基于用电信息采集系统的电能计量装置异常智能分析方法研究

An Intelligent Analytical Method of Abnormal Metering Device Based on Power Consumption Information Collection System

用户电能计量装置运行情况的诊断分析需依赖现场校验来实现,工作繁琐且时效性差。用户用电信息采集系统建立之后,即可通过远程采集用电信息来分析用户电能计量装置运行情况,但是庞大的采集数据仅靠人工分析和筛查异常信息所花时间较长,而且人工分析中常常会有疏漏,同时一些数据分析工具难以满足要求。本文提出了规律性非连续算法和分类连续差值算法,可有效锁定电能计量装置运行异常及疑似用电异常用户。经过实践表明,该方法高效可靠,运行简单,可准确识别电能计量装置运行异常,为电能计量装置异常排查提供技术保障。

Diagnostic analysis on the performance of the electric energy metering device users needs to rely on site check, which is a big workload. After the founding of power consumption information collection system, we can analyze the operation of electric energy metering device of remotely through using the electricity information collected by power consumption information collection system. But it will take a long time to analysis and screen the abnormal information among the huge collect data artificially, and manual analysis often has misunderstandings. Besides, some analysis tools are difficult to meet the requirements. This paper proposes the regularity discontinuous algorithm and classification continuous algorithm, which can screen out the abnormally operating electric energy metering device and the suspected abnormal electricity users. Field practices indicate that the method is efficient, reliable and easy to operate. The effect of analysis of abnormally operating electric energy metering device and the suspected abnormal electricity users is obvious.