Code exposed: Review of five open-source frameworks for modeling renewable energy systems

Soner Candas, Christoph Muschner, Stefanie Buchholz, Rasmus Bramstoft, Jonas van Ouwerkerk, Karlo Hainsch, Konstantin Löffler, Stephan Günther, Sarah Berendes, Stefanie Nguyen and Aparna Justin

Renewable and Sustainable Energy Reviews, 2022, vol. 161, issue C

Abstract: Energy system modeling is a commonly used method to provide policy recommendations and insight to transformation pathways of energy systems. However, the low open-source availability of the frameworks in practice often leads to low interpretability and transparency of energy modeling system configurations. The configuration of an energy model entails how its system components, such as power plants, storage systems and grids operate, and which parameters are used to define them. In order to understand the impact of different model configurations and working principles on the model output, a thorough comparison between various modeling frameworks is necessary. This work thereby consists of a comparison of five open-source energy system modeling frameworks (OS-ESMFs) oemof, GENeSYS-MOD, Balmorel, urbs and GENESYS-2 on the mathematical level and spotlights selected methodological differences in renewable energy system modeling. The comparison shows diversity in the complexity of selected system components and helps to define the best use-cases and scales of application for each framework. Impacts of modeled features on the results were demonstrated by implementing two harmonized scenarios depicting the German electricity system using each framework. While similar model results were obtained for both scenarios, some differences were present, especially in the long-term expansion planning model. Some of those differences could be traced back to the identified modeling differences.

Keywords: Energy system modeling; Energy transition; Open-source frameworks; Model comparison; Sector-coupling; Renewable energy (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (7)

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DOI: 10.1016/j.rser.2022.112272

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