中国电力 ›› 2017, Vol. 50 ›› Issue (8): 98-105.DOI: 10.11930/j.issn.1004-9649.2017.08.098.08

• 电网 • 上一篇    下一篇

电能表故障与地域气候、行业负荷关系研究

薛阳1, 杜新纲2, 张蓬鹤1, 张加海3, 邹宇汉3, 彭楚宁2   

  1. 1. 中国电力科学研究院,北京 100192;
    2. 国家电网公司,北京 100031;
    3. 烟台东方威思顿电气股份有限公司,山东 烟台 264011
  • 收稿日期:2016-12-01 出版日期:2017-08-25 发布日期:2017-08-25
  • 作者简介:薛阳(1987—),男,山西万荣人,硕士,工程师,从事电能计量设备故障诊断、失效分析与可靠性研究。E-mail:xueyang3@epri.sgcc.com.cn
  • 基金资助:
    国家电网公司科技项目(计量装置运行状态评估与寿命诊断分析技术)(JL7114035)

Research on the Relationship Between Electric Energy Meter Fault and Regional Climate & Load in Different Industries

XUE Yang1, DU Xingang2, ZHANG Penghe1, ZHANG Jiahai3, ZOU Yuhan3, PENG Chuning2   

  1. 1. China Electric Power Research Institute, Beijing 100192, China;
    2. State Grid Corporation of China, Beijing 100031, China;
    3. Yantai Dongfang Wisdom Electric Co. Ltd., Yantai 264011, China
  • Received:2016-12-01 Online:2017-08-25 Published:2017-08-25
  • Supported by:
    This work is supported by Science and Technology Project of SGCC (Operation State Evaluation and Life Diagnosis Analysis Technology of Electric Energy Meter) (No.JL7114035)

摘要: 通过对电能表运维地区气候环境、电网负荷的数据采集、量化与聚类分析,依气候特征划分用电地区,同时按电网负荷特征将用电行业分类,结合电能表在各个地区与用电行业的故障统计数据,最终,将电能表按气候严酷程度划分6个地区,作为区域化配置电能表的依据;同时,从对烧表故障影响较大的7种负荷入手进行负荷特征描述与研究,推进了实验室条件下的电能表故障和失效机理的研究,利于对电能表从元器件筛选、设计、生产工艺等各个环节提出改进措施,降低电能表故障率。

关键词: 电能表, 气候, 负荷, 故障, 聚类分析

Abstract: Based on collection, quantification and cluster analysis of climate and power grid load data in operation and maintenance area of electric energy meter, meter operation regions are divided by climatic characteristics and user industry are classified by load characteristics. The clustering method is validated by statistical data of energy meter fault in each region and electricity industry. Six regions are classified according to climate severity as basis for electric energy meter selection. The description and study of the load characteristics, started with seven kinds of loads which have greater impact on meter fault, facilitates research of meter fault and failure mechanism under laboratory condition. Those analyses can not only improve component selection, design and production process, but also reduce electric energy meter fault rate.

Key words: electric energy meter, climate, load, failure, cluster analysis

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