Regional building energy consumption platform data mending method

Abstract

The invention relates to a regional building energy consumption platform data mending method. The method includes the following steps: receiving building energy consumption data from a data source in real time, mending missing data according to a meter number and the uploading time, and inserting complemented building energy consumption data to an energy consumption database to reduce manual data maintenance of maintenance workers; determining uploading time intervals, performing rapid treatment on building energy consumption data with short missing time intervals so as to reduce the data mending time; and performing special treatment on building energy consumption data with long missing time intervals, allowing the complemented energy consumption data to be close to actual energy consumption data and meet the energy consumption trend of a building per week to the greatest extend in the condition that the energy growth trends in adjacent 7 days are identical. Compared with the prior art, the method can mend the building energy consumption data in real time, allow the complemented energy consumption data to be close to the actual data to the greatest extent, and has a high execution efficiency.

Description

technical field [0001] The invention relates to a data patching method, in particular to a data patching method for a regional building energy consumption platform. Background technique [0002] In the regional building energy consumption monitoring platform, the repair scheme of building energy consumption data is one of the important technologies. Because it is a platform-level application, the energy consumption data of hundreds or even thousands of buildings are aggregated to the platform, the collector fails, and the abnormal problems of the instrument data itself occur from time to time. If the situation is serious, it will directly lead to the loss of the summary data of the platform. , unable to effectively count the energy consumption of problematic buildings. The traditional data patching method is to use the average of two adjacent effective energy consumption data to fill in the missing energy consumption data. In addition, the traditional repair method is most...

AI Technical Summary

Problems solved by technology

Because it is a platform-level application, the energy consumption data of hundreds or even thousands of buildings are aggregated to the platform, the collector fails, and the abnormal problems of the instrument data itself occur from time to time. If the situation is serious, it will directly lead to the loss of the summary data of the platform. , unable to effectively count the energy consumption of problematic buildings

The traditional data patching method is to use the average of two adjacent effective energy consumption data to fill in the missing energy consumption data. In addition, the traditional repair method is mostly delayed processing, and the operation and maintenance personnel cannot timely see the relatively accurate summary of energy consumption data, resulting in the inability to judge the operation of the building equipment in a timely manner. operating conditions, according to some unnecessary losses

Images