Method forpredicting the operation status of coal electricity desulfurization and denitration based on PSO-Attention-LSTM algorithm
HOU Shen
ZHU Yeqing
LI Xiang
PAN Yun
Abstract：The normal operation of coal-fired desulfurization and denitrification has a significant impact on the safety and stability of the power system.However,traditional prediction methods have the problem of low accuracy.An improved PSO-Attention LSTM method for predicting the operational status of coal-fired desulfurization and denitrification is proposed.Firstly,establish the main indicators and their weight indicators for optimizing the operation status of coal-fired power desulfurization and denitrification.In the data input stage,obtain the spatiotemporal characteristics related to the operation status data through PSO-Attention LSTM,predict the operation status of coal-fired power desulfurization and denitrification,and complete the warning information of potential faults in coal-fired power desulfurization and denitrification.The experimental results show that the prediction accuracy of this prediction method for the operational status of coal-fired power desulfurization and denitrification is 84％,which can effectively and accurately predict the operational status of coal-fired power desulfurization and denitrification.It can be used as a reference assistance for the operation and maintenance management of coal-fired power desulfurization and denitrification.
Keywords：coal electric desulfurization and denitrificationstate predictionPSOattention mechanismLSTM
Publication Date：2024-08-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 60-64 )