Comparison of power sector models by analyzing the impact of modeling features on optimal capacity expansion
Jonas van Ouwerkerk, Hans Christian Gils, Hedda Gardian, Martin, Kittel, Wolf-Peter Schill, Alexander Zerrahn, Alexander Murmann, Jann Launer,, Laura Torralba-D\'iaz, Christian Bu{\ss}ar

TL;DR
This study compares six power sector models to understand how different assumptions and modeling features influence optimal capacity expansion decisions for renewable and flexible energy technologies.
Contribution
It systematically analyzes the impact of modeling assumptions on capacity expansion outcomes across various simplified use cases.
Findings
Deviations in assumptions on technology availability cause significant differences in results.
Fixed energy-to-power ratios in storage alter the balance between short- and long-duration storage.
Limited dispatch foresight leads to higher capacity investments compared to linear optimization.
Abstract
The transition towards decarbonized energy systems requires the expansion of renewable and flexibility technologies in power sectors. In a model comparison, we examine the optimal expansion of such technologies with six capacity expansion power system models. The technologies under investigation include base- and peak-load power plants, electricity storage, and transmission. We define four highly simplified and harmonized use 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 use cases. Fixed energy-to-power-ratios of storage can entirely change model optimal expansion outcomes, especially shifting the ratio between short- and long-duration…
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Taxonomy
TopicsSmart Grid Energy Management · Integrated Energy Systems Optimization · Electric Power System Optimization
