TY - GEN
T1 - A novel grid computing approach for probabilistic small signal analysis
AU - Xu, Z.
AU - Ali, Mohsin
AU - Dong, Z. Y.
AU - Li, X.
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2006
Y1 - 2006
N2 - 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. ©2006 IEEE.
AB - 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. ©2006 IEEE.
KW - Eigenvector
KW - Grid computing
KW - Monte Carlo simulation
KW - Participation factor
KW - Small signal stability
UR - https://www.scopus.com/pages/publications/35348919429
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-35348919429&origin=recordpage
U2 - 10.1109/pes.2006.1709449
DO - 10.1109/pes.2006.1709449
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 1424404932
SN - 9781424404933
T3 - 2006 IEEE Power Engineering Society General Meeting, PES
BT - 2006 IEEE Power Engineering Society General Meeting, PES
PB - IEEE Computer Society
T2 - 2006 IEEE Power Engineering Society General Meeting (PES 2006)
Y2 - 18 June 2006 through 22 June 2006
ER -