Proceedings of the 4th International Conference on Information Technology and Management Innovation

Sampling Data Identification In Smart Grid

Authors
W.B. Xuan, Bing. Zhang
Corresponding Author
W.B. Xuan
Available Online October 2015.
DOI
10.2991/icitmi-15.2015.32How to use a DOI?
Keywords
abnormal sampling data; real identification; linear interpolation
Abstract

The real-time identification of sampling data can avoid incorrect action of protection and monitoring device. It is difficult to distinguish abnormal sampling data and electric parameters in system failure for single sampling points. The existence of second derivative of electrical quantity in power system is proved firstly; the error between the adjacent remainder of Lagrange Linear Interpolation is deduced secondly; and the error threshold are given last. This method has the strong real-time processing capability and suitable for all kinds of relay protection and real-time systems such as measurement and control device.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 4th International Conference on Information Technology and Management Innovation
Series
Advances in Computer Science Research
Publication Date
October 2015
ISBN
10.2991/icitmi-15.2015.32
ISSN
2352-538X
DOI
10.2991/icitmi-15.2015.32How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - W.B. Xuan
AU  - Bing. Zhang
PY  - 2015/10
DA  - 2015/10
TI  - Sampling Data Identification In Smart Grid
BT  - Proceedings of the 4th International Conference on Information Technology and Management Innovation
PB  - Atlantis Press
SP  - 174
EP  - 178
SN  - 2352-538X
UR  - https://doi.org/10.2991/icitmi-15.2015.32
DO  - 10.2991/icitmi-15.2015.32
ID  - Xuan2015/10
ER  -