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ETHOS.REFLOW: An open-source workflow for reproducible renewable energy potential assessments
Pelser, T.; Weinand, J.M.; Kuckertz, P.; Stolten, D. (2025). ETHOS.REFLOW: An open-source workflow for reproducible renewable energy potential assessments. Patterns 6(2): 101172. https://dx.doi.org/10.1016/j.patter.2025.101172
In: Patterns. Cell Press/Elsevier. e-ISSN 2666-3899, more
Peer reviewed article  

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  • Pelser, T.
  • Weinand, J.M.
  • Kuckertz, P.
  • Stolten, D.

Abstract
    Global efforts to mitigate climate change involve transitioning energy systems toward renewable energy sources, including wind and solar photovoltaics (PV). Due to the variable nature of these energy sources, integration into existing energy systems is complex and requires a high degree of planning. An important input to energy system models is the “energy potential” for a given technology, referring to the maximum achievable installable capacity or power yield for the study area. Inconsistencies in methods, data, and assumptions in resource potential assessments may hinder accurate energy system planning. To address this gap, we develop ETHOS.REFLOW, a Python-based workflow manager for automating renewable energy potential analyses. We demonstrate the tool’s utility through an assessment of the North Sea’s technical wind potential. We employ REFLOW to compare two distinct workflows, illustrating how the tool can be used to ensure reproducibility and to help energy system modelers compare workflows.

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