Comprehensive Monitoring And Self-assessment Method Study Of Intelligent Transformers

Transformers are essential apparatuses of the grid. The operationalreliability largely determined the safety and stability of transformersubstation and electric power systems. Online monitoring and conditionassessment are the prerequisites of transformer condition maintenance,which can significantly improve transformer reliability and economicefficiency. Meanwhile, intellectualizing and informationizing onlinemonitor of transformers are the key to realize the informationization ofpower systems.Based on studies of the hitherto newest international series standards,i.e. IEC61850, of substation communication network and systems, theTechnical Guide to High-Voltage Apparatus Intellectualization and theneeds of practical functions, transformer intelligent components aredeveloped. A modeling method of condition information stream inintelligent transformer monitoring is presented, and the main-IED (theclient) and sub-IED (the server) of the intelligent components are modeled.The intelligent transformer monitor system and communication system arestructured. Information sharing and interacting method based on MMSreports, logs and files is presented. A standardized platform, integratingsampling, transmission and storage of transformer condition data, isestablished. Being applied to a particular example, the algorithm is provedcorrect. Meanwhile, an approach of self-assessing diagnosis based oncomposition weighting and fuzzy theory, is studied and realized.The developed software for transformer intelligent comprehensivemonitoring and self-assessment can realize transformer comprehensive monitoring and condition assessment in a brief and simple way. It supportsmultiple functions including data storage, parameter configuration andpartial discharge graph plotting.