Electric power data quality evaluation method and device
A quality assessment and power data technology, applied in the direction of electrical digital data processing, special data processing applications, digital data information retrieval, etc., can solve data disasters, power grid all-round, multi-view services, statistical data collection, sorting, and analysis difficulties and other issues to achieve the effect of accurate evaluation
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Embodiment 1
[0060] Such as Figure 1-2 As shown, the power data quality assessment method and its device provided by the present invention were used to analyze the data quality of power consumption information collected by a power company in a certain city in March 2015. The analysis work included overall normative analysis, file data quality Analysis, curve data quality analysis and historical data quality analysis are carried out in four aspects. The specific analysis is as follows (the data quality evaluation process of the criterion layer is Figure 5 ).
[0061] analysis object
[0062] The analysis is aimed at collecting detailed data of electricity consumption information in a certain city in 2015, and the specific analysis objects are shown in Table 1.
[0063] Table 1 List of database tables involved in data quality analysis
[0064]
[0065] This data quality analysis is based on Hadoop's big data analysis platform, making full use of HDFS distributed storage, Hive databas...
Embodiment 2
[0072] Such as image 3 As shown, the evaluation and verification of the basic layer data evaluation index system includes three levels: verification of time series data based on grid operation attribute values; data verification based on multiple data sources of power grid operation; correlation relationship between power grid operation data verification;
[0073] The verification level of time series data based on grid operation attribute values includes;
[0074] Threshold discrimination by time interval setting: Divide the regular data set into intervals of different intervals, set the maximum threshold and minimum threshold respectively with reference to their fluctuation ranges, and determine each data within the intervals of the maximum threshold and minimum threshold as meeting the interval threshold evaluation rules.
[0075] Data horizontal comparison: compare the data at a certain time with the data at the time before and after it, and if the difference is greate...
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