A position is offered for a Post-doctoral Researcher to upgrade RTE's (French electricity Transmission System Operator) stochastic transmission expansion planning (TEP) model along three connected axes: accelerating the Benders decomposition of the TEP problem; automatically discovering candidate investment projects; and mapping the near-optimal space of expansion plans to be able to interpret these expansion solutions. The research work will be conducted at the Institute for Research and Technology, in person at Rey Francisco 4.
Funding modality: private project commissioned by RTE.
Desired start date: January 1st, 2027.
Tasks:
The research project is to be structured in Work Packages closely related to the main scientific activities the PostDoc should undertake:
- WP1 focusses on accelerating RTE’s Benders decomposition around different levers — e.g. semi-relaxed cuts, relaxed master resolutions, regularisation of the master iterates and convergence-oriented candidate management — a family of techniques with demonstrated savings of about 50% of solution time on stochastic TEP cases.
- WP2 focusses on automatic candidate discovery to define the search space in case a candidate set is not available, filtering with optimality safeguards, and data-driven definition of investment projects and their relationships.
- WP3 focusses on mapping the near-optimal space of expansion plans, delivering diverse alternatives, no-regret reinforcements and a multi-criteria decision-support workflow.
All results are delivered as open, documented modules embedded in RTE's expansion planning model.
Several scientific articles in journals and reports are to be produced out of the research activities developed within these WPs. Regular remote meetings with the RTE team commissioning the project are also being held, as well as trips to meet them in person throughout the year.
Degree: degree and PhD. in engineering, mathematics, physics, or a closely related science.
Experience: candidates should have undertaken extensive research in optimization, preferably applied to energy systems.
Language: English is needed; French and Spanish are desirable.
Other technical skills: knowledge in data science, as well as in the engineering and economics of power systems is highly relevant.
Benefits:
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