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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Junfang Li Buhan Zhang Yifang Liu |
| Copyright Year | 2009 |
| Abstract | This paper presents a technique framework to evaluate the nonlinear a.c. probabilistic load flow using Monte Carlo simulation with data mining off-line. It provides the whole process of Monte Carlo simulation with data mining technique from which the probability-density curves of the injected reactive powers, voltages, angles, active and reactive power flows can be made. The indices to evaluate the severity of risk for power system static security assessment are presented. To speed up the algorithm, parallel computation is suggested according to the scale of the bulk power system. The IEEE 14-bus test system has been taken for case study. The case has shown that the method is effective and efficient. |
| Starting Page | 833 |
| Ending Page | 836 |
| File Size | 317353 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424449095 |
| e-ISBN | 9781424457281 |
| DOI | 10.1109/ICISE.2009.448 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-12-26 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Concurrent computing Reactive power Data security Power system simulation Voltage Power system reliability Data mining Power system security Power system modeling Load flow |
| Content Type | Text |
| Resource Type | Article |
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