Accuracy indicators for evaluating retrospective performance of energy system models

Xin Wen, Marc Jaxa-Rozen and Evelina Trutnevyte

Applied Energy, 2022, vol. 325, issue C, No S0306261922011667

Abstract: Retrospective evaluation of energy system models and scenarios is essential for ensuring their robustness for prospective policy support. However, quantitative evaluations currently lack systematic methods to be more holistic and informative. This paper reviews existing accuracy indicators used for retrospective evaluations of energy models and scenarios with the aim to find a small suite of complementary indicators. We quantify and compare 24 indicators to assess the retrospective performance of D-EXPANSE electricity sector modeling framework, used to model 31 European countries in parallel from 1990–2019. We find that symmetric mean percentage error, symmetric mean absolute percentage error, symmetric median absolute percentage error, root-mean-squared logarithmic error, and growth error together form the most informative suite of indicators. This study is the first step towards developing a model accuracy testbench to assess energy models and scenarios in multiple dimensions retrospectively.

Keywords: Energy system models; Energy projections; Energy scenarios; Accuracy indicators; Optimization; Model evaluation (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (10)

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DOI: 10.1016/j.apenergy.2022.119906

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