Power Factor Improvement by using Artificial Neural Network with Single Inductor Dual Output circuit implementation

Due to the negative effects of the non-linear semiconductor devices and the passive electrical components (inductor and capacitor) in the converter circuits, and that are deteriorating the power factor (PF) and total harmonics distortion (THD) of grid current, this study proposes a novel unity PF correction controller based on a new algorithm of neural network to improve the performance of a single phase boost DC-DC converter with respect to the mentioned concerns. The controller guarantees stable load voltage. The PF corrector, firstly measures the phase shift between grid voltage and grid current waveforms, then through a new artificial neural network (ANN) algorithm, a suitable duty cycle is predicted to guide and control the converter to reduce the phase shift between grid voltage and grid current as possible to have maximum PF which is unity PF, and to improve the THD level of grid current. The proposed system is simulated and evaluated via Simulink of MATLAB, the simulation results are collected at constant duty cycle and at controlled duty cycle through the proposed PF controller using different loads. The presented PF controller guarantees the unity power factor, and enhances the grid alternating current THD.

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Capacitor bank controller using artificial neural network with closed-loop system

Bulletin of Electrical Engineering and Informatics ◽

10.11591/eei.v9i4.2411 ◽

2020 ◽

Vol 9 (4) ◽

pp. 1379-1386

Author(s):

Widjonarko Widjonarko ◽

Cries Avian ◽

Andi Setiawan ◽

Moch. Rusli ◽

Eka Iskandar

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Control System ◽

Low Power ◽

Power Factor ◽

Closed Loop ◽

Capacitor Bank ◽

Industrial Equipment ◽

Closed Loop System ◽

Artificial Neural

The problem of power factor in the industry is critical. This is due to the issue of low power factor that can make the vulnerability of industrial equipment damaged. This problem has been resolved in various ways, one of which is the Automatic Power Factor Correction, with the most popular device called capacitor bank. There are also many methods used, but several methods require certain calculations so the system can adapt to the new plant. In this study, researchers proposed a capacitor bank control system that can adapt to plants with different capacitor values without using any calculations by using an Artificial Neural Network with a closed-loop controller. The system is simulated using Simulink Matlab to know the performance with two testing scenarios. The first is changing the value of the power factor on the system and changing the value of the capacitor power at each bank, the second comparing it with the conventional methods. The results show that the system has been able to adapt to different capacitor power values and has a better performance than the conventional method in power factor oscillation due to the extreme power factor interference

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Efficient bridgeless SEPIC converter fed PMBLDC motor using artificial neural network

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v9i4.pp3025-3031 ◽

2019 ◽

Vol 9 (4) ◽

pp. 3025

Author(s):

Meena Devi R. ◽

L. Premalatha

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Power Factor ◽

Motor Drive ◽

Switching Frequency ◽

Loop Analysis ◽

Conduction Loss ◽

Switching Losses ◽

Artificial Neural ◽

Artificial Neural Network Ann

<p>In this paper, a new design of Bridgeless SEPIC (Single Ended Primary Inductance converter) with Artificial neural network (ANN) fed PMBLDC Motor drive is proposed to improve Power Factor. The proposed converter has single switching device of MOSFET, so the switching losses is reduced.ANN is used to achieve the higher power factor and fixed dc link voltage. Also the ANN methodology the time taken for computation is less since there is no mathematical model. The output voltage depends on the switching frequency of the MOSFET. The BLSEPIC act as a buck operation in continuous conduction mode. Detailed converter analysis, equivalent circuit and closed-loop analysis are presented for 36V, 120W, 1500rpm BLDC Motor drive. This proposed converter produces low conduction loss, low total harmonic reduction, low settling time and high power factor reaching near-unity. All the simulation work is verified with MATLAB – Simulink.</p>

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