Journal Article10.1109/TIE.2021.3060645
Asynchronous Particle Swarm Optimization-Genetic Algorithm (APSO-GA) Based Selective Harmonic Elimination in a Cascaded H-Bridge Multilevel Inverter
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TL;DR: 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.
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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.
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Citations
Multilevel Inverter: A Survey on Classical and Advanced Topologies, Control Schemes, Applications to Power System and Future Prospects
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Artificial Neural Network and Newton Raphson (ANN-NR) Algorithm Based Selective Harmonic Elimination in Cascaded Multilevel Inverter for PV Applications
TL;DR: In this paper, a hybrid Artificial Neural Network - Newton Raphson (ANN-NR) is introduced to mitigate the undesired lower-order harmonic content in the cascaded H-bridge multilevel inverter for solar photovoltaic (PV).
Investigation on load harmonic reduction through solar-power utilization in intermittent SSFI using particle swarm, genetic, and modified firefly optimization algorithms
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PSO-Optimized SHE-PWM Technique in a Cascaded H-Bridge Multilevel Inverter for Variable Output Voltage Applications
TL;DR: In this article , a particle swarm optimization algorithm is used to solve the selective harmonic elimination pulsewidth modulation (SHE-PWM) problem for different output voltage values, which allows achieving a high-quality output waveform in a cascaded H-bridge multilevel inverter.
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References
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TL;DR: In this paper, the authors proposed a generalized formulation for selective harmonic elimination pulsewidth modulation (SHE-PWM) control suitable for high-voltage high-power cascaded multilevel voltage source converters (VSC) with both equal and nonequal dc sources used in constant frequency utility applications.
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TL;DR: In this paper, a GA optimization technique is applied to determine the switching angles for a cascaded multilevel inverter which eliminates specified higher order harmonics while maintaining the required fundamental voltage.
A complete solution to the harmonic elimination problem
TL;DR: In this paper, all possible solutions to the problem of eliminating harmonics in a switching converter are found. But, the authors did not consider the case of the fifth and seventh harmonics.
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A complete solution to the harmonic elimination problem
John Chiasson,Leon M. Tolbert,K.J. McKenzie,Zhong Du +3 more
- 19 Feb 2003
TL;DR: In this article, all possible solutions to the problem of eliminating harmonics in a switching converter were found by converting the transcendental equations that specify the harmonic elimination problem into an equivalent set of polynomial equations.
Harmonic Minimization in Multilevel Inverters Using Modified Species-Based Particle Swarm Optimization
TL;DR: In this paper, a novel particle swarm optimization (PSO) approach based on species-based PSO (SPSO), which increased the robustness of algorithm to find global optimum of the search space.
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