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dc.contributor.author
Gabrielli, Paolo
dc.contributor.author
Gazzani, Matteo
dc.contributor.author
Martelli, Emanuele
dc.contributor.author
Mazzotti, Marco
dc.date.accessioned
2018-05-29T07:32:36Z
dc.date.available
2018-04-09T04:12:57Z
dc.date.available
2018-04-12T14:45:08Z
dc.date.available
2018-05-04T11:48:02Z
dc.date.available
2018-05-29T07:32:36Z
dc.date.issued
2018-06
dc.identifier.other
10.1016/j.apenergy.2017.07.142
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/256201
dc.identifier.doi
10.3929/ethz-b-000256201
dc.description.abstract
Optimal design and operation of multi-energy systems involving seasonal energy storage are often hindered by the complexity of the optimization problem. Indeed, the description of seasonal cycles requires a year-long time horizon, while the system operation calls for hourly resolution; this turns into a large number of decision variables, including binary variables, when large systems are analyzed. This work presents novel mixed integer linear program methodologies that allow considering a year time horizon with hour resolution while significantly reducing the complexity of the optimization problem. First, the validity of the proposed techniques is tested by considering a simple system that can be solved in a reasonable computational time without resorting to design days. Findings show that the results of the proposed approaches are in good agreement with the full-scale optimization, thus allowing to correctly size the energy storage and to operate the system with a long-term policy, while significantly simplifying the optimization problem. Furthermore, the developed methodology is adopted to design a multi-energy system based on a neighborhood in Zurich, Switzerland, which is optimized in terms of total annual costs and carbon dioxide emissions. Finally the system behavior is revealed by performing a sensitivity analysis on different features of the energy system and by looking at the topology of the energy hub along the Pareto sets.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Elsevier
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
Multi-energy systems
en_US
dc.subject
Microgrids
en_US
dc.subject
Seasonal storage
en_US
dc.subject
Investment planning
en_US
dc.subject
Yearly scheduling
en_US
dc.subject
MILP
en_US
dc.subject
Power-to-gas
en_US
dc.title
Optimal design of multi-energy systems with seasonal storage
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2017-10-05
ethz.journal.title
Applied Energy
ethz.journal.volume
219
en_US
ethz.pages.start
408
en_US
ethz.pages.end
424
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.grant
Integration of sustainable multi-energy-hub systems at neighbourhood scale (IMES)
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Amsterdam
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02629 - Institut für Verfahrenstechnik / Institute of Process Engineering::03484 - Mazzotti, Marco / Mazzotti, Marco
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02629 - Institut für Verfahrenstechnik / Institute of Process Engineering::03484 - Mazzotti, Marco / Mazzotti, Marco
ethz.grant.agreementno
153890
ethz.grant.fundername
SNF
ethz.grant.funderDoi
10.13039/501100001711
ethz.grant.program
NFP 70: Gesuch
ethz.relation.isReferencedBy
handle/20.500.11850/224904
ethz.date.deposited
2018-04-09T04:13:00Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2018-05-29T07:32:54Z
ethz.rosetta.lastUpdated
2018-12-02T10:07:20Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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