Context of intervention
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The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities in their decisions and businesses in their strategies.
You will be part of the LIST Environmental Research and Innovation department
As part of a Research and Technology Organization (RTO), the Luxembourg Institute of Science and Technology (LIST), the work of the Environmental Research and Innovation (ERIN) Department tackles some of the major environmental challenges our society is facing today, particularly climate change mitigation, sustainable energy systems and the efficient use of renewable resources.
The applicant will join the Environmental Sustainability Assessment and Circularity (SUSTAIN) Unit of ERIN, which is developing knowledge, transferable technologies (e.g. software) and practical methods for the integrative evaluation and management of the sustainability of human driven systems. Within the SUSTAIN Unit, the applicant will be incorporated in the Sustainable Energy Systems (SES) Group. The SES Group conducts research and develops innovative tools for the planning and operations of electric energy systems, with a specific focus on renewable energy integration in smart grids.
We are offering a full time 36 months postdoctoral researcher position in the topics of:
- Computational enhancements, via machine learning techniques, of security-constrained optimal power flow solution algorithms and
- Reactive power reserves planning in renewable-dominated power systems. The project positions within the key societal challenge of the “energy transition” towards 100% clean energy supply, during which power systems are hosting steadily growing amounts of renewable energy sources (RES), which are gradually displacing large fossil-fuel power plants, and pose major challenges to reliable system operation.
This project is concerned with the key challenge of maintaining the transmission power grid reliability, which is under the responsibility of transmission system operator (TSO).
A specific objective is to significantly enhance the SCOPF algorithms under the Alternative Current (AC) physical model. From mathematical perspective, this AC-SCOPF problem is computationally hard (due to intrinsic challenging features like huge size, non-linearity and non-convexity). The limitations of existing algorithms to solve the AC-SCOPF problem currently prevent agile/informed TSO decision-making under increasingly variable operating conditions and hamper thereby cost-efficient and reliable integration of RES.
A second objective is to develop a methodology to evaluate when reactive power reserves will become scarce and to re-think the reactive power plan.
The postdoctoral researcher will work in the project ML4SCOPF, funded jointly by FNRS Belgium and FNR Luxembourg, as a collaboration between University of Liège (PI: Prof. Louis Wehenkel) and LIST (PI: Florin Capitanescu) and will be responsible to:
- Develop an AC SCOPF solution algorithm, enhanced with machine learning-based proxy models, to address the problem of reactive power dispatch for correcting voltages outside the statutory limits, balancing reactive power reserves, and minimizing active power losses;
- Develop an AC SCOPF-based tool for reactive power reserves assessment and management during the energy transition toward 100% renewable supply;
- Present and publish the main findings at peer-reviewed conferences and in top journals.
- PhD in electrical power engineering, applied mathematics or operations research
- Ideally up to 4 years research experience upon PhD graduation
- Good skills in: power systems operation and optimisation (particularly in transmission system), applied mathematics/mathematical optimisation, programming
- Fluent in English (written and oral)
- Knowledge in at least one of the official languages of Luxembourg (French, German or Luxembourgish) is an asset