Impacts of power sector model features on optimal capacity expansion: A comparative study (van Ouwerkerk et al. 2022)

Jonas van Ouwerkerk, Hans Christian Gils, Hedda Gardian, Martin Kittel, Wolf-Peter Schill, Alexander Zerrahn, Alexander Murmann, Jann Launer, Laura Torralba-Díaz and Christian Bußar

This publication has been published in the context of the project FlexMex

Abstract — The transition towards decarbonized energy systems requires the expansion of renewable and flexibility technologies in power sectors. Many powerful tools exist to find optimal capacity expansion. In a stylized comparison of six models, we evaluate the capacity expansion results of basic power sector technologies. The technologies under investigation include base- and peak load power plants, electricity storage, and transmission. We define four highly simplified and harmonized test cases that focus on the expansion of only one or two specific technologies to isolate their effects on model results. We find that deviating assumptions on limited availability factors of technologies cause technology-specific deviations between optimal capacity expansion in models in almost all test cases. Fixed energy-to-power ratios of storage can entirely change optimal expansion outcomes, especially shifting the ratio between short- and long-duration storage. Fixed initial and final-period storage levels can affect the seasonal use of long-duration storage. Models with a pre-ordered dispatch structure substantially deviate from linear optimization models, as missing foresight and limited flexibility can lead to higher capacity investments. A simplified net transfer capacity approach underestimates the need for grid infrastructure compared to a more detailed direct current load flow approach. We further find deviations in model results of optimal storage and transmission capacity expansion between regions, and link them to variable renewable energy generation and demand characteristics. We expect that the general effects identified in our stylized setting also hold in more detailed model applications, although they may be less visible there.

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Published in: Renewable and Sustainable Energy Reviews 157 (2022) 112004.