DTC-IM drive using adaptive neuro fuzzy inference strategy with multilevel inverter

Banu, J. Barsana; Jeyashanthi, J.; Ansari, Anzum

doi:10.1007/s12652-021-03244-3

Cited by 9 publications

(1 citation statement)

References 32 publications

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“…To lessen the Harmonics, [12][13][14][15] studies the usage of many forms of Selective Harmonics Elimination procedures. Normally Multilevel inverter step angles are frequently determined using optimization techniques [16]. In [17], the author used a Genetic Algorithm (GA) to train the neural network to reduce the harmonics.…”

Section: Introductionmentioning

confidence: 99%

Selective Harmonics Elimination Technique for Artificial Bee Colony Implementation

DeepikaVinothini¹,

Karthigaivel²,

Banu³

2023

Computer Systems Science and Engineering

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In this research, an Artificial Bee Colony (ABC) algorithm based Selective Harmonics Elimination (SHE) technique is used as a pulse generator in a reduced switch fifteen level inverter that receives input from a PV system. Pulse width modulation based on Selective Harmonics Elimination is mostly used to suppress lower-order harmonics. A high gain DC-DC-SEPIC converter keeps the photovoltaic (PV) panel's output voltage constant. The Grey Wolf Optimization (GWO) filter removes far more Photovoltaic panel energy from the sunlight frame. To eliminate voltage harmonics, this unique inverter architecture employs a multi-carrier duty cycle, a high-frequency modulation approach. The proposed ABC harmonics elimination approach is compared to SHE strategies based on Particle Swarm Optimization (PSO) and Flower Pollination Algorithm (FPA). The suggested system's performance is simulated and measured using the MATLAB simulation tool. The proposed ABC approach has a THD level of 4.86%, which is better than the PSO and FPA methods.

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