**ABBREVIATIONS**  
  
<table>  
<tr>  
<th>

DMP

</th>  
<th>

Data management plan

</th> </tr>  
<tr>  
<td>

DSM

</td>  
<td>

Demand side management

</td> </tr>  
<tr>  
<td>

DWH

</td>  
<td>

Data warehouse

</td> </tr>  
<tr>  
<td>

EIM

</td>  
<td>

Exploitation and Innovation Manager

</td> </tr>  
<tr>  
<td>

EMS

</td>  
<td>

Energy models system

</td> </tr>  
<tr>  
<td>

LCA

</td>  
<td>

Life Cycle Assessment

</td> </tr>  
<tr>  
<td>

RES

</td>  
<td>

Renewable Energy Sources

</td> </tr> </table>

**SCOPE OF THE DOCUMENT**

This document provides the draft version of the Data Management Plan (DMP) for
the REFLEX project according to the Open Research Data Pilot (ORD pilot) under
Horizon 2020. The purpose of the DMP is to support the data management life
cycle of all data that will be collected, processed or generated by the
project.

The document structure and contents are based on the Guidelines on FAIR Data
Management in Horizon 2020 (Version 3.0, 26 July 2016) and on the Guidelines
on Open Access to Scientific Publications and Research Data in Horizon 2020
(Version 2.1, 15 February 2016). The document was generated by using the
Digital Curation Centre's DMP online tool. The following sections outline the
types of collected and generated data, how these data will be exploited and
made accessible for verification and re-use and how data will be curated and
preserved upon closure of the project. Changes are reserved – the DMP will be
continuously updated during the project.

**ADMIN DETAILS**

**Project Name:** REFLEX (Horizon 2020 DMP)

**Grant Agreement No.:** 691685

**Principal Investigator / Researcher:** Prof. Dominik Möst, TU Dresden

**Project Description:**

The future energy system is challenged by the intermittent nature of
renewables and requires therefore several flexibility options. Still, the
interaction between different options, the optimal portfolio and the impact on
environment and society are unknown. It is thus the core objective of REFLEX
to analyse and evaluate the development towards a low-carbon energy system
with focus on flexibility options in the EU to support the implementation of
the SET-Plan. The analysis are based on a modelling environment that considers
the full extent to which current and future energy technologies and policies
interfere and how they affect the environment and society while considering
technological learning of low-carbon and flexibility technologies.

For this purpose, REFLEX brings together the comprehensive expertise and
competences of known European experts from six different countries. Each
partner focusses on one of the research fields techno-economic learning,
fundamental energy system modelling or environmental and social life cycle
assessment. To link and apply these three research fields in a compatible way,
an innovative and comprehensive energy models system (EMS) is developed, which
couples the models and tools from all REFLEX partners. It is based on a common
database and scenario framework. The results from the EMS will help to
understand the complex links, interactions and interdependencies between
different actors, available technologies and impact of the different
interventions on all levels from the individual to the whole energy system. In
this way, the knowledge base for decision-making concerning feasibility,
effectiveness, costs and impacts of different policy measures will be
strengthened, which will assist policy makers and support the implementation
of the SETPlan. Stakeholders will be actively involved during the entire
project from definition of scenarios to dissemination and exploitation of
results via workshops, publications and a project website.

**Nature:** Research and innovation actions based on energy systems modelling

**Research Questions:**

  1. How do current and future energy technologies and policies interfere? 

  

  2. What will be an optimal combination of flexibility options to cope with the future flexibility needs? 

  

  3. How do these technologies and policy measures affect the environment, economy and society? 

  

  

**Purpose:**

Support for the implementation of the SET-Plan:

  * Analysing the impacts of technological development and innovation on the energy system and its dynamics 

  

  * Comparative assessment of the impacts and the sustainability performance of all relevant energy technologies 

  

  * Assessing the related impacts on the environment, society and economy - Analysing of technology policy measures in the framework of the SET-Plan 

  

  * Understanding the complex links/interactions/interdependencies between the different actors, the available technologies and the impact of the different interventions on all levels from the individual to the whole energy system 

  

  * Providing model based decision support tools for the different actors in the energy system in order to facilitate handling the complex system 

  

**Funder:** European Commission (Horizon 2020)

**1 DATA SUMMARY**

The core objective of the REFLEX project is to analyse and evaluate the
development towards a low-carbon energy system in the EU up to the year 2050.
The focus is laying on flexibility options to support a better system
integration of Renewable Energy Sources (RES). The analysis and the assessment
of REFLEX are based on a modelling environment that considers the full extent
to which current and future energy technologies and policies interfere and how
they affect the environment and society.

###  1.1 PURPOSE OF DATA COLLECTION AND GENERATION

The purpose for data collection and their preparation within REFLEX is to
provide the needed input data for the applied mathematical energy system
models. The model pool of the REFLEX partners contains bottom-up simulation
tools and fundamental system optimisation models on national and therewith
also on European level as well as approaches for Life Cycle Assessment (LCA).
Typically, one model cannot cover all aspects of an energy system or the
implications of specific policies. Each of these different models focuses on a
specific sector or aspect (heat, electricity, mobility, environmental/ social
impacts etc.) of the energy system.

For analysing and answering the given research questions (see Admin Details
above), the different models and approaches will be coupled to a so called
integrated Energy Model System (EMS). The analysis by applying the EMS allows
to perform an in-depth and at the same time holistic assessment of the system
transformation and shall contribute to the scientific underpinning of the SET-
Plan. The final result data of the EMS helps to understand and investigate the
complex links, interactions and interdependencies between the different actors
and technologies within the energy system as well as their impact on society
and environment.

The results of a model based analysis depend not only on the chosen
methodology, but also on the quality of the data used. For a consistent
analysis within the EMS in REFLEX, a common database with harmonised datasets
is needed. It will be implemented in a form of a Data Warehouse  1  (DWH). The
DWH of the REFLEX project will contain four groups of data (see Table 1 for an
overview), which will be explained in more detail in the following sections.

**Table 1: Groups of data within the DWH of the REFLEX project**  
  
<table>  
<tr>  
<th>

**Data group**

</th>  
<th>

**Description/Contains**

</th> </tr>  
<tr>  
<td>

**Existing model input data**

</td>  
<td>

  * Data collected, generated or purchased from commercial providers by a project partner before the start of the REFLEX project 

  

  * Input data collected, generated or purchased from commercial providers by a project partner in the context of projects on behalf of other clients run in parallel to the REFLEX project 

  

</td> </tr>  
<tr>  
<td>

**Collected and generated new model input data**

</td>  
<td>

  * Data collected from public available sources or purchased from commercial providers by a project partner in the context of REFLEX 

  

  * Data collected through surveys conducted by a project partner in the context of REFLEX 

  

  * Data generated based on existing, new collected or new purchased data by a project partner in the context of REFLEX 

  

</td> </tr>  
<tr>  
<td>

**Generated intermediate model output data**

</td>  
<td>

\- Intermediate results of the model applications for data exchange between
the models or for further assessments within the project; due to this the 2
nd  and the 3  rd  data group could overlap

</td> </tr>  
<tr>  
<td>

**Generated final result data of the EMS**

</td>  
<td>

\- Final results of REFLEX generated by model applications, e.g. CO2-emission,
energy demand, technology impact evaluation etc.

