| Autor: |
Yue Zhang, Lianfei Shan, Jianming Yu, Ruyi Li, Pengrui Du |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2019, Vol. 2073 Issue 1, p020077-1-020077-8, 8p |
| Abstrakt: |
Aiming at the problem that the predictive fault set depends on the artificial experience in the static security analysis of the smart grid dispatching control system (D5000), a self-adaptive and super real-time forecast system based on D5000 is proposed. The power system static security analysis technology, the predictive fault set generation technology and the artificial intelligence algorithm are combined organically, the static sample library of the fault set is established firstly, then the static sample library of the fault set is edited established based on the classification error. The artificial intelligence technology is used to classify the fault set, and the adaptive super real-time prediction model of the fault set is established. In this paper, the software environment, function design and key technologies of the proposed system are described in detail. The system can scientifically predict fault sets and improve the intelligence of software [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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