基于用电信息采集数据的低压台区异常线损诊断新方法

低压配电网台区的线损分析对发现和解决异常线损问题,减小用电损失以及用户的精细化管理具有重要意义。文章基于全事件用电信息采集系统采集的真实台区数据,提出了一种新的低压台区线损诊断方法。该方法利用电网诊断规则对所采集的原始数据进行质量分析,并通过对台区线损特征地提取和分类,建立了基于电压信息的二分K-Means聚类诊断算法和基于电量信息的全局搜索诊断算法,实现了对台户异常用户的快速定位及台区线损异常的治理。通过剔除异常电表和实际检验表明,该方法具有较高的准确性和一定的实用性。

New Diagnosis Method of Abnormal Line Loss in Low Voltage Area Based on Electricity Information Collection Data

The line loss analysis of the low-voltage distribution network station area is of great significance to discover and solve the problem of abnormal line loss, reduce electricity loss and fine management of users. Based on the real data collected by the full-event electricity information collection system, this paper proposes a new line loss diagnosis method for low voltage station area. The method uses the grid diagnostic rules to analyze the quality of the collected raw data, and through the extraction and classification of the line loss characteristics of the station area, establishes a binary K-Means clustering diagnostic algorithm based on voltage information and a global search diagnostic algorithm based on power information, which realizes the rapid positioning of abnormal users and the treatment of line loss anomalies in the station area. By eliminating abnormal meters and actual tests show that the method has high accuracy and certain practicability.