Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Applied Energyarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Applied Energy
Article . 2019 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
versions View all 1 versions
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

Modeling framework for planning and operation of multi-modal energy systems in the case of Germany

Authors: Andre Hoffrichter; Simon Paulus; Lothar Wyrwoll; M. Küppers; Daniel Beulertz; Hans Jörg Heger; Matthias Huber; +8 Authors

Modeling framework for planning and operation of multi-modal energy systems in the case of Germany

Abstract

Abstract In order to reach the goals of the United Nations Framework Convention on Climate Change, a stepwise reduction of energy related greenhouse gas emissions as well as an increase in the share of renewable energies is necessary. For a successful realization of these changes in energy supply, an integrated view of multiple energy sectors is necessary. The coupling of different energy sectors is seen as an option to achieve the climate goals in a cost-effective way. In this paper, a methodical approach for multi-modal energy system planning and technology impact evaluation is presented. A key feature of the model is a coupled consideration of the sectors electricity, heat, fuel and mobility. The modeling framework enables system planners to optimally plan future investments in a detailed transition pathway of the energy system of a country, considering politically defined climate goals. Based on these calculations, in-depth analyses of energy markets as well as electrical transmission and distribution grids can be performed using the presented optimization models. Energy demands, conversion and storage technologies in households, the Commerce, Trade and Services (CTS) area and the industry are modeled employing a bottom-up modeling approach. The results for the optimal planning of the German energy system until 2050 show that the combination of an increased share of renewable energies and the direct electrification of heat and mobility sectors together with the use of synthetic fuels are the main drivers to achieve the climate goals in a cost-efficient way.

Related Organizations
  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    51
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
Powered by OpenAIRE graph
Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
51
Top 1%
Top 10%
Top 1%
bronze