</td> </tr>  
<tr>  
<td>

</td>  
<td>

</td> </tr> </table>

###  1.2 EXISTING MODEL INPUT DATA

Energy system models need many different input data for modelling the real
world. Each of the applied models in REFLEX has already been used as stand-
alone applications. Therefore each model has its own database with already
existing data. By this input data are rather model specific and an un-
conditional application over several models is limited. They originate from
own previous work and own assumptions of the project partners as well as from
literature and have been developed over many years. Some of this existing data
will be re-used in the REFLEX project, if they are up to date or if no better
data are available.

Not all of the existing data are relevant for the DWH. Only data that

  * are needed for more than one model within the EMS and therefore have to be harmonized and/or 

  

  * are needed to validate the results presented in scientific publications (so called 

  

"underlying data") will be included in the DWH.

The harmonization of input data is necessary to ensure a consistent analysis
within the EMS. For the same information the same dataset (values) have to be
used in all models. The consortium decides which of the existing datasets will
be used. They will be included in the DWH and will be provided to all models
before initializing the EMS run. Table 2 gives an overview of the existing and
re-used input datasets/parameters.

#  Table 2: Existing essential (re-used) datasets in REFLEX  
  
<table>  
<tr>  
<th>

Sub- Period

Spatial

Dataset (category) categories (from Source

Reference (Quantity) until)

</th>  
<th>

Values per scenario

(Quantity)

</th> </tr>  
<tr>  
<td>

Buildings average life time of heating systems  1  
</td>  
<td>

0

</td>  
<td>

2015

2050

</td>  
<td>

EU28

</td>  
<td>

EU regulation, other projects, own assumptions

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Buildings compliance rate index  1  
</td>  
<td>

0

</td>  
<td>

2015

2050

</td>  
<td>

EU28

</td>  
<td>

EU regulation, other projects, own assumptions

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Buildings energy efficiency increase due to mandatory commissioning  1  
</td>  
<td>

0

</td>  
<td>

2015

2050

</td>  
<td>

EU28

</td>  
<td>

EU regulation, other projects, own assumptions

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Buildings energy efficiency investement cost (with national financial
incentives)  1  
</td>  
<td>

0

</td>  
<td>

2015

2050

</td>  
<td>

EU28

</td>  
<td>

EU regulation, other projects, own assumptions

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Buildings minimum energetic standards  1  
</td>  
<td>

0

</td>  
<td>

2015

2050

</td>  
<td>

EU28

</td>  
<td>

EU regulation, other projects, own assumptions

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Buildings thermal renovation  1  
</td>  
<td>

0

</td>  
<td>

2015

2050

</td>  
<td>

EU28

</td>  
<td>

EU regulation, other projects, own assumptions

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Power plants availability

</td>  
<td>

6

</td>  
<td>

2010

2050

</td>  
<td>

EU28

</td>  
<td>

DIW 2013

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Power plants efficiency

</td>  
<td>

11

</td>  
<td>

2010

2050

</td>  
<td>

EU28

</td>  
<td>

DIW 2013

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Power plants emisson factor

</td>  
<td>

3

</td>  
<td>

2010

2050

</td>  
<td>

EU28

</td>  
<td>

UBA 2014

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Power plants interest rate

</td>  
<td>

0

</td>  
<td>

2010

2050

</td>  
<td>

EU28

</td>  
<td>

IEA et al. 2010

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Power lifetime of investment

</td>  
<td>

6

</td>  
<td>

2010

2050

</td>  
<td>

EU28

</td>  
<td>

IEA et al. 2010

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Power plants load change cost (depreciation)

</td>  
<td>

0

</td>  
<td>

2010

2050

</td>  
<td>

EU28

</td>  
<td>

DIW 2013, Traber & Kemfert 2011, own assumptions

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Power plants load change cost (fuel factor)

</td>  
<td>

0

</td>  
<td>

2010

2050

</td>  
<td>

EU28

</td>  
<td>

DIW 2013, Traber & Kemfert 2011

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Power plants operations management cost fixed

</td>  
<td>

18

</td>  
<td>

2010

2050

</td>  
<td>

EU28

</td>  
<td>

DIW 2013, VGB PowerTech 2011a

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Power plants operations management cost variable

</td>  
<td>

11

</td>  
<td>

2010

2050

</td>  
<td>

EU28

</td>  
<td>

DIW 2013, Traber & Kemfert 2011

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Power plants specific investment  2  
</td>  
<td>

11

</td>  
<td>

2010

2050

</td>  
<td>

EU28

</td>  
<td>

DIW 2013

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Power plants start-up cost (depreciation)

</td>  
<td>

18

</td>  
<td>

2010

2050

</td>  
<td>

EU28

</td>  
<td>

Traber & Kemfert 2011

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Power plants start-up cost (fuel factor)

</td>  
<td>

18

</td>  
<td>

2010

2050

</td>  
<td>

EU28

</td>  
<td>

Traber & Kemfert 2011

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Tertiary & residential sector tax energy carrier  1  
</td>  
<td>

3

</td>  
<td>

2015

2050

</td>  
<td>

EU28

</td>  
<td>

EU regulation, other projects, own assumptions

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Vehicles CO  2  standard  1  
</td>  
<td>

2

</td>  
<td>

2015

2050

</td>  
<td>

EU28

</td>  
<td>

EU regulation, own assumptions

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Vehicles fuel consumption factors

</td>  
<td>

4

</td>  
<td>

2015

2050

</td>  
<td>

EU28

</td>  
<td>

GHG-TransPoRD project, ASSIST project

</td>  
<td>

</td> </tr>  
<tr>  
<td>

1 2

Scenario-dependent Only for technologies for which no experience curve data
are available or will be generated

</td>  
<td>

</td> </tr> </table>

###  1.3 COLLECTED AND GENERATED NEW MODEL INPUT DATA

Some of the needed input data for the models will be updated or newly defined
according to the research questions and the focus of the analysis within the
REFLEX project. Therefor publicly and commercially available data will be
used. Unavailable data will be generated by empirical surveys and/or
appropriate assumptions. These data will be included in the DWH and in that
way provided as harmonized datasets for all models within the EMS. This group
includes data for:

  * Scenario framework 

  

  * Demand side management  Experience curves 

  

####  1.3.1 DATA FOR SCENARIO FRAMEWORK

These data describe the overall framework for the model-based analysis and
include the main macro-economic and societal drivers as well as techno-
economic parameters and regulations/conditions of the political environment.
Therefor the defined scenario storylines for REFLEX will be translated into
quantitative model input parameters until the year 2050, which is the defined
horizon for the analysis. They may be defined on a European level, or be
further distinguished on a national, sectoral or technological level. The
macro-economic trends and the societal drivers are likely to be based upon
official projections provided by the European Commission (e.g. the upcoming
Reference Scenario). All political assumptions will be elaborated considering
current and past policy implementations and will be discussed with the
European Commission and stakeholders. Table 3 gives an overview of the data
for the scenario framework.

