Investment Decision Model for new technologies

»InvE₂St«

© Fraunhofer ISE

Model design of InvE2St – Investment Decision Model.

Central research topics

  • Analysis of the purchase intention of private investors and corporate enterprises
  • Analysis and simulation of the market development of technologies (e.g. renewable energies, electric vehicles or Power2Gas plants)
  • Impact assessment of the policy framework on the market development

 


Background of model application

In the field of energy system analysis, a number of models are providing answers to the question of how the energy system could look like in the future if the German government's CO2-emission reduction targets are met. It implies that the target, e.g. the CO2-reduction, is an input condition for the model. In contrast, the InvE2St model aims at exploratively simulating (based on the current technology stock), how energy system relevant technologies penetrate the market.

The model shows whether the target corridors of individual technologies, which result from the modelling of future energy systems, can be achieved under the given framework conditions or deviate from these corridors. The respective framework conditions can be varied in order to draw conclusions about their influence on technology diffusion and to examine which framework conditions have to be modified in which manner in order to reach a certain target.

The modelling is based on the most important factors and their weighting in relation to each other, which influence an investment decision. Each technology is initially divided into two groups of actors: On the one hand, there are private actors who make a personal investment decision, such as an investment in a solar-powered battery system or in a private electric vehicle. For this purpose, methods from the social sciences and psychology are used to determine the factors influencing a purchase intention. The other group are corporate actors who make investments as part of their business plan in order to generate profits. Therefore, methods from the social sciences are applied to describe the investment decision processes and to depict them in a decision model.

With the knowledge about decision-influencing factors and their possible future development it can be simulated, how the technology penetrates the market under the assumed framework developments and whether adjustments of the framework conditions are necessary to reach a given goal.

Characteristics of the model

The following characteristics describe the model InvE₂St:

  • Conception and evaluation of explorative development paths for energy system relevant technologies on the basis of investment decisions up to the year 2050
  • Type of energy system model: bottom-up simulation of investment decisions
  • Technologies: PV battery systems, mobility (private sector), Power2Gas, tenant electricity
  • Sectors: electricity, heat, transport
  • Investor groups: Private decision-makers, corporate decision-makers (small municipal utilities, large and very large municipal utilities, regional electricity suppliers, cooperatives, project planners)
  • Spatial level: Germany
  • Temporal disaggregation: annual until 2050
  • Programming language: Python, modular design, open source

Clients

  • Industry
  • Energy service providers
  • Political decision makers
  • Single stakeholders

References

Projects:

  • Renewable Energy Scenarios  (E2S) Modelling Tool: In-house research project Fraunhofer ISE, 2011-2014
  • »Open source Energiesystemmodellierung« Influence of socio-cultural factors on transformation paths of the German energy system (Sozio-E2S), funded by the Federal Ministry of Economics and Energy (BMWi)  2017-2019 

Publications:

  • Jülch, Verena; Senkpiel, Charlotte; Hartmann, Niklas; Schlegl, Thomas (2018): Meta Study on Future Cross-Sectoral Decarbonization Target Systems in comparison to current Status of Technologies. Discussion Paper. Fraunhofer Institute for for Solar Energy Systems ISE. Available online at https://www.ise.fraunhofer.de/content/dam/ise/en/documents/publications/studies/Meta_Study_Crossectoral_Decarbonization_Target_Systems.pdf.
  • Schrage, Alexander; Wassermann, Sandra; Berneiser, Jessica; Gölz, Sebastian (2018): Stuttgarter Beiträge zur Risiko- und Nachhaltigkeitsforschung. Sozialwissenschaftliche Determinanten von Investitionsentscheidungen in erneuerbare Energietechnologien. ZIRUS, Universität Stuttgart; DIALOGIK; Fraunhofer Institut für Solare Energiesysteme ISE (36).
  • Senkpiel, Charlotte; Wassermann, Sandra; Berneiser, Jessica; Hofmaier, Christian (2018): Concept on modelling the adoption of energy-related technologies on the basis of investment decisions of. Editor: Markus Hackenfort, Vicente Carabias-Hütter, Cathérine Hartmann, Marcel Janser, Natalie Schwarz und Peter Stücheli-Herlach (Behave 2018, 5th-7th september 2018, Zürich, Switzerland - Book of abstracts). Available online at https://www.zhaw.ch/storage/hochschule/ueber-uns/veranstaltungen/behave-2018-proceedings.pdf, zuletzt geprüft am 01.10.2018.
  • Senkpiel, Charlotte (2014): Der Weg zu einer Erneuerbaren Stromversorgung in Deutschland - ein Investorenbasierter Ansatz. In Energiewirtschaftliche Tagesfragen (64 No.5), pp. 49–52.
  • Taumann, Michael., Senkpiel, Charlotte., Kost, Christoph., Schlegl, Thomas.,: Long-term development of regional distribution and ownership of renewable energy projects in German electricity sector, IARES Conference 2013, Düsseldorf, International association for energy economics, August 2013, presentation.