what we will study in the MATCH project, namely
“smart grid solutions”. The meter is a component in the smart grid, one of countless potential technologies. For some actors, simply “rolling out” smart meters could be considered implementing a “smart grid solution”. In what follows, we will turn to such solutions,

3 http://energy.gov/oe/services/technology-development/smart-grid
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while discussing some past research relevant to the MATCH project. Our primary focus is
on solutions that are relevant to small and medium sized customers.
3.2 Smart energy solutions for small and medium sized users
In what follows we will outline three proposed “solution focus areas” that are intended to
help MATCH researchers navigate the field studies of their native smart energy solution
trials, in a similar fashion as a botanist might bring along a flora, a handbook of flowers
on her quest to discover the forests botanical life. However, just as the botanist, we
should not see this as a forced straight jacket, for what could be more exciting than discovering a new breed of flowers? That said, even new flowers are likely to contain some
elements that are known from the flora: the color, the shape, the numbers they come in,
etc. The point of this metaphorical de-tour to the forest is to highlight that we should also
keep our eyes open to different and unexpected configurations, and to new combinations
of humans and technologies that work in other ways than pointed out in the discussion of
solution focus areas.
From the beginning, much focus has been put on the rollout of “smart metering”. Advanced or “smart” electricity meters typically measure the use of energy and the power
output (effect) (Löfström 2014) from consumers, and send this information to the electricity suppliers. At the same time, the meter has the capacity to provide real-time data
to consumers about the levels and costs of consumption. One practical outcome of this is
that meter readings do not have to be done manually, the process is automated. In some
countries such as Denmark and Norway, this has in the past been done by the customers.
However, research quite clearly indicates that stand-alone smart meters do very little to
achieve reduced energy consumption, shifting the time of energy use or increase customer engagement with the energy system more generally (e.g. Bertoldo, Poumadère,
and Rodrigues Jr 2015, Darby 2010, 2001). Actually, some studies have suggested that
the use of smart meters without additional technologies might do more harm than good
since it allows for complete automation of the relationship between householders and
electricity providers, and therefore potentially limits engagement with the electricity system (Jørgensen 2015, Throndsen and Ryghaug 2015).
For us in the MATCH project, it is therefore unlikely that we will be interested in studying
smart meters as such. On the other hand, the smart meter quite often serves as a sort of
technological hub, facilitating the connection of many other technologies as well as the
construction of new services and tariffs etc. related to households or small-medium businesses. As such, it is quite likely that smart meters will be one of many components of
the several solution constellations that we study in MATCH. For us, then, it will be important to try to understand what role they play in the specific solutions studied, how
they are made sense of or interpreted, how they enable or disable certain modes of action, etc.
With these introductory words about smart metering etc., we will now present the three
solution focus areas, which will be in focus for this study.
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3.2.1 Demand side management/Demand side response
Demand-side-management refers to a set of technologies or technological set-ups, where
the goal, as the name indicates, is to manage or steer the demand of electricity by reducing it and/or shifting it away from peak load periods. Thus, it concerns trying to trigger change amongst consumers in some way which means that it is highly relevant for
MATCH. As Fell et al. (2015) state, it refers to creating “change in electricity consumption
patterns in response to a signal”. A “signal” often refers to the price in combination with
some sort of information device, but in principle the signal can be any impulse meant to
trigger change, including automated response.
Such schemes are typically built “on top of” smart meters, and in line with the definition
above involve some sort of technology that sends a “signal”, and often also some sort of
technology meant to facilitate the consumption change. Broadly speaking, it is possible to
differentiate between two ideal typical strategies. In the first, the active choice of changing consumption is left to the consumers, in the other, making this choice is delegated to
technologies, i.e. they are automated. In practice, of course, solutions are often placed
somewhere between complete automation and complete active engagement. Thus, the
level of automation or agency given to users is something we should study empirically,
because choices made with respect to this issue tends to produce very different smart
energy system solutions, with different expectations for the actors involved. In turn, this
will most likely also influence how different actors evaluate the solution, and ultimately
how the solution “works” with the present actor constellation and in the present context.
An example of the first strategy includes providing customers with in-home-displays
(IHD) or other direct feedback technologies (Hargreaves, Nye, and Burgess 2010, 2013,
Wallenborn, Orsini, and Vanhaverbeke 2011). These technologies use the data generated
from smart meters to provide customers with feedback (signals) e.g. about the cost of
their current consumption, about the environmental impact of the consumption or about
the level of current electricity use. Such feedback can be given at an aggregate level
(household), but earlier research indicates that achieving energy savings is more likely if
the feedback is given in a non-aggregate way, e.g. broken down per appliance
(Hargreaves, Nye, and Burgess 2013), which facilitate both ease of use and understanding (Darby 2010).
Another point which has been made in the past is that the feedback given should provide
information deemed relevant to the users. One way to achieve this could be to ensure
some sort of comparability: how does the current household perform compared to neighbors and other relevant households? (Christensen et al. 2016). Another potential example: what are the current environmental “expense” of the households’ consumption, compared e.g. to other phenomena such as air travel or driving a car? On a general note, it
should be pointed out that “what is relevant” will most likely differ between user groups
and contexts, a point that highlights the importance of trying to design solutions inclusively (Sørensen, Faulkner, and Rommes 2011), e.g. through actively incorporating the
competences of prospective users and their everyday practice in the design of smart grid
solutions (Jelsma 2003, 2006, Skjølsvold and Lindkvist 2015). On a cautionary note, it
should be added that the positive effects of feedback seldom reach the optimistic assumptions provided by engineers and some economists, because raised awareness levels
do not necessarily translate into altered practices.
Solutions like IHDs can be implemented as a stand-alone technology or in combination
with other technologies, incentives and modes of organization. One example of this is the
implementation of new incentive structures such as time-of-use pricing (TOU), e.g. making electricity much more expensive during peak hours. This can be done in different
ways.
Deliverable No. 1 | Studying smart energy solutions 16
As an example a recent study from Denmark shows that schemes based on fixed price
intervals (also called Static time-of-use pricing) are easier to understand for the households compared to schemes based on prices that change continuously from hour to hour
and day to day (also called Real-time pricing). Static time-of-use pricing makes it easier
for the household members to develop new routines and shift electricity consumption on
a permanent basis. The Danish study indicates that the time-shifting in electricity consumption was not so much depending on the actual cost savings (which were in general
small), but rather because the static time-of-use pricing conveyed a general knowledge
about at what times it would be most suitable for the system and for the participants
personal economy to consume electricity (Christensen et al. 2016)
The other strategy focuses on delegating the response to signals to pre-programmed
technologies. This can be done quite crudely through reducing the allowed volume of
electricity consumption at any given time, often described as load capping. Another alternative is so called direct load control (DLC) where operators are allowed to remotely
switch off electrical appliances such as water heaters when this is deemed necessary.
Other prospective technologies involve washing and drying machines, freezers and refrigerators, which may provide some flexibility. Studies that MATCH researcher have been
involved in earlier, however, suggest that this has limited effects on the grid (Meisl et al.
2012). Still, many actors argue the case that making these applications become “smart”,
interacting directly with new price signals or other pre-programmed settings, and limiting
the need for user involvement, is a feasible strategy.
Some earlier studies have indicated that for many users, such solutions might entail a
sense of loss of control of vital elements of everyday life (Rodden et al. 2013), while
other studies (Fell et al. 2015) suggest that this is an area where users are quite open to
relatively radical innovations and change. To us this indicates that there is significant interpretative flexibility here, both across cases and contexts, which we should explore empirically. Another consideration to make is that while automation might facilitate change,
it might also entrench and solidify new practices to the extent that they become even
harder to change, more “naturally” integrated in everyday life than pre-existing patterns
(e.g. Strengers 2013 for a critical discussion).
When we discuss how solutions meant to trigger changes in energy usage patterns work,
it is in light of the above likely that we will come across different formulations of what the
“goals” of implementing such solutions are. Some might see these technologies as components of strategies meant to empower end-users to become more engaged in the energy system4
, or even producing new forms of energy citizenship (Devine-Wright 2007).
For others, these technologies are part of a strategy where the primary goal is to reduce
consumption and shift loads, for instance as a way to reduce peaks, or to cater for new
intermittent renewables.
In sum, the discussion indicates that technologies meant to change consumption patterns
on the so-called “demand side” (DSM or DR) is a broad class of technologies, often targeting the kinds of consumers that are of interest to the MATCH project. While they have
been extensively studied, discussed and criticized in the past, there is little indication

4 This is at least rhetorically stressed in many of the calls from the European Commission in the Horizon 2020
work programme. For an example from an upcoming call, see EE-07-2016-2017 “Behavioural change toward energy efficiency through ICT”, http://ec.europa.eu/research/participants/portal/desktop/en/opportunities/h2020/topics/5059-ee-07-2016-2017.html
Deliverable No. 1 | Studying smart energy solutions 17
that they are disappearing or that there will be fewer experiments with them in the years
ahead. We thus make this one of the key MATCH solution focus areas.
3.2.2 Micro generation
Another frequently discussed option for the smart energy system is to turn the attention
towards micro generation of electricity. Typically, this can be done through rooftop solar
PV, micro wind turbines, small CHP-systems or in some instances even small-scale hydropower.
For MATCH, this development raises interesting questions with respect to the role of actors in the energy system, new technologies, as well as the market structures of the energy system. As far as the actors go, a key issue to ponder is the relationship between
actors at what has traditionally been called the supply and the demand side of the electricity system. With the introduction of micro generation, the small and medium sized
electricity consumers might actually become suppliers of electricity, both producing electricity that they can use in their own buildings, and selling electricity to the grid. Thus,
this is a potentially disruptive development, which includes technological changes, huge
implications for market structures, and changed roles for many different actors in the
electricity system. In a recent paper discussing the emergence of so-called “prosumers”,
Parag and Sovacool (2016) highlight:
“Fundamentally, markets for prosumption services are different from existing engagement platforms, such as demand-reduction or demand-response programmes. That is because, in prosumer markets, users on the demand side not
only react to price signals, but also actively offer services that electric utilities,
transmission systems operators, or other prosumers have to bid for” (p. 1)
While micro generation will often be accompanied by many of the technologies discussed
under the header of demand side management, it is a more novel smart energy solution,
which has so far been less studied in practice. However, there is currently much experimentation going on in demonstration sites, which is also one of the main reasons for
making this one of the key solutions studied in MATCH.
How the prosumer-energy system relationship will look like, and how prosumer markets
and actor-relationships will unfold, will likely depend on local context, on the goals set by
operators of smart grid demonstration processes, on the potential for renewables like
wind and solar in a given area, the levels of trust amongst electricity users, between
electricity users and utilities, pricing structures, national regulation (e.g. taxes), etc. As
an example, one can easily imagine situations where groups of citizens who distrust the
government, central grid and traditional electricity market want to develop prosumer
models to become independent and go “off grid”, while other groups might use the very
same technologies to create new social and business opportunities within existing market
structures. There are already examples of controversy emerging in some contexts, e.g.
Spain has recently enforced a “sun tax” which effectively removes many of the potential
incentives for prosumption and distributed electricity production.5
Parag and Sovacool (2016, 2-3) discuss three potentially emerging models of prosumer
markets, all with their distinct characteristics, potential upsides and potential downsides,