#  Table 3: Data for scenario framework  
  
<table>  
<tr>  
<th>

Dataset (category)

</th>  
<th>

Subcategories

(Quantity)

</th>  
<th>

Period (from until)

</th>  
<th>

Spatial Reference

</th>  
<th>

Source

</th>  
<th>

Values per scenario

(Quantity)

</th> </tr>  
<tr>  
<td>

GDP-Gross domestic product

</td>  
<td>

0

</td>  
<td>

2000 2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Capros et al. 2016 (Assumptions for NO+CH based on other Horizon 2020
projects)

</td>  
<td>

330

</td> </tr>  
<tr>  
<td>

POP-population

</td>  
<td>

0

</td>  
<td>

2000 2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Capros et al. 2016(Assumptions for NO+CH based on other Horizon 2020 projects)

</td>  
<td>

330

</td> </tr>  
<tr>  
<td>

Price electricity (initial average cost of gross electricity generation)

</td>  
<td>

0

</td>  
<td>

2000 2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

(Assumptions for NO+CH based on other

Horizon 2020 projects)

</td>  
<td>

330

</td> </tr>  
<tr>  
<td>

Price fossil energy carrier

</td>  
<td>

3

</td>  
<td>

2015

2050

</td>  
<td>

EU28

</td>  
<td>

Capros et al. 2016

</td>  
<td>

24

</td> </tr>  
<tr>  
<td>

ETS-CO  2  -Price  1  
</td>  
<td>

0

</td>  
<td>

2015

2050

</td>  
<td>

EU28

</td>  
<td>

Capros et al. 2016, own assumptions

</td>  
<td>

8

</td> </tr>  
<tr>  
<td>

NON-ETS-CO  2  -Price  1  
</td>  
<td>

0

</td>  
<td>

2015

2050

</td>  
<td>

EU28

</td>  
<td>

own assumptions

</td>  
<td>

8

</td> </tr>  
<tr>  
<td>

Vehicles CO  2  standard  1  
</td>  
<td>

2

</td>  
<td>

2015

2050

</td>  
<td>

EU28

</td>  
<td>

Capros et al. 2016

</td>  
<td>

16

</td> </tr>  
<tr>  
<td>

1

Scenario-dependent

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td> </tr> </table>

####  1.3.2 DATA FOR DEMAND SIDE MANAGEMENT

Relevant data for investigating system flexibility by Demand Side Management
(DSM) are rarely available from public and commercial sources. In particular
the available database for the tertiary sector with regard to DSM is
incomplete. Therefore, an empirical survey on DSM in the tertiary sector will
be conducted with the aim to improve the model input data and to fill data
gaps. Based on the analysis of the collected specific empirical data, existing
datasets will be extended as well as new datasets generated. The design of the
survey will be established by the REFLEX partners and it will be conducted for
10 European countries by an international market research institute. The DSM
data for further countries will be deduced from the survey results. Relevant
model input parameters for modelling DSM options which should be deduced from
the empirically ascertained data are given in Table 4\.

#  Table 4: Parameters for modelling DSM options  
  
<table>  
<tr>  
<th>

Dataset (category)

</th>  
<th>

Subcategories

(Quantity)

</th>  
<th>

Period (from until)

</th>  
<th>

Spatial Reference

</th>  
<th>

Source

</th>  
<th>

Values per scenario

(Quantity)

</th> </tr>  
<tr>  
<td>

DSM potential (share of flexible load per energy usage process)

</td>  
<td>

50

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0

(EU28+NO

+CH)

</td>  
<td>

empirical survey, public and commercial sources

</td>  
<td>

28000

</td> </tr>  
<tr>  
<td>

DSM cost (activation cost per energy usage process)

</td>  
<td>

50

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0

(EU28+NO

+CH)

</td>  
<td>

empirical survey, public and commercial sources

</td>  
<td>

28000

</td> </tr>  
<tr>  
<td>

DSM time of interfere (maximum load reduction time)

</td>  
<td>

50

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0

(EU28+NO

+CH)

</td>  
<td>

empirical survey, public and commercial sources

</td>  
<td>

28000

</td> </tr>  
<tr>  
<td>

DSM number of interventions (frequency of DSM measures)

</td>  
<td>

50

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0

(EU28+NO

+CH)

</td>  
<td>

empirical survey, public and commercial sources

</td>  
<td>

28000

</td> </tr>  
<tr>  
<td>

DSM shifting time (allowed points of time or time periods/frames for DSM)

</td>  
<td>

50

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0

(EU28+NO

+CH)

</td>  
<td>

empirical survey, public and commercial sources

</td>  
<td>

28000

</td> </tr>  
<tr>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td> </tr> </table>

####  1.3.3 DATA FOR EXPERIENCE CURVES

To enable endogenous modelling of technological developments and due to this
to production cost reductions, experience curves for the most relevant
technologies for each sector will be developed and implemented in the sectoral
models. Special attention will be given to determination of uncertainty ranges
of progress ratios (i.e. the slopes of the experience curves), as these can
have a major impact on modelling results, especially for long-term modelling
until 2050. In addition, especially for technologies that depend strongly on
either the available geographical potential (e. g. wind onshore, offshore,
biomass) or on raw material prices, decomposition of the experience curve
using a multi-level experience will be performed. This allows determination of
the most important factors behind cost development, such as variations in
steel or oil prices, as well as scale effects. The needed empirical data for
defining the experience will be surveyed by means of interviewing experts,
specific survey methods and by analysing detailed statistics (e. g.
construction, production and consumer price indices as well as installed
capacities and cost developments in the electricity, heat and mobility
sector). Table 5 gives an overview of the technologies for which

##  experience curves will be developed.

**Table 5: Defined technologies per sector for which experience curves will be
developed**  
  
<table>  
<tr>  
<th>

Category

</th>  
<th>

Technology

</th> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

CCS (Membrane, Oxyfuel, Pre, Post)

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

CCGT (Gas)

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

EFCC (Gas)

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

Biomass: digestion

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

Biomass: gassification

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

Biomass: combustion

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

Concentrated Solar Power (CSP)

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

Geothermal: (dry, flash, binary)

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

Photovoltaics: modules (mono/poly, CdTe)

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

Photovoltaics: system level aspects

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

Photovoltaics: CdTe

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

Wind: onshore

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

Wind: offshore

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

CHP

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

micro-CHP

</td>  
<td>

</td> </tr> </table>

**Table 5 (continuation)**  
  
<table>  
<tr>  
<th>

Category

</th>  
<th>

Technology

</th> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

Pulverized Coal-fired

</td> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

(P)FBC (Coal)

