MVMO-based tuning of Active Power Gradient Control of VSC-HVDC links for Frequency Support

Conference Paper (2019)
Author(s)

Jose Luis Rueda (TU Delft - Intelligent Electrical Power Grids)

A.D. Perilla Guerra (TU Delft - Intelligent Electrical Power Grids)

E. Rakhshani (TU Delft - Intelligent Electrical Power Grids)

Peter Palensky (TU Delft - Intelligent Electrical Power Grids)

M. van der Meijden (TenneT TSO B.V., TU Delft - Intelligent Electrical Power Grids)

Alex Alefragkis (TenneT TSO B.V.)

Research Group
Intelligent Electrical Power Grids
Copyright
© 2019 José L. Rueda, A.D. Perilla Guerra, E. Rakhshani, P. Palensky, M.A.M.M. van der Meijden, Alex Alefragkis
DOI related publication
https://doi.org/10.1109/SGRE46976.2019.9020696
More Info
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Publication Year
2019
Language
English
Copyright
© 2019 José L. Rueda, A.D. Perilla Guerra, E. Rakhshani, P. Palensky, M.A.M.M. van der Meijden, Alex Alefragkis
Research Group
Intelligent Electrical Power Grids
ISBN (electronic)
9781728129600
Reuse Rights

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Abstract

The active power gradient (APG) control of MMC-HVDC links can contribute to frequency support in AC networks affected by severe active power imbalances. This functionality is particularly convenient if the coupled AC systems (through MMC-HVDC) have similar levels of available inertia. This paper tackles the problem of determining the optimal APG parameters that entail bounding frequency excursions within acceptable limits while helping to quickly damp out electromechanical oscillations. The tuning task is tackled as a single objective computationally expensive optimization problem. Since the optimization search procedure involves repetitive time-domain (RMS) simulations, the major challenge resides in solving the problem within reduced amount of fitness evaluations. In view of this, an emerging metaheuristic algorithm, namely, the mean-variance mapping optimization (MVMO) is selected. Numerical results prove the effectiveness of MVMO in finding the optimal solution within a few fitness evaluations.

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