LAPSE:2023.32766
Published Article
LAPSE:2023.32766
Microsecond Enhanced Indirect Model Predictive Control for Dynamic Power Management in MMC Units
April 20, 2023
The multi-modular converter (MMC) technology is becoming the preferred option for the increased deployment of variable renewable energy sources (RES) into electrical power systems. MMC is known for its reliability and modularity. The fast adjustment of the MMC’s active/reactive powers, within a few milliseconds, constitutes a major research challenge. The solution to this challenge will allow accelerated integration of RES, without creating undesirable stability issues in the future power system. This paper presents a variant of model predictive control (MPC) for the grid-connected MMC. MPC is defined using a Laguerre function to reduce the computational burden. This is achieved by reducing the number of parameters of the MMC cost function. The feasibility and effectiveness of the proposed MPC is verified in the real-time digital simulations. Additionally, in this paper, a comparison between an accurate mathematical and real-time simulation (RSCAD) model of an MMC is given. The comparison is done on the level of small-signal disturbance and a Mean Absolute Error (MAE). In the MMC, active and reactive power controls, AC voltage control, output current control, and circulating current controls are implemented, both using PI and MPC controllers. The MPC’s performance is tested by the small and large disturbance in active and reactive powers, both in an offline and online simulation. In addition, a sensitivity study is performed for different variables of MPC in the offline simulation. Results obtained in the simulations show good correspondence between mathematical and real-time analytical models during the transient and steady-state conditions with low MAE. The results also indicate the superiority of the proposed MPC with the stable and fast active/reactive power support in real-time simulation.
Keywords
Model Predictive Control, modular multilevel converter, power management, real-time digital simulation
Suggested Citation
Shetgaonkar A, Lekić A, Rueda Torres JL, Palensky P. Microsecond Enhanced Indirect Model Predictive Control for Dynamic Power Management in MMC Units. (2023). LAPSE:2023.32766
Author Affiliations
Shetgaonkar A: Intelligent Electrical Power Grids, Electrical Sustainable Energy, Faculty of Electrical Engineering, Mathematics and Computer Science, TU Delft, 2628 CD Delft, The Netherlands [ORCID]
Lekić A: Intelligent Electrical Power Grids, Electrical Sustainable Energy, Faculty of Electrical Engineering, Mathematics and Computer Science, TU Delft, 2628 CD Delft, The Netherlands [ORCID]
Rueda Torres JL: Intelligent Electrical Power Grids, Electrical Sustainable Energy, Faculty of Electrical Engineering, Mathematics and Computer Science, TU Delft, 2628 CD Delft, The Netherlands [ORCID]
Palensky P: Intelligent Electrical Power Grids, Electrical Sustainable Energy, Faculty of Electrical Engineering, Mathematics and Computer Science, TU Delft, 2628 CD Delft, The Netherlands [ORCID]
Journal Name
Energies
Volume
14
Issue
11
First Page
3318
Year
2021
Publication Date
2021-06-05
Published Version
ISSN
1996-1073
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Original Submission
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PII: en14113318, Publication Type: Journal Article
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LAPSE:2023.32766
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doi:10.3390/en14113318
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Apr 20, 2023
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