配网主站系统的配变运维关键技术分析
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引用本文:钱玉麟1,张洋1,姜建2,郑伟彦2,吕坚1.配网主站系统的配变运维关键技术分析[J].电网与清洁能源,2018,34(2):36~42
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作者单位
钱玉麟1 1. 国电南瑞科技股份有限公司 
张洋1 1. 国电南瑞科技股份有限公司 
姜建2 2. 国网浙江省电力有限公司 杭州供电公司 
郑伟彦2 2. 国网浙江省电力有限公司 杭州供电公司 
吕坚1 1. 国电南瑞科技股份有限公司 
基金项目:国家重点研发计划项目(2017YFB0902600)
中文摘要:配网设备在供电环节起着至关重要的作用,设备的状态监测及运维检修直接影响配网供电质量和稳定性,而配网变压器是配网设备中非常重要的部分,其运行可靠性很大程度上决定了电网运行的安全性。供电企业越来越关注供电保障与稳定性,以提升用户的用电质量,而传统的数据分析模式已无法满足规模日益增大的配电网规模。主要针对目前配变在线状态监测功能的状况及配变设备运维的重要性,设计网格化区域管理方式,基于设备主人的运维理念,强化设备主人对现场设备的负荷、环境监控和隐患消除能力,结合负荷预警和智能告警,改善目前处理配变设备异常的被动应对状况。
中文关键词:区域化  配变  运维检修  负荷预测  设备主人
 
Key Technology Analysis of Transformer Operation and Maintenance in Distribution Automation Main Station System
Abstract:The distribution network equipment plays a crucial role in the power supply link. The condition monitoring and maintenance of the equipment directly affect the quality and stability of the power distribution network. The distribution transformer is a very important part of the distribution network equipment, whose operational reliability largely determines the safety of the grid operation. Recently, power supply companies are paying more and more attention to the power supply security and stability so as to improve the power quality of users. However, the traditional data analysis models are hardly able to meet requirements of the increasing scale of distribution networks. This article focuses on the current status of distribution transformer online monitoring, as well as the importance of equipment operation and maintenance, and proposes a concept of operation and maintenance based on the device ownership, and designs a grid-based regional management model to strengthen the equipment owner’s monitoring capability of the field equipment and environment and its elimination ability of hidden dangers. Together with the load warning and intelligent alarm, the proposed method helps to improve the current passive response of the handling of abnormalities in the distribution transformer equipment.
keywords:regional grid  transformer  operation and maintenance  load forecasting  equipment master
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