Energy consumption statistical method based on table bottom value

Abstract

An energy consumption statistical method based on a table bottom value comprises the steps that minute, hour, day, month and year energy consumption statistics is carried out based on a previous value; performing elimination statistics processing on abnormal data; and carrying out the special treatment of meter bottom value reduction after meter replacement is carried out. By giving the energy consumption statistical method based on the last table bottom value, compared with a traditional calculation method for calculating hour consumption by accumulating minute consumption, calculating dailyconsumption by accumulating hour consumption, calculating monthly consumption by accumulating daily consumption and calculating annual consumption by accumulating monthly consumption, errors of all subsequent data caused by errors of one datum are avoided. Meanwhile, abnormal data and meter bottom value reduction logic for meter replacement are processed, so that statistics is more accurate and perfect. According to the energy consumption statistical method, a more accurate energy consumption statistics means is provided for an energy management system, and the energy consumption statistical method has more practical application value for energy consumption statistics.

Description

technical field [0001] The invention belongs to the technical field of energy management, and relates to an energy consumption statistical method based on a bottom value, in particular to an energy consumption statistical method based on a bottom value last time. Background technique [0002] Energy has always been an important topic in the issue of sustainable development, and energy conservation has become the task of the whole society. Nowadays, the energy crisis is becoming more and more serious, and the energy shortage has become an important factor for the sustainable development of the economy. Energy conservation and consumption reduction have become an arduous task that must be completed. The first prerequisite for realizing energy saving and consumption reduction is to comprehensively monitor energy and conduct energy consumption statistics correctly. [0003] There are many energy consumption systems on the market. After investigation, it is found that the calcul...

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Problems solved by technology

However, the disadvantage of this method is that once an abnormality occurs in the data of a bottom layer at a certain moment, all subsequent data in the upper layer will be wrong.

For example, if at a certain moment, the minute data is wrong due to the abnormality of the meter data, then all subsequent hour, day, month, and year data will have statistical errors

[0004] Therefore, it is an important research content for those skilled in the art to avoid the occurrence of energy consumption statistics errors in high-level data due to errors in some low-level data through hierarchical statistics in the traditional sense.

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