Energy Consumption Prediction Model of Wastewater Treatment Plant Based on Stochastic Configuration Networks

Abstract

In the face of increasingly scarce fresh water resources, the treatment of urban sewage has become an important resource conservation. Sewage treatment is a high power consumption industry, the effective prediction of power consumption has a far-reaching impact on the energy saving optimization of sewage treatment plant. Aiming at the problems of uneconomic scale allocation, insufficient load rate and excessive energy consumption of current sewage treatment facilities in China, this paper establishes an energy consumption prediction model for sewage treatment plants based on Stochastic Configuration Networks. In order to verify the effectiveness of the method, the modeling and simulation were completed with the help of MATLAB software, Stochastic Configuration Networks model is trained until the best accuracy is achieved. Stochastic Configuration Networks is compared with BP neural network modeling method. It is found that the prediction error of the residential energy consumption prediction model is small, which has important value for policy makers in planning new sewage treatment plants and making management plans to improve the energy efficiency of sewage treatment.