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Public defence in Industrial Electronics and Electric Drives, M.Sc. Meysam Saeedian

The title of the thesis is Integration of Renewable Energy Sources into Power Grids Applying Distributed Virtual Inertia and Model Predictive Controls

M.Sc. Meysam Saeedian will defend the thesis "Integration of Renewable Energy Sources into Power Grids Applying Distributed Virtual Inertia and Model Predictive Controls" on 20 January 2023 at 12 (EET) in Aalto University School of Electrical Engineering, Department of Electrical Engineering and Automation, in lecture hall TU2, Maarintie 8, Espoo.

Opponent: Prof. Paolo Mattavelli, University of Padova, Italy
Custos: Prof. Edris Pouresmaeil, Aalto University School of Electrical Engineering, Department of Electrical Engineering and Automation

Thesis available for public display 10 days prior to the defence at: https://aaltodoc.aalto.fi/doc_public/eonly/riiputus/
Doctoral theses in the School of Electrical Engineering: https://aaltodoc.aalto.fi/handle/123456789/53

Public defence announcement:

Continuous decrease in power grid inertia is the paramount challenge in energy transition, from fossil fuel-based production to power electronic converter-interfaced renewable generation. Loss of inertia changes the nature of power system, making low-inertia grids more sensitive to frequency disturbances (i.e. power mismatch between generation and demand) and jeopardizes system stability.

Hence, this doctoral thesis focuses on synthetic inertia provision concept, as a remedy, for the insufficient grid inertia owing to the rising shares of renewable energy sources and concurrent decommissioning of synchronous generators.

This is a interdisciplinary research, comprising elements of control theory and system modelling. Accordingly, two converter control schemes, i.e. distributed virtual inertia and model predictive controls, are developed aimed at enhancing electricity system stability and resiliency of wider integrated power electronic-based generators.

In particular, the following major contributions to the research field of converter controllers are made: (1) the proposed distributed virtual inertia-augmented controller, unlike the basic solution, allows the grid-following converter to operate in weak grid connections and to stabilize the DC-side voltage after each frequency event. And, (2) the proposed model predictive controller avoids limited bandwidth of conventional grid-forming converters, offering very short rise time, slight overshoot, robust control, and inherent overcurrent protection in the case of fault or overloading.

The results of this thesis find applications in renewable energy generation, e.g. solar and wind generators, as well as in the converter-dominated AC microgrids.

Contact information of doctoral candidate:

Email

[email protected]

Mobile

+358 46 897 4200

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