5 http://www.renewableenergyworld.com/articles/2015/10/spain-approves-sun-tax-discriminates-against-solarpv.html
Deliverable No. 1 | Studying smart energy solutions 18
for different actors across the electricity system. Fig. 1 is a graphical representation of
these potential models.
The first model is a peer-to-peer model, an organic and not very structured model, involving decentralized and relatively autonomous networks, developed bottom-up (fig 1,
model a). Some have envisaged an Uber or Airbnb-inspired model, where a social platform of some sort allow consumers and producers of electricity to bid and sell services.
This would entail a radical shift in market structures, the role of actors and involved technologies, and as such, it is likely that incumbent actors have diverging views on the
model, and that new types of actors might push this development. In Norway, such models of energy sector “revolution” are promoted primarily by ICT actors. In 2015 a group
of such actors joined forces with actors from the energy sector and sought funding for a
centre of excellence from the Norwegian research council with the goal of “unlocking” this
potential.6
The second model – termed prosumer-to-grid models – is more structured and involves
prosumers linking up to local microgrids through brokerage systems. Parag and Sovacool
point out that microgrids can be connected to a main grid, or that they can operate in an
“island mode” (see fig. 1, models b and c). Connection to a main grid implies the possibility of selling to the grid, a potential incentive to produce as much as possible, while an
“island mode” introduces many challenges of local optimization and balancing of the grid.
While “island” in Parag and Sovacools instance is a metaphor, several potential cases in
the MATCH project are located at actual islands, which we might hypothesize creates
conditions favourable to “island mode” microgrids with a high penetration of local, small
scale renewables.
The final model, an organized prosumer model, is a model where groups of prosumers
organize in new ways to establish virtual power plants (fig. 1, model d). This is more organized than peer-to-peer models, but less so than prosumer-to-grid models. Parag and
Sovacool foresee potential for such models in urban areas where local communities,
neighbourhoods or organizations might collectively manage and pool their resources in
new ways. This model poses interesting questions with respect to collective action and
the management of common pool resources, where collective gains depend on individual
decisions (e.g. Ostrom 1990, and Wolsink 2012 related to electricity).
Figure 1 Potential structural attributes of prosumer markets. Parag & Sovacool 2016, p. 3

6 See: http://www.uis.no/research-and-phd-studies/research-areas/information-technology/energy-informatics/. The centre was not funded, but the research group pursues this agenda.
Deliverable No. 1 | Studying smart energy solutions 19
The introduction of micro generation and prosumption as a smart grid solution is highly
interesting in the MATCH context as it has the potential to re-configure key parameters of
how markets, actors and technologies interrelate in the energy system. Also for this reason, we will make it one of three key smart grid solutions to be studied in the project.
3.2.3 Integration of storage technologies
As the share of intermittent renewables increase, many energy systems are facing challenges of balance. Since wind and solar power production depends on the sun cycle and
weather conditions, there is a question of how one should secure a reliable low-carbon
base load or reserve capacity. One promising way of handling the issue is the installation
of some sort of storage technology to decrease the dependence on fluctuating wind and
sun. One option can be to install batteries in households, in the way that Tesla has proposed through its high profile Powerwall project.7 In other sites, thermal storage is more
likely to be implemented, or other kinds of building-to-grid technologies. Another type of
storage that we might come across, particularly in the Norwegian case, is the aggregated
use of batteries from electric vehicles (EVs). These can potentially play a dual role in future smart energy systems, because they on the one hand might generate new need for
electricity production and increased power capacity, while on the other hand serve as a
flexible load by ways of the batteries.
Introducing storage technologies could be a particularly promising strategy in contexts
characterized by some sort of micro grid organization with a high penetration of intermittent renewables. As Wolsink (2012) wrote, with a specific focus on the potential of EVs:
“The flexibility in time-of-loading, inherent in the energy storage of a large electric vehicle fleet, offers opportunities to increase the feasibility of smart applications of renewable energy. Hence, options for reloading electric vehicles within the domain of microgrid community (e.g., at home) becomes a significant factor in advancing the deployment of renewable energy” (p. 826)
Other storage technologies can play similar roles as a solution in reconfiguring the future
smart energy system. Thus, storage integration will be one of the key MATCH solution focus areas.
3.3 From individual solutions to integrated hybrid configurations
As is emergent from the discussion above, the introduction of smart energy solutions entails reconfigurations of social and technical character. As a pragmatic choice, and to
ease the burden both of writing and reading this report, the thematic description of the
solution areas above has taken the introduction of new technology as a sort of starting
point.
This, however, does not mean that we study technological solutions. As discussed in the
section on theoretical considerations, our perspectives in different ways ask us to account
for the social elements of any solution we study. This does not mean that we study how
what many engineers would call “the human factor” are influencing technology performance. Rather, we are interested in the configuration of smart energy system solutions
as a whole, meaning that we want to grasp the relationships between human and non-

7
see https://www.teslamotors.com/powerwall. There are, of course, many other actors working with batteries
that we are more likely to come across in MATCH.
Deliverable No. 1 | Studying smart energy solutions 20
human actors in specific solution configurations or assemblages, and further, how these
solutions interact with a broader contextual setting. Thus, we apply a symmetrical gaze,
where neither humans nor technologies are privileged a priori. Their capacity to act, to
do work, as well as the character and outcomes of this work needs to be accounted for
on a case-to-case basis.
With this in mind, it should also be clear that we will seldom (though we might!) come
across solutions that focus purely on one type of technology or one type of actor. One
reason for this is that the world tends to be messier, and that any typology or classification implies some sort of reduction in complexity.
Another, more concrete reason can be found in the empirical field that we are interested
in, which seems to have shifted away from a belief in individual solutions to more systems-oriented approaches. As an example, Norwegian policy makers had quite naïve
ideas about what smart meters combined with feedback could achieve in terms of energy
reduction and load shifting (Ballo 2015, Skjølsvold 2014). In the following years, however, studies of various individual solutions have provided sobering and somewhat disappointing results. As a response, many demonstration sites are now experimenting with
much more hybrid, integrated solutions, where different components is expected to do
different kinds of work. Arguably, we are currently seeing the exploration of second or
even third8 generation smart energy system solutions for small and medium consumers.
This would mean that a strict delineation of what we can study in MATCH based on the
three categories of proposed solution areas would severely limit our possibilities both of
being relevant and of producing meaningful, comprehensive analyses. It is the ambition
of the MATCH project to move beyond individual solutions.
At this point it is difficult to practically say how a studied solution should be delineated,
beyond stating that what the solutions consists of is an empirical question. As an example, it would make little sense to study exclusively a rooftop solar PV “solution”, if what is
really installed is a combination of smart home technology, rooftop PV and battery capacity.

