摘要
传统的故障诊断方法仅针对保护信息进行分析,没有充分利用电气量信息反映出的电网故障特征信息。提出多智能体系统(MAS)框架信息融合模型,针对大规模电网的结构和特性,集成多种故障诊断方法,在不同区域对故障录波器、SCADA系统、保护故障信息管理系统(RPMS)等获得的故障信息进行分析,采用D-S证据理论信息融合技术,进行信息融合获得局部的故障诊断,然后通过全局故障诊断确定故障元件,实现大规模电网实时快速的故障诊断。仿真计算表明,所提出的模型与方法正确、有效。
Traditional fault diagnosis methods only analyze the information of protections but the information of grid features reflected by the electrical variables.A fault diagnosis model based on MAS （Multi-Agent System） and information fusion technology is proposed,which,according to the structure and characteristics of large scale power grid,integrates different fault diagnosis methods to analyze for different areas the fault information collected from data recorders,SCADA and RPMS,employs the evidence theory to perform the information fusion to obtain the divisional fault diagnosis conclusions,and identifies finally the faulty components by the global fault diagnosis.The simulation indicates the proposed model and method is accurate and effective.
出处
《电力自动化设备》
EI
CSCD
北大核心
2010年第7期14-18,共5页
Electric Power Automation Equipment
基金
国家自然科学基金创新群体项目(60721062)
国家自然科学基金资助项目(50677062)
新世纪优秀人才支持计划资助项目(NCET-07-0745)
浙江省自然科学基金资助项目(R107062)~~
