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An expert survey to assess the current status and future challenges of energy system analysis

Scheller, Fabian ; Wiese, Frauke; Weinand, Jann Michael 1; Dominković, Dominik Franjo; McKenna, Russell
1 Institut für Industriebetriebslehre und Industrielle Produktion (IIP), Karlsruher Institut für Technologie (KIT)

Abstract:

Decision support systems like computer-aided energy system analysis (ESA) are considered one of the main pillars for developing sustainable and reliable energy strategies. Although today's diverse tools can already support decision-makers in a variety of research questions, further developments are still necessary. Intending to identify opportunities and challenges in the field, we classify modelling topics into modelling capabilities (32), methodologies (15), implementation issues (15) and management issues (7) from an extensive literature review. Based on a quantitative expert survey of energy system modellers (N = 61) mainly working with simulation and optimisation models, the Status of Development and the Complexity of Realisation of those modelling topics are assessed. While the rated items are considered to be more complex than actually represented, no significant outliers are determinable, showing that there is no consensus about particular aspects of ESA that are lacking development. Nevertheless, a classification of the items in terms of a specially defined modelling strategy matrix identifies capabilities like land-use planning patterns, equity and distributional effects and endogenous technological learning as “low hanging fruits” for enhancement, as well as a large number of complex topics that are already well implemented. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000143108
Veröffentlicht am 16.02.2022
Originalveröffentlichung
DOI: 10.1016/j.segy.2021.100057
Scopus
Zitationen: 10
Dimensions
Zitationen: 13
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Industriebetriebslehre und Industrielle Produktion (IIP)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2021
Sprache Englisch
Identifikator ISSN: 2666-9552
KITopen-ID: 1000143108
Erschienen in Smart Energy
Verlag Elsevier Ltd
Band 4
Seiten Art.-Nr.: 100057
Schlagwörter Energy models; Modelling approaches; Mathematical optimisation models; Simulation models; Modelling challenges; Expert survey
Nachgewiesen in Dimensions
Scopus
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