NDLI: Study on islanding detection of grid-connected distributed generations with random properties

Content Provider	IEEE Xplore Digital Library
Author	Weimin Chen Wei Wang Guocheng Chen
Copyright Year	2009
Description	Author affiliation: College of Mechatronics Engineering and Automatic Shanghai University, 200072, China (Guocheng Chen) \|\| Electrical and Mechanical Institute China Jiliang University, Hangzhou, 310018, China (Weimin Chen; Wei Wang)
Abstract	With the development of renewable energy, distributed generations such as photovoltaic generation, wind power systems need to be connected to a utility power grid for the systems to work effectively as energy sources. Islanding detection is one of the most important techniques to develop for the distributed generation systems. A novel active islanding detection algorithm based in pseudo-random signal is proposed in this paper. The modulation waveform will be modified by a binary pseudo-random signal (M-sequence signal), then the voltage of PCC (the point of common coupling) would have random properties. When in grid-connected scenario, the voltage of PCC is dominated by voltage of power grid and the variance has no remarkable peak; however, once the islanding event takes place, the variance of PCC has a remarkable peak. Therefore the islanding can be detected by monitoring a peak of the variance. Doing simulation and experiment based on photovoltaic grid-connected generation systems, the experimental results demonstrate effectiveness and being easy to realize the proposed algorithm.
Starting Page	2486
Ending Page	2489
File Size	291713
Page Count	4
File Format	PDF
ISBN	9781424435562
DOI	10.1109/IPEMC.2009.5157822
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-05-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Distributed control Voltage Photovoltaic systems Solar power generation Mesh generation Power grids Renewable energy resources Distributed power generation Power generation Wind energy generation
Content Type	Text
Resource Type	Article

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