</td> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

IGCC (Coal)

</td> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

Gas Turbine (inlc. Mini- and Micro-Gas-Turbine)

</td> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

Nuclear (generation 2, 3 and 4)

</td> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

Steam turbine (coal/gas)

</td> </tr>  
<tr>  
<td>

Electricity Generation

</td>  
<td>

Photovoltaics: CIGS

</td> </tr>  
<tr>  
<td>

Electricity Storage

</td>  
<td>

Battery: Lithium-(Ion, Polymer, Air)

</td> </tr>  
<tr>  
<td>

Electricity Storage

</td>  
<td>

Battery: Redox-Flow

</td> </tr>  
<tr>  
<td>

Electricity Storage

</td>  
<td>

CAES

</td> </tr>  
<tr>  
<td>

Electricity Storage

</td>  
<td>

Flywheel

</td> </tr>  
<tr>  
<td>

Electricity Storage

</td>  
<td>

Pumped Storage Plants

</td> </tr>  
<tr>  
<td>

Electricity Storage

</td>  
<td>

Battery: Molten Salt

</td> </tr>  
<tr>  
<td>

Electricity Storage

</td>  
<td>

Battery: NiMH

</td> </tr>  
<tr>  
<td>

Electricity Storage

</td>  
<td>

Battery: NiCd

</td> </tr>  
<tr>  
<td>

Heating/cooling

</td>  
<td>

Electric boiler (P2H)

</td> </tr>  
<tr>  
<td>

Heating/cooling

</td>  
<td>

Heat Pump (air/air)

</td> </tr>  
<tr>  
<td>

Heating/cooling

</td>  
<td>

Heat Pump (air/water/ground)

</td> </tr>  
<tr>  
<td>

Heating/cooling

</td>  
<td>

Solar Thermal (process heat or large scale)

</td> </tr>  
<tr>  
<td>

Heating/cooling

</td>  
<td>

Air conditioning

</td> </tr>  
<tr>  
<td>

Heating/cooling

</td>  
<td>

Thermal Energy Storage: (sensible, underground, Phase Change, TCS, Ice)

</td> </tr>  
<tr>  
<td>

Heating/cooling

</td>  
<td>

Night-Storage Heaters

</td> </tr>  
<tr>  
<td>

Heating/cooling

</td>  
<td>

Electric boilers for district heating

</td> </tr>  
<tr>  
<td>

Heating/cooling

</td>  
<td>

Gas- or oil boiler

</td> </tr>  
<tr>  
<td>

Heating/cooling

</td>  
<td>

Fridges, freezers: cooling

</td> </tr>  
<tr>  
<td>

Industry

</td>  
<td>

Air separation: membrane

</td> </tr>  
<tr>  
<td>

Industry

</td>  
<td>

Air separation: conventional

</td> </tr>  
<tr>  
<td>

Industry

</td>  
<td>

Aluminium electrolysis

</td> </tr>  
<tr>  
<td>

Industry

</td>  
<td>

Chemical & mechanical pulp production

</td> </tr>  
<tr>  
<td>

Industry

</td>  
<td>

Electric arc and induction furnaces: copper, cink, etc.

</td> </tr>  
<tr>  
<td>

Industry

</td>  
<td>

Electrolysis (wet chemical): copper, cink, etc.

</td> </tr>  
<tr>  
<td>

Industry

</td>  
<td>

Electrolysis, chemical industry

</td> </tr>  
<tr>  
<td>

Industry

</td>  
<td>

ODC, chlorine electrolysis

</td> </tr>  
<tr>  
<td>

Industry

</td>  
<td>

Fischer-Tropsch-synthesis

</td> </tr>  
<tr>  
<td>

Industry

</td>  
<td>

Industrial CCS

</td> </tr>  
<tr>  
<td>

Industry

</td>  
<td>

Industrial heat

</td> </tr>  
<tr>  
<td>

Industry

</td>  
<td>

Cement and raw mill: cement production

</td> </tr>  
<tr>  
<td>

Industry

</td>  
<td>

Electric booster: container glas production

</td> </tr>  
<tr>  
<td>

Industry

</td>  
<td>

HIsarna process: steel production

</td> </tr>  
<tr>  
<td>

Industry

</td>  
<td>

ULCOWIN process: steel production

</td> </tr>  
<tr>  
<td>

Mobility

</td>  
<td>

Battery electric vehicles

</td> </tr>  
<tr>  
<td>

Mobility

</td>  
<td>

Fuel Cell vehicles

</td> </tr>  
<tr>  
<td>

Mobility

</td>  
<td>

Plug-in hybrid electric car

</td> </tr>  
<tr>  
<td>

Mobility

</td>  
<td>

Flexifuel car

</td> </tr>  
<tr>  
<td>

Mobility

</td>  
<td>

Overhead wiring trucks

</td> </tr>  
<tr>  
<td>

Mobility

</td>  
<td>

Biofuels (jet, vehicle, marine)

</td> </tr>  
<tr>  
<td>

Mobility

</td>  
<td>

CNG vehicles

</td> </tr>  
<tr>  
<td>

Mobility

</td>  
<td>

LPG car

</td> </tr>  
<tr>  
<td>

Mobility

</td>  
<td>

Diesel vehicles

</td> </tr>  
<tr>  
<td>

Mobility

</td>  
<td>

Gasoline car

</td> </tr>  
<tr>  
<td>

Power to X

</td>  
<td>

Power to Hydrogen

</td> </tr>  
<tr>  
<td>

Power to X

</td>  
<td>

**Power to Methane**

</td> </tr>  
<tr>  
<td>

Power to X

</td>  
<td>

Power to Methanol

</td> </tr>  
<tr>  
<td>

Power to X

</td>  
<td>

**Hydrogen synthesis, ammonia**

</td> </tr>  
<tr>  
<td>

Electricity end-use

</td>  
<td>

Lighting: LED

</td> </tr>  
<tr>  
<td>

Electricity end-use

</td>  
<td>

**Elevators/escalators**

</td> </tr>  
<tr>  
<td>

Electricity end-use

</td>  
<td>

Data centers

</td> </tr>  
<tr>  
<td>

Electricity end-use

</td>  
<td>

**Building Energy Management/Automation systems**

</td> </tr>  
<tr>  
<td>

Electricity end-use

</td>  
<td>

Ventilation

</td> </tr>  
<tr>  
<td>

Electricity end-use

</td>  
<td>

**Dishwashers, dryers, washing machines**

</td> </tr>  
<tr>  
<td>

Other

</td>  
<td>

Power Grids (HVDC point-to-point, also meshed systems)

</td> </tr>  
<tr>  
<td>

</td>  
<td>

</td> </tr> </table>

In order to estimate the potential of alternative fuel technologies, both
regarding Europe (e. g. MID in Germany or UKTS in UK) and regarding Asia and
North America, mobility patterns and related market potentials will be derived
from available mobility surveys. The analysis will be focused on major common
driving patterns. The reason for the analysis of main global passenger car
markets is to identify the global market penetration of electric vehicles,
which will influence the demand for Li-ion batteries substantially in order to
assess the future prices of electric vehicle batteries and fuel cells based on
the learning curve theory. In this sense, the global automotive market
(especially including Northern America and Asia) will be taken into account
for investigating the uptake of alternative car technology in Europe.

