Method for data exception judgment and repairing on the basis of energy statistics

Abstract

The invention specifically relates to a method for data exception judgment and repairing on the basis of energy statistics. The method comprises a judgment process and a repairing process. The judgment process comprises the following steps that: according to whether the original data aN of a current particle size is obtained or not, judging whether the particle size N is collected data which needsto be repaired or not; according to whether the adjacent particle size statistical value N of the particle size N is smaller than 0 or not, judging whether the particle size N is collection data which suddenly becomes small and needs to be repaired; according to whether the adjacent particle size statistical value N of the particle size N is that value N is greater than or equal to k*A or not, judging whether the collection data suddenly becomes big and needs to be repaired or not. The repairing process comprises the following steps that: directly adding a historical average value, and if data which is collected subsequently is recovered to an original base number, repairing is carried out according to a ratio of adjacent particle size statistical values. By use of the method, original collection data exception caused by equipment problems in an energy related management system can be intelligently judged, and in addition, the statistics data of an exceptional scene is repaired.

Description

technical field [0001] The invention relates to the field of smart grid and energy metering, in particular to a method for judging and repairing abnormality based on energy statistical data. Background technique [0002] The energy management statistics system involved in the present invention includes various energy classification and sub-item equipment, including electricity meters, water meters, gas meters, heat meters, oxygen meters and the like. In the energy-related management system, the remote pulse data of the energy metering equipment is usually input into the relevant energy platform or system, and the platform or system processes and stores the data. The quality of statistical value data in the process of processing has always been a relatively difficult problem to solve, mainly manifested in: the device layer data itself is unstable, and the proportion of device data not reported according to the actual value caused by device failure is quite high; network envir...

AI Technical Summary

Problems solved by technology

The quality of statistical value data in the process of processing has always been a relatively difficult problem to solve, mainly manifested in: the device layer data itself is unstable, and the proportion of device data not reported according to the actual value caused by device failure is quite high; network environment factors cause The reported value of the data is misplaced; the environment measured by the equipment is unstable, resulting in abnormal environmental data, etc.

In the case of partial data mutation or loss, the data statistics of energy management-related systems will become worthless. In order to effectively solve the abnormal statistical data, it is necessary to provide various energy management platforms and systems. In order to judge the abnormality of the collected data and carry out the method of repairing the abnormality,

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