Multi-objective investment optimization for energy system models in high temporal and spatial resolution

Matteo Giacomo Prina, Valeria Casalicchio, Cord Kaldemeyer, Giampaolo Manzolini, David Moser, Alexander Wanitschke and Wolfram Sparber

Applied Energy, 2020, vol. 264, issue C, No S0306261920302403

Abstract: Energy system modelling supports decision-makers in the development of short and long-term energy strategies. In the field of bottom-up short-term energy system models, high resolution in time and space, the implementation of sector coupling and the adoption of a multi-objective investment optimization have never been achieved simultaneously because of the high computational effort. Within this paper, such a bottom-up short-term model which simultaneously implements (i) hourly temporal resolution, (ii) multi-node approach thus high spatial resolution, (iii) integrates the electric, thermal and transport sectors and (iv) implements a multi-objective investment optimization method is proposed. The developed method is applied to the Italian energy system at 2050 to test and show its main features. The model allows the evaluation of the hourly curtailments for each node. The optimization highlights that the cheapest solutions work towards high curtailments and low investments in flexibility options. In order to further reduce the CO2 emissions the investments in flexibility options like electric storage batteries and reinforcement and enlargement of the transmission grid become relevant.

Keywords: Energy scenarios; Photovoltaics; Wind; Oemof; Multi-objective optimization; Linear programming; Evolutionary algorithms; Pareto (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (22)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261920302403
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:264:y:2020:i:c:s0306261920302403

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2020.114728

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().