Emission degression data will also be considered in REFLEX. However, the
content, nature and scope of these data are still under discussion and will be
determined during the project.

###  1.4 GENERATED INTERMEDIATE MODEL OUTPUT DATA

By coupling the different approaches of the RFELEX partners, the systems
boundaries of each stand-alone model will be partly disbanded and most
exogenous parameters of each model will become endogenous variables of the
EMS. This will be done by using the relevant output data of one model as input
data of another model.

To achieve a stable final state of the EMS within each REFLEX scenario
storyline, several iterations with all models are performed. The generated
results during these iterations are needed for the data exchange between the
different models. Therefore these data will be included in the DWH and will be
provided to each model by using a data interface. Table 6 shows the relevant
datasets for the data exchange within the EMS.

#  Table 6: Datasets as intermediate results for data exchange between models
within the EMS  
  
<table>  
<tr>  
<th>

Dataset (category)

</th>  
<th>

Subcategories

(Quantity)

</th>  
<th>

Period (from until)

</th>  
<th>

Spatial Reference

</th>  
<th>

Source

</th>  
<th>

Values per scenario/iteration (Quantity)

</th> </tr>  
<tr>  
<td>

Price electricity

(hourly, wholesale and retail prices incl. taxes)

</td>  
<td>

0

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

12,264,000

</td> </tr>  
<tr>  
<td>

Demand electricity (hourly)

</td>  
<td>

50

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

12,264,000 - 245,280,000

</td> </tr>  
<tr>  
<td>

Demand electricity for mobility (yearly)

</td>  
<td>

7

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

1,050

</td> </tr>  
<tr>  
<td>

Demand district heating (yearly)

</td>  
<td>

3

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

450

</td> </tr>  
<tr>  
<td>

Power plants installed capacity and operating (yearly and hourly)

</td>  
<td>

22

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

5,280 - 67,200

</td> </tr>  
<tr>  
<td>

Power plants emissions (yearly)

</td>  
<td>

132

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

15,840

</td> </tr>  
<tr>  
<td>

Power plants demand energy (yearly)

</td>  
<td>

22

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

2,640

</td> </tr>  
<tr>  
<td>

Mobility demand energy (yearly)

</td>  
<td>

56

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

6,720

</td> </tr>  
<tr>  
<td>

Mobility emissions (yearly)

</td>  
<td>

56

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

6,720

</td> </tr>  
<tr>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td> </tr> </table>

###  1.5 GENERATED FINAL RESULT DATA OF THE EMS

After achieving a stable state based on several iterations with all models
within the EMS within each REFLEX scenario storyline, the result data of the
different models will be collected and combined within the DWH to the final
result data of the EMS. These data will be analysed to derive the key findings
and are the basis for answering the research questions of the REFLEX project
(see ADMIN DETAILS). Table 7 gives an overview on the major result data of the
EMS.

#  Table 7: Major result data of the EMS  
  
<table>  
<tr>  
<th>

Dataset (category)

</th>  
<th>

Subcategories

(Quantity)

</th>  
<th>

Period (from until)

</th>  
<th>

Spatial Reference

</th>  
<th>

Source

</th>  
<th>

Values per scenario

(Quantity)

</th> </tr>  
<tr>  
<td>

Price electricity average yearly

(wholesale and retail prices incl. taxes)

</td>  
<td>

0

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

120-240

</td> </tr>  
<tr>  
<td>

Demand electricity (yearly)

</td>  
<td>

50

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

6000

</td> </tr>  
<tr>  
<td>

Demand district heating (yearly)

</td>  
<td>

3

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

450

</td> </tr>  
<tr>  
<td>

Power plants installed capacity (yearly)

</td>  
<td>

22

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

2640

</td> </tr>  
<tr>  
<td>

Power plants operation (yearly)

</td>  
<td>

22

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

2640

</td> </tr>  
<tr>  
<td>

Power plants emissions (yearly)

</td>  
<td>

132

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

15,840

</td> </tr>  
<tr>  
<td>

Net transfer capacities between countries installed (yearly)

</td>  
<td>

143

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

572

</td> </tr>  
<tr>  
<td>

Net transfer capacities between countries operation (yearly)

</td>  
<td>

143

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

572

</td> </tr>  
<tr>  
<td>

Mobility demand energy (yearly)

</td>  
<td>

56

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

6,720

</td> </tr>  
<tr>  
<td>

Mobility emissions (yearly)

</td>  
<td>

56

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

6,720

</td> </tr>  
<tr>  
<td>

Life cycle environmental and resource impacts

</td>  
<td>

19

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

2280

</td> </tr>  
<tr>  
<td>

Life cycle human health (damage / toxicity)

</td>  
<td>

2

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

240

</td> </tr>  
<tr>  
<td>

Life cycle societal impacts (risk level)

</td>  
<td>

5

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

600

</td> </tr>  
<tr>  
<td>

Costs external

</td>  
<td>

1

</td>  
<td>

2015

2050

</td>  
<td>

NUTS 0 (EU28+NO+CH)

</td>  
<td>

Applied energy system models

</td>  
<td>

120

</td> </tr>  
<tr>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td> </tr> </table>

###  1.6 DATA UTILITY

REFLEX collects and generates a certain amount of research data. On one hand,
these data are necessary to meet the objectives of the project. On the other
hand most of the collected and generated data will be useful for further
research and even for the energy industry.

####  1.6.1 DATA FOR SCENARIO FRAMEWORK

The collected and prepared data for the scenario framework are tailored to the
aim and scope as well as the specific research questions of the REFLEX project
and the applied models to answering them. They are thus primarily useful as
underlying data to ensure the transparency of the generated results and the
comparability of the project outcomes to other studies with similar analysing
scope. However, the data will be used for updating the existing databases of
the different models and will be used for further model based research of the
project partners outside of REFLEX.

####  1.6.2 DATA FOR DEMAND SIDE MANAGEMENT

The empirical survey on DSM aims to provide the needed model input data for
the REFLEX project. With the collected specific empirical data the database
for investigating system flexibility by DSM will be improved in general,
because relevant data – especially for the tertiary sector – are rarely
available from public and commercial sources. Thus, existing datasets will be
extended as well as new datasets generated. Furthermore, the survey data will
allow the identification of promising energy applications and DSM potentials
in the selected sector in different European countries. These data have a high
potential for re-use after the end of the REFLEX project within further
research projects. They are useful for other researchers and for stakeholders
from industry and policy making.

