首页|低压电网节点实时数据和状态采集方法研究

低压电网节点实时数据和状态采集方法研究

扫码查看
针对传统方法存在电网节点数据采集自动化程度低、状态监测能力差的缺点,对基于电力终端台账的低压电网节点实时数据和状态采集方法开展了研究.首先,构建包括终端台账模块、服务器监测模块的采集监测架构.然后,利用配置于变电站端的终端台账模块,获取电网节点实时数据;利用位于调控中心的服务器监测模块,调用、获取电网实时数据.最后,运用T型灰色关联度抽取待校验节点,通过皮尔逊相关系数衡量待校验节点与其余节点直接的趋势相似性,将所得异常电网节点数据修正回正确阈值内,从而完成对低压电网节点实时数据的状态监测.试验结果表明,该方法可以准确地完成对电网节点的信息采集与状态监测,且具有较高的平稳性.当阈值设置为0.4 时,该方法的整体采集监测性能最佳.
Research on Real-Time Data and State Acquisition Methods for Low Voltage Grid Nodes
Aiming at the shortcomings of low automation degree of grid node data collection and poor condition monitoring ability of traditional methods,the real-time data and state acquisition method for low voltage grid nodes based on power terminal account is researched.Firstly,the collection and monitoring architecture including terminal account module and server monitoring module is constructed.Then,the terminal account module configured at the substation end is used to acquire real-time data of grid nodes;the server monitoring module located at the control center is used to call and acquire real-time data of the grid.Finally,the T-type gray correlation is applied to extract the nodes to be calibrated,and the direct trend similarity between the nodes to be calibrated and the rest of the nodes is measured by the Pearson correlation coefficient,and the obtained abnormal grid node data are corrected back to within the correct threshold,thus completing the state monitoring of the real-time data of the low voltage grid nodes.The experimental results show that the method can accurately complete the information acquisition and state monitoring of the grid nodes with high smoothness.The overall acquisition and monitoring performance is best of this method when the threshold is set at 0.4.

Low voltage grid nodePower terminal accountT-type gray correlationReal-time dataPearson correlation coefficientCondition monitoring

黄国政、赵瑞锋、李礼兵、任剑辉、冯志华

展开 >

广东电网有限责任公司江门供电局,广东 江门 529000

广东电网有限责任公司电力调度控制中心,广东 广州 510000

低压电网节点 电力终端台账 T型灰色关联度 实时数据 皮尔逊相关系数 状态监测

中国南方电网有限责任公司科技基金资助项目

GDKJXM20220767

2024

自动化仪表
中国仪器仪表学会 上海工业自动化仪表研究院

自动化仪表

CSTPCD
影响因子:0.655
ISSN:1000-0380
年,卷(期):2024.45(10)