8
Solutions for prosumers involving batteries or EVs could be said to be the third generation.
Deliverable No. 1 | Studying smart energy solutions 21
4 Studying how solutions work
By now, we have a basic understanding of what we mean when we say “smart grids”. In
fact, we have shifted our attention from the grid towards smart energy system solutions.
We also have an idea of what we mean when we say that we want to study specific smart
energy system “solutions”. In MATCH we will study smart energy solutions targeting
small to medium customers. In the above we have discussed three types of solutions
that we propose should form a sort of basis for the studies in the three countries. These
are:
 Solutions aimed at changing demand side consumption patterns: Demand side
management or Demand-response
 Micro generation
 Integration of storage
As discussed, this forms a relatively open-ended starting point for our studies, which also
should allow us to study various combinations of integrated solutions and how they work.
These will be compared in order to develop sound analysis of which kinds of solutions
that are expected to work under which conditions, and further to formulate recommendations that feed into various discussions on how to best implement smart energy solutions. This section of the report will do two things. First, it will roughly outline the process
of doing case studies, from research questions and selecting cases to writing up case
study reports. In doing this, we will discuss some of the challenges we will come across.
We will then proceed to discuss some analytical challenges related to comparatively assessing what it means that something works (see 4.7).
Issues to be discussed here include aspects such as how we define what it means that a
smart energy solution “works”, how we move from cross-case comparative work to generalizations, and how we deal with issues such as “context”.
4.1 The research questions
As stated, the overall aim of MATCH is to study how complexities of factors influence the
effectiveness of smart grid initiatives in order to contribute to better and more comprehensive smart grid (energy) solutions. More specifically, the case studies will analyse
both the direct implications of smart energy solutions on the (everyday) practices of the
users as well as how the solutions (and how they are used in practice) are integrated in a
network of mutually dependent actors. The case studies will apply both analytical perspectives on the studied solutions, which are essentially closely related.
An example of the focus on the implications of the smart energy solutions for social practices could be, e.g., how the combined ownership of PVs and electric vehicles affects
households’ (or other types of actors’) daily practices. For instance with regard to driving
patterns, the timing of EV-charging or other electricity-consuming household practices
etc.? In addition, an important question would be how this affects the energy consumption patterns of the users?
Similarly, an example of the focus on the network of the smart energy solutions could be
how the PVs and electric vehicles are related to (dependent on), e.g., local actors (electricity suppliers, DSOs, the municipality etc.), national regulation of EVs, subscription
schemes for prosumers, accessibility to local/national network of EV charging stations
etc.
Deliverable No. 1 | Studying smart energy solutions 22
In carrying out the case studies, the earlier presented research questions (Section 2) will
work as guidelines for the analysis.
4.2 Choosing cases
On a basic level, three case studies should be conducted in each country. These case
studies should be examples of smart energy solutions, targeting small to medium consumers. These consumers could be ordinary households, but small-to-medium companies
are also viable as users for our purpose. Smart energy solutions consist of a set of technologies, services, incentives, actor groups, users, practices, processes, meanings, etc.
Thus, they are truly heterogeneous sociotechnical collectives. That said, the easiest point
of entry, or the easiest way for the MATCH researchers to recognize them as new solutions, will most likely be through the identification of some sort of trial site where someone is engaged with testing new technology.
When such a trial (or trials) has been identified, the three solution focus areas give some
pointers with respect to what to study. This means that a trial or a demonstration project
might not necessarily be the same as a “solution”, because it could in principle be testing
dozens of solutions for different purposes. On the other hand, a smart energy demonstration project could easily be limited to the testing of one solution. Table 1 is a very
simple matrix illustrating how three imagined cases might incorporate several different
aspects from the proposed solution focus areas. If needed, such a matrix could be expanded and concretized in order to visualize and make comparisons between cases more
tangible.
DSM Micro gen. Storage
Case 1 x
Case 2 x x
Case 3 x x x
Table 1: Matrix illustrating different degrees of hybridity and integration in three imagined cases.
The three solution focus areas are broad enough to allow us to cover a broad range of
the aspects of what is frequently discussed as “the smart grid”, or the smart distributed
energy system. It also allows us to look into both relatively mature types of solutions as
well as less mature solutions and different types of experiments with integration of different solutions.
For the purpose of the MATCH project, it would be useful to choose cases where some
experiences – positive or negative – have been gained from the solutions at hand. That
said, there are likely lessons that can be learned also from projects that have been established more recently.
4.3 Doing case studies: some preliminary thoughts
Once cases have been identified, how do we study them? The focus of the project has
originally emerged from engagement with the three-layer model as emphasized by the
Deliverable No. 1 | Studying smart energy solutions 23
funding body for this project. This model proposes that there are basically three categories of elements involved in the development of the smart energy system. These are a)
markets, b) actors and c) technologies.
As our discussion on potential solution focus areas indicate, it is quite clear that any
smart energy solution entail some sort of re-configuration of these elements, and that a
clear-cut differentiation between the three is not feasible. It will most likely be difficult at
times to distinguish clearly between the categories. In the case of micro generation solutions, for example, small customers could potentially re-define market structures through
the use of new technologies.
This brings some interesting questions for the MATCH consortium. In our proposal we
have said that we want to study the relative “success” of such solutions. The very dynamic and shifting situation with respect to the smart energy system, however, suggests
that a focus on success is too narrow. As an example, a solution could be a disaster for
the business models of an incumbent industry actor, while at the same time being a raging success for a small consumer. In such a case – should we consider it as a success?
Thus, we once again shift focus somewhat, and rather ask how the specific smart energy
solutions work. This reflects our view on such solutions as hybrid collectives established
by the relations between involved humans and technologies, and that what “works” is relational and contingent on the specific context of the solution. In practice, this means
that it will also be useful to map how the solution in question works for different kinds of
implicated actors.
However, while it is true, stating that “everything is complex” will not be very productive,
at least not at this stage of the project. Hence, for the sake of making this report a more
hands-on guide, let us begin with a brief and pragmatic discussion about what our key
focus is when it comes to looking at the – admittedly simplistic – categories markets, actors and technologies.
4.4 Markets, actors, technologies
4.4.1 Markets
Market conditions are generally considered to be one of several framework conditions for
smart energy solutions in the three countries. The countries have different taxation regimes, different market mechanisms for phasing in new renewables, different energy mixes, different levels of liberalization, integration with other countries, the EU, and most
likely different public attitudes towards new regulations, new technologies, etc. Thus, one
of the ways that we will incorporate markets in our studies is through doing a national
study in each country. This study should be a descriptive and informative piece of text,
which highlights the framework conditions in each country. This national study should be
conducted before the actual empirical case study work begins (or in the very beginning of
the case studies).
National study contents:
 A very brief description of the country.
 Information on current energy mix, and some broad historical lines on how this
have developed over time.
 Information primarily on electricity use/consumption, and, if available, trends over
time.
Deliverable No. 1 | Studying smart energy solutions 24
 A description of how the electricity system works together with/interacts with
other parts of the energy system as well as some key statistics for the entire system.
 Information on the general state of the current electricity market – how is it regulated, how open is it, how does it relate to broader markets (EU, etc.),
 Information on general national policies, regulations, strategies for phasing in new
renewables and/or other sustainable technologies (e.g. feed in tariffs, certificate
schemes, subsidies, market liberalization, etc.)
 Information on specific policies, regulations, strategies, etc. targeting the development of the smart grid.
 Information on national smart grid initiatives, both research programmes and
similar activities (players in the field, programmes, main projects, etc.) and industrial activities (networking activities, companies involved, etc.)
The production of the three national studies could provide interesting added value to our
project. On the one hand, it opens for the possibility of doing some sort of comparative
policy study. Further, we should also keep in mind that our empirical work on the smart
energy solutions might shed new light on and create the need for elaborations on what
we “know” about the three national energy contexts. Thus, while we should aim to have
the documents on national context ready by the end of September 2016, we could consider keeping them “open” to be revisited at a later point in the project.
Related to the three case studies of smart energy solutions, MATCH researchers should
also be sensitive to the business models built around the case solutions studied. What is
done by whom in order to try to profit from the new solutions? What changes of the existing market rules would support the new solutions?
4.4.2 Actors
The key actors for MATCH are the small and medium consumers. Key questions to study
are how they are involved and engaged in the smart energy solutions, and through this
we should be able to give some recommendations on the potentials and limits to engagement. Typical modes of engagement could be as prosumers or as providers of “flexibility”
when trying to balance the grid. We should also search for other (perhaps more innovative) ways that actors are engaged, e.g. through meetings, workshops, design exercises,
empowerment mechanisms, etc.
However, actors are not only the small/medium customers. They could be the incumbent
electricity generators, grid operators, ICT-companies, housing industry, heath care and
welfare technology sector, entertainment industry, intermediaries of various types or
others engaged in the development and testing of smart energy solutions. A key point
here is that we should let the cases at hand direct us towards the actors. Who are involved, what are their roles, and what do they do? This also relates to matters such as
organization of the solutions and the relationship between involved actors. Who formulates the solutions, and how do actors work to engage other types of actors in their proposed solutions? This could feed into related discussions about the ownership of various
components in the “solution”. As an example, Norwegian prosumers typically tend to purchase, and thus own, their PV panels, whereas similar solutions in other contexts have
been based on home owners leasing PV panels, e.g. from DSOs.
For us, all of this might feed into discussions about what the organizational obstacles to
making smart energy system solutions “work” are, and which modes of organization that
Deliverable No. 1 | Studying smart energy solutions 25
helps. On a practical level, this can be operationalized by studying matters like rules,
contracts, responsibilities and organizational practices, etc. We should also look for patterns of which actors are involved, as well as which roles different types of actors take on
across cases and contexts.
4.4.3 Technology
Our discussion of the three proposed solution focus areas contains relatively rich descriptions of some of the potential technologies that we will come across in the MATCHproject. However, we are not studying technologies as such. Rather, our interest is how
technologies work in interaction with people, households, organizations, markets, industry actors, “old” technologies, existing infrastructures, etc. Thus, technology is simply
one of multiple elements that make up a “solution”.
The gateways into studying technologies in a project like these are many. One potential
way is through what we broadly can call technology development. It is quite likely that
many of our studied solutions are parts of demonstration projects where such development is one of the goals. Technology development here should not be understood to be
limited to the engineering exercises of producing new “gadgets”, or to being limited to
exercises of design. Instead, it could just as easily refer to combining existing technologies in new ways. An example could be technologies coming from different industrial realms, merging in the smart energy context. Combination of ideas about welfare technology with ideas from smart energy systems and the ICT-realm could be an example of
this, combinations that in the past have resulted in the emergence of new and increased
focus on matters like universal design and usability (Skjølsvold and Ryghaug 2015).
Thus, for us the technologies are not only interesting as carriers of certain technical qualities that can somehow be realized, e.g. through achieving “social acceptance” of the new
technologies. Rather, the technologies are elements of any solution that comes with a set
of expectations (including wider societal implications) with respect to future use, as well
as with respect to the competences, and abilities of future users. The technologies stand
in relation to other technologies, to users, to technology developers, policy maker, etc.,
and it is in relation to other actors that we might be able to say whether a technology
“works” as part of a solution. A novelty in the MATCH project compared to many other
projects on the smart grid and smart energy systems is that we will not only conduct
studies of this type for individual technologies, but for integrated hybrid solutions, or solutions that in a much broader sense allows for discussions about what it might entail to
upscale and disseminate solutions profoundly.
4.5 Doing case studies: a proposed five-step plan
In order to account for the market aspects, actors and technologies of each selected case
(smart grid solution), we propose a five-step plan for the case studies at hand, which
should ensure that all cases include a common basis of elements, which will enable the
cross-case comparative analysis. This will cater for the production of descriptive case
study reports from the countries, where we should strive to provide relatively descriptive
accounts of the solutions.
The proposed procedure should not be read as a straight jacket, and where it is needed,
the case studies should absolutely be tailored and adopted to the local conditions. It is an
attempt to anticipate what we might come across and what might be expected, but as
such it is also filled with the preconceived ideas of the authors, which might not correspond well to what we actually come across in the field. Another way to think of it is as a
sort of baseline, which should ensure comparability.
Deliverable No. 1 | Studying smart energy solutions 26
In addition, the individual research partners might have individual research interests that
they want to pursue, which is not covered in the following procedure. It should be
stressed that this would provide obvious added value to the project and that it is encouraged.
With all these reservations in mind, the following has been written with the purpose of
helping to generate a rich, comparable narrative for all cases, which can subsequently be
analysed in different ways by different members of the consortium. The five steps are as
follows:
4.5.1 Context
To add contextual depth from the national study, we should begin by mapping and describing relevant insights into the local context of the studied smart grid solution. This includes:
 Local/regional energy system characteristics (energy mix, status of the grid in the
area, etc.)
 If applicable: a brief description of the broader demonstration project that the
particular solution is a part of.
 Historical actor-constellations in the local energy system. E.g., ownership structures: cooperative, centralized, municipal, commercial, etc.
In most instances, this local insight can be obtained through desktop exercises. If necessary, local research teams can supplement with interviews, etc. as they see fit.
4.5.2 History
We should also have a brief “history” of the solution at hand. What was the original idea
behind it? Who was involved in developing the idea, and what was their rationale? For
how long has the solution it been tested? What has been learned so far – from the perspective of those testing the solution?
Has the solution been researched in relevant ways in the past, and if so – are there available results from such studies that might be relevant to the MATCH project? Questions
concerning the history of the solution are important to gain insights into the visions and
expectations of actors behind the solutions, and to gain a sense of the dynamics involved
as smart grid solutions change over time. In many instances, this exercise can be done
as a desktop exercise, supplemented with interviews of actors involved in the project
start-up if needed.
4.5.3 Map
Once we have an overview of the context and the history of the solution, we can begin
mapping the current state of the smart grid solution, its actor and technology constellations. This includes details on infra-technological relationships, e.g. on how the solution
at hand have been involved with existing energy systems, technologies and actors.
 Who are the actors involved, and what are their goals/rationales?
 How do these actors interpret what it means that such a solution “works”, or that
they are successful?
 What are the technologies involved, including existing energy system infrastructures?
 What small scale/medium sized consumers are involved?
 What is expected from them in the project?
Deliverable No. 1 | Studying smart energy solutions 27
 How are they recruited – what incentives are they given to participate?
 How are the involved elements configured?
On one level, this mapping exercise can be considered purely descriptive. However, once
we begin to understand how users were recruited and on which conditions they were recruited9
, the levels of technology subsidy funding, or other ways that technological solutions might be “shielded” from ordinary technology selection criteria in such trials, we
can also begin to think about the relationship between the “trial conditions” and “real
world conditions”. At this stage, interviews with implicated actors are needed.
4.5.4 Experience
Based on these three steps, we should have a good understanding of the smart grid solutions, and we should be ready to study how the small/medium consumers act and interact with the technologies, incentives, organizations, etc. introduced as part of the smart
grid solution. Given the largely qualitative character of the work, and the likelihood that
cases will differ substantially, it is difficult to standardize this exercise too much. However, some pointers can be given:
 We should seek out small/medium consumers using the solutions with the goal of
identifying their experiences (e.g. “negative” or “positive”) with the technology.
This should both include the users’ own interpretations of their experiences (e.g.
how the solutions have affected their everyday lives, etc.), but should also include
descriptions of how practices are changed (if so).
 We should interview a broad sample of users and intermediaries, reflecting to the
extent that this is possible the diversity of users involved in the smart grid solution trial. Thus, we should avoid the trap of interviewing only “Resource men”
(Strengers 2013), but rather aim to include as many as possible of the actors that
make up everyday-life (or work-life) situations for the users involved.
 We should probe for rich stories concerning technology use and related practices,
patterns of use, how technologies have been integrated in everyday lives (or work
life for SMEs), difficulties, understandings and interpretations of technologies etc.
The methods used will, as said, primarily be qualitative (interviews, observations, focus
groups etc.), but might also, if relevant and possible, include some statistical data of existing data (for instance in order to analyse the energy implications of the studied solutions for the energy consumption patterns).
4.5.5 Product
Finally, we are ready to write up case study reports. To facilitate the cross-country and
cross-case analysis, these should describe the cases, the actors involved, relevant market dynamics and technologies, implications for the practices of the users etc. They
should also aim to provide as clear narratives as possible concerning how the studied solution works, and for whom it works.
Following the discussions in this report, this assessment needs some extra considerations. It is clear that something can work in multiple ways, and that it can work in different ways for different actors. It is also clear that what works for one set of actors, might

