Improving the simulation of variable renewable energy in the MEDEAS integrated assessment model
Promotor(s) : Quoilin, Sylvain
Date of defense : 4-Sep-2023/5-Sep-2023 • Permalink :
|Improving the simulation of variable renewable energy in the MEDEAS integrated assessment model
|Translated title :
|[fr] Améliorer la simulation des source d'énergie variable dans les modèles d'évaluation intégrés
|Date of defense :
|Committee's member(s) :
|Number of pages :
|Engineering, computing & technology > Energy
|Target public :
|Université de Liège, Liège, Belgique
|Master en ingénieur civil en informatique, à finalité spécialisée en "intelligent systems"
|Master thesis of the Faculté des Sciences appliquées
[en] This master thesis explores the application of a surrogate model to achieve the integration of electricity network constraints into integrated assessment models, that attempt to predict the evolution of the main features of the society, including economic, demographic, climatic and energy
Tools were developped to run Dispa-SET, a dispatch model for the European electricity network, to build a dataset of simulations on adequate sample points. This dataset is then used to train the surrogate model employing appropriate machine learning methods. Finally, this model is integrated into the MEDEAS IAM, connecting their variables in a meaningful way, and the resulting model is run for different scenarios.
Results show that integrating the model in MEDEAS leads to a lower prediction of the production of variable renewable energy sources compared to the initial MEDEAS output.
Cite this master thesis
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