Bridging granularity gaps to decarbonize large‐scale energy systems—The case of power system planning. Issue 8 (4th May 2021)

• Record Type: Journal Article
• Authors: Cao, Karl‐Kiên; Haas, Jannik; Sperber, Evelyn; Sasanpour, Shima; Sarfarazi, Seyedfarzad; Pregger, Thomas; Alaya, Oussama; Lens, Hendrik; Drauz, Simon R.; Kneiske, Tanja M.
• Is Part Of: Energy science & engineering. Volume 9:Issue 8(2021)
• Page Start: 1052
• Page End: 1060
• Publication Date: 2021-05-04
• Subjects: decarbonization -- decentral flexibility -- energy system modeling -- granularity gaps -- model coupling -- security of supply; Energy industries -- Periodicals; Energy development -- Periodicals; Power resources -- Periodicals; 621.042
• DOI: 10.1002/ese3.891
• Languages: English
• ISSNs: 2050-0505

Abstract

Abstract: The comprehensive evaluation of strategies for decarbonizing large‐scale energy systems requires insights from many different perspectives. In energy systems analysis, optimization models are widely used for this purpose. However, they are limited in incorporating all crucial aspects of such a complex system to be sustainably transformed. Hence, they differ in terms of their spatial, temporal, technological, and economic perspective and either have a narrow focus with high resolution or a broad scope with little detail. Against this background, we introduce the so‐called granularity gaps and discuss two possibilities to address them: increasing the resolutions of the established optimization models, and the different kinds of model coupling. After laying out open challenges, we propose a novel framework to design power systems in particular. Our exemplary concept exploits the capabilities of power system optimization, transmission network simulation, distribution grid planning, and agent‐based simulation. This integrated framework can serve to study the energy transition with greater comprehensibility and may be a blueprint for similar multimodel analyses. Abstract : Shaping future energy systems translates to merging the findings from diverse perspectives on the energy sector and the expertise from the appropriate research disciplines, each increasingly relying on specific energy system models. In our Perspective, we discuss the "granularity gaps" that arise for a multidimensionality of spatial, temporal, technological, and economic scopes of energy system models. Moreover, we suggest a novel model coupling concept based on automated and cross‐institutional workflows to more efficiently bridge these gaps.