Fuzzy Logic Based Power Factor Correction in Single Phase AC-DC System

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Tarih

2021

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Erişim Hakkı

info:eu-repo/semantics/openAccess

Özet

In recent years, there has been a significant increase in the number of power electronics converters used in both industrial and home appliances devices. The utilization of electronic ballasts and switching mode power supply in power conservation introduced the trouble of power quality. The currents used by these devices are not sinusoidal and these currents are known as non- linear. Boost type power factor correction (PFC) converters are becoming popular due to their conformity in power system quality problems. Conventionally, power factor correction converters were controlled using Proportional-Integral- Differential (PID) controller to reduce harmonic disturbances and enhance the power factor (PF). Conversely, for non-linear system, their performances are not very acceptable. Because PFC circuit is not linear, in this paper fuzzy logic (FL) controller used to adjust the gain PID controller to improve the performance is presented. It is proposed that when there is fluctuation in the voltage input, the input current should be made by a FL controller. This FL controller has a great effect by keeping the phase angle between current and voltage at a very small value, bringing the PF factor closer to 1.0. This great effect has also been demonstrated in experimental studies. The proposed FL based PFC controller converter is analyzed in MATLAB/Simulink environment under variable loads and different voltages. The Performance results (total harmonic distortion, PF and efficiency) has been calculated for different input voltage and different loads. From these results it can be seen that the PF value is always improved to a value greater than 0.985, efficiency is more than 85% and total harmonic distortion of current is around 4% to 12,5%. The performance results of the FL based PFC is in acceptable ranges in terms of THD according to IEC 61000-3-2. For the THD values the cubic polynomial regression analysis was performed in MATLAB/ Basic Toolbox. (Version R2020b).

Açıklama

Anahtar Kelimeler

Kaynak

Bitlis Eren Üniversitesi Fen Bilimleri Dergisi

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Cilt

10

Sayı

2

Künye