Name
Abstract | ||
|---|---|---|
In recent years, the research on fluctuation phenomenon in power network has received more and more attention. In this paper, the authors give an example in the 22-node system of Chinese Electric Power Research Institute to research the fluctuation phenomenon in cascading overload events. The results show that under the condition of random initial failures the flow state of power network has important effects on the fluctuation indexes of relative physical quantities, and the fluctuation index changes along with the flow level of power network. Furthermore, FCM clustering method is applied in this paper to verify that principle, which provides the basis for further research on cascading overload phenomenon. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-13498-2_81 | ICSI |
Keywords | Field | DocType |
flow level,cascading overload phenomenon,cascading overload event,fluctuation phenomenon,power network,22-node system,fluctuation index,chinese electric power research,fluctuation index change,fcm clustering method,flow state,electric power,indexation | Electric power,Data mining,Physical quantity,Computer science,Flow (psychology),Power network,Electric power system,Blackout,Phenomenon,Cluster analysis | Conference |
Volume | ISSN | ISBN |
6146 | 0302-9743 | 3-642-13497-1 |
Citations | PageRank | References |
1 | 0.40 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Huiqiong Deng | 1 | 1 | 2.76 |
| Weilu Zhu | 2 | 1 | 1.41 |
| Shuai Wang | 3 | 1 | 0.40 |
| Keju Sun | 4 | 1 | 1.07 |
| Yan-Ming Huo | 5 | 1 | 0.73 |
| Li-Hua Sun | 6 | 1 | 1.41 |