基于密度聚类的能耗数据采集网关设计

Design of power information collection gateway based on density clustering

现有用电信息采集网络集中器不具备对异常用电量进行检测功能,导致主站对异常用电行为分析与响应滞后。设计一款具备异常检测功能的用电信息采集网关,将网关安装在集中器侧对集中器能耗数据进行异常分析是应对该问题的有效解决方案。根据用电信息采集网络的特征和相关电网规约,网关通过构造数据帧查询主站地址池配置自身地址;基于密度聚类DBSCAN算法和决策树C4.5算法对异常用电行为进行判断。实验结果表明,该网关能够快速地对自身地址进行配置并对能耗数据进行异常分析。

Existing power collection network concentrator doesn ′ t have ability to detect abnormal power load, which leads the main station of abnormal electricity behavior analysis and response lag. An information collection gateway with anomaly detection function is designed. Installing the gateway on the concentrator side to conduct anomaly analysis of the energy consumption data of the concentrator is an effective solution to the problem. According to the characteristics of the information collection network and the relevant grid regulations, the gateway constructs its own address by constructing the data frame to query the address pool from the master station. The abnormal electric behavior is judged based on the density clustering DBSCAN algorithm and the decision tree C4. 5 algorithm. Test results show that the gateway can quickly configure its own address and conduct anomaly analysis of energy consumption data.