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文章摘要
基于逻辑回归算法的异常用电辨识方法研究
Identification of abnormal power consumption mode based on logistic regression algorithm
Received:November 12, 2019  Revised:December 03, 2019
DOI:10.19753/j.issn1001-1390.2021.12.012
中文关键词: 异常用电  离群算法  离群邻近度  逻辑回归  学习速率
英文关键词: abnormal power consumption, outlier algorithm, Outlier proximity, logic regression, learning rate
基金项目:国家电网公司总部科技项目,JL71-17-006电能计量箱检测及质量评价关键技术研究(5442JL170007)
Author NameAffiliationE-mail
Yuan Xiangyu* The China Electric Power Research Institute yxyhit1@163.com 
Zhang Penghe The China Electric Power Research Institute zhangpenghe@epri.sgcc.com.cn 
Xiong Suqin The China Electric Power Research Institute 13778029@qq.com 
Zhao Bo Beijing Information Science and Technology University 13910889512@126.com 
Cheng Da The China Electric Power Research Institute chengda@epri.sgcc.com.cn 
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中文摘要:
      检测异常用电的目的是打击异常用电,并减少电能的非技术性损失。文中提出了一种基于逻辑回归算法的异常用电辨识方法,主要包括特征提取、算法构建以及检验模型等模块。首先提取电网用电量等相关数据,并从数据集中提取出电量下降趋势指标、线损指标和告警类指标用作异常用电评判体系。然后进行电量下降趋势指标、线损指标和告警类指标的归一化处理,再进行离群邻近度的计算,初步筛选异常用电用户。再对初步筛选的结果进行逻辑回归算法的再次筛选,进一步提高识别准确率。经过电网部分用电数据的检验后,该算法相较于逻辑回归算法,识别率更高,识别效果更好。
英文摘要:
      The purpose of detecting abnormal power consumption is to strike abnormal power consumption and reduce non-technical loss of power. In this paper, an method based on logistic regression algorithm is proposed to identify abnormal power consumption, which includes feature extraction, algorithm construction and test model. Firstly, the related data such as power consumption of power grid are extracted, and the index of power decline trend, line loss index and warning index are extracted from the data set as the evaluation system of abnormal power consumption. Then, the trend index, line loss index and alarm index are normalized and used to calculate the outlier proximity so that part normal users can be distinguished. And then, the rest data will be used to calculate by logic regression. Compared with the logic regression algorithm, the differentiation of these abnormal users is more obvious by using the combine algorithm.
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