Ongoing research projects
Ongoing research projects in iMMC (August 2022)
This a short description of research projects which are presently under progress in iMMC.
Hereunder, you may select one research direction or choose to apply another filter:
List of projects related to: multi-energy systems
|Generating energy transition pathways- application to Belgium|
Researcher: Gauthier Limpens
Supervisor(s): Hervé Jeanmart
The transition towards more sustainable, fossil-free energy systems is interlinked with a high penetration of stochastic renewables, such as wind and solar.
Integrating these new energy resources and technologies will lead to profound structural changes in energy systems, such as an increasing need for storage and a radical electrifcation of the heating and mobility sectors.
To capture the increasing complexity of such future energy systems, new
flexible and open-source optimization modelling tools are needed.In collaboration with EPFL (Ecole Polytechnique Fédérale de Lausanne), we develop EnergyScope, a new open-source energy model for strategic energy planning of urban and national energy systems.
We applied our methodolgy to Switzerland and Belgium. During the end of the thesis, we are developping a transition pathway model representing the transition from 2015 until a long term target (such as 2050) with intermediary steps. The technologies merit order and the total cost of the transition will be key results.
In addition, other studies are under investigation (by master thesis or myself) about more countries, a multi-cells versions, an urban version, model coupling (EnergyScope-DispaSET), create an educational interface for citizens and policy makers or apply the model for uncertainty characterisation.
|Robust integration of carbon capture in renewable methanation|
Researcher: Dierderik Coppitters
Supervisor(s): Francesco Contino
Robust and antifragile design optimization of energy systems, considering computationally-efficient uncertainty quantification methods.
Improvement of computational efficiency of surrogate models for uncertainty quantification, using active learning methods.
Process simulation and optimization of direct air capture systems in power-to-gas systems.