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Related Experiment Video

Updated: Mar 21, 2026

Author Spotlight: Development of a Novel Finite Element Analysis Model for Improved Orthognathic Surgical Techniques
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Robust capacity expansion modeling for renewable energy systems.

Sebastian Kebrich1, Felix Engelhardt2, David Franzmann1

  • 1Forschungszentrum Jülich GmbH, Institute of Climate and Energy Research, Jülich Systems Analysis (ICE-2), Jülich, Germany.

Iscience
|March 20, 2026
PubMed
Summary

Future energy systems rely on renewables, facing weather uncertainties. This study proposes a capacity planning algorithm that iteratively adjusts solutions to prevent supply gaps, ensuring system robustness against extreme weather events.

Keywords:
Applied sciences

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Area of Science:

  • Energy Systems Analysis
  • Renewable Energy Integration
  • Climate Change Adaptation

Background:

  • Future energy systems will heavily depend on variable renewable energy sources.
  • Uncertain weather conditions pose significant challenges to energy supply reliability.
  • Capacity expansion planning must account for extreme weather and seasonal fluctuations.

Purpose of the Study:

  • To develop and evaluate an algorithm for robust capacity expansion planning in greenhouse gas neutral energy systems.
  • To quantify the cost implications of ensuring energy system robustness against supply gaps.
  • To assess the impact of atypical weather scenarios on energy system feasibility.

Main Methods:

  • An iterative algorithm for capacity expansion planning was developed.
  • Solutions were optimized using single-year data and tested against diverse weather years.
  • The algorithm modifies solutions to address detected supply gaps, particularly during cold, dark periods.

Main Results:

  • Ensuring system robustness against supply gaps increases total annual costs by 1.6-2.9%.
  • Non-robust systems risk a loss of load approaching 50% of total demand during certain periods.
  • The study highlights the necessity of using atypical time-series for model validation.

Conclusions:

  • Robust capacity expansion planning is crucial for reliable energy supply in renewable-dominated systems.
  • The proposed algorithm effectively mitigates supply gaps caused by weather variability.
  • Validating energy system models with extreme weather data is essential for accurate feasibility assessments.