9 For instance: Did they invest in technologies, or did they lease/borrow them? Are they volunteers, or are everyone in a geographical location users? Are there other incentives for participating? Etc.
Deliverable No. 1 | Studying smart energy solutions 28
do the opposite for others. This also feeds into discussions about the relationship between the individual cases that we study and the wider energy systems and contexts that
they are part of. The case study reports could be a good place to begin a preliminary
analysis of such matters. This can be done in a two-step way, following the rich case description.

  1. An evaluation of the case solution in hand. What was its core strengths and weaknesses? Why does it appear to work in the way that it does, or why does it not appear to work as intended? This step should include reflections on unintended consequences and wider implications of the introduction of the solution.
  2. A first attempt at briefly exploring the consequences of upscaling the solution at
    hand. This would imply some sort of speculative scenario writing, where researchers contemplate potential consequences and pathways based on the information
    and knowledge available to them.
    In the end, this will provide us with at least nine case study reports, three from each
    country. These will form the basis for the following comparative analytical work and
    should provide a rich and inspiring source to work further on.
    4.6 A brief note on energy system models and scenarios
    In addition to the qualitatively oriented work discussed above, MATCH will produce some
    energy system models and scenarios that might help producing narratives about the effects of certain types of solutions. It is currently somewhat unclear what types of data we
    need to be able to produce relevant model simulations. When and if such data are available, however, we should try to collect the following:
     Data on economics: the costs of installations and operation
     Data on how the solution in question influence the households
    power consumption. In practical terms this would be data indicating
    changes (or non-change) in load profiles for participant households.
     Data on savings per household (e.g. Kilowatt-hours per year per
    household)
    As the case studies start, we should have an open dialogue within the consortium on the
    status of these issues, on what we need and what we can achieve through these and
    similar data collection exercises.
    4.7 What does it mean that a solution “works”
    A key outcome of the MATCH-project should be an increased knowledge about what
    smart energy solutions work under which circumstances. Thus, we should evaluate existing cases, and we should to a certain degree be able to harvest wider and applicable lessons from these evaluations. As the discussions throughout this report have indicated,
    this raises the question: what do we mean, when we say that something works? If we return to the earlier discussed peer-to-peer model of prosumer markets, it is clear that something like this could be said to work well for consumers, who in new ways become empowered and through this take control over the system in new ways. For incumbent actors, however, this would not necessarily constitute a success, because it undermines
    their business model and operation.
    Deliverable No. 1 | Studying smart energy solutions 29
    Thus, a “working solution” can be many things. Towards the end of this report we therefore find it fruitful to present a brief discussion of how to deal with the issue at later
    stages in the project. This section is mainly intended for reflection.
    4.7.1 It works when the project goals are realized
    MATCH is a project where researchers collaborate closely with industry/market actors.
    Several of these partners are owners of demonstration sites experimenting with the kinds
    of solutions that we aim to explore. For this reason, it might be argued that we should
    pay particular attention to what it would mean that a solution works for these actors.
    One way to measure this is simply to look at the goals of the solution case in question,
    and to measure the performance of the trial in relation to this. E.g., some “solutions”
    might be implemented to “unlock” flexibility, or to reduce electricity demand. If data will
    be available, it would be relatively simple to determine if it works or not. If (sufficient)
    time shifting or electricity reduction has been achieved – it works. Thus, this way of identifying working solutions looks at performance output indicators before and after the trial
    started, and links this to the stated goal. The added value from MATCH compared to a
    more standard technical project would be to highlight that output in such instances is a
    result of the way that the socio-technical solution is configured, or the way that practices
    and elements of practices are bundled in the particular instance.
    Through our interviews and studies of implicated actors we can get a sense of why and
    how the particular solution works for the particular actor groups, and through this be
    able to paint a richer picture of why the particular solution works to realize the industry
    actor goals. A concrete way to operationalize this in our studies would be to map the
    links between the expectations of the actors as they ventured into the smart energy system solution, and compare this to their actual experiences.
    As an example, a study from Norway have indicated that when small consumers expect
    to save a lot of money, they have to re-interpret their participation in smart energy system trials, when they learn that they do not. For some small to medium consumers, this
    might lead to alienation from smart energy technologies as such, which leads to practices
    that do not cater for reaching the goals of the project operators. Other customers, however, are very happy to be part of a project where they mainly learn how cheap it is to
    spend electricity. This allows them to raise comfort levels. For such consumers, the solution has arguably “worked” in some way, in the sense that it resulted both in learning
    and the establishment of new practices, but obviously not for the benefit of the grid and
    the system in the way that the project owners would like.
    4.7.2 Broadening the definition of a working solution
    This indicates that it is probably wise to have a broader definition of what it could mean
    that a solution “works”, when we do our analysis. Through our mapping exercises we
    gain insights into the rationales and goals of many actors, and we will most likely also
    gain much knowledge about their experiences. Further, we will learn much about how the
    cases in question relate to their contexts, and the ways that external actors work to influence the solution in question. For instance, are there shielding mechanisms involved,
    such as subsidies, or other schemes meant to influence either the technology choices
    made or the usage patterns of these technologies?
    A key point for us is that we are aware that solutions might have different implications
    for different implicated actor groups. If we take the users as an example, these might be
    a very diverse group. Single men, elderly couples and families with children might have
    Deliverable No. 1 | Studying smart energy solutions 30
    very different ways of relating to energy, managing everyday lives and integrating new
    solutions into existing practices.
    The realization that different actor groups might have different understandings, goals,
    aspirations and expectations does of course complicate things. However, for the MATCH
    consortium, it is arguably the strength that might give our recommendations more thrust
    than it would otherwise have.
    This might also allow us to give advice with differing degrees of strength. The identification of a solution that is working, both in the sense that it fulfils the goals of the experimenters, and is integrated nicely into the everyday lives of various user groups, as well
    as works for other implicated actors, most likely indicate a relatively robust solution, with
    significant transfer value to other sites. Should the solution only work for some actors,
    however (e.g. grid operators and resource men), but leave other user groups (families,
    the elderly, teens, students, etc.) alienated or discouraged, this opens for recommendations on how to improve the performance. Table 2 is a crude idea for how we could begin
    to think about operationalizing this on a case-by-case basis. This rough sketch will have
    to be adopted to the situation for each specific case, and it is not certain that we actually
    end up using it in the end.
    Expectations Experiences
    Micro
    gen
    DSM/DR Storage Micro gen DSM/DR Storage
    Families w/childeren
    Single men
    Single woman
    Elderly
    Small company
    ICT company
    Construction company
    Energy producer
    PV supplier
    Description of solution «shielding mechanisms»:
    With nine case studies, it is likely that the degree of success for different implicated actors will differ across cases, and hopefully some patterns will emerge that we can exploit
    for the development of success criteria later in the MATCH-project.
    Deliverable No. 1 | Studying smart energy solutions 31
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Recommendations for researchers, designers and system planners

438368_match_d5.1_v2-1.pdf

Michael Ornetzeder & Steffen Bettin
Toke Haunstrup Christensen, Freja Friis & Hannah Mareike Marczinkowski
Tomas Moe Skjølsvold, Marianne Ryghaug & William Throndsen

NTERNAL REFERENCE

• Deliverable No.: D 5.1
• Deliverable Name: Recommendations for researchers, designers and system
planners
• Lead Partner: Institute of Technology Assessment (ITA), OeAW
• Work Package No.: 5
• Task No. & Name: -
• Document (File): MATCH_D5.1_v2.docx
• Issue (Save) Date: 2018-10-31

CONTENTS

1 INTRODUCTION… 1
2 RECOMMENDATIONS FROM THE MATCH PROJECT … 2
2.1 How to design a “working” smart energy solution in general… 2
2.2 How to ensure local anchoring, acceptance and support… 3
2.3 How to make price incentives work in practice… 4
2.4 How to balance generation and demand … 5
2.5 How to involve technology users… 6
2.6 How to integrate smart energy solutions into national energy systems …7
REMARKS… 9
REFERENCES… 11

Disclaimer
The content and views expressed in this material are those of the authors and do not necessarily
reflect the views or opinion of the ERA-Net SES initiative. Any reference given does not necessarily
imply the endorsement by ERA-Net SES.
About ERA-Net Smart Energy Systems and MATCH
ERA-Net Smart Energy Systems (ERA-Net SES) – formerly ERA-Net Smart Grids Plus – is a
transnational joint programming platform of 30 national and regional funding partners for
initiating co-creation and promoting energy system innovation. The network of owners and
managers of national and regional public funding programmes along the innovation chain
provides a sustainable and service-oriented joint programming platform to finance projects in
thematic areas such as smart power grids, regional and local energy systems, heating and cooling
networks, digital energy and smart services, etc.
Co-creating with partners who help to understand the needs of relevant stakeholders, we team
up with intermediaries to provide an innovation eco-system supporting consortia for research,
innovation, technical development, piloting and demonstration activities. These co-operations
pave the way towards implementation in real-life environments and market introduction.
In addition, ERA-Net SES provides a knowledge community, involving key demonstration projects
and experts from all over Europe, to facilitate learning between projects and programmes from
local level up to European level.
www.eranet-smartenergysystems.eu
The Markets, actors, technologies: a comparative study of smart grid solutions (MATCH) project ran
from February 2016 to October 2018 and was supported by ERA-Net SES.
https://www.match-project.eu
Improving energy efficiency and replacing fossil fuels with renewable energy are among the most
important measures on the road to a sustainable energy system. This entails new ways of
generating and consuming energy as well as new forms of relationships between energy
producers and consumers. The MATCH project contributes to the shift towards a carbon-neutral
energy system by focussing on the changing roles of small consumers in the future electricity
system (the “smart grids”).
The overall objective of MATCH was to expand our knowledge on how to design and implement
comprehensive smart grid solutions that take into account the complexity of factors influencing
the effectiveness and success of smart grid initiatives targeted at small consumers. The study is
cross-disciplinary and based on detailed studies of current smart grid demonstration projects in
Austria, Denmark and Norway. Through comparative analysis across cases and countries, the
study identified key factors related to technology, market and actor involvement in developing
integrated solutions that “work in practice”. Furthermore, the project applied energy system
analysis and scenarios to discuss the wider energy system implications by upscaling the studied
cases and solutions.
On this basis, the project developed recommendations for decision-makers, engineers and
project developers. This final part of the MATCH project is included in this report.

