Building energy consumption prediction method and system based on big data

Abstract

The invention discloses a building energy consumption prediction method and system based on big data, and relates to the field of building energy consumption monitoring. The method comprises the steps: obtaining the current energy consumption reference data and historical energy consumption sample data of a to-be-detected building; determining target energy consumption data close to the energy consumption reference data from the energy consumption sample data based on the energy consumption trend between the target energy consumption data and the energy consumption reference data and a presetrule; determining a second candidate energy consumption item set composed of candidate energy consumption items closer to the energy consumption reference data from the target energy consumption databased on the relationship between the respective energy consumption trends of the target energy consumption data and the energy consumption reference data; and finally predicting an energy consumptionresult based on the second candidate energy consumption item set capable of accurately reflecting the consumption trend of the energy consumption reference data obtained after multiple times of screening and the reference energy consumption trend. Compared with the prior art that the energy consumption result is predicted without performing any screening processing on the historical energy consumption data, the steps of the method of the invention can enable the predicted energy consumption result to more accord with the real situation.

Description

technical field [0001] The invention relates to the field of building energy consumption monitoring, in particular to a method and system for predicting building energy consumption based on big data. Background technique [0002] With the improvement of people's living standards and the recommendation of urbanization, more and more buildings have been built. Whether it is a commercial building for living or an office building for office, there is related energy consumption in the construction process and use process, and building energy consumption is an important reference index for cost control and building management. , due to the large number of energy consumption detection items involved, it is not easy to realize real-time monitoring, and the prediction of building energy consumption can only be processed based on simple statistics based on historical data, and the obtained energy consumption prediction results are not reliable. The high reference value cannot correct...

AI Technical Summary

Problems solved by technology

Whether it is a commercial building for living or an office building for office, there is related energy consumption in the construction process and use process, and building energy consumption is an important reference index for cost control and building management. , due to the large number of energy consumption detection items involved, it is not easy to realize real-time monitoring, and the prediction of building energy consumption can only be processed based on simple statistics based on historical data, and the obtained energy consumption prediction results are not reliable. High reference value, unable to correctly predict the real development trend of building energy consumption

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