摘要
提出一种电力大数据一体化环境下电能计量智能监测方法,搭建电力大数据一体化环境下电能计量智能监测平台,在该平台中通过MapReduce并行化模式融合多种电力数据,构成一体化电力大数据集合;通过流式传输机制实现监测平台中数据资源层、平台服务层以及应用层三层之间的数据传输,将一体化大数据传输至服务层中提取单数据、多数据特征,利用模糊聚类处理后将其传输至应用层中进行异常大数据监测,获取监测结果并预警电能计量的异常情况。实验结果验证:该方法可精确监测到异常电量流失度,同时能够监测到多种电能计量装置异常现象,监测误检率最高也未超过5%,还可以通过电压、电流异常变化合理判断电能计量异常情况。
This paper proposes an intelligent monitoring method for electrical energy metering in the context of power big data integration.Build an abnormal monitoring platform for electric energy measurement under the integrated environment of power big data,in which multiple power data are integrated through MapReduce parallelization mode to form an integrated power big data set.The streaming transmission mechanism is used to realize the data transmission among the data resource layer,platform service layer and application layer in the monitoring platform.The integrated big data is transmitted to the service layer to extract single data and multi data features.After fuzzy clustering processing,it is transmitted to the application layer for abnormal big data monitoring,so as to obtain the monitoring results and warn the abnormal situation of power metering.The experimental results showed that this method could accurately monitor the abnormal power loss degree,and could also monitor the abnormal phenomena of a variety of electric energy metering devices.The highest monitoring error rate was not more than 5%.It could also reasonably judge the abnormal situation of electric energy metering through the abnormal changes of voltage and current.
作者
史琳
周信行
韩丽丽
SHI Lin;ZHOU Xinxing;HAN Lili(Guangzhou Power Supply Bureau,Guangdong Power Grid Co.,Ltd.,Guangzhou510013,China)
出处
《粘接》
CAS
2023年第6期192-196,共5页
Adhesion
基金
广东电网科技项目(项目编号:GZKJXM20170867)。
关键词
电能计量
模糊聚类
数据传输
多数据特征
electric energy measurement
fuzzy clustering
data transmission
multi-data feature
