Applying Endogenous Learning Models in Energy System Optimization

@article{Ouassou2021ApplyingEL,
  title={Applying Endogenous Learning Models in Energy System Optimization},
  author={Jabir Ali Ouassou and Julian Straus and Marte Fodstad and Gunhild Allard Reigstad and Ove Wolfgang},
  journal={Energies},
  year={2021}
}
Conventional energy production based on fossil fuels causes emissions that contribute to global warming. Accurate energy system models are required for a cost-optimal transition to a zero-emission energy system, which is an endeavor that requires a methodical modeling of cost reductions due to technological learning effects. In this review, we summarize common methodologies for modeling technological learning and associated cost reductions via learning curves. This is followed by a literature… 
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References

SHOWING 1-10 OF 104 REFERENCES

Learning and cost reductions for generating technologies in the national energy modeling system (NEMS)

TLDR
This report describes how Learning-by-Doing is implemented endogenously in the National Energy Modeling System (NEMS) for generating plants, and organizes the relevant information from the NEMS documentation, source code, input files, and output files, in order to make the model's logic more accessible.

Innovation modelling and multi-factor learning in wind energy technology

Endogenous learning in climate-energy-economic models – an inventory of key uncertainties

This paper gives an overview of uncertainties related to endogenous learning as observed in integrated assessment models (IAMs) of global warming, both for bottom-up and top-down

Improving cost estimates for advanced low-carbon power plants

  • E. Rubin
  • Environmental Science, Engineering
    International Journal of Greenhouse Gas Control
  • 2019
...