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Research on Substation Intelligent Load Transfer System Based on Panorama Data
- Source :
- 2019 6th International Conference on Information Science and Control Engineering (ICISCE).
- Publication Year :
- 2019
- Publisher :
- IEEE, 2019.
-
Abstract
- Substation equipments are faced with incomplete information, multiple system data cannot be effectively shared, and maintenance personnel are not aware of the status of the equipment. In view of the above problems, this paper proposes a substation intelligent monitoring decision platform based on panorama data, which can realize the centralized access of substation main equipment and auxiliary equipment datas. The equipment state assessment model and intelligent load transfer decision-making base are established based on the decision platform, which realize the intelligent judgment of quantifying equipment fault and abnormal state by comprehensive evaluation method, and provide transfer strategy for substation based on device status discrimination result. Finally, The transfer strategy and model are validated by an actual engineering data, the results show that based on the method proposed in this paper, all optional load transfer schemes are formed and the best solution is given, which can improve the emergency repair and pre-control ability and have great practical value in the automation system of substation and deserves extensive application.
- Subjects :
- Equipment state
Panorama
Computer science
05 social sciences
050109 social psychology
Fault (power engineering)
Process automation system
Transfer system
Reliability engineering
Complete information
0502 economics and business
Evaluation methods
0501 psychology and cognitive sciences
State (computer science)
050203 business & management
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2019 6th International Conference on Information Science and Control Engineering (ICISCE)
- Accession number :
- edsair.doi...........a23e2a8b75eccd9c86b9b221e18e7a7a
- Full Text :
- https://doi.org/10.1109/icisce48695.2019.00173