Decision support methods for distribution networks with telemetry data

You will be working at the Ghent campus of KU Leuven, as part of the Electa - Ghent division. You will join a new team led by the recently appointed prof. Vanin, which is part of a larger, young, international and growing research group, with strong ties to industry as well as other academic realities in Belgium, Europe, and overseas.
Electa-Ghent is part of EnergyVille, a collaboration between the Belgian research partners KU Leuven, VITO, imec and UHasselt in the fields of sustainable energy and intelligent energy systems. Spread across the different campuses of Electa and EnergyVille, tens of colleagues (PhD students, postdocs, permanent research staff and lab engineers) work on a variety of related energy problems, making it a stimulating work environment.

The PhD will be performed in the framework of the Arenberg doctoral school: https://set.kuleuven.be/phd . The position if full-time and fully-funded for four years, which is the nominal duration of a PhD program at KU Leuven.
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European distribution networks are facing increased risk of congestion as a consequence of the ongoing electrification process. To allow the connection of additional low carbon technology (heat pumps, electric vehicles, etc.) without compromising the safe and reliable operation of the grid, and without causing excessive cost to society, distribution system operators (DSOs) need novel, advanced decision support tools that are presently not available.

Many of such tools require some degree of awareness with respect to the network’s operating conditions, which was not possible to obtain prior to the introduction of digital telemetry. Smart meters (and similar measurement devices) are becoming more widely adopted, but are still relatively sparse and present a number of non-ideal conditions: low signal-to-noise ratios, slow acquisition times, etc. In addition to that, multiple features of distribution networks (e.g., cable impedances) are not known accurately. The sub-optimal quality of measurements and network data brings challenges and uncertainties that propagate to the decision making process, and cannot be ignored in modern grid decision support tools. Thus, the goal of this doctoral project is to develop (sub-parts of) decision support solutions for DSOs that can address these challenges and the uncertainties they entail.

The candidate can start from existing software that has been developed in the Electa research group, and that is based on state-of-the-art mathematical optimization frameworks. The existing software can perform, among other, distribution system state estimation, phase connectivity identification, and cable impedance matrix estimation, but many more optimization and estimation challenges still exist. The candidate should be interested in modelling accurate mathematical models of complex decision and/or estimation problems, to solve with exact or heuristic methods depending on what is most appropriate.

As this position is not related to a specific project, the candidate has substantial academic freedom to shape their research according to their interest, along the lines described in this job advertisement, and in agreement with the supervisor.

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