####  1.6.3 DATA FOR EXPERIENCE CURVES

Endogenizing technological learning through experience curves allows for an
enhanced assessment of the evaluation of impacts from policy measures or
alternative incentive schemes on realizable future cost reduction. In
addition, in view of current rapid and necessary changes in energy systems
(driven partially by policies and partially by markets) and the ensuing need
for flexibility, the endogenous modelling of the cost development of existing
and new energy-related technologies in bottom-up models will become even more
important.

However, the data and experience curves required to do so are not readily
available. A comprehensive review of many energy supply (and some energy
demand) technologies have been published by Junginger et al. (2010), but these
require updating. Since then, recent studies have been published for some
individual technologies (e. g. Bolinger and Wiser 2012; Candelise et al. 2013
or Chen et al. 2012). However, an up-to-date overview is not available.
Especially with regard to technologies needed for increasing the flexibility
in energy systems (such as storage technologies or DSM-devices) little or no
experience curves have been published. Thus, to advance the energy models
included in REFLEX beyond the state-of-the-art by implementing these
experience curves, data collection will be required to devise or update
experience curves for existing technologies and to estimate experience curves
for new technologies.

Furthermore, it will require smart and innovative incorporation and
interlinkage of these experience curves in various sectoral energy models to
comprehensively assess the effects of technological learning and the demand
for increased flexibility in energy systems. The outcome – a state-of-the-art
and up-to-date overview of experience curves and underlying database – could
benefit other energy models outside the project, i.e. developed in the EU as
well as worldwide) to meet the challenges of modelling our changing energy
systems for the coming decades.

####  1.6.4 GENERATED INTERMEDIATE MODEL OUTPUT DATA

These data are only intermediate results of the EMS and will transfer between
the models during the iteration process of the EMS. A relevant benefit of
these data for further applications outside the framework of REFLEX is not
expected.

####  1.6.5 GENERATED FINAL RESULT DATA OF THE EMS

The overall objective of REFLEX is to support the SET-Plan by strengthening
the knowledge base for transition paths towards a low carbon energy system
based on a cross-sectoral analysis for the entire energy system of the
European Union. Due to the complexity of this system, it is obvious that the
implementation of the SET-Plan requires in-depth knowledge on the
interrelationship between the different energy sectors (electricity, heat and
mobility), energy technologies but also on the interdependencies between
energy and non-energy industries, environment (beyond greenhouse gas
emissions) and society.

The result data of the EMS within REFLEX helps to understand and investigate
the complex links, interactions and interdependencies between the different
actors and technologies within the energy system as well as their impact on
society and environment. Based on the EMS result data, recommendations for
effective strategies for a transition of the European energy system to a low-
carbon system will be derived. Policy makers at EU level as well as at
regional level can use these findings when developing policy measures.
Furthermore, the data of the REFLEX project can be used as a reference or
starting point for further research work on the future design of the energy
system of the European Union.

###  1.7 DATA PROTECTION AND EXPLOITATION STRATEGY

In order to ensure efficient implementation of dissemination and exploitation
activities amongst the participants, a Consortium Agreement (CA) was signed by
all partners. The CA is among other things dealing with the exact details on
the participants’ background data, the rights to, the protection of and the
exploitation of data/results generated solely and/or jointly during the
project. Moreover the CA sets up specific rules on how to deal with
dissemination activities and to ensure open access to all peer-reviewed
scientific publications. The model used is the DESCA template, version 1.0
(www.desca-2020.eu).

The following basic rules apply:

  * All participants define their individual background data required for their successful participation in the project (own model input data and commercial model input data purchased before the start of the project). The rights to this background remain with the respective owner but royalty-free access to other participants is granted if not restricted by third parties and if it is required to enable other participants to carry out their research and development activities in the context of the project. 

  

  * During the project: Background data that is acquired by individual partners during the project, e. g. in the context of projects on behalf of other clients run in parallel, will be treated as pre-existing background data. 

  

  * The property rights to data collected and data/results generated during the project belong to those involved in its collection and generation. When more than one consortium member is involved in the creation of results it will be jointly owned by the respective consortium member. 

  

Dissemination and exploitation of data and results will be executed in
accordance with EU laws and with respect to specific laws in the participating
countries. Before any dissemination activity will take place, respective legal
aspects will be examined and clarified. This is particularly the case for data
from the DSM-survey and data purchased from commercial providers. The
possibility for protection of generated results within the project
(consortium) will be also examined before publication. All participants have
departments specifically devoted to managing intellectual property. These
departments will manage the relevant protection processes.

Within REFLEX the dissemination and exploitation of data will be coordinated
by the Exploitation and Innovation Manager (EIM) regarding knowledge
management and innovation activities. The EIM is responsible for:

  * maintaining a registry of background data, 

  

  * maintaining a registry of data gathered and generated in the work packages during the project, 

  

  * assessing the opportunities for exploitation, for example by following political events in the energy sector or searches of other scientific databases for similar developments and 

  

  * proposing specific exploitation measures, e. g. policy briefs and events. 

  

In REFLEX periodic analysis of transfer opportunities to adjust the
exploitation strategies takes place. All consortium partners contribute to the
exploitation plan of the project throughout its life span. Thereby, the EIM is
in close contact and regularly informed about the exploitation plans of the
partners to use synergies and to ensure the best and suitable use and
exploitation of results. Furthermore, the EIM will regularly advise the
consortium and individual partners about possible strategies.

The exploitation strategy is outlined below:

  * First it will be decided whether to disseminate a dataset and in what way. 

  

  * Participants inform the EIM and other consortium members if they wish to publish or disseminate any datasets, whether in a direct way or indirectly. 

  

  * Before any dissemination activity may take place the participants must examine the possibility of protecting generated results. 

  

  * Upon (affirmative) dissemination decision the dataset will be made available (regarding different dissemination types see section 2.2) 

  

**2 FAIR DATA**

All collected and generated data will be implemented in the DWH in a
standardized way. The DWH includes several databases which are depending on
the structure and contents of the different datasets. For managing the
databases the database-management-tool “Mesap” will be used, which provides
also several data preparing and identifier mapping functions. Mesap is
developed and commercially provided by the Seven2one GmbH.

A selection of existing data as well as data collected and generated during
the project will be made available to interested research groups and
interested parties from policy and industry. The following section outlines
how the data will be exploited and made accessible for verification and re-use
and how data will be curated and preserved upon closure of the project.

###  2.1 MAKING DATA FINDABLE

For making data findable, a data catalogue will be prepared, which will be
implemented in the REFLEX project website ( _www.reflex-project.eu_ ). The
catalogue gives an overview of all provided datasets and affords the metadata
of them. The scope and design of the metadata will be oriented on the metadata
structure of the “Open Power System Data” platform ( _www.data.open-power-
system-data.org/_ ) see Table 8.

