23-level Single DC Source Hybrid PUC (H-PUC) Converter Topology With Reduced Number of Components: Real-Time Implementation With Model Predictive Control

In this paper, a new configuration of single DC source hybrid packed U-cell (H-PUC) converter with reduced number of components is proposed. The proposed H-PUC only requires one dc source, twelve power switches, and three capacitors to provide 23-level output voltage. It is comprised of two high vol...

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Vydané v:IEEE open journal of the Industrial Electronics Society Ročník 1; s. 127 - 137
Hlavní autori: Sorto-Ventura, Kevin-Rafael, Abarzadeh, Mostafa, Al-Haddad, Kamal, Dessaint, Louis A.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Capacitors
Converters
Energy conversion efficiency
Grid-connected converter
hybrid puc (h-puc)
Inverters
Low voltage
Mathematical model
model predictive control (mpc)
multilevel inverter (mli)
packed u-cell (puc)
Predictive control
Predictive models
Real time
real-time simulation
single dc source
Switches
Topology
Voltage control
ISSN:2644-1284, 2644-1284
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Abstract In this paper, a new configuration of single DC source hybrid packed U-cell (H-PUC) converter with reduced number of components is proposed. The proposed H-PUC only requires one dc source, twelve power switches, and three capacitors to provide 23-level output voltage. It is comprised of two high voltage low frequency (LF) and low voltage high frequency (HF) sub-modules which leads to less power losses and higher efficiency of the proposed H-PUC converter. Moreover, a finite control set model predictive control (FCS-MPC) method is proposed to generate 23-level staircase output voltage with low THD and to regulate voltages of three capacitors to their desired values simultaneously. A real-time model of the proposed 23-level H-PUC converter and its suggested FCS-MPC are developed and implemented in OPAL-RT OP4510 platform to evaluate and validate the feasibility of the proposed H-PUC in grid-connected operation mode. The provided real-time implementation results verify and demonstrate the performance and viability of the proposed 23-level H-PUC and its associated FCS-MPC to provide low THD 23-level output voltage and all three capacitors voltages balancing.
AbstractList In this paper, a new configuration of single DC source hybrid packed U-cell (H-PUC) converter with reduced number of components is proposed. The proposed H-PUC only requires one dc source, twelve power switches, and three capacitors to provide 23-level output voltage. It is comprised of two high voltage low frequency (LF) and low voltage high frequency (HF) sub-modules which leads to less power losses and higher efficiency of the proposed H-PUC converter. Moreover, a finite control set model predictive control (FCS-MPC) method is proposed to generate 23-level staircase output voltage with low THD and to regulate voltages of three capacitors to their desired values simultaneously. A real-time model of the proposed 23-level H-PUC converter and its suggested FCS-MPC are developed and implemented in OPAL-RT OP4510 platform to evaluate and validate the feasibility of the proposed H-PUC in grid-connected operation mode. The provided real-time implementation results verify and demonstrate the performance and viability of the proposed 23-level H-PUC and its associated FCS-MPC to provide low THD 23-level output voltage and all three capacitors voltages balancing.
Author Abarzadeh, Mostafa
Dessaint, Louis A.
Al-Haddad, Kamal
Sorto-Ventura, Kevin-Rafael
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StartPage 127
SubjectTerms Capacitors
Converters
Energy conversion efficiency
Grid-connected converter
hybrid puc (h-puc)
Inverters
Low voltage
Mathematical model
model predictive control (mpc)
multilevel inverter (mli)
packed u-cell (puc)
Predictive control
Predictive models
Real time
real-time simulation
single dc source
Switches
Topology
Voltage control
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Title 23-level Single DC Source Hybrid PUC (H-PUC) Converter Topology With Reduced Number of Components: Real-Time Implementation With Model Predictive Control
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