摘要
针对当前配电线路布局不合理、存在线损异常的问题,该研究设计出民航10 kV供配电线路的自动化主站系统,采集并存储配电线路的运行数据,设计出配电线路信息采集模块,并加入故障限流功能,防止线路中故障电流电压对模块采集精度产生影响。基于深度学习神经网络建立线损分析模型,并识别统计线损率与其它变量之间的关系,对数据集中缺失的电力信息进行统计线损率预测填充。通过试验,该方法损失电量最多减小了608 kWh,线损计算误差最小为0%。
Aiming at the problems of unreasonable layout of current distribution lines and abnormal line loss,this research designs an automatic master station system for civil aviation 10 kV power supply and distribution lines.The system can collect and store the operation data of distribution lines.It also designs a distribution line information collection module,and adds the fault current limiting function to prevent the fault current and voltage in the line from affecting the acquisition accuracy of the module.A line loss analysis model is established based on a deep learning neural network,the relationship between the statistical line loss rate and other variables is identified,and the missing power information in the data set is predicted and filled with the statistical line loss rate.Through experiments,the power loss of this method is reduced by 608 kWh at most,and the calculation error of line loss is at least 0%.
作者
梁毅
LIANG Yi(Gansu Civil Aviation Construction(Group)Co.,Ltd.,Lanzhou 730020,China)
出处
《微型电脑应用》
2023年第11期152-155,159,共5页
Microcomputer Applications
关键词
配电线路
民航
线路优化配置
深度学习神经网络
线损分析
distribution line
civil aviation
line optimization configuration
deep learning neural network
line loss analysis
