Multi-Step Ahead Prediction of Main Steam Flow Using PCA and Pyraformer in MSWI Process

The effective multi-step forecasting of the main steam flow in municipal solid waste incineration (MSWI) can help the steam power generation module to make decision responses in advance and control the system effectively. As the main steam flow is affected by multiple process flows and the strong coupling between each process flow in the MSWI system, there are numerous variables affecting the main steam flow, and the variable redundancy is high, and the noise is high. This results in low accuracy of steam flow prediction. To solve the above problem, a multi-step prediction method based on principal component analysis (PCA) and Pyraformer model is proposed. Based on the multi-modular MSWI process and low coupling between modules, we divided the variables affecting the main steam flow into four parts and carried out PCA dimension reduction treatment. The processed data was input into the Pyraformer model to obtain the multi-step predicted value of the main steam flow. Pyraformer is a time series prediction model based on Transformer, which can capture different range of time dependencies and has better computational efficiency and prediction effect for prediction tasks with more variable input. Experiments show that the proposed method has high prediction accuracy and stability, which can provide a better basis for advanced decision making of steam power generation tasks and other processes of MSWI.