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Energy
Article . 2018 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Modelling the integrated power and transport energy system: The role of power-to-gas and hydrogen in long-term scenarios for Italy

Authors: Colbertaldo, Paolo; Guandalini, Giulio; Campanari, Stefano;

Modelling the integrated power and transport energy system: The role of power-to-gas and hydrogen in long-term scenarios for Italy

Abstract

Abstract This work analyses future energy scenarios at country scale, focusing on the interaction between power and transport sectors, where Power-to-Gas is expected to play a key role. A multi-node model is developed to represent the integrated energy system, including additional electrical load from plug-in electric vehicles, energy storage, and hydrogen production from excess electricity for fuel cell vehicles. Electricity supply-demand balance is solved hourly, while liquid and gaseous fuels for mobility are accounted for cumulatively over the year. The Italian system is investigated, considering different evolution scenarios up to 2030 and 2050. The simulations yield a maximum 57% share of renewable sources in the electricity mix in 2050, while biomass could account for a further 5%. Results show that the use of Power-to-Gas increases the overall share of renewable sources across the sectors. High coverage of hydrogen mobility demand by clean production (about 81%) is achieved in presence of a large installation of renewables and a substantial introduction of fuel cell vehicles. However, greenhouse gas emissions reduction does not attain the ambitious long-term targets. In the best scenario, transport approaches the 60% cut, while power sector achieves only half of the desired 95% variation, thus calling for additional measures.

Country
Italy
Related Organizations
Keywords

Power-to-Gas; Hydrogen; Multi-node modelling; Long-term scenarios; Integration; Power and transport.

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    citations
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    88
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    Top 1%
    influence
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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!
88
Top 1%
Top 10%
Top 1%
Green