NOx emission prediction method based on attention mechanism LSTM (Long Short Term Memory) model

Abstract

The invention discloses a method for realizing NOx emission prediction based on an attention mechanism LSTM (Long Short Term Memory) model. The method comprises the following steps: (1) acquiring data from a power station boiler system operation database; (2) preprocessing the acquired data; (3) carrying out data sorting according to the data format requirement of the LSTM model; (4) using an Attention-LSTM (Long Short Term Memory) model for outputting the NOx emission amount; and (5) decoding the features output by the attention module, and outputting a predicted value. According to the method, the problem that model convergence is difficult due to the fact that the input time period is too long when the LSTM model is established through high-dimensional data can be solved, the phenomenon that important information is forgotten by the model in the modeling process is reduced, and the unit NOx emission prediction precision is improved.

Description

technical field [0001] The invention relates to an LSTM model based on attention mechanism to realize NO x Emissions Forecasting Methods. Background technique [0002] At present, my country's NOx produced by coal-fired power plants x There are three main methods of control: denitrification before combustion, denitrification during combustion and denitrification after combustion. Denitrification before combustion refers to the use of low-nitrogen fuels, but this method is very costly and technically difficult to achieve, so there are few engineering applications. Denitrification in combustion refers to reducing the amount of nitrogen oxides produced by boilers by improving the production process and combustion method and adopting low-nitrogen combustion technology. Denitrification after combustion is also called flue gas denitrification, which refers to the installation of denitrification devices in the tail flue of the boiler. The latter two denitrification methods are ...

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to provide an LSTM model based on attention mechanism to realize NO x The emission prediction method is used to solve the problem of difficulty in model convergence due to the long input time period when using high-dimensional data to establish the LSTM model, reduce the model's forgetting of important information during the modeling process, and improve the forecast unit NO x Emission Accuracy

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