Code exposed: Review of five open-source frameworks for modeling renewable energy systems. (June 2022)

• Record Type: Journal Article
• Authors: Candas, Soner; Muschner, Christoph; Buchholz, Stefanie; Bramstoft, Rasmus; van Ouwerkerk, Jonas; Hainsch, Karlo; Löffler, Konstantin; Günther, Stephan; Berendes, Sarah; Nguyen, Stefanie; Justin, Aparna
• Is Part Of: Renewable & sustainable energy reviews. Volume 161(2022)
• Publication Date: 2022-06
• Subjects: Energy system modeling -- Energy transition -- Open-source frameworks -- Model comparison -- Sector-coupling -- Renewable energy; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.rser.2022.112272
• Languages: English
• ISSNs: 1364-0321

Abstract

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. Highlights: Selected mathematical features of five open energy modeling frameworks are compared. A common terminology to facilitate direct mathematical comparison is developed. Key feature differences are presented to increase transparency of modeling activities. Influences of the modeling differences on the model results is demonstrated. The frameworks show various differences, but remain flexible in specific application.