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EMPIRE: An open-source model based on multi-horizon programming for energy transition analyses

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2022Publisher:Elsevier BVJournal:SoftwareX, volume 17, page 100,877 (issn: 2352-7110,

Authors: Backe, Stian; Skar, Christian; del Granado, Pedro Crespo; Turgut, Ozgu; Tomasgard, Asgeir;

doi: 10.1016/j.softx.2021.100877

EMPIRE: An open-source model based on multi-horizon programming for energy transition analyses

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Abstract

Energy and power system models represent important insights on the technical operations of energy technologies that supply the energy consumption in time steps with hourly resolution. This paper presents the European Model for Power system Investments with Renewable Energy (EMPIRE) that combines short-term operations with the representation of long-term planning decisions including infrastructure expansion. The EMPIRE model has an unique mathematical modelling structure based on multi-horizon stochastic programming, which means investment decisions are subject to short-term uncertainty represented by different realizations of operational scenarios. The model is open source and ready to use to analyse energy transition scenarios towards 2050 and beyond. This paper outlines the building blocks of the model and its software structure. We also present an illustrative example of results from using the software.

Related Organizations

Norwegian University of Science and Technology
Norway

Keywords

Multi-horizon representation, Stochastic programming, Power system planning software, Energy systems modelling, QA76.75-76.765, Computer software

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).	50
	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 10%
	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%