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

Fabian Scheller*, Frauke Wiese, Jann Michael Weinand, Dominik Franjo Dominković, Russell McKenna

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
1 Downloads (Pure)

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. The remaining “tough nuts” regarding modelling capabilities include non-energy sector and social behaviour interaction effects. In general, the optimisation and simulation models differ in their respective strengths, justifying the existence of both. While methods were generally rated as quite well developed, combinatorial optimisation approaches, as well as machine learning, are identified as important research methods to be developed further for ESA.

Original languageEnglish
Article number100057
Number of pages20
JournalSmart Energy
Volume4
Early online date30 Nov 2021
DOIs
Publication statusPublished - Nov 2021

Keywords

  • Energy models
  • Expert survey
  • Mathematical optimisation models
  • Modelling approaches
  • Modelling challenges
  • Simulation models

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