State analysis method of power utilization information collector based on big data parallel computing

Abstract

The invention discloses a state analysis method of a power utilization information collector based on big data parallel computing. The method comprises that 1) a collection terminal is taken as a unit, and a main station receives data collected by the collection terminal, and classifies the data; 2) each type of data is cached in a distributed manner; and 3) a resource dynamic distribution service is used to distribute resources dynamically aimed at the processing speed of each type of data according to the data bulk, data computing complexity, data priority and computing resources of each data type. According to the invention, the operation state analysis speed of the present collector is improved, and the method for collecting the operation state of the collector is given on the basis of the big data parallel computing technology. Power utilization behaviors of users can be analyzed, abnormity response speed is improved, electricity larceny behaviors are prevented, power supply quality and real-time line loss of the users are monitored, and it is ensured that the power grid runs safely and the power supply reliability is improved.

Description

technical field [0001] The invention belongs to the technical field of electric power big data calculation, and in particular relates to a state analysis method of power consumption information collection equipment based on big data parallel calculation. Background technique [0002] At present, the online monitoring of equipment operating status is realized by the principle of equal distribution of the number of computing queues. There are a large number of data with high computing responsibility allocated in the same computing queue, which leads to a long calculation time of online monitoring data results of equipment operating status, which is not conducive to Timely investigation of metering errors, analysis of user electricity consumption behavior, handling of electricity stealing behavior, guarantee of grid operation safety, analysis of orderly electricity consumption, and timeliness of obtaining distribution transformer status have been reduced. Contents of the inven...

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Problems solved by technology

[0002] At present, the online monitoring of equipment operating status is realized by the principle of equal distribution of the number of computing queues. There are a large number of data with high computing responsibility allocated in the same computing queue, which leads to a long calculation time of online monitoring data results of equipment operating status, which is not conducive to Timely troubleshooting of metering errors, analysis of user electricity consumption behavior, handling of electricity theft behavior, guarantee of grid operation safety, analysis of orderly electricity consumption, and reduced timeliness of distribution transformer status acquisition

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