| 基于配电物联网的反窃电预警系统研究及应用 |
投稿时间：2019-05-29 修订日期：2019-07-15  点此下载全文 |
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| 中文摘要:基于国家电网公司泛在电力物联网建设方向,结合大数据、人工智能深度机器学习技术,提出基于配电物联网的反窃电预警系统研究及应用,以信息化支撑营销稽查与反窃电预警应用,提供配电台区“变-线-相-户”分段、分层的窃电台区嫌疑分析,客户用电负荷曲线的特征分析,提高各级供电单位对窃电行为发生的预警能力,从而达到降低配电线损率,提高安全生产保障能力的目标。本文首先简述反窃电预警系统由用电特征数据采集、反窃电预警模型和警电联动反窃电应用三部分组成。其次介绍了用电特征数据采集采用边缘物联代理技术,实现台区智能电表计量、电气分钟级冻结数据的采集,和“变-线-相-户”关系的自动拓扑识别及数据分类；反窃电预警模型采用聚类分析、分层分析,并结合专家诊断库精准锁定窃电嫌疑用户清单；警电联动反窃电应用将窃电嫌疑用户清单精准推送至公安侦办系统,形成警电联动体系。最后展望系统扩展对相关业务的支撑,旨在探讨电网企业应用反窃电预警系统的价值。 |
| 中文关键词:配电物联网智能终端 反窃电预警系统 窃电行为辨识 |
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| Research and Application of Anti-stealing Early Warning System Based on Distribution Internet of Things |
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| Abstract:Based on the direction of the construction of the ubiquitous power Internet of Things of the State Grid Corporation, combined with the technology of large data and deep machine learning of artificial intelligence, this paper puts forward the research and application of the anti-stealing early warning system based on the distribution Internet of Things to support the application of marketing inspection and anti-stealing early warning by informationization, to provide the suspicious analysis of the transformer-line-phase-household sectional and hierarchical stealing radio area in the distribution station area, and the load curve of customers The analysis of line characteristics can improve the early warning ability of power supply units at all levels to the occurrence of electricity theft, so as to achieve the goal of reducing the loss rate of distribution lines and improving the ability of safety in production. Firstly, the anti-stealing early warning system consists of three parts: data acquisition of electricity characteristics, anti-stealing early warning model and anti-stealing application of police-electricity linkage. Secondly, this paper introduces the use of edge material-link agent technology in data acquisition of electricity characteristics, which realizes the measurement of smart meters in stations, the collection of freezing data at minute level, and the automatic topology identification and data classification of the "variable-line-phase-household" relationship. The anti-stealing early warning model adopts cluster analysis and hierarchical analysis, and precisely locks the list of suspected users in combination with expert diagnostic database. The application of electricity theft will precisely push the list of suspected users of electricity theft to the public security investigation system, forming a police-electricity linkage system. Finally, it looks forward to the support of system expansion for related business, aiming at discussing the value of the application of anti-stealing early warning system in power grid enterprises.
KEY WORDS: Intelligent terminal of power distributionInternet of things,Anti-stealing Early Warning System,Identification of Electricity Theft Behavior |
| keywords:Intelligent terminal of power distribution Internet of things,Anti-stealing Early Warning System,Identification of Electricity Theft Behavior |
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