Asynchronous Particle Swarm Optimization-Genetic Algorithm (APSO-GA) Based Selective Harmonic Elimination in a Cascaded H-Bridge Multilevel Inverter

In this article, a hybrid asynchronous particle swarm optimization-genetic algorithm (APSO-GA) is proposed for the removal of unwanted lower order harmonics in the cascaded H-bridge multilevel inverter (MLI). The APSO-GA is applicable to all levels of MLI. In the proposed method, ring topology based...

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Vydáno v:	IEEE transactions on industrial electronics (1982) Ročník 69; číslo 2; s. 1477 - 1487
Hlavní autoři:	Memon, Mudasir Ahmed, Siddique, Marif Daula, Mekhilef, Saad, Mubin, Marizan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.02.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Convergence Evolutionary algorithms Evolutionary computation Genetic algorithm (GA) Genetic algorithms Harmonic analysis Harmonics Inverters Machine learning multilevel inverter (MLI) Multilevel inverters Optimization Particle swarm optimization particle swarm optimization (PSO) Rings (mathematics) selective harmonic elimination pulsewidth modulation (SHEPWM) Switches Switching Topology
ISSN:	0278-0046, 1557-9948
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Abstract	In this article, a hybrid asynchronous particle swarm optimization-genetic algorithm (APSO-GA) is proposed for the removal of unwanted lower order harmonics in the cascaded H-bridge multilevel inverter (MLI). The APSO-GA is applicable to all levels of MLI. In the proposed method, ring topology based APSO is hybrid with GA. APSO is applied for exploration and GA is used for the exploitation of the best solutions. In this article, optimized switching angles are calculated using APSO-GA for seven-level and nine-level inverter, and results are compared with GA, PSO, APSO, bee algorithm (BA), differential evolution (DE), synchronous PSO, and teaching-learning-based optimization (TLBO). Simulation results show that APSO-GA can easily find feasible solutions particularly when the number of switching angles is high; however, the rest of all stuck at local minima due to less exploration capability. Also, the APSO-GA is less computational complex than GA, BA, TLBO, and DE algorithms. Experimentally, the performance of APSO-GA is validated on a single-phase seven-level inverter.
AbstractList	In this article, a hybrid asynchronous particle swarm optimization-genetic algorithm (APSO-GA) is proposed for the removal of unwanted lower order harmonics in the cascaded H-bridge multilevel inverter (MLI). The APSO-GA is applicable to all levels of MLI. In the proposed method, ring topology based APSO is hybrid with GA. APSO is applied for exploration and GA is used for the exploitation of the best solutions. In this article, optimized switching angles are calculated using APSO-GA for seven-level and nine-level inverter, and results are compared with GA, PSO, APSO, bee algorithm (BA), differential evolution (DE), synchronous PSO, and teaching-learning-based optimization (TLBO). Simulation results show that APSO-GA can easily find feasible solutions particularly when the number of switching angles is high; however, the rest of all stuck at local minima due to less exploration capability. Also, the APSO-GA is less computational complex than GA, BA, TLBO, and DE algorithms. Experimentally, the performance of APSO-GA is validated on a single-phase seven-level inverter.
Author	Mekhilef, Saad Mubin, Marizan Memon, Mudasir Ahmed Siddique, Marif Daula
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SubjectTerms	Convergence Evolutionary algorithms Evolutionary computation Genetic algorithm (GA) Genetic algorithms Harmonic analysis Harmonics Inverters Machine learning multilevel inverter (MLI) Multilevel inverters Optimization Particle swarm optimization particle swarm optimization (PSO) Rings (mathematics) selective harmonic elimination pulsewidth modulation (SHEPWM) Switches Switching Topology
Title	Asynchronous Particle Swarm Optimization-Genetic Algorithm (APSO-GA) Based Selective Harmonic Elimination in a Cascaded H-Bridge Multilevel Inverter
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