TY - GEN
T1 - A grid computing based approach for probabilistic load flow analysis
AU - Ali, M.
AU - Dong, Z. Y.
AU - Li, X.
AU - Zhang, P.
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 collaborative problems; those require secured data sharing, high performance computing (HPC) and large size of memory resources. This technology can be useful in many areas of power system analysis; those involve the use of computing resources. As continuing research towards grid computing based probabilistic reliability and security analysis, this paper presents a novel grid computing approach for probabilistic load flow analysis. A prototype system has been designed and developed in our research lab based on previously proposed grid computing framework. Experiments are performed on the prototype grid for probabilistic load flow analysis on the standard IEEE 30-bus system. Results show that this approach has given better accuracy, reliability and performance as compared to traditional computing techniques.
AB - Grid computing is an advanced technique for collaboratively solving collaborative problems; those require secured data sharing, high performance computing (HPC) and large size of memory resources. This technology can be useful in many areas of power system analysis; those involve the use of computing resources. As continuing research towards grid computing based probabilistic reliability and security analysis, this paper presents a novel grid computing approach for probabilistic load flow analysis. A prototype system has been designed and developed in our research lab based on previously proposed grid computing framework. Experiments are performed on the prototype grid for probabilistic load flow analysis on the standard IEEE 30-bus system. Results show that this approach has given better accuracy, reliability and performance as compared to traditional computing techniques.
KW - Grid Computing
KW - Monte Carlo simulation
KW - Power System Planning
KW - Probabilistic Load Flow
UR - https://www.scopus.com/pages/publications/70350228268
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-70350228268&origin=recordpage
U2 - 10.1049/cp:20062127
DO - 10.1049/cp:20062127
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 0863412467
SN - 9780863412462
T3 - IET Conference Publications
BT - 7th IET International Conference on Advances in Power System Control, Operation and Management (APSCOM 2006)
T2 - 7th IET International Conference on Advances in Power System Control, Operation and Management, APSCOM 2006
Y2 - 30 October 2006 through 2 November 2006
ER -