DocumentCode :
3771993
Title :
Study on Harmonic Current Detection in Grid-Connected PV Generation Systems
Author :
Libin Yang;Chao Xiong;Yun Teng;Qian Hui;Yipeng Zhu
Author_Institution :
Electr. Eng., Shenyang Univ. of Technol., Shenyang, China
fYear :
2015
Firstpage :
752
Lastpage :
755
Abstract :
A novel harmonic current detection method based on the adaptive neural networks is proposed in this paper to improve the PV power station Grid-connected quality. In the supposed algorithm, the fundamental frequency and the harmonic amplitude-phase parameters are introduced as weights needed to be adjusted. The harmonic parameters are estimated through the adaptive measurement theorem. It can predict the future time of harmonic currents according to the current data and the former historical data, achieving the harmonic real-time and fast detection. Simulations are conducted on the PV Power stations in a certain area. The results show that the algorithm achieves high accuracy and rapid speed in convergence and is a good candidate for measuring the harmonics with asynchronous sampling and short data in PV power plant Grid-connected.
Keywords :
"Harmonic analysis","Power harmonic filters","Artificial neural networks","Adaptive systems","Training"
Publisher :
ieee
Conference_Titel :
Intelligent Systems Design and Engineering Applications (ISDEA), 2015 Sixth International Conference on
Type :
conf
DOI :
10.1109/ISDEA.2015.190
Filename :
7462727
Link To Document :
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