In response to the problems of long carbon emission accounting time,large errors in continuous emission monitoring systems,and difficulties in fitting traditional models in power companies,the ResNet-BiLSTM model for carbon emissions in the power industry was successfully constructed,which combined with the characteristics of fuel combustion in power companies and the existing online monitoring results of pollutants.The model was validated using data from 113 power companies in Zhejiang Province as samples.The results showed that compared with current mainstream data prediction algorithms such as Regression,RNN and BPNN models,the average absolute percentage error of ResNet-BiLSTM model was 5.7,4.1,and 2.8 percentage points lower,respectively.The prediction of carbon emissions was closer to the calculation of carbon emissions fluctuations by power companies,and the prediction accuracy(96％)was the highest.The successful application of the ResNet-BiLSTM model not only provided a new approach for carbon emission prediction for power companies,but also supported the improvement of carbon emission data supervision efficiency for relevant management departments.
维普
万方数据