|Table of Contents|

 Applied research of WT-ANFIS in islanding detection
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[ISSN:1007-449X/CN:23-1 408/TM]

Issue:
2016年01
Page:
35-42
Research Field:
Publishing date:

Info

Title:
 Applied research of WT-ANFIS in islanding detection
Author(s):
 ZHOU Hao13 LI Wei-gang2 TONG Chao-nan1 LI Wei-li3 MAO Mei-qin4

1. School of Automation & Electronic Engineer,University of Science and Technology Beijing,Beijing 100083,China; 2. College of Information Science and Engineering,Wuhan University of Science and Technology,Wuhan 430081,China; 3. School of Electrical Engineering,Beijing Jiaotong University,Beijing 100044,China; ,China)4. Research Center for PV System Engineering Ministry of Education,Hefei University of Technology,Hefei 230009
Keywords:
islanding detection wavelet transform ( WT) adaptive network based fuzzy inference system ( ANFIS) detail signals characteristic vectors
PACS:
TM 615
DOI:
10. 15938 / j. emc. 2016. 01. 006
Abstract:
The detecting time is long and non-detection zone ( NDZ) is large for traditional passive islan-ding detection methods,while active methods have some negative effects on power quality. A novel islan-ding detection method was proposed based on wavelet transform ( WT) and adaptive network based fuzzy inference system ( ANFIS) . Firstly,output current of inverter and the voltage of point of common cou-pling ( PCC) were gathered,and then WT was adopted to analyze the current signal and the voltage sig-nal. Secondly,the detail signals on all levels were used to extract characteristic vectors. Lastly,ANFIS used these characteristic vectors to pattern recognition and determine whether there was an island phe-nomenon. The simulation and experiment results show that the proposed method has the advantages that detecting time is short and non-detection zone ( NDZ) is small and effectively identify all kinds of load conditions such as the power of grid-connected inverter match and mismatch the one of local loads,and can be used for single-phase and three-phases photovoltaic grid-connected system.

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Last Update: 2016-03-21