A Fast Dual Vector Model Predictive Voltage Control Strategy for the Permanent Magnet Synchronous Generator based on T-type Three-level Converter
In this paper, a fast dual-vector model predictive voltage control (FDV-MPVC) strategy for the permanent magnet synchronous generator (PMSG) based on the T-type three-level converter is proposed, which is expected to reduce the computation burden, eliminate the weighting factor, and improve the stea...
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Published in | 2024 IEEE 7th International Electrical and Energy Conference (CIEEC) pp. 4068 - 4073 |
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Main Authors | , , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
10.05.2024
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Subjects | |
Online Access | Get full text |
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Summary: | In this paper, a fast dual-vector model predictive voltage control (FDV-MPVC) strategy for the permanent magnet synchronous generator (PMSG) based on the T-type three-level converter is proposed, which is expected to reduce the computation burden, eliminate the weighting factor, and improve the steady-state performance of conventional model predictive control method. Based on the sectors of spatial voltage vectors, only two voltage vectors are selected within five candidate vectors, avoiding testing all feasible voltage vectors, which reduces the computation burden and improves the steady-state performance of FDV-MPVC. In addition, the working characteristics of the redundant small vector are utilized to replace the midpoint potential balance cost function, eliminating the need for setting and adjusting weighting factors, while ensuring balanced midpoint potential. Furthermore, a modulation model is applied to calculate the duration of vectors, and an optimized vector selection strategy is introduced to reduce the switching frequency of the converter. A comprehensive analysis of the converter topology, PMSG model, and control system is presented. Simulation results demonstrate that the FDV-MPVC can efficiently achieve stable DC voltage output while maintaining good steady-state and dynamic-state performance. |
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DOI: | 10.1109/CIEEC60922.2024.10583660 |