#  Table 8: Scope and contents of the metadata for a provided dataset  
  
<table>  
<tr>  
<th>

**Category**

</th>  
<th>

**Content**

</th> </tr>  
<tr>  
<td>

**Name**

</td>  
<td>

Name of dataset - a concise one (short but informative)

</td> </tr>  
<tr>  
<td>

**ID**

</td>  
<td>

Dataset identifier

</td> </tr>  
<tr>  
<td>

**Description/Notes**

</td>  
<td>

Short description of scope/contents of the dataset. Also specific remarks (e.
g. restrictions, data gaps etc.)

</td> </tr>  
<tr>  
<td>

**Keywords**

</td>  
<td>

List of used keywords for the dataset

</td> </tr>  
<tr>  
<td>

**Version**

</td>  
<td>

Dataset version given as number and/or date. Also the information if it is the
latest available version

</td> </tr>  
<tr>  
<td>

**Last changes**

</td>  
<td>

Short description of changes to previous dataset version

</td> </tr>  
<tr>  
<td>

**Timescale**

</td>  
<td>

If the dataset is a time series:

  * Values for which years e. g.: - 2010-2050 (yearly) 

    * 2010-2030 (5-year-steps) 

  

    * 2010, 2012, 2017, 2022 

  

  

  * Values structure in the course of year if applicable e. g.: - seasonal 

    * hourly 

  

    * quarter-hourly 

  

  

  * Structure of type days if used 

  

</td> </tr>  
<tr>  
<td>

**Spatial reference**

</td>  
<td>

Spacial reference of values with scope and level of
differentiation/aggregation e. g.: - EU 28 (NUTS 0)

\- EU 28 + X (NUTS 3) - Poland, Germany,…

</td> </tr>  
<tr>  
<td>

**Sectoral reference**

</td>  
<td>

Sectoral reference of values, if applicable e. g.: - Households, Industy,
Traffic…

  * Road Traffic, Rail Traffic, Aviation... 

  

  * C24_C25 , D, E (Codes from Eurostat) 

  

</td> </tr>  
<tr>  
<td>

**Sources**

</td>  
<td>

Used sources to prepare/provide the dataset, if possible with links to the
primary data/original input data

</td> </tr>  
<tr>  
<td>

**Attribution**

</td>  
<td>

Recommended text for attribution

</td> </tr>  
<tr>  
<td>

**Contact**

</td>  
<td>

Contact information for questions/remarks

</td> </tr>  
<tr>  
<td>

**Access**

</td>  
<td>

Terms of data access/usage (licence, free of charge, XX € protective charge
etc.)

</td> </tr>  
<tr>  
<td>

**Field documentation**

</td>  
<td>

List of used fields within the dataset with following subcategories:

  * field name: e. g. capacity_installed 

  

  * type (format): e. g. number (float) 

  

  * unit: e. g. MW 

  

  * description: e. g. installed electrical capacity at the end of year 

  

</td> </tr>  
<tr>  
<td>

</td>  
<td>

</td> </tr> </table>

Each dataset can be unambiguously identified via the combination of dataset
name and the version label. Both will be included in the unique dataset ID.
With regard to the publication and transparency of results of the project work
(e. g. in journals), the preparation of tailored dataset packages for the
publications is considered. A package contains together with a short content
description of the package a compilation of:

  * the metadata of the published results 

  

  * the metadata of the relevant datasets required to verify the results, as long as these can be made available. 

  

It will be discussed within the REFLEX consortium, if for these dataset
packages digital object identifiers (DOI) will be used, which could be easily
included in publications as a reference.

###  2.2 MAKING DATA OPENLY ACCESSIBLE

Within REFLEX three different possibilities for data dissemination will be
considered, as described in Table 9.

Both, the collected input data as well as generated data, will be made
available, mostly as open access according to the guidelines of the EU. The
specification of data which will be made openly available is still under
discussion. It will be decided within the project consortium case by case and
after that updated in this section of the DMP.

#  Table 9: Possibilities of data dissemination considered in REFLEX  
  
<table>  
<tr>  
<th>

**Dissemination**

</th>  
<th>

**Description**

</th> </tr>  
<tr>  
<td>

**Open Access Publication**

</td>  
<td>

Owners will be granting royalty-free access of a meaningful selection of
generated results to other participants and to the public, possibly restricted
by appropriate embargo periods and/or respecting restrictions from editors of
scientific journals and organizers of conferences.

</td> </tr>  
<tr>  
<td>

**Commercial Exploitation**

</td>  
<td>

Data suitable for commercial exploitation (e. g. for a commercial re-use by
consulting companies) will be managed by the project partner ESA  2  which was
funded after completion of the EU funded innovation project ESA2 explicitly
with the purpose to exploit research results (including research data) related
to (coupled) energy systems modelling.

</td> </tr>  
<tr>  
<td>

**Indirect**

</td>  
<td>

Parts of the generated data will be disseminated only indirectly as part of
intermediate or final results of models and/or as qualitative outcome based on
post-analysis of results.

</td> </tr>  
<tr>  
<td>

</td>  
<td>

</td> </tr> </table>

The access to all provided data will be offered via the project website (
_www.reflexproject.eu/_ ). The planned formats are:

  * csv 

  

  * xlsx 

  

  * sql 

  

In the case of an _Open Access Publication_ , the dataset can be easily
downloaded. The download links for different formats are given within the
metadata in the category “Access”.

In case of _Commercial Exploitation_ of a dataset, a registration procedure
for all those interested in such datasets will be implemented. This includes
the opportunity, to differ the conditions for access depending on type of the
inquirer or planned re-usage (e. g. dataset is free of charge for public
scientific institutions for scientific work, but with a charge in case of
commercial re-use by a company). After registration of the request of a
dataset, a timelimited download link will be provided via e-mail to the
registered contact together with the terms of usage and as the case may be
with the invoice. The requisition will be implemented in the metadata, which
are available free of charge in any case, in the category “Access”.

###  2.3 MAKING DATA INTEROPERABLE

To increase the interoperability of provided data, commonly used vocabularies
for the metadata contents as well as for the identifiers and the contents of
the identifiers within the datasets will be applied. These include
standardized name conventions and codes used in official statistics (e. g. for
countries, regions etc.). Furthermore, specific energy system topics related
name conventions will be orientated on the “Open Power System Data” platform (
_www.data.open-power-system-data.org/_ ). An additional mapping procedure or
the provision of mapping tools for data users is not envisaged.

###  2.4 INCREASE DATA RE-USE

The datasets will be made available to third parties as soon as they are
generated, prepared and reviewed for publication/commercial exploitation and
when the conditions of dissemination are decided and possible protections of
dataset are clarified within the consortium. However, additional restrictions
by setting appropriate embargo periods and/or respecting restrictions from
editors of scientific journals and organizers of conferences are also
possible. A generally valid statement regarding the embargo periods is not
possible at the moment. It can differ from case to case.

