Pollution discharge prediction method based on industrial user electricity consumption data

Abstract

The invention relates to a pollution discharge prediction method based on industrial user electricity consumption data. The method has the following steps: 1), obtaining industrial user electricity consumption sample data; 2), performing preprocessing on the sample data; 3), establishing a complex network representing relations between industrial users in industries according to the pre-processed data; 4), predicating the electricity quantities of the industrial users according to the complex network; 5), according to the industrial user electricity consumption sample data, establishing a quantity relation between the electricity quantities of industrial enterprises and direct pollutant discharge amounts; and 6), according to the prediction result in the step 4) and the quantity relation in the step 5), predicting the direct pollutant discharge amounts of the industrial users. Compared to the prior art, the method provided by the invention has the advantages of high accuracy, high reliability and the like.

Description

Technical field [0001] The invention relates to the field of big data processing, in particular to a method for predicting pollution emissions based on industrial user electricity data. Background technique [0002] As the level of social and economic development continues to increase, the relationship between the national economy and power consumption has become closer. From the current point of view, industrial enterprises are the main power consumers, and changes in the power consumption of industrial users will have an important impact on the power consumption and power dispatch of the entire society. The main influencing factors of the power consumption of industrial users are themselves. Production behavior and industry prosperity. [0003] In the face of frequent haze weather, environmental problems and multiple constraints of economic development, how to use energy efficiently and cleanly, improve atmospheric environmental governance, and solve the balance of industrial po...

AI Technical Summary

Problems solved by technology

Traditional environmental monitoring and quality improvement can no longer meet the needs of the intelligent era. It is necessary to establish a new, high-frequency, and real-time supervision system to conduct demand-side management for industrial users.