1 Introduction

The overall objective of MATCH was to expand our understanding of how to design and
implement comprehensive smart energy systems solutions that take into account the complexity
of factors influencing the effectiveness and success of such initiatives targeted at small
consumers.
Based on detailed case studies (three in each country), comparative analysis and an energy
system modelling analysis, key factors related to technology, market and the involvement of
actors (stakeholders) in developing integrated and workable smart energy solutions were
identified. In addition, a number of energy system scenarios were developed in order to further
explore the systemic implications of local solutions. The results from the project may inform
designers, system planners and policy-makers about how to develop better smart energy
solutions for small consumers such as households and small to medium-sized enterprises
(SMEs).
As a result, MATCH aims to contribute to the ongoing energy transition in Europe. Main policy
targets of this envisioned transition are 1) energy saving (reduction in absolute terms), 2) energy
efficiency (reduction in relative terms), and 3) a higher share of renewable energy sources in all
the systems (European Commission 2016). In addition to these energy objectives, the European
Commission addresses industrial policy aims (global leadership in renewable energies) and
societal goals (providing a fair deal for consumers) as equally important objectives. All these
political positions are important points of reference when it comes to recommendations based
on findings from the MATCH project.
Smart energy solutions – as studied in MATCH – usually involve a high degree of complexity:
More (and new) actors and more (and new) technologies are involved in emerging configurations
to create working and integrated solutions that fulfil several functions at the same time. A good
example of this is the building-to-grid configuration in the Rosa Zukunft project. The configuration
aims to support several goals of the politically encouraged clean energy transition at the same
time: Energy saving, energy efficiency, a higher share of renewables (locally and trans-regional by
providing balancing capacities for the electricity grid) and satisfied customers. The studied
solution certainly worked in the specific local context. Moreover, to analyse whether these
context-specific solutions can have positive system effects on a national level, when generalised
and upscaled, a system analysis was carried out in MATCH.
Based on the nine case studies carried out in the project (WP2), we gained knowledge about the
history of the studied projects, the actors involved, the (national, regional) framework conditions,
the aims and objectives, outcomes and lessons learned. In WP3, we compared (and contrasted)
findings from similar types of solutions obtained from different sites to identify key factors (e.g.
similar patterns) related to technology, market and the involvement of actors (stakeholders) in
developing integrated and workable smart energy solutions. WP4 relied on these findings,
selected promising solutions and analysed their implications for the existing national energy
systems in Austria, Denmark and Norway.
An earlier version of the following recommendations was presented to and discussed in detail
with interested audiences in each of the three partner countries. The results of these three
workshops have been incorporated in the formulation of the below recommendations.

2 Recommendations from the MATCH project

Each of the following sections starts with a presentation of the issue under discussion, followed
by a brief analysis based on MATCH’s results, and the resulting recommendation. Most
recommendations deal with the overall question of how to develop and operate locally
successful solutions. On the one hand, this was the main focus of the empirical research in the
project. On the other hand, most of the solutions presented here are still at a relatively early
innovation stage. It can therefore be assumed that further diversification (broadening) and
improvement of existing solutions (deepening) will be seen over the coming years. However,
given the socio-technical nature of the solutions studied, even a more or less straightforward
replication of already tested solutions will heavily rely on tacit knowledge and experience from
previous demonstration projects in order to adapt solutions as effectively as possible to existing
local and regional conditions – in technical, economic, legal and social terms. This was one central
argument for focussing the recommendations on the development of locally well-functioning
solutions.
However, since we are aware that solutions functioning locally may lead to suboptimal results on
a regional or national level, a final recommendation is presented with regard to the systematic
effects of local solutions – based on the energy system analysis applied in WP4.
The recommendations presented below focus on the design of concrete solutions as sociotechnical configurations, the question of their local anchoring, the role of tariff systems and price
incentives, the question of how consumption and demand can be better aligned with each other,
the role of users in the development and the operation of local solutions for small consumers,
and finally the question of possible systemic effects of locally successful solutions.

2.1 How to design a “working” smart energy solution in general

Issue: The anticipated transformation of the energy system demands a wide range of different
solutions that fit local and regional conditions and simultaneously fulfil various functions and
requirements (e.g. better integration of renewable energy sources, higher levels of energy
efficiency, grid parity, security of supply). Based on previous research, we might expect that a few
one-fits-all solutions are not going to be the answer. Hence, socio-technical variation and testing
of a large number of possible solutions is (and will be in the future) key for a successful transition
of the energy system. Solutions studied in the MATCH project represent a good part of the
current state-of-the-art, but certainly not the final stage of development in this area. Additional
and better solutions must and will be developed and implemented over the coming years. Based
on this assumption, we may ask which general recommendations can be derived from the
MATCH analysis of already applied solutions for further development of new and enhanced
solutions in the European context.
Analysis: The MATCH project showed that the studied projects successfully defined, set up,
tested, and in most cases also ran a considerable number of new and quite different smart
energy solutions. Main actors involved did provide sufficient information about the working of
the implemented solutions and were able to name various qualities of “success”. In WP2 and WP3
we aimed to improve our understanding of the different aspects of what was defined as success.
One of our main research claims was that the working of the solutions could only be understood
adequately if they were framed as socio-technical configurations. In doing so, technologies
appear as one element amongst several others combined into a working structure.
Consequently, this specific combination is the basis for their functioning. Technical elements such
as photovoltaic (PV) panels, smart meters or battery systems are closely linked to social elements
such as formal and informal agreements, tailor-made tariff schemes, specific ownership
structures, user preferences and aspirations, or new maintenance routines. Designing such a “working” smart energy solution thus requires a broad focus, a variety of skills, different kinds of
knowledge, and a sense of flexibility and adaptability with regard to pre-existing local conditions
(culture, technology, infrastructure, social capital, etc.). In almost all of our cases, interdisciplinary
teams were responsible for the development of the studied solutions. Moreover, designing is a
process that does not end with the first implementation of a concept, but usually needs an
introduction phase allowing for information, mutual exchange, social learning and adaptation.
Such a design approach may in the end lead to working business models; however, what we did
see in our cases usually went beyond a simple supplier-customer relationship.
Recommendation: Smart energy innovation could benefit from an approach that takes the
comprehensive socio-technical configurations into account from the outset. Such a design
approach would recognise heterogeneous elements as equally important for the working of
solutions, focus on the combination and interaction of crucial elements, and consider and
mobilise existing local conditions in a sensible way. The most important criterion for the
development of such solutions is that the best possible outcome is achieved through joint
alignment of social and technical elements. Critical for the implementation of such a strategy are
interdisciplinary project teams and robust local networks.

2.2 How to ensure local anchoring, acceptance and support

Issue: A thorough transition and decarbonisation of the energy system ideally involves a wide
range of actors and should be grounded upon widespread public acceptance. One promising
road towards this appears to be the combination of comprehensive energy solutions that cover
all sectors and the development of a wide range of integrated solutions (as already described in
section 2.1) with local anchoring. In this section, we focus particularly on how to ensure the local
anchoring of the energy transition. The assumption is that without this local anchoring, it will be
difficult to realise the energy transition on a wider scale. Also, local anchoring can be part of
activating local resources and actors in realising ambitious transition goals. On this basis, we may
ask what general recommendations can be derived from the MATCH analysis of different cases
for the development of locally-anchored solutions in the European context.
Analysis: The MATCH project shows that the success of community-oriented projects is
dependent on three key characteristics. First, ambitious community-led transition strategies
covering a specific locality or region played a strategic role in several cases. These strategies
create a frame and narrative for local initiatives targeted at energy transition. It helps to
coordinate and organise individual initiatives into a coherent move towards a decarbonised, local
economy. By associating single initiatives with the overall strategy, the strategy itself becomes an
organic and evolving vision that helps branding the local area. The strategies often also become
recognised nationally or even internationally, which helps new initiatives secure funding by
referring to the overall strategy and vision. In some of our cases, the energy transition strategies
and visions were also connected with broader societal goals such as revitalising the local
economy through attracting more business and citizens. This seems to provide the energy
transition with further legitimacy within the local community. In this regard, we even found
evidence of local citizens and business people being proud of the local achievements and their
contributions to this. Second, a long history of transition initiatives played a key role in several of
the studied cases. The history of energy conservation and installing local renewable energy
capacity sometimes dated back several decades and represents a long list of initiatives that
together form a successive progression towards decarbonisation and energy autonomy. New
initiatives often build upon previous experiences and local networks of actors developed
throughout the years. The long history of activities often also contributes to a local identity or
narrative of being a national or international frontrunner in terms of the energy transition. Third,
in the studied cases we identified one or more “entities” that coordinate and align the single, local initiatives. This entity can be the previously mentioned shared narrative (strategy) of local energy
transition or the long history of initiatives that creates a local network of actors with mutual trust
and interests. Another type of coordinating entity can be a local key actor (e.g. an energy
provider/grid owner or a public-private partnership) that facilitates communication between
other local actors, provides advice or technical expertise, coordinates proposals for funding, etc.
In addition to these three key elements, long-term funding opportunities (e.g. local/regional
funding programmes for energy transition) can play an important role. In most of the studied
MATCH cases, several – or even all – of the above-mentioned three key characteristics could be
identified.
Recommendation: Smart energy innovation needs to support processes of local anchoring in
order to promote solutions with a high level of local legitimacy and to make local resources and
actors become an active part in the transition. This can be done by promoting and nurturing the
three key characteristics identified in the MATCH study: creating ambitious and community-led
transition strategies covering local areas or regions; creating conditions that support a continued
local engagement (e.g. through long-term funding programmes or by tapping into and build
upon existing and previous energy transition initiatives); and supporting locally-anchored entities
(key actors or shared narratives) that can help coordinate and align individual initiatives.

