基于用户综合用能信息的用能行为异常识别系统设计  

Design of Abnormal Energy Use Identification System Based on Comprehensive Energy Use Information of Users

作　　者：王宏刚 王一蓉 赵晓龙 WANG Honggang;WANG Yirong;ZHAO Xiaolong(Big Data Center,State Grid Corporation of China,Beijing 100000,China)

机构地区：[1]国家电网有限公司大数据中心,北京100000

出　　处：《自动化仪表》2022年第11期99-104,共6页Process Automation Instrumentation

摘　　要：为了提高用户综合用能信息异常监控能力、识别用户综合用能信息,设计了一种基于用户综合用能信息的用能行为异常识别系统。该系统包括用能异常识别报警模块和主控单元。其中,主控单元使用STM32F103VET6处理器。该处理器能够实时采集用户用能场景中的各类用能数据,并在用能参数超过系统阈值时使报警模块发出报警信号。使用改进后的Apriori算法建立诊断模型,通过将合理的关联规则引入诊断规则库,构建了异常用能诊断规则库,使系统能够根据综合用能信息进行异常识别。试验测试结果显示:系统用能数据采集精度更高,对异常用能行为响应更快,诊断模型识别到的异常能耗数据高达68条。该系统提高了用户综合用能信息的用能行为异常识别能力。In order to improve the ability of monitoring abnormal user integrated energy use information and identifying user integrated energy use information, an abnormal energy use behavior identification system for user integrated energy use information is designed. The system includes an abnormal energy use identification alarm module and a master control unit.The master control unit uses the STM32 F103 VET6 processor. The processor can collect all kinds of energy use data in user energy use scenarios in real time, and causing the alarm module to issue an alarm signal when the energy usage parameters exceed the system threshold. The improved Apriori algorithm is used to establish a diagnostic model, and by introducing reasonable association rules into the diagnostic rule base, a library of abnormal energy use diagnostic rules is constructed, enabling the system to identify abnormalities based on comprehensive energy use information. The test results show that the system has the higher accuracy in collecting energy use data, the faster response to abnormal energy use behavior, and the diagnostic model identifies up to 68 abnormal energy consumption data. The system improves the ability to identify abnormal energy use behavior based on comprehensive energy use information of users.

关 键 词：综合用能信息 异常识别 报警模块 APRIORI算法 诊断规则库 诊断模型 关联规则 

分 类 号：TH391[机械工程—机械制造及自动化]