SpineOpt:A flexible open-source energy system modelling framework

Autor: Maren Ihlemann, Iasonas Kouveliotis-Lysikatos, Jiangyi Huang, Joseph Dillon, Ciara O’Dwyer, Topi Rasku, Manuel Marin, Kris Poncelet, Juha Kiviluoma
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Ihlemann, M, Kouveliotis-Lysikatos, I, Huang, J, Dillon, J, O'Dwyer, C, Rasku, T, Marin, M, Poncelet, K & Kiviluoma, J 2022, ' SpineOpt : A flexible open-source energy system modelling framework ', Energy Strategy Reviews, vol. 43, 100902 . https://doi.org/10.1016/j.esr.2022.100902
Popis: 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.
Databáze: OpenAIRE