A novel grid computing approach for probabilistic small signal analysis

Xu, Z., Ali, M., Dong, Z. Y. and Li, X. (2006). A novel grid computing approach for probabilistic small signal analysis. In: Proceedings of the 2006 IEEE Power Engineering Society General Meeting. 2006 IEEE Power Engineering Society General Meeting, Montreal, Canada, (1709449.1-1709449.8). 18-22 June, 2006.


Author Xu, Z.
Ali, M.
Dong, Z. Y.
Li, X.
Title of paper A novel grid computing approach for probabilistic small signal analysis
Conference name 2006 IEEE Power Engineering Society General Meeting
Conference location Montreal, Canada
Conference dates 18-22 June, 2006
Proceedings title Proceedings of the 2006 IEEE Power Engineering Society General Meeting
Journal name 2006 IEEE Power Engineering Society General Meeting, PES
Place of Publication Piscataway, NJ, United States
Publisher IEEE
Publication Year 2006
Sub-type Fully published paper
ISBN 1424404932
9781424404933
Volume 1
Issue 1
Start page 1709449.1
End page 1709449.8
Total pages 8
Collection year 2006
Language eng
Abstract/Summary Grid computing is an advanced technique for collaboratively solving complicated scientific problems using geographically and organisational dispersed computational, data storage and other recourses. Application of grid computing could provide significant benefits to all aspects of power system that involves using computers. Based on our previous research, this paper presents a novel grid computing approach for probabilistic small signal stability (PSSS) analysis in electric power systems with uncertainties. A prototype computing grid is successfully implemented in our research lab to carry out PSSS analysis on two benchmark systems. Comparing to traditional computing techniques, the gird computing has given better performances for PSSS analysis in terms of computing capacity, speed, accuracy and stability. In addition, a computing grid framework for power system analysis has been proposed based on the recent study.
Subjects E1
290901 Electrical Engineering
660304 Energy systems analysis
280000 Information, Computing and Communication Sciences
660301 Electricity transmission
Q-Index Code E1
Institutional Status UQ

 
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Created: Thu, 23 Aug 2007, 22:25:33 EST