The use of Creative-Commons-Licences (CC) for provided data will be discussed
within the consortium. Table 10 gives an overview of conceivable licences for
the different types of dissemination. Which licence is used will be decided
dataset by dataset and after that updated in this section of the DMP.

#  Table 10: Conceivable licences for the different types of dissemination  
  
<table>  
<tr>  
<th>

**Dissemination**

</th>  
<th>

**Data group Licences**

</th> </tr>  
<tr>  
<td>

**Open Access Publication**

</td>  
<td>

Existing model input data

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Collected and generated new model input data

</td> </tr>  
<tr>  
<td>

Generated final result data of the EMS

</td>  
<td>

</td> </tr>  
<tr>  
<td>

**Commercial Exploitation**

</td>  
<td>

Existing model input data

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Collected and generated new model input data

</td> </tr>  
<tr>  
<td>

Generated final result data of the EMS

</td>  
<td>

</td> </tr>  
<tr>  
<td>

**Indirect**

</td>  
<td>

</td>  
<td>

</td> </tr>  
<tr>  
<td>

</td>  
<td>

</td>  
<td>

</td> </tr> </table>

Regarding the data quality assurance the processes given in Table 11 are
implemented in the project work.

#  Table 11: Processes of data quality assurance  
  
<table>  
<tr>  
<th>

**Data group**

</th>  
<th>

**Processes**

</th> </tr>  
<tr>  
<td>

**Existing model input data**

</td>  
<td>

  * Harmonization of model input data to ensure a consistent analysis within the EMS and regarding the defined scenario storylines. For the same information have to be used the same dataset (values) in all models. (Consortium decision) 

  

  * Harmonized data will be provided to all models before initializing the EMS run 

  

</td> </tr>  
<tr>  
<td>

**Collected and generated new model input data**

</td>  
<td>

  * Minimum two internal reviews of the generated new model input data 

  

  * Additionally Peer-Reviews in case of publication in Journals 

  

  * Harmonization of model input data to ensure a consistent analysis within the EMS and regarding the defined scenario storylines. For the same information have to be used the same dataset (values) in all models. (Consortium decision) 

  

  * Harmonized data will be provided to all models before initializing the EMS run 

  

</td> </tr>  
<tr>  
<td>

**Generated intermediate model output data**

</td>  
<td>

\- Check of plausibility of intermediate output data of a model during EMS
runs by the responsible modeller before implementation of the data in the DHW
for data transfer to another model

</td> </tr>  
<tr>  
<td>

**Generated final result data of the EMS**

</td>  
<td>

  * Minimum two internal reviews of the generated final result data 

  

  * Additionally Peer-Reviews in case of publication in Journals 

  

</td> </tr>  
<tr>  
<td>

</td>  
<td>

</td> </tr> </table>

The consortium will continue to provide the data via the REFLEX project
website for a limited period of time after the end of the REFLEX project. The
project website will be maintained during this period. After this period, an
appropriate reference/link to the final data repository will be integrated in
the REFLEX project website, which is no longer being maintained after that.

The final repository for these data has not been chosen yet. The choice of
repository will depend on:

  * location of repository 

  

  * research domain 

  

  * costs 

  

  * open access options 

  

  * prospect of long-term preservation. 

  

The following approaches for long term data provision (or a combination of
them) are conceivable:

  1. The data remain in the DWH of the project partner ESA². The data provision is transferred to the website of the ESA² Company ( _www.esa2.eu_ ). 

  

  2. Another repository could be ZENODO _https://zenodo.org/_ . This is online, free of charge storage created through the European Commission’s OpenAIREplus project and is hosted at CERN, Switzerland. It encourages open access deposition of any data format, but also allows deposits of content under restricted or embargoed access. Contents deposited under restricted access are protected against unauthorized access at all levels. Access to metadata and data files is provided over standard protocols such as HTTP and OAI-PMH. Data files are kept in multiple replicas in a distributed file system, which is backed up to tape every night. Data files are replicated in the online system of ZENODO. 

  

  

Data files have versions attached to them, whilst records are not versioned.
Derivatives of data files are generated, but the original content is never
modified. Records can be retracted from public view; however, the data files
and records are preserved. The uploaded data is archived as a Submission
Information Package in ZENODO. Files stored in ZENODO will have MD5 checksum
of the file content, and it will be checked against their checksum to assure
that a file content remains correct. Items in the ZENODO will be retained for
the lifetime of the repository which is also the lifetime of the host
laboratory CERN which currently has an experimental programme defined for the
next 20 years. Each dataset can be referenced at least by a unique persistent
identifier (DOI), in addition to other forms of identifications provided by
ZENODO.

  3. A third option is provided by the Technische Universität Dresden, which is currently setting up an institutional, inter-disciplinary repository with long-term archive in the project OpARA. It will provide open access long-term storage of data, including metadata and will go into production in 2017. 

  

  

Other institutional and thematic repositories will be considered and evaluated
in the next months. The procedure will be discussed and decided at the end of
the project lifespan. In any case the data will be available for third parties
after the end of the project. The length of time for which the data will
remain re-usable is not restricted.

  3. **ALLOCATION OF RESOURCES**

  

  

The EIM is responsible for data management within the REFLEX project (see
section 1.7). The estimated costs for making REFLEX data FAIR are 50.000 Euro.

The costs include:

  * the clarification of data protection and licences, 

  

  * the final preparation of data by each project partner for publishing (without effort/costs for data collection/purchasing/generation etc.), 

  

  * the processes for assurance of data quality, 

  

  * the development and implementation of the data catalogue in the project website, 

  

  * the implementation of the registration procedure for access to commercially exploited datasets, 

  

  * the data hosting and backup for security, 

  

  * the data updating and maintenance of the data and of the data provision 

  

during the project lifespan. These costs are covered by the project funds,
mainly by the budgeted personnel costs.

The costs for long term preservation after the end of the project are
difficult to estimate at the moment. They depend mainly on the level of
convenience of data providing (with/without comprehensive search routines
and/or additional consulting) but also on the scope and size of the collected
and generated datasets. The permanent costs of preserving datasets on the
ZENODO repository will be free of charge as long as the single dataset storage
is no greater than the maximum 2GB of data. The permanent costs of preserving
datasets on the OpARA repository are planned to be free of charge for TUD
members. But the final decision on costs has not been taken.

The costs for long term preservation shall be covered by the collected charges
from the commercial exploitation of datasets during the project lifespan and
after.

  4. **DATA SECURITY**

  

  

Most of the data handled in the REFLEX project are not sensitive regarding the
laws governing data protection and data security. An exception represents the
data from the DSM-survey. A provision/publication of these data is only
possible in an anonymous form.

The DWH as well as the data provision via websites will be implemented on
servers with regular backup and data recovery procedures.

  5. **ETHICAL ASPECTS**

  

  

The data collection, data storage, data usage, data generation and data
dissemination in this project do not affect to ethical issues.

  6. **OTHER**

  

  

No other national/funder/sectorial/departmental procedures for data management
will be used.