Performance Enhancement of Shunt Active Power Filter Application using Adaptive Neural Network

被引:0
|
作者
Govind, Annu [1 ]
Prakash, Anupama [1 ]
Kumar, Prakash [1 ]
机构
[1] Amity Univ Uttar Pradesh, Noida, India
来源
JOURNAL OF POWER TECHNOLOGIES | 2021年 / 101卷 / 01期
关键词
DSP controller; harmonic minimization; neural network; power quality; shunt active power filter;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Adaptive neural network (ANN) topology-based control is proposed in this paper for three phase three wire shunt active power filter (SAPF) application. The proposed controller improves power quality and compensates harmonic components. The system includes a current controlled voltage source inverter (CC-VSI) using three phase insulated gate bipolar transistors (IGBT), a DSP module for generating regulated pulse width modulated (PWM) pulse and reference DC bus. The increase in nonlinear load applications has raised power quality issues. SAPF has emerged as one of the best solutions to improve power quality. Application of ANN in SAPF eliminates the need for unit template generation and the tuning requirement of phase locked loop (PLL), as required in traditional SAPF. The proposed ANN based SAPF can be dynamically regulated for minimum harmonic contamination. The results were obtained and verified in Matlab/ Simulink platform.
引用
收藏
页码:78 / 85
页数:8
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