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Energies 2018, 11(9), 2394;

FPGA-Based Implementation of MMC Control Based on Sorting Networks

Department of Energy Technology, Aalborg University, 9100 Aalborg, Denmark
SATIE lab, Cergy-Pontoise University, 95031 Cergy Pontoise, France
Author to whom correspondence should be addressed.
Received: 6 August 2018 / Revised: 6 September 2018 / Accepted: 10 September 2018 / Published: 11 September 2018
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In Modular Multilevel Converter (MMC) applications, the balancing of the capacitor voltages is one of the most important issues for achieving the proper behavior of the MMC. The Capacitor Voltage Balancing (CVB) control is usually based on classical sorting algorithms which consist of repetitive/recursive loops. This leads to an increase of the execution time when many Sub-Modules (SMs) are employed. When the execution time of the balancing is longer than the sampling period, the proper operation of the MMC cannot be ensured. Moreover, due to their inherent sequential operation, sorting algorithms are suitable for software implementation (microcontrollers or DSPs), but they are not appropriate for a hardware implementation. Instead, in this paper, Sorting Networks (SNs) are proposed due to their convenience for implementation in FPGA devices. The advantages and the main challenges of the Bitonic SN in MMC applications are discussed and different FPGA implementations are presented. Simulation results are provided in normal and faulty conditions. Moreover, a comparison with the widely used bubble sorting algorithm and max/min approach is made in terms of execution time and performance. Finally, hardware-in-the-loop results are shown to prove the effectiveness of the implemented SN. View Full-Text
Keywords: modular multilevel converters; capacitor voltage balancing; sorting networks; field-programmable gate array modular multilevel converters; capacitor voltage balancing; sorting networks; field-programmable gate array

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Ricco, M.; Mathe, L.; Monmasson, E.; Teodorescu, R. FPGA-Based Implementation of MMC Control Based on Sorting Networks. Energies 2018, 11, 2394.

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