SpineOpt: A flexible open-source energy system modelling framework

• Published in: Energy strategy reviews Vol. 43; p. 100902
• Main Authors: Ihlemann, Maren, Kouveliotis-Lysikatos, Iasonas, Huang, Jiangyi, Dillon, Joseph, O’Dwyer, Ciara, Rasku, Topi, Marin, Manuel, Poncelet, Kris, Kiviluoma, Juha
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.09.2022; Elsevier
• Subjects: Energy system analysis; Energy system modelling; Integrated energy systems; Investment planning; Open source tool; Sector coupling; Sector coupling; Energy system modelling; Energy system analysis; Integrated energy systems; Investment planning; Open source tool
• ISSN: 2211-467X; 2211-4688; 2211-467X
• DOI: 10.1016/j.esr.2022.100902

The transition towards more sustainable energy systems poses new requirements on energy system models. New challenges include representing more uncertainties, including short-term detail in long-term planning models, allowing for more integration across energy sectors, and dealing with increased model complexities. SpineOpt is a flexible, open-source, energy system modelling framework for performing operational and planning studies, consisting of a wide spectrum of novel tools and functionalities. The most salient features of SpineOpt include a generic data structure, flexible temporal and spatial structures, a comprehensive representation of uncertainties, and model decomposition capabilities to reduce the computational complexity. These enable the implementation of highly diverse case studies. SpineOpt’s features are presented through several publicly-available applications. An illustrative case study presents the impact of different temporal resolutions and stochastic structures in a co-optimised electricity and gas network. Using a lower temporal resolution in different parts of the model leads to a lower computational time (44%–98% reductions), while the total system cost varies only slightly (-1.22–1.39%). This implies that modellers experiencing computational issues should choose a high level of temporal accuracy only when needed. •Open-source energy system model with a rich set of features suitable for modelling operational and planning optimisation problems.•Novel composition of the temporal structure allowing for a trade-off between required modelling detail and complexity reduction.•New flexible stochastic structure for custom branching and recombining of scenarios.•Multitude of open-source published case studies for different energy sectors.