2.3 How to make price incentives work in practice

Issue: Throughout the years, much trust has been put in financial incentives as a main driver for
behavioural change. In particular, time-of-use (ToU) pricing (or “dynamic pricing”) has attracted
attention as a way to promote demand response (DR) through making consumers time-shift their
consumption from hours with high electricity prices to hours with low prices. This rests upon the
idea of the price-sensitive energy consumer (customer), i.e. the idea of the individual customer as
a “rational agent” who responds to price-signals. However, experience from pilots and
demonstrations shows a more mixed picture as households did not respond to economic
incentives in the expected way. Therefore, there is a need to revise the naive conceptualisation of
the price-sensitive and economic-rational customer and develop a more nuanced and productive
understanding of what role price can play, and under which conditions?
Analysis: The studied cases in MATCH included a variety of ToU pricing schemes, e.g. combining
micro-PV generation with hourly net metering (promoting self-consumption through
synchronisation with PV power generation), dynamic prices reflecting spot market prices or tariffs
based on the customer’s peak power consumption. Several analytical observations can be made
regarding the role of economic incentives (price) in promoting load shifting (demand response) in
households. First, ToU pricing (including capacity-based tariffs) had a positive influence on
households’ active engagement in time-shifting consumption in several of the studied cases. Also,
the size of the price spread between lowest and highest price appears to play a role for
households’ engagement (with lower spreads implying lower interest). However, the specific
impact of price incentives on households’ active demand response engagement depends on a
wide range of other (non-economic) elements in the socio-technical configuration, which the
price schemes are part of. In particular: a) micro-generation appears to help make the local
power production more “visible” to households and thereby promote engagement in active load
shifting; b) dynamic ToU pricing schemes with unpredictable prices are generally refused by
households as they are seen as too difficult to adapt to and build new routines around; c) the
framing of ToU schemes and households’ trust in these are important (e.g. distrust in the energy
company promoting a scheme can disengage participants, while local anchoring of ToU initiatives
is often a productive framing for active engagement); d) physical and material conditions such as
the proximity to neighbours are pivotal, e.g. households in apartment buildings find it difficult to
time-shift consumption to night hours due to problems of noise; f) the socio-economicparameters of the households such as education and income level, job, age, size, etc., also seem
to influence the flexibility of households to time-shift; g) the design of ToU trials in terms of the
strategic participatory approach, value framing and process is significant for households’
persistence and commitment to establish and perform new routines related to demand respond;
h) finally, it is mainly energy-intensive and/or semi-automated energy consumption such as
dishwashing, laundering and electric vehicle (EV) charging that households manage to time-shift.
With regard to the latter, it seems that households generally prefer automation of load shifting
(e.g. by use of home batteries to store PV surplus production for later self-consumption),
although automation only works in cases where the automated time-shifting of consumption
does not affect daily household routines too much.
Recommendation: The overall recommendation is to avoid overestimating the effectiveness of
financial incentives and ToU pricing as the essential means to promote active load shifting
amongst small consumers and households. Financial incentives (and their size) do play a role, but
often more as a “marker” or “signifier” that can attract households’ attention to demand response
schemes and to anchor the idea of time-shifting consumption. The actual effectiveness of ToU
pricing schemes is conditioned by the wider context of the schemes, i.e. the socio-technical
elements that the pricing schemes are embedded in. From the analysis, the following specific
recommendations can be made: 1) Combining ToU pricing with local renewable energy
production (e.g. rooftop PV systems) can help motivate local consumers to time-shift their
consumption because of the visibility and profitability of the intermittent energy production; 2) it
is recommended to avoid too complex ToU pricing schemes, especially those based on dynamic
and unpredictable ToU prices – overall, static ToU pricing schemes should be preferred as these
make it possible for people to adopt new daily routines and temporal rhythms according to the
price scheme; 3) if possible, it is recommended to ensure a long-lasting and local anchoring of the
ToU demand response initiative – noteworthy in this context is awareness of the importance of
establishing people’s trust and confidence in the scheme, e.g. through communication and local
meetings; 4) local material conditions, e.g. households living in apartment buildings often find it
more challenging to time-shift consumption (especially to night hours because of noise), must be
taken into consideration; 5) consideration should be given to whether a proposed ToU pricing
scheme promotes time-shifting actions that are practical and can easily be adapted to the daily
routines and temporal rhythms of the (socio-economic) individual characters of the households.

2.4 How to balance generation and demand

Issue: A main challenge concerning the influx of smart energy technologies in households, such
as e.g. PV systems and storage, is how to effectively use these additions when it comes to grid
balancing. The fundamental expectation of the smart grid is that it introduces ways of alleviating
strain in the grid as well as on the climate by giving end users the tools to reduce and time-shift
electricity use to better accommodate intermittent resources and reduce grid investment costs.
Analysis: The move towards a smarter grid is happening in a context of ever-increasing
electricity use, as for instance e-mobility and heating are switched over to electricity as energy
carrier. This challenge has a double solution. On the one hand, smarter appliances can be
programmed to achieve concerted load profiles that take into account restrictions in the system
on a large scale. In our analysis, this was found to be a successful strategy in the case of
apartment complexes and in professional settings. Here, the benefit was centralised and
professionalised control of medium and large-scale measures (a fleet of EVs, a large PV park, heat
pump, large water storage, etc.), ensuring they were effective and continuously maintained, in
combination with a robust and powerful control and monitoring unit. This type of solution leaves
out the role of end user agency to a large extent, and requires a high level of competence on part
of the building operators who have a long-term commitment to deal with the system.
Conversely, our findings included cases where new technology, tariff schemes, knowledge, and
practices were introduced into households in order to have balancing measures maintained by
end users themselves. This proved feasible in several cases, but requires resources spent on
professional surveillance/control of robust automation are instead diverted to spending time and
resources on social learning. Social learning is necessary when the aim is to enrol end users as
prosumers or flexibility providers, in addition to merely introducing the technological tools
required for empowering households to participate in balancing generation and demand.
Technological tools are of course necessary, and in our cases included things that either
contributed or consumed a lot of electricity, for instance PV systems, EVs, heat pumps, and water
boilers. But in order to influence and change the practices related to the use of these material
objects, and thereby bringing about the actual load shifting behaviour that allocates and allows
making use of end use flexibility, monitoring technologies and price signals are important, too. A
higher degree of success in engaging end users and making them partake in balancing of
generation and demand is thus contingent on a sufficient process of social learning. By sufficient
we mean that it provides impetus for action in the form of price signals and potential for
economic remuneration, but that it also provides practical knowledge of methods and tools that
may be effectively employed to achieve results, such as reaping benefits from price incentives
(e.g. capacity-based tariff). In other words, users must be in a position to act in accordance with
smart grid design.
Notably, when relying on end users for bringing about the flexibility the successful smart grid
relies on, it is possible to also introduce measures alongside user-centred interventions that are
more or less centrally controlled with professional surveillance/control. This was demonstrated
for example in the case of Heat-as-a-Service (GreenCom) and a trial involving intelligent demandside management (DSM) equipment for appliances (Smart Energi Hvaler).
Recommendation: Balancing generation and demand on the scale of the household or
neighbourhood can successfully be accomplished in two ways, either by 1) implementing
automation that is maintained by professional operators, or 2) have users manually implement
balancing measures by installing and programming automation and/or changing behaviour and
practices. Our findings suggest both are feasible, but relying on user agency is less predictable
(more contingent) and necessitates that project owners focus time and resources on social
learning. Social learning involves applying multiple tools and inroads to increase user knowledge
and agency over balancing measures. In sum, social learning should rely on an introduction of
price signals and visualisation tools as well as training in what constitutes effective practice
change, and/or automation tools and how to ideally employ them.

2.5 How to involve technology users

Issue: A key debate in discussions about smart energy technologies and their deployment
revolve around how to engage and motivate users. The same is true for the socio-technical
configurations and solutions explored in the MATCH project. This is not unusual since the
“success” of all smart energy technologies heavily depends on the way they are actually used: e.g.
technologies that aim at producing end user flexibility require practice changes amongst users in
order for them to “work”; a technology meant to enable shared electro mobility does not really
work unless anyone uses it to share electro mobility services. In addition, however, users may
already play a decisive role in earlier phases of development under certain conditions, which has
an influence on the design of the respective configuration.
Analysis: The analysis in the MATCH project supports recent claims in the sustainability
transition literature highlighting that the role of users in smart energy innovation is much more
diverse than “end users” who either accept or reject pre-defined technology scripts (e.g. Schot etal. 2016; Ryghaug et al. 2018). Instead, many of the cases indicated that users can take on a range
of different roles which allow them to engage with the solution in question in different ways.
First, users, in cases studied in the MATCH project, have taken the form of ordinary consumers in
which their engagement with the solution is limited to being a customer of companies involved in
developing a demonstration project. Second, in other instances, users have been engaged as
research partners or citizen scientists. In these cases, recruited technology users try out new
technology and agree to be studied, but they often also contribute actively in developing and
disseminating new knowledge. Sometimes, this is done in explicit technology development
collaboration, sometimes even initiated by prospective users themselves. Third, several of our
cases involved users as prosumers, which entails producing and selling electricity to the grid
operator. An important, not to be underestimated aspect in this case is the fact that these users
take a certain amount of entrepreneurial risk. Fourth, we have identified users that act as energy
citizens. These users act as politically engaged stakeholders in the transition of the energy system
towards greater sustainability, thus taking on a sense of responsibility that transcends
participation as buying or selling something. Fifth, affiliated users are usually employees of the
project owner. They effectively take on the role as early end users and test the solutions under
development in real-world contexts. Sixth, there are user-innovators or user-producers. These
users are drivers of innovation who develop a smart energy solution according to their own
needs, and that are mainly based on their own resources and capacities.
The study of users in MATCH indicates that technology development and use is a much more
complex phenomenon than simple instances of human-technology encounters in which humans
either accept or reject technologies. Rather, we have seen that users participate in transition
activities in very different ways. Since different roles usually appear in combination with each
other, we called the resulting principle “bundles of user roles”. These bundles inform the
technical design, influence the way in which problems are solved, and support the social and
political stabilisation of the solutions.
Recommendation: The success of most smart energy solutions depends on users and their
adoption of technology as well as associated changes in behaviour. Yet, this is not a challenge of
“acceptance” where the clue is to find a “trick” to bring all possible users (addressed as
customers) on board. Instead, it is important to manage the necessary diversity of different user
roles and their associated perspectives, interests and requirements that may have a positive
impact on the development and operation of the solutions. Based on our analysis, it can also be
concluded that a certain degree of diversity makes sense even in early development phases, and
that it is therefore less a question of a chronological sequence than of the particular bundles of
different user roles in parallel. Generally speaking, project developers have to think about users
as a diverse resource, and also a potential source of innovation from which we can pool
important insights.

