基于随机矩阵的海量智能电能表异常个体定位方法
TM933; 智能电能表是电力计量计费的核心装置,关系业主、电网等多方经济利益,具有数量庞大、运行环境复杂等特点.为有效精准发现海量智能电能表的异常个体,提出了一种基于随机矩阵的海量智能电能表异常个体定位方法.提出了智能电能表健康状态的多个参数表征方法,包括比差、角差、温度、湿度、震动等非电气量参数和一次电压、磁场等电气参数.为了更加准确全面地对智能电能表的状态进行评估,将智能电能表的实时数据、仿真数据和历史运行数据等作为数据源,选取智能电能表健康状态时的参数构建高维随机矩阵进行分析,实现了智能电能表异常个体的定位.结合南网新一代智能电能表实际数据验证了文章所提方法的有效性,以期为我国智能电能...
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| Published in | 电测与仪表 Vol. 61; no. 4; pp. 212 - 217 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
中国南方电网有限责任公司,广州 510623%南方电网数字电网研究院有限公司,广州 510623%河南许继仪表有限公司,河南许昌 461000
15.04.2024
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-1390 |
| DOI | 10.19753/j.issn1001-1390.2024.04.030 |
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| Abstract | TM933; 智能电能表是电力计量计费的核心装置,关系业主、电网等多方经济利益,具有数量庞大、运行环境复杂等特点.为有效精准发现海量智能电能表的异常个体,提出了一种基于随机矩阵的海量智能电能表异常个体定位方法.提出了智能电能表健康状态的多个参数表征方法,包括比差、角差、温度、湿度、震动等非电气量参数和一次电压、磁场等电气参数.为了更加准确全面地对智能电能表的状态进行评估,将智能电能表的实时数据、仿真数据和历史运行数据等作为数据源,选取智能电能表健康状态时的参数构建高维随机矩阵进行分析,实现了智能电能表异常个体的定位.结合南网新一代智能电能表实际数据验证了文章所提方法的有效性,以期为我国智能电能表发展高效低成本的计量装置检验提供技术借鉴. |
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| AbstractList | TM933; 智能电能表是电力计量计费的核心装置,关系业主、电网等多方经济利益,具有数量庞大、运行环境复杂等特点.为有效精准发现海量智能电能表的异常个体,提出了一种基于随机矩阵的海量智能电能表异常个体定位方法.提出了智能电能表健康状态的多个参数表征方法,包括比差、角差、温度、湿度、震动等非电气量参数和一次电压、磁场等电气参数.为了更加准确全面地对智能电能表的状态进行评估,将智能电能表的实时数据、仿真数据和历史运行数据等作为数据源,选取智能电能表健康状态时的参数构建高维随机矩阵进行分析,实现了智能电能表异常个体的定位.结合南网新一代智能电能表实际数据验证了文章所提方法的有效性,以期为我国智能电能表发展高效低成本的计量装置检验提供技术借鉴. |
| Abstract_FL | Smart meters are the core device for electricity metering and billing,which is related to the economic interests of owners,power grids and other parties.It has the characteristics of a large number and complex operating environment.In order to effectively massive smart meters,a random matrix-based method for locating abnormal individuals of massive smart meters is proposed.A number of parameter characterization methods for the health of smart meters are proposed,in-cluding non-electrical parameters such as ratio difference,angular difference,temperature,humidity,vibration,and elec-trical parameters such as primary voltage and magnetic field.In order to evaluate the state of the smart meter more accu-rately and comprehensively,the data obtained from the test of the smart meter,simulation data and historical operating da-ta are used as the data source,and the parameters of the health state of the smart meter are selected to construct a high-di-mensional random matrix,to realize the positioning of abnormal individuals of smart meters.In order to provide technical reference for the development of high efficiency and low cost metering device inspection of smart meters in China,the ac-tual data of the new generation smart meter in China Southern Power Grid is used to verify the effectiveness of the method in this paper. |
| Author | 周尚礼 石少青 连新凯 张乐平 谢文旺 |
| AuthorAffiliation | 中国南方电网有限责任公司,广州 510623%南方电网数字电网研究院有限公司,广州 510623%河南许继仪表有限公司,河南许昌 461000 |
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| Author_FL | ZHOU Shangli SHI Shaoqing LIAN Xinkai ZHANG Leping XIE Wenwang |
| Author_FL_xml | – sequence: 1 fullname: SHI Shaoqing – sequence: 2 fullname: ZHOU Shangli – sequence: 3 fullname: XIE Wenwang – sequence: 4 fullname: ZHANG Leping – sequence: 5 fullname: LIAN Xinkai |
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| Keywords | smart meter 智能电能表 异常定位 随机矩阵理论 random matrix theory state evaluation 状态评估 abnormal location |
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| Title | 基于随机矩阵的海量智能电能表异常个体定位方法 |
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