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

Abstract

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

The effect of the thyristor energy router on harmonics

“…Harmonic enhancement in microgrid with applications on sensitive loads discusses in [20]. Widjonarko et al [21] 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 results of theoretical and experimental studies on the problems of effective application of shunt active filters for power quality improvement and electromagnetic compatibility ensuring were presented in [22].…”

Novel Design to Tune SVC for Power Factor Correction and Reactive Power Control Using Cascaded ANN Approach (CANNA

“…This is approach is an optimizing approach rather than actual reactive power control to improve the power factor to unity. In [22], ANN has been applied to adjust power factor correction automatically. The results obtained indicate that the implementation of ANN has a better performance than the conventional method for tackling the problem, has closer value to the set point value.…”