Asynchronous particle swarm optimization-genetic algorithm (APSO-GA) based selective harmonic elimination in a cascaded h-bridge multilevel inverter
Document Type
Article
Publication Date
2-1-2022
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.
Keywords
Harmonic analysis, Switches, Genetic algorithms, Convergence, Multilevel inverters, Particle swarm optimization, Optimization, Genetic algorithm (GA), multilevel inverter (MLI), Particle swarm optimization (PSO), Selective harmonic elimination pulse width modulation (SHEPWM)
Divisions
sch_ecs
Funders
Ministry of Higher Education, Malaysia under the Project Large Research Grant Scheme [LRGS/1/2019/UKM/01/6/3]
Publication Title
IEEE Transactions on Industrial Electronics
Volume
69
Issue
2
Publisher
IEEE-Inst Electrical Electronics Engineers Inc
Publisher Location
445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA