Artificial intelligence prediction model construction method applying global big data of power distribution network

Abstract

The invention discloses an artificial intelligence prediction model construction method applying global big data of a power distribution network. The invention discloses an artificial intelligence prediction model construction method applying global big data of a power distribution network. The method is characterized by comprising the following steps; constructing an artificial intelligence prediction model based on the global big data of the power distribution network; various models of deep learning are adopted; information is obtained from different platforms and devices such as various online monitoring systems, unmanned aerial vehicles or robot inspection systems, PMS production management systems, OMS systems, monitoring systems, electric energy management systems and intelligent interruptions. By considering the load change trend, the feeder line transfer capability, the post-accident electric quantity loss rate, the post-accident electricity consumption household number loss rate and the important user influence degree, the risk prediction analysis is realized, the risk sources of historical risks can be counted, and the risk source influence importance degree sorting is realized.

Description

technical field [0001] The invention relates to the field of power grids, in particular to a method for constructing an artificial intelligence prediction model by applying big data in the whole area of ​​a distribution network. Background technique [0002] With the increasing complexity of the distribution network, the overall coverage area is wide, the operation and maintenance service is complex, the equipment is changed frequently, the network connection is diverse, and the operation mode is changeable, resulting in complex and changeable distribution network faults and frequent load changes . In order to better deal with key links such as distribution network load changes and equipment failures, it has become particularly urgent to provide effective power supply reliability analysis methods. Power supply reliability is affected by system load, component reliability performance, component electrical performance and grid structure. Through research, if the operating dat...

AI Technical Summary

Problems solved by technology

[0002] With the increasing complexity of the distribution network, the overall coverage area is wide, the operation and maintenance business is complex, the equipment changes frequently, the network connection is diverse, and the operation mode is changeable, which leads to complex and changeable distribution network faults and frequent load changes.