Training content

Control model for robust control:

How to capture the dynamics of interest into a small-size model? How to account for the neglected dynamics? Advanced damping control which takes into account the uncertainty quantified into a good control model.

Identification of power system components:

Models, tests, parameter estimation, examples of identification of excitation and speed-governing systems.

Modal Analysis:

Eigenvalues, eigenvectors, modal controllability and observability factors, residues, participation factors, eigenvalue sensitivities, single machine and multimachine system examples.

Eigenvalue sensitivity approach to damping controller tuning:

Two step approach (phase compensation and gain calculation), single step approach (dynamic gains approach), single machine and multi-machine system examples.

Modelling and Control of Wind turbines (WTs):

Reduced modelling of WTs for control design, Control objectives and assessment criteria (Power and rotor speed fluctuation, mechanical loads, fault diagnoses, fault tolerance), Base-line control design in the frequency domain, Advanced wind turbine control using LMI Approach, Controller validation with FAST.

Specific contribution to MRE

Learn more about power grids, renewable generator control and connection to the grid, power electronics control in general (grids, microgrids, standalone and embedded systems).

Professional skills

  • To explain modern and future power systems with high penetration of renewables, requiring complex dynamic models.
  • To discover how dynamics essential to power oscillations can be extracted from an overall model into a small-size control model.
  • To fulfill high performance renewable grid connection specifications, advanced control methods which take into account uncertainties of the models will be explained.