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PhD position: Tools for the detection, analysis, and mitigation of converter-driven interactions in electric energy systems

A. García-Cerrada

March 2026 - April 2029

Funding entity MICIU, AEI, FSE+


In the PhD work we seek systematic approaches to the detection, analysis and classification of converter-driven interactions in electric power systems. These interactions can involve only electronic converters, but also conventional synchronous generators, grid elements and loads. They can even appear within modular converters. The origin and nature of these interactions are not well understood, yet. Elaborating a systematic and realistic taxonomy of these interactions must be the first step to find countermeasures and/or mitigating actions.
The fast response of electronic power converters, together with the progressive reduction of the system conventional inertia, calls for a thorough reconsideration of the models and tools used so far to study the behaviour of modern electric energy systems with a massive integration of power electronics, because the bandwidth within which converter-interactions may take place is very different from the bandwidth we are used to. In this regard, we critically revisit applicable models and methods.
Finally, we explore a systematic approach to a robust design of converter controllers taking into account those interactions detected, so that good overall stability and safety margins can be guaranteed. Local solutions without taking into account the rest of the system may not always be effective enough. In those situation, SP1 study systematic approaches to find out the most critical operation points, and an adequate design procedure for all necessary controllers in order to eliminate or, at least, mitigate the problems.


Layman's summary: We seek systematic approaches to the detection, analysis and classification of converter-driven interactions in electric power systems. Experts agree on the fact that Power Electronics contribute decisively to the incorporation of revewable energy sources into the electricity generation mix.



Techniques employed: Dynamic System Analysis, Algebra, similation



SESHFPC-FPI