Title :
ANN-based Control Method Implemented in a Voltage Source Converter for Industrial Micro-grid
Author :
Xu, Jinbang ; Wu, Zhizhuo ; Yang, Xuan ; Ye, Jie ; Shen, Anwen
Author_Institution :
Dept. of Control Sci. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China
Abstract :
With more and more attention on the grid current harmonic in recent years, many control schemes of the Pulse Width Modulation Voltage Source Converter (PWM-VSC) have been investigated. Conventional PI controller has shown limitations such as sensitivity to load and system parameter variation. Even the stability of the system can be threatened under a large and sudden load change. In this paper, the practical situation of a VSC for industrial Micro Grid (MG) is considered and an Artificial neural network (ANN) based control method is employed to solve the problem. Meanwhile, an on-line parameter tuning algorithm is introduced for its advantage of self-tuning and system character identification. The proposed control scheme is verified through simulation based on SABER software. The simulation results have shown the advantage of the proposed method and the performance of the parameter tuning session.
Keywords :
PWM power convertors; distributed power generation; neurocontrollers; power distribution control; power generation control; ANN-based control method; PI controller; PWM-VSC; SABER software; artificial neural network control method; grid current harmonic; industrial microgrid; on-line parameter tuning algorithm; pulse width modulation voltage source converter; self-tuning identification; system character identification; system parameter variation; system stability; Artificial neural networks; Frequency control; Power conversion; Regulators; Voltage control; Voltage measurement; PWM-VSC; micro-grid; neural network;
Conference_Titel :
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2011 Sixth International Conference on
Conference_Location :
Penang
Print_ISBN :
978-1-4577-1092-6
DOI :
10.1109/BIC-TA.2011.18