Multi-temporal dimension data fusion method for large data of power distribution network

Abstract

The invention discloses a multi-temporal dimension data fusion method for the large data of a power distribution network. The method comprises the steps of classifying data according to data sources; setting a statistical cycle and determining a sliding window value; calculating the smoothing factor value and the predictive value of the n cycle; calculating the deviation degree between an actual monitoring value and the predictive value of the n cycle; comparing the deviation degree with a preset deviation degree; when the deviation degree is larger than the preset deviation degree, calculating and obtaining a corrected sliding window value; when the deviation degree is smaller than the preset deviation degree, obtaining actual monitoring values obtained during several cycles from the n cycle and ranking the monitoring values according to the numbers of the cycles to obtain a window data set; calculating the weight coefficient of each data; calculating to obtain reported data; adding the reported data obtained through calculation to a similar reporting data set; and forming a new data set based on similar reporting data sets obtained through calculation. According to the technical scheme of the invention, the sliding window value can be dynamically adjusted. Meanwhile, data within a window can be fused according to weight factors in real time, so that the better data fusion effect is ensured. Moreover, a data basis is provided for upper-layer services.

Description

technical field [0001] The invention relates to a multi-temporal dimension data fusion method for distribution network big data, belonging to the technical field of data fusion. Background technique [0002] The concept of data fusion was born in the 1970s, but it directly promoted its development after entering the 1990s. With the rapid development of computer technology and communication technology, and the increasingly close relationship between them, as a data processing Emerging technology--data fusion technology has been developing at a rapid speed in recent years. The scope of data fusion research is wide. The data fusion technology originally aimed at military applications can also be used in industry and agriculture, such as resource management, urban planning, weather forecasting, crop and geological analysis and other fields. The basic purpose of data fusion is to obtain more information through certain regular data combinations rather than any individual element...

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is to overcome the deficiencies of the existing technology, provide a multi-temporal dimension data fusion method for distribution network big data, and solve the problem that when the data fluctuates severely due to the fixed smoothing coefficient in the existing data fusion method, The problem that the predicted data value has a large error

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