2.6 How to integrate smart energy solutions into national energy systems

Issue: Even though the studied socio-technical configurations work well for small customers and
can be replicated and rescaled to a certain extent, the dynamic relationships and integration into
the system level can prove difficult. A number of smart energy system solutions were studied and
presented in WP2, but the question remained on how small-scale solutions can fit into the
national energy system in Austria, Norway and Denmark. What works well in one situation cannot
always be expected to work in a similar way in even slightly different situations. Instead, some
solutions might only work on a certain local or national level, but may not work in a different
location or nation. The remaining issue is therefore to discuss options and limits when wanting to
replicate small successes to a larger scale. In this context, the focus cannot stay on the electricity sector only, but should evaluate smart energy system solutions affecting the whole energy
system(s).
Analysis: Whilst the various study cases were successful on a small scale, some of their aspects
were addressed on the national scale to point out opportunities as well as weaknesses. For this,
the approaches in the field of DSM or DR, micro generation and storage were included, while
representing typical technical solutions for the studied countries. Instead of being seen as
independent smart grid solutions, the MATCH demonstration projects were rather put into
context, both in terms of size and sector integration. This was done to evaluate the expansion or
upscaling of the solutions as well as evaluating changes in the electricity sector and their impact
on other sectors, such as the heating or transport sector, with its effects on fuel consumption
and emissions. This way, the smart energy solutions are seen as not just individual projects, but
as part of something bigger, namely as an integrated part of an energy system. In doing so, the
possible implications can be evaluated beyond the local level and under different circumstances.
At the same time, local aspects such as behaviour and social conditions can be included and
tested on a larger scale than individual projects would have done. In relation to 2.2 (Ensure local
anchoring), local anchoring was also kept in mind for the analysis. The coordination and
communication in the smaller local context creates the basis for the results in the larger context.
However, WP4 is rather addressing the technical simulation of upscaling the demonstration
projects that included social aspects to a large extend, but cannot keep up with all the details of
the small-scale versions. Three final energy system analyses (ESAs) were made addressing:
applied micro-production and storage; DSM and DR; and DSM through electric vehicles – thereby
including markets, actors and technologies (see MATCH deliverable D4.1 for further details on the
energy system analyses). Therefore, the energy system analyses present options and possibilities
that require the reader to bridge the gap between real projects and system evaluation, looking at
both the local and the national level at the same time.
Recommendation: Through the ESAs, a basic comprehension of the contextual consequences
should be achieved to understand the full impact of smart energy projects and “solutions”. This
entails further research and modelling of the MATCH study cases, for example their functionality
in other geographical areas or on different scales. Furthermore, the varying results and impacts
must be understood because a certain solution might not be replicable elsewhere under the
same conditions, and therefore causing different results. Depending on the targeted outcome, a
replication or up-scaling can be seen as positive for some but not for others. For example,
a reduction in imported and exported electricity or fuels can have different effects and results in
different countries. Depending on the existing renewable energy sources capacity, the impact can
vary greatly, and our recommendation is therefore to have awareness of the necessity of locally
establishing sufficient renewable electricity, heat and fuels. If demands increase without such
accompanying development, existing capacity will be drained fast and power plants would have
to supply them by using coal or gas. For this, a detailed analysis, taking into account short-term
variations, seasonal changes and future possibilities, is recommended, too. Finally, these
considerations can help choose and integrate the “right” smart energy solutions to design and
balance future energy systems.

3 Concluding remarks

The main focus of the MATCH project was to improve our understanding of how “successful” local
energy solutions are designed and implemented. Success, however, was defined in relative
terms, elaborated through statements and ascriptions mainly by the actors directly involved in
the various projects and solutions. By comparing projects and configurations across the three
participating countries, it was possible to describe a number of critical aspects more precisely
and conduct more thorough analyses.
• We have pointed out that successful implementation of the solutions
depends to a large extent on a well-designed interplay of social and
technical elements. We have furthermore argued that smart energy
solutions should be considered as heterogeneous configurations from the
very beginning.
• We have shown that such solutions must rely on local anchoring activities
and, based on our case studies, have made suggestions as to how this can
be achieved in practice.
• We have discussed the role of tariff systems and price incentives (ToU
pricing) and have concluded that financial incentives often work as a
“marker” or “signifier” that may attract consumers’ attention, but the
actual effectiveness of pricing schemes is determined by the wider context
of the schemes, i.e. the overall socio-technical configuration the pricing
scheme is embedded in.
• We have addressed the issue of balancing consumption and demand, and
pointed out that the success of such approaches essentially depends on
the extent to which social learning is implemented.
• We have studied the role of users in innovation processes and seen that
successful solutions are simultaneously influenced by a variety of user
roles already during early phases of development. Based on this
knowledge, we recommend that it is important to ensure diversity of
different user roles and their associated perspectives, interests and
requirements from early on.
• Finally, on the basis of our energy system modelling, we have suggested
that it is important to examine the various systemic effects of locally
successful solutions for existing energy systems (regional, national) before
replicating or upscaling them.

One topic repeatedly addressed over the course of the project and discussed more intensively in
the three public MATCH workshops carried out in 2018 relates to the upscaling and increased
dissemination of already available (and well-working) smart energy solutions. Given the
ambitious energy policy goals within the European Union, this is a legitimate question. Although
this highly relevant question was outside of the scope of MATCH, a few comments and
observations from the project will be addressed in this final section in brief.
• Although we have been presenting configurations that are already
successful, there is hardly any solution in our sample which could be
distributed on a large scale in its present form. There are three main
reasons for this: First, the success of these solutions depends to a large
extent on a coordinated interplay of elements and well-functioning local anchoring activities. This means, on the other hand, that replication
depends on appropriate adaptation services: in another local or regional
context, different elements of a successful configuration would need to be
arranged differently. Second, from the point of view of the system as a
whole, the widespread dissemination of a solution often does not appear
to make sense, but rather the combination of many different solutions
(see Eikeland and Inderberg 2016). And third, an explicit recommendation
for the accelerated dissemination of solutions would have to include an
external assessment of the direct effects and possible unintended
consequences, something which could not be achieved in the present
project.
• However, we were also able to observe diffusion processes in the context
of this research. Some operate mainly via traditional market mechanisms,
others essentially via locally established social networks. An example of the
first type of distribution is the building-to-grid solution in the city of
Salzburg. Following the example of the Rosa Zukunft project, the local
energy supplier has already implemented similar projects in cooperation
with local housing developers. Another example is the electric vehicle fleet
solution from the VLOTTE project: the experience gained over the years is
already being offered as a consulting service. ProjectZero in the Danish
region of Sønderborg represents an example in which solutions are
predominantly disseminated via social networks. ProjectZero is a publicprivate partnership between several local (energy-related) companies and
the municipality of Sønderborg. The project acts as an intermediary that
promotes and coordinates all relevant actions that support the local
energy transition. The dissemination of solutions is very effective with this
model, but remains limited to the respective region.
• Another way in which the results of local demonstration projects can be
disseminated is by generalising specifically selected experiences. We found
such an example e.g. in the case of the low-voltage grid field test in the
municipality of Köstendorf in the province of Salzburg. The conducted
real-world experiments showed that – at least up to a certain extent of PV
distribution – the existing grid is sufficiently protected against overloading
by phase shifting (phase-shifted current is fed into the low-voltage grid).
Consequently, high investment costs for controllable transformers can be
avoided with this measure in the future. The grid operator translated this
result into an obligatory requirement for all new PV systems in the area.

References

Christensen, T. H. & Friis, F. (2017). Case study report Denmark - Findings from case studies of
ProjectZero, Renewable Energy Island Samsø and Innovation Fur. Danish Building Research
Institute, Aalborg University. Deliverable D2.2.
European Commission. (2016). Clean Energy For All Europeans, COM(2016)860 final, Brussels.
Eikeland, P. O. & Inderberg, T. H. J. (2016). Energy system transformation and long-term interest
constellations in Denmark: can agency beat structure? Energy Research & Social Science 11,
164-173.
Marczinkowski, H. M. & Østergaard, P. A. (2018). Energy system analysis. Department of Planning,
Aalborg University. Deliverable D4.
Ornetzeder, M., Sinozic, T., Gutting, A. & Bettin, S. (2017). Case study report Austria - Findings
from case studies of Model Village Köstendorf, HiT Housing Project and VLOTTE. Institute of
Technology Assessment, Austrian Academy of Sciences. Deliverable D2.1.
Ornetzeder, M., Bettin, S., Gutting, A. Christensen, T. H. & Friis, F., Skjølsvold, T. M., Ryghaug, M. &
Throndsen, W. (2018). Determining factors for integrated smart energy solutions. Institute of
Technology Assessment, Austrian Academy of Sciences. Deliverable D5.1.
Ryghaug, M., Skjølsvold, T. M. & Heidenreich, S. (2018). Creating energy citizenship through
material participation. Social studies of science, 48(2), 283-303.
Schot, J., Kanger, L. & Verbong, G. (2016). The roles of users in shaping transitions to new energy
systems. Nature Energy, 1(5), 16054.
Skjølsvold, T. M., Ryghaug, M., Throndsen, W., Christensen, T. H., Friis, F., Ornetzeder, M., Sinozic,
T. & Strauß, S. (2016). Studying smart energy solutions for small to medium consumers.
Norwegian University of Science and Technology, Danish Building Research Institute, Institute
of Technology Assessment (Austria). Deliverable D1.
Throndsen, W., Skjølsvold, T. M., Koksvik, G. & Ryghaug, M. (2017). Case study report Norway -
Findings from case studies of PV Pilot Trøndelag, Smart Energi Hvaler and Asko Midt-Norge.
Dpt. of Interdisciplinary Studies of Culture, Norwegian University of Science and Technology.
Deliverable D2.3.

PARTNERS

List of organisations participating in the MATCH project.

DANISH BUILDING RESEARCH INSTITUTE (SBI)

Project manager / Contact person
Toke Haunstrup Christensen
Phone: +45 9940 2256
E-mail: thc@sbi.aau.dk

SBi, Aalborg University Copenhagen
A. C. Meyers Vænge 15
2450 Copenhagen SV
Denmark

AALBORG UNIVERSITY

Contact person
Brian Vad Mathiesen
Phone: +45 9940 7218
E-mail: bvm@plan.aau.dk

Department of Development and Planning
A. C. Meyers Vænge 15
2450 Copenhagen SV
Denmark

NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY (NTNU)

Contact person
Marianne Ryghaug
Phone: +47 930 93 210
E-mail: marianne.ryghaug@ntnu.no

Department of Interdisciplinary Studies of Cultures
Høgskoleringen 1
7491 Trondheim
Norway

NCE SMART ENERGY MARKETS

Contact person
Dieter Hirdes
Phone: +47 905 50 268
E-mail: dieter.hirdes@ncesmart.com

c/o Smart Innovation Østfold AS
Håkon Melbergs vej 16
1783 Halden
Norway

SAMSØ ENERGIAKADEMI

Contact person
Michael Kristensen
Phone: +45 8792 1011
E-mail: mk@energiakademiet.dk

Strandengen 1
8305 Samsø
Denmark

PROJECT ZERO A/S

Contact person
Peter Rathje
Phone: +45 4040 8636
E-mail: peter.rathje@projectzero.dk

Alsion 2
6400 Sønderborg
Denmark

ENIIG FORSYNING & SERVICE A/S

Contact person
Gitte Wad Thybo
Phone: +45 4027 8985
E-mail: gwt@energimidt.dk

Tietgensvej 4
8600 Silkeborg
Denmark

INSTITUTE OF TECHNOLOGY ASSESSMENT

Contact person
Michael Ornetzeder
Phone: +43 1 51581 6589
E-mail: ornetz@oeaw.ac.at

