变电站采样偏差自动学习和补偿技术研究  

Research on Automatic Learning and Compensation Technology of Sampling Deviation in Substation

作　　者：蔡亮亮 龚世敏 唐斌 李帅 CAI Liangliang;GONG Shimin;TANG Bin;LI Shuai(Nanjing SAC Power Grid Automation Co.,Ltd.,Nanjing 211100,China)

机构地区：[1]南京国电南自电网自动化有限公司,江苏南京211100

出　　处：《电工技术》2024年第24期15-18,共4页Electric Engineering

摘　　要：在传统变电站中,测控和保护装置自行采集模拟量,但气候改变尤其是温度的变化常常会对采样精度造成不良影响,为此提出可通过自我学习完成环境因素对采样精度的影响数据统计,再通过数据分析和拟合形成精度偏差曲线的技术。现场运行的装置可参考该曲线自动补偿采样误差。In traditional substations,measurement and control devices,protection devices collect analog quantity by themselves,but climate change,especially the change of temperature,often adversely affects the sampling accuracy.The technology proposed in this paper can complete the data statistics of the influence of environmental factors on the sampling accuracy through self-learning,and then form the accuracy deviation curve through data analysis and fitting.The sampling deviation can be automatically compensated by the equipment according to the curve.

关 键 词：二次设备 气候改变 采样精度 偏差曲线 

分 类 号：TM73[电气工程—电力系统及自动化]