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智能变电站二次设备状态的灰色层次聚类评估
引用本文:王洪彬,曾星星,张友强,欧阳金鑫,熊小伏,魏甦.智能变电站二次设备状态的灰色层次聚类评估[J].重庆大学学报(自然科学版),2016,39(3):28-36.
作者姓名:王洪彬  曾星星  张友强  欧阳金鑫  熊小伏  魏甦
作者单位:1. 国网重庆市电力公司电力科学研究院,重庆,401123;2. 国家电网公司西南分部,成都,610000;3. 重庆大学输配电装备及系统安全与新技术国家重点实验室,重庆,400044
基金项目:重庆市科技攻关(应用重点)资助项目(cstc2012gg-yyjsB90003)。
摘    要:智能变电站作为智能电网建设的核心部分,其二次设备运行状态关系着电力系统的安全性和稳定性。针对智能变电站二次设备故障原因错综复杂以及运行状态信息不完全的特征,建立智能变电站二次设备状态评估层次模型和指标体系,引入灰色聚类对智能变电站二次设备状态进行灰色分类以及构建灰色白化权函数,并利用层次分析法计算状态指标权重,结合层次分析法与灰色聚类对智能变电站二次设备进行定性和定量的状态评估。实例分析验证了文中方法有效易行,为智能变电站二次设备状态检修工作提供了理论依据。

关 键 词:智能变电站  二次设备  状态评估  层次分析法  灰色聚类
收稿时间:2/5/2016 12:00:00 AM

Grey hierarchy cluster assessment on the operating condition of intelligent substation secondary equipment
WANG Hongbin,ZENG Xingxing,ZHANG Youqiang,OUYANG Jinxin,XIONG Xiaofu and WEI Su.Grey hierarchy cluster assessment on the operating condition of intelligent substation secondary equipment[J].Journal of Chongqing University(Natural Science Edition),2016,39(3):28-36.
Authors:WANG Hongbin  ZENG Xingxing  ZHANG Youqiang  OUYANG Jinxin  XIONG Xiaofu and WEI Su
Institution:Chongqing Electric Power Research Institute, Chongqing 401123, P. R. China,State Grid Corporatron of China Southwest Branch, Chengdu 610000, P. R. China,Chongqing Electric Power Research Institute, Chongqing 401123, P. R. China,State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing 400044, P. R. China,State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing 400044, P. R. China and Chongqing Electric Power Research Institute, Chongqing 401123, P. R. China
Abstract:Intelligent substation is the core part of smart grid, and the operating condition of its secondary equipment concerns the security and the stability of the power system. For the features of intricate failure reasons and incomplete operating status information of intelligent substation secondary equipment, we established a hierarchical model and an index system to assess its operating condition. Grey clustering algorithm was introduced to classify the conditions and the whitening weight function of grey was established first, and then the analytic hierarchy process was used to calculate the weight of status indicators. Finally, the analytic hierarchy process and grey clustering algorithm was combined to qualitatively and quantitatively assess the operating condition. Practical case study verifies the effectiveness and feasibility of this method and it provides a theoretical basis for the secondary-equipment-condition-based maintenance work.
Keywords:substations  secondary equipment  condition assessment  analytic hierarchy process  grey clustering algorithm
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