Line Loss Management Of Low Voltage Transformer District Based On Power Big Data

With the development of UPIoT(Ubiquitous Power Internet of Things),it has become the focus of power enterprises to effectively research and mine the massive electric power big data accumulated over the years.Line loss is an important index to measure the design,production technology and management of power enterprises.Line loss management has a significant impact on the economic benefits of power enterprises.The management of area line loss is an important part for line loss management.The key point of this paper is how to apply power big data in the management of area line loss.This paper studies the development situation of big data at home and abroad and the application of big data in all walks of life.For the large workload of line loss detection in low-voltage area,and it is difficult to distinguish the loss degree of line loss in low voltage area.It is proposed a method that the management of line loss by big data in low voltage area.In order to realize the rapid positioning of the problem area.It can distinguish the loss degree of line loss in low-voltage area.It can carry out anti-electricity-stealing analysis to problem area.The low-voltage transformer district is divided into abnormal transformer district with obvious line loss,abnormal transformer district with line loss but less obvious transformer district to be promoted,and normal transformer district with acceptable line loss.To help the staff to distinguish the extent of line loss in the.It is convenient for priority maintenance and treatment of low-voltage transformer district with serious line loss.And repair the low voltage transformer district with lighter line loss.It were grasped and solved the main problems of line loss management in low voltage transformer district.It can effectively improve the working efficiency of managers and improve the economic benefits of line loss management in power enterprises,which reflects the lean line loss management in low-voltage transformer district.After the main problems are solved,the transformer district to be upgraded can be further reduced line loss.The anti-electricity-stealing analysis on the low-voltage transformer district can quickly locate the transformer district where there may be electricity-stealing behavior,and help enterprises to further verify the possible electricity-stealing risk.The research of this paper has certain reference value for line loss management in low voltage transformer district.In this paper,in the face of a large number of big power data,data preprocessing is first carried out to screen out the line loss data in the low-voltage transformer district.The processed data source was made into a visual worksheet with the help of Tableau software,and the line loss data was visualized,and the relationship between the line loss data in the low-voltage transformer district was analyzed,and the anti-electricity-stealing analysis was carried out in the low-voltage transformer district.It were performed on the line loss data by K-means clustering analysis,visual analysis and boxplot analysis.It has summarized the threshold range of each line loss index corresponding to the abnormal transformer district,the transformer district to be lifted and the normal transformer district.Finally,it has built the visual interactive platform of line loss anomaly analysis in the transformer district.By referring to the threshold range of relevant line loss indexes,the problem area can be quickly located and searched,and the loss degree of line loss in the transformer district can be distinguished.And it can quickly locate the transformer district where may be has electricity-stealing behavior.