Title :
Research on static VAR generator based on the neural network
Author :
Nie, Wenyan ; Wang, Zhonggen
Author_Institution :
Dept. of Electr. & Inf. Eng., Huainan Normal Univ., Huainan, China
Abstract :
Along with the social requirements of power quality improvement, power quality problems are becoming the higher demands of social, reactive power compensation increasingly become the research focus. Based on neural network, non-linear mapping characteristics, puts forward a suitable for direct current control of static VAR generator detecting reactive and harmonic current method, established the neural network predictive model, and gives corresponding algorithm. Simulation shows that the method has a real-time and accurate, adaptive tracking of power system load change characteristics.
Keywords :
electric current control; harmonics suppression; load (electric); neural nets; power supply quality; reactive power control; static VAr compensators; adaptive tracking; direct current control; harmonic current method; neural network; nonlinear mapping characteristics; power quality improvement; power system load change; reactive power compensation; static VAR generator; Artificial neural networks; Control systems; Generators; Harmonic analysis; Neurons; Power system harmonics; Reactive power; harmonic detection; neural network; reactive compensation static; reactive power generator;
Conference_Titel :
Computer Science and Service System (CSSS), 2011 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-9762-1
DOI :
10.1109/CSSS.2011.5972190