摘要
电力系统信息量巨大,完整传输暂态稳定性数据困难,导致监控结果不精确。本研究采用物联网技术,通过传感器采集关键参数并传输至数据管理单元。利用多颗粒度扫描挖掘,提取暂态稳定性特征并构建判别指标,实现电力系统的实时监控。仿真测试显示,该方法与实际结果重合率高达98.7%,能精确捕捉电力系统暂态变化,为安全运行提供可靠保障。
Due to the vast amount of information in power systems,it is difficult to completely transmit transient stability data,leading to inaccurate monitoring results.This study adopts the Internet of Things(IoT)technology to collect key parameters through sensors and transmit them to a data management unit.Multi-granularity scanning mining is utilized to extract transient stability features and construct discriminant indicators,enabling real-time monitoring of the power system.Simulation tests have shown that the coincidence rate of this method with actual results is as high as 98.7%,which can accurately capture transient changes in the power system and provide reliable guarantees for safe operation.
作者
伍芳
Wu Fang(Changzhou Haineng Electric Appliance Co.,Ltd.,Changzhou,Jiangsu,China,213002)
出处
《仪器仪表用户》
2024年第11期3-5,共3页
Instrumentation
关键词
物联网
电力系统
暂态
稳定性
实时监控
颗粒度
Internet of Things(IoT)
power system
transient
stability
real-time monitoring
granularity
