Elimination of harmonics using bacterial foraging optimized shunt active power filter

Sharaf, A. M.; Pandey, Rahul; Singh, Mahesh; Jhapte, Rajkumar

doi:10.1109/rdcape.2017.8358296

Cited by 1 publication

(1 citation statement)

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“…Particle swarm optimization (PSO) methods are used to fine-tune the PI controllers' gain settings [20], [21]. Gain settings of the PI controller in SAPFs have been optimized using evolutionary algorithms including genetic algorithm (GA) [22], bacterial foraging (BF) [23], firefly [24], ant colony optimization (ACO) [25], and differential evolution (DE) [26], and to steer clear of sub-optimal pitfalls. More recently PSO has been outlined for solving optimization problems; it is a swarm intelligence based stochastic optimization technique.The primary objective is to devise a strategy for optimizing all SAPF design controller parameters and to reduce the THD.…”

Section: Introductionmentioning

confidence: 99%

PSO based optimized PI controller design for hybrid active power filter

Sujith

Govindaraj

Pardeshi

et al. 2023

IJPEDS

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This research study presents the design and simulation of a hybrid active power filter (HAPF) for reducing harmonics. The reference currents have been determined using the synchronous reference frame technique. To achieve its goals, the proposed HAPF employs AI algorithm known as particle swarm optimization (PSO) to fine-tune the proportional-integral PI controller's parameters. With the help of PI-PSO controller the DC link voltage is regulated in the HAPF-inverter. A non-linear current control strategy based on hysteresis employed here to construct the pulse gate by comparing the retrieved reference and real currents necessitated by the HAPF. Simulations were carried out in MATLAB and shown that the proposed method is extremely adaptable and efficient in reducing harmonic currents caused by non-linear loads.

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