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

Conference Paper (2019)
Author(s)

Jose L.Rueda Torres (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Arcadio Perilla (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Elyas Rakhshani (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Peter Palensky (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Mart A.A.M. Van Der Meijden (TenneT TSO B.V., TU Delft - Electrical Engineering, Mathematics and Computer Science)

Alex Alefragkis (TenneT TSO B.V.)

Research Group
Intelligent Electrical Power Grids
DOI related publication
https://doi.org/10.1109/SGRE46976.2019.9020696 Final published version
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Publication Year
2019
Language
English
Research Group
Intelligent Electrical Power Grids
Article number
9020696
ISBN (electronic)
9781728129600
Event
2nd International Conference on Smart Grid and Renewable Energy, SGRE 2019 (2019-11-19 - 2019-11-21), Doha, Qatar
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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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