摘要
当前电量信息采集设备线损故障检测存在检出率偏低、应用适用性较差问题,现提出一种电量信息采集设备线损故障自动检测方法。通过确定线损故障检测系统整体架构,将硬件部分分为主站、C/S分布式处理器与用户终端等模块,同时将软件划分为储存层、处理层与表示层,制定每个层次对应的任务,并对采集到的相同用户负荷数据做归一化处理。利用果蝇算法设计搜索操作,不断迭代优化果蝇群体中心位置。分别利用相关系数与相对距离指标实现时间序列的模式匹配,获取匹配度偏好程度,设定线损故障预警阈值,完成电量信息采集设备线损故障的自动检测。实验结果表明,该方法故障检出率高、适应性强,与传统方法相比具有更好的应用性能。
At present,there are some problems in line loss fault detection of electric quantity information acquisition equipment,such as low detection rate,poor applicability and so on. An automatic line loss fault detection method for electric quantity information acquisition equipment was proposed. By determining the overall architecture of the line loss fault detection system,the hardware was divided into modules such as master station,C/S distributed processor and user terminal. At the same time,the software was divided into storage layer,processing layer and presentation layer. The corresponding tasks of each layer were formulated,and the collected load data of the same user were normalized. The drosophila algorithm was used to design the search operation,and the central position of drosophila population was optimized iteratively. The correlation coefficient and the relative distance index were respectively used to realize the pattern matching of time series,obtain the matching degree preference,set the line loss fault early warning threshold,and complete the automatic detection of line loss fault of electric quantity information acquisition equipment. The simulation results show that this method has high fault detection rate,strong adaptability and better application performance compared with the traditional method.
作者
杨莉萍
王海云
丁冬
于希娟
王立永
吴红林
YANG Liping;WANG Haiyun;DING Dong;YU Xijuan;WANG Liyong;WU Honglin(Electric Power Research Institute of State Grid Beijing Electric Power Company,Beijing 100075,China;State Grid Beijing Electric Power Company,Beijing 100032,China)
出处
《电气传动》
2022年第19期75-80,共6页
Electric Drive
基金
国家电网有限公司科技项目(52022319003P)。
关键词
电量信息采集设备
线损故障
自动检测
负荷模式
时间序列
electric quantity information acquisition equipment
line loss fault
automatic detection
load mode
time series
