Funding entity Ministerio de Ciencia, Innovación y Universidades, Agencia Estatal de Investigación
Participated by Universidad de Alcalá
This is Subproject 1 (SP1) of a coordinated project with Alcalá University. It 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, SP1 critically revisit applicable models and methods
Finally, SP1 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: The application of a number of new technologies in electric power systems calls for a thorough revision of the operation and control of those systems. This project seeks a positive contribution towards a flexible operation of those systems while maintaining reliability and robustness.
Techniques employed: Sensitivity analysis, model reduction, simulation, advanced control
SESHFPC
