摘要
针对电网输电线路故障频发、表象随机性强、提前预判难度大等问题,在分析电网历史故障数据的基础上,对电网输电线路故障原因与特点进行深入剖析。采用大数据挖掘法建立多维度、多业务间的量化关系,提出并确定了典型故障类型,全面展现了典型故障的线路分布、电压等级分布、时间分布和重复发生概率等,明确了电网安全运维检修的重点环节。研究成果为制定电网运维管理策略和线路大修、投资计划提供了有力技术支撑。
In view of the problems of frequent failures in transmission lines of power grid, and the strong randomness of appearance, it is difficult to predict in advance. On the basis of historical power grid fault data,the causes of faults and the features are analyzed in - depth. By using big data mining method, the quantitative relationship of multi - dimensional, and multiple businesses is established, the typical fault types are put forward and determined. The distribution upon lines,voltage grade,and time of typical faults as well as the repeated probability of occurrence are comprehensively demonstrated, thus the focused aspects of safety operation, maintenance, and management of power grid are defined. The research results provide strong technical support to formulate the strategies of operation, maintenance, and management ; as well as the plans of overhaul, technical retrofits, and investment.
出处
《自动化仪表》
CAS
2016年第12期91-93,共3页
Process Automation Instrumentation
关键词
电网
线路故障
大数据挖掘
线路分布
电压等级分布
时间分布
运维管理
Power grid Line fault Big data mining Line distribution Voltage grade distribution Time distribution Operation and maintenance management
