
Open access
Date
2018-06Type
- Journal Article
Citations
Cited 224 times in
Web of Science
Cited 282 times in
Scopus
ETH Bibliography
yes
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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. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000256201Publication status
publishedExternal links
Journal / series
Applied EnergyVolume
Pages / Article No.
Publisher
ElsevierSubject
Multi-energy systems; Microgrids; Seasonal storage; Investment planning; Yearly scheduling; MILP; Power-to-gasOrganisational unit
03484 - Mazzotti, Marco / Mazzotti, Marco
Funding
153890 - Integration of sustainable multi-energy-hub systems at neighbourhood scale (IMES) (SNF)
Related publications and datasets
Is referenced by: http://hdl.handle.net/20.500.11850/224904
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Show all metadata
Citations
Cited 224 times in
Web of Science
Cited 282 times in
Scopus
ETH Bibliography
yes
Altmetrics