Austrian Academy of Sciences
Strohgasse 45/5
1030 Vienna
Austria

Oversigt over EAN-lokationsnr. på Aalborg Universitet

Fællesområdet

Rektor 5798000417076 Fredrik Bajers Vej 5 9220 Aalborg Ø
Universitetsdirektøren 5798000417083 Fredrik Bajers Vej 5 9220 Aalborg Ø
AAU Cph adm 5798000432918 A.C. Meyers Vænge 15 2450 København SV
Campus Esbjerg 5798000420700 Niels Bohrs Vej 8 6700 Esbjerg
Rektorsekretariatet 5798000420571 Fredrik Bajers Vej 5 9220 Aalborg Ø
AAU Innovation 5798000420878 Niels Jernes Vej 10 9220 Aalborg Ø
AAU Kommunikation 5798000433083 Fredrik Bajers Vej 5 9220 Aalborg Ø
Studieservice 5798000417106 Fredrik Bajers Vej 5 9220 Aalborg Ø
Studievalg Nordjylland 5798000420779 Slotsgade 27 9000 Aalborg
Internationalt Bolig Kontor 5798000421349 Studenterhuset, Gl. Torv 10 9000 Aalborg
AAU It Services 5798000432987 Selma Lagerlöfs Vej 300 9220 Aalborg Ø
AAU It Services - Support /Indkøb 5798000433045 Selma Lagerlöfs Vej 300 9220 Aalborg Ø
AAU - Campus Service 5798000417120 Myrdalstræde 268 9220 Aalborg Ø
HR-afdelingen 5798000417144 Fredrik Bajers Vej 7F 9220 Aalborg Ø
Økonomiafdelingen 5798000417151 Fredrik Bajers Vej 7F 9220 Aalborg Ø
AUB 5798000417090 Langagervej 2 9220 Aalborg Ø
Energi fakturaer 5798000421325 Myrdalstræde 268 9220 Aalborg Ø

Det Humanistiske Fakultet

Humanistisk Fakultetssekretariat 5798000420588 Fibigerstræde 5 9220 Aalborg Ø
Humanistisk Fakultetsadministration 5798000420595 Fibigerstræde 5 9220 Aalborg Ø
Institut for Kommunikation 5798000420786 Rendsburggade 14 9000 Aalborg
Institut for Kommunikation - Masteruddanelse 5798000433090 Rendsburggade 14 9000 Aalborg
Institut for Kommunikation - Projektadministrationen 5798000421424 Rendsburggade 14 9000 Aalborg
Ph.d. & MIL institut 11 5798000421431 Nyhavnsgade 14 9000 Aalborg
Institut for Læring og Filosofi 5798000420922 Kroghstræde 3 9220 Aalborg Ø
Institut for Læring og Filosofi, Master i IT-uddannelse (MIT) 5798000433144 Kroghstræde 3 9220 Aalborg Ø
Institut for for Kultur og Globale Studier 5798000420793 Kroghstræde 1 9220 Aalborg Ø

Det Humanistiske Fakultet

Humanistisk Fakultetssekretariat 5798000420588 Fibigerstræde 5 9220 Aalborg Ø
Humanistisk Fakultetsadministration 5798000420595 Fibigerstræde 5 9220 Aalborg Ø
Institut for Kommunikation 5798000420786 Rendsburggade 14 9000 Aalborg
Institut for Kommunikation - Masteruddanelse 5798000433090 Rendsburggade 14 9000 Aalborg
Institut for Kommunikation - Projektadministrationen 5798000421424 Rendsburggade 14 9000 Aalborg
Ph.d. & MIL institut 11 5798000421431 Nyhavnsgade 14 9000 Aalborg
Institut for Læring og Filosofi 5798000420922 Kroghstræde 3 9220 Aalborg Ø
Institut for Læring og Filosofi, Master i IT-uddannelse (MIT) 5798000433144 Kroghstræde 3 9220 Aalborg Ø
Institut for for Kultur og Globale Studier 5798000420793 Kroghstræde 1 9220 Aalborg Ø
Skolen for Musik, Musikterapi, Psykologi, Art, Kommunikation og Teknologi 5798000431843 Rendburggade 14 9000 Aalborg
Studienævn for Musik 5798000421202 Rendburggade 14 9000 Aalborg
Studienævn for Kommunikation og Digitale Medier 5798000420960 Rendburggade 14 9000 Aalborg
Studienævn for Art & Technology 5798000421387 Rendburggade 14 9000 Aalborg
Studienævnet for Psykologi 5798000420984 Kroghstræde 3 9220 Aalborg Ø
Studienævnet for Musikterapi 5798000421004 Musikkens Plads 1 9000 Aalborg
School of Culture and Global Studies 5798000431836 Kroghstræde 1 9220 Aalborg Ø
Studienævn for Dansk 5798000421295 Kroghstræde 1 9220 Aalborg Ø
Studienævnet for International Virksomhedskommunikation 5798000420946 Kroghstræde 3 9220 Aalborg Ø
Studienævnet for Engelsk, Tysk og Kulturforståelse 5798000420939 Kroghstræde 3 9220 Aalborg Ø
Studienævnet for Sprog og Internationale Studier 5798000421271 Kroghstræde 3 9220 Aalborg Ø
Studienævnet for Tværkulturelle Studier 5798000421288 Kroghstræde 3 9220 Aalborg Ø
Skolen for Erkendelses- og Forandringsprocesser 5798000431850 Kroghstræde 3 9220 Aalborg Ø
Studienævn for IT & Læring 5798000433038 A.C Meyers Vænge 15 2450 København SV
Studienævnet for Uddannelse, Læring og Forandring 5798000421011 Kroghstræde 3 9220 Aalborg Ø
Studienævn for Anvendt Filosofi 5798000433021 Kroghstræde 3 9220 Aalborg Ø

Det Ingeniør- og Naturvidenskabelige Fakultet

Det Ingeniør- og Naturvidenskabelige Fakultet 5798000420632 Niels Jernes Vej 10 9220 Aalborg Ø
Forskerskolen (TEKNAT) 5798000420625 Niels Jernes Vej 10 9220 Aalborg Ø
Institut for Fysik og Nanoteknologi 5798000420809 Skjernvej 4A 9220 Aalborg Ø
Institut for Energiteknik 5798000420816 Pontoppidanstræde 101 9220 Aalborg Ø
Institut for Mekanik og Produktion 5798000420755 Fibigerstræde 16 9220 Aalborg Ø
CIP, Center for Industriel Produktion 5798000420762 Fibigerstræde 10 9220 Aalborg Ø
MMT Master’s Programme in Management of Technology 5798000421240 Fibigerstræde 10 9220 Aalborg Ø
Institut for Matematiske Fag 5798000420847 Fredrik Bajers Vej 7G 9220 Aalborg Ø
Institut for Kemi og Biovidenskab - Sektion for Bioteknologi 5798000420854 Fredrik Bajers Vej 7H 9220 Aalborg Ø
Institut for Kemi og Biovidenskab - Sektion for Kemi 5798000420861 Fredrik Bajers Vej 7H 9220 Aalborg Ø
Institut for Kemi og Biovidenskab - Sektion for Miljøteknologi 5798000420885 Fredrik Bajers Vej 7H 9220 Aalborg Ø
Institut for Kemi og Biovidenskab - Sektion for Bæredygtig Bioteknologi 5798000421394 A.C Meyers Vænge 15 2450 København SV
Institut for Kemi og Biovidenskab - Sektion for Kemiteknologi 5798000431829 Ole Rømers Vej 5 6700 Esbjerg
Institut for Byggeri og anlæg 5798000420687 Sofiendalsvej 9-11 9200 Aalborg SV
SBI Statens Byggeforskningsinstitut 5798000019034 A.C Meyers Vænge 15 2450 København SV
School of Engineering and Science (SES) 5798000421158 Fibigerstræde 10 9220 Aalborrg Ø
Diverse
Adgangskursus (TEKNAT) 5798000421189 Strandvejen 12-14 9000 Aalborg

Det Tekniske Fakultet for IT og Design

Det Tekniske Fakultet for IT og Design 5790002046544 Niels Jernes Vej 10 9220 Aalborg Ø
Institut for Arkitektur og Medieteknologi MTC+MTE 5798000421400 A.C Meyers Vænge 15 2450 København SV
Institut for Arkitektur og Medieteknologi AD 5798000420892 Rendsburggade 14 9000 Aalborg
Institut for Arkitektur og Medieteknologi MTA 5798000420694 Rendsburggade 14 9000 Aalborg
Institut for Elektroniske Systemer 5798000420717 Fredrik Bajers Vej 7B 9220 Aalborg Ø
Elektroniske Systemer - CMI 5798000421370 A.C Meyers Vænge 15 2450 København SV
Afdeling for Proceskontrol 5798000420724 Fredrik Bajers Vej 7C 9220 Aalborg Ø
Afdeling for Kommunikationsteknologi 5798000420731 Fredrik Bajers Vej 7A 9220 Aalborg Ø
Institut for Datalogi 5798000420830 Selma Lagerlöfs Vej 300 9220 Aalborg Ø
CISS - Center for Indlejrede Software Systemer 5798000421417 Selma Lagerlöfs Vej 300 9220 Aalborg Ø
Institut for Planlægning - Administration Aalborg 5798000420908 Vestre Havnepromonade 5,1 9000 Aalborg
Institut for Planlægning - Sektion A 5798000420953 Skibbrogade 3,1 9000 Aalborg
Institut for Planlægning - Sektion B 5798000420991 Skibbrogade 3,1 9000 Aalborg
Institut for Planlægning - Sektion C 5798000421257 Vestre Havne promonade 5,1 9000 Aalborg
Institut for Planlægning - Sektion D 5798000432925 Skibbrogade 5,1 9000 Aalborg
Institut for Planlægning - IFM 5798000432949 Skibbrogade 3,1 9000 Aalborg
Institut for Planlægning - København 5798000421448 A.C Meyers Vænge 15 2450 København SV

School of Architecture, design and Planning (SADP) 5798000421196 Vestre Havnepromenade 5,1 9000 Aalborg

Teknoantropologi, Bæredygtigt Design og Integrerede Fødevarestudier (TBI) 5798000421219 A.C. Meyers Vænge 15 2450 København SV
Planlægning, Geografi og Landinspektøruddannelsen (PGL) 5798000421226 Vestre Havnepromenade 5,1 9000 Aalborg
Arkitektur & Design 5798000421141 Rendsburggade 12 9000 Aalborg

School of Information and Communication Technology (SICT) 5798000421165 Selma Lagerlöfs Vej 300 9220 Aalborg Ø

Diverse
Første Studieår for TECH, ENG & SUND Fakulteterne 5798000421172 Strandvejen 12-14 9000 Aalborg

Det Sundhedsvidenskabelige Fakultet

Det Sundhedsvidenskabelige Fakultet 5798000432901 Niels Jernes Vej 10 9220 Aalborg Ø
Institut for Medicin og Sundhedsteknologi 5798000420915 Fredrik Bajers Vej 7 D2 9220 Aalborg Ø
MMDS,Center for Modelbaseret Beslutningsstøtte 5798000421264 Fredrik Bajers Vej 7 E 9220 Aalborg Ø
Klinisk Institut 5798000433007 Forskningens Hus, Sdr. Skovvej 159000 Aalborg
Klinisk Institut København 5798000433106 Frederikskaj 10B 2450 København SV
School of Medicine and Health 5798000421233 Niels Jernes Vej 12, A5 9220 Aalborg Ø