Big data-based court line loss data deep mining analysis method

Abstract

The invention provides a big data-based court line loss data deep mining analysis method. The method comprises the steps of obtaining historical power data of a watt-hour meter in a court and power characteristic attributes of the court where the watt-hour meter is located; integrating the power data according to different buses, and calculating the power line loss of the buses according to different types of line loss models by the integrated power data; classifying the courts according to the power characteristic attributes of the courts where the buses are located, and training a court line loss fitting model by combining the power line loss of each bus in the courts; and calculating the real-time electric quantity unbalance rate of each bus, judging the transformer area where the fault bus is located, obtaining the electric power characteristic attribute of the current transformer area, taking the electric power characteristic attribute as the input of the transformer area line loss fitting model, and calculating the electric power prediction line loss of the current bus. According to the invention, through carrying out analysis and research on the bus watt-hour meter power data under the background of big data, the technical problems of difficult analysis and calculation of a large number of transformer area line loss rates, indefinite line loss rate control targets, incapability of judging transformer area line loss rate abnormity and the like in the prior art can be effectively solved.

Description

technical field [0001] The invention relates to the technical field of electric power line loss, in particular to a deep mining analysis method based on large data station area line loss data. Background technique [0002] In the power system, the line loss rate is the percentage of the loss of electric energy in the transmission process of the power grid to the power supply to the power grid, and it is the main indicator for evaluating the loss level of the power grid. Among the various voltage levels that make up the power grid, the power loss generated by the distribution network of 10kV and below accounts for a large part of the total network loss, which is the key factor causing the high line loss rate of the power grid. Since there are many electric energy measuring instruments and equipment in the station area, factors affecting line loss may include wiring errors, completion of data information collection, error rate of CT magnification at gateways, and power theft b...

AI Technical Summary

Problems solved by technology

[0005] In view of this, the present invention provides a deep mining and analysis method based on large data station area line loss data. By carrying out analysis and research on the power data of bus watt-hour meters under the background of big data, it can effectively solve the problem of a large number of station area line loss data in the prior art. It is also an effective way to deepen the construction of smart grid and promote the development of electric power big data management technology.

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