Method, system, device, and storage medium for predicting power consumption of energy Internet users

Abstract

The embodiment of the invention provides an energy Internet user electricity consumption prediction method. The method comprises the following steps of dividing user electricity consumption data to bepredicted into multiple target data blocks to be predicted; obtaining the correlation coefficient and the amplitude ratio between the target data block to be predicted corresponding to each time period and the plurality of reference target data blocks based on a prediction model corresponding to each time period after training; and carrying out weighted average on the reference target data blockwhose correlation coefficient is greater than a first preset threshold and an amplitude ratio is less than a second preset threshold, and taking the result of weighted average as the prediction resultof the target data block to be predicted. By using the energy Internet user electricity consumption prediction method and system, through the correlation coefficient and the amplitude ratio among autoregressive estimation sequence blocks, estimation matching and the weighted average are combined so as to realize accurate multi-point simultaneous electricity consumption prediction.

Description

technical field [0001] The embodiments of the present invention relate to the field of energy technology, and in particular to a method and system for predicting electricity consumption of energy Internet users. Background technique [0002] With the development of society and economy, global electricity consumption continues to grow rapidly, and the electricity consumption of household users accounts for a large part of it. Effective management and control of household electricity consumption is an important guarantee for the sustainable development of the global energy system. It can achieve energy saving and improve energy efficiency, reduce power supply costs and environmental pollution, and ensure the rapid and stable development of the global economy. . [0003] The Energy Internet is the most advanced energy system at present. Based on the ubiquitous and efficient information and communication infrastructure and the open and shared Internet concept, combined with the...

AI Technical Summary

Problems solved by technology

[0004] The traditional power consumption forecasting algorithm needs to use different power forecasting technologies according to the power consumption characteristics in different dimensions, and the existing forecasting method uses iterative estimation in the forecasting process, which causes the forecasting accuracy to decrease with the change of time and distance , so there is an urgent need for an energy Internet user electricity consumption prediction method to achieve accurate prediction of electricity consumption

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