Relationships Exploration for Real-time Static Voltage Stability Prediction of Power Systems

DOI

10.2991/lemcs-15.2015.140How to use a DOI?

Keywords

Maximal information coefficient (MIC); Pearson product-moment correlation coefficient (PPMCC); Relationships exploration; Static voltage stability

Abstract

An approach based on data mining and relationships exploration is presented for estimating the static voltage stability relative margin of power systems. The data set is created based on simulations by the software PSS/E. The input variables selected for estimation are corresponding to the relationships highly ranked by MIC and PPMCC. These relationships are also shown and some of them are explained from the perspective of power system operation. If the measured values of these variables are obtained from wide area measurement system (WAMS), the relative margin can be estimated in real time since its relationships with these variables are explored. The approach is tested on a 39-bus system provided by PSS/E and illustrative results indicate the scheme is accurate and effective.

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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TY  - CONF
AU  - Songkai Liu
AU  - Cheng Tian
AU  - Huimin Qiu
AU  - Xinyuan Cui
AU  - Dong Chen
AU  - Li Tu
PY  - 2015/07
DA  - 2015/07
TI  - Relationships Exploration for Real-time Static Voltage Stability Prediction of Power Systems
BT  - Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science
PB  - Atlantis Press
SP  - 714
EP  - 718
SN  - 1951-6851
UR  - https://doi.org/10.2991/lemcs-15.2015.140
DO  - 10.2991/lemcs-15.2015.140
ID  - Liu2015/07
ER  -