| 基于ARIMA和递归贝叶斯的窃电用户识别算法 |
| |
| 引用本文： | 胡一伟,刘珊,黄浩.基于ARIMA和递归贝叶斯的窃电用户识别算法[J].电测与仪表,2022,59(6):196-200. |
| |
| 作者姓名： | 胡一伟 刘珊 黄浩 |
| |
| 作者单位： | 国网北京城区供电公司,北京100031,广东电网有限责任公司珠海供电局,广东 珠海519000,美国德州农工大学,美国 德克萨斯州77840 |
| |
| 摘 要： | 低压窃电负荷小，难以被及时发现，给电力企业造成了巨大的经济损失。文中基于差分整合移动平均自回归模型(Auto-regressive Integrated Moving Average model, ARIMA)和递归贝叶斯算法，构建了一种针对配电网低压窃电行为的识别方法，该方法结合用户历史数据对低压用户与台区表夜间各时段电力负荷数据进行分析，并算出用户窃电概率，从而发现用户是否存在窃电行为。仿真与实际结果表明：该方法对及时准确发现窃电行为，提高配电线路线损治理效率具有重要意义。
|
| 关 键 词： | 窃电识别 ARIMA 递归贝叶斯 高速电力采集系统 |
| 收稿时间： | 2020/1/29 0:00:00 |
| 修稿时间： | 2020/1/29 0:00:00 |
An Energy Theft Detection Approach based on ARIMA and Recursive Bayesian |
| |
| Hu Yiwei,Liu Shan and Huang Hao.An Energy Theft Detection Approach based on ARIMA and Recursive Bayesian[J].Electrical Measurement & Instrumentation,2022,59(6):196-200. |
| |
| Authors: | Hu Yiwei Liu Shan and Huang Hao |
| |
| Affiliation: | State Grid Beijing Chengqu Power Supply Company,Guangdong Power Grid Corporation Zhuhai Power Supply Bureau,Texas A&M University |
| |
| Abstract: | The energy theft is difficult to be discovered due to the low theft load, also causes huge economic losses to utility companies. This paper introduced an algorithm based on ARIMA and recursive Bayesian method to identify the energy theft behavior through the selected period historical data. The case study proves this approach is able to timely and accurately discover energy theft and improve the line loss management. |
| |
| Keywords: | Power theft detection ARIMA Recursive Bayesian High speed power communication system |
| 本文献已被 万方数据 等数据库收录！ |
| 点击此处可从《电测与仪表》浏览原始摘要信息 |
|
点击此处可从《电测与仪表》下载全文 |
