Design and Simulation of Active Power Filter Based on Feed Forward Neural Network for Harmonic Detection and Elimination

Author(s):  
Mohammad Naim Uddin ◽  
Md. Tawfiq Amin
2011 ◽  
Vol 403-408 ◽  
pp. 1668-1671
Author(s):  
Dong Fang Wang ◽  
Qian Jin Liu ◽  
Bao You Xu

This article proposed the adaptive harmonic detection based on artificial neural network,and which can test the amplitude and phase of all the harmonics. This paper also proposed the quasi-resonant control ratio strategy of active power filter. This strategy can compensate a specific harmonic of power system in real time, can achieve Static error-free control and with a strong ability of anti-grid frequency fluctuations. The results show that the method is feasible and effective.


Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4351
Author(s):  
Sarawut Janpong ◽  
Kongpol Areerak ◽  
Kongpan Areerak

This paper presents an efficient harmonic detection for real-time generation of the reference current fed to a shunt active power filter using the ADALINE neural network. This proposed method is a single layer with 101 nodes generating the coefficients referred to as weights of the reference current model. It effectively overcomes the drawback of the current technology, which is instantaneous power theory (PQ). The proposed method was implemented on the TMS320F28335 DSP board and tested against MATLAB with Simulink as a hardware-in-loop (HIL) structure. This method gives a good performance by producing a precise reference current in a short period with uncomplicated calculation. It also efficiently can eliminate individual harmonic current. The achieved percentage of total harmonic distortion (%THD) in the current is reduced following the IEEE standard, while the power factor can be maintained to unity.


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