Predicting NOx and SO2 Emissions in CHP Systems with TEBA-Net for Sustainable Operations

Abstract

AbstractThis study presents TEBA-Net, an advanced deep learning model for simultaneous prediction of NOx and SO2 emissions from coal-fired combined heat and power (CHP) plants. The model integrates temporal convolutional networks (TCN), bidirectional ...Practical ApplicationsThe TEBA-Net model and its associated dynamic chemical treatment strategy offer significant industrial relevance by enabling real-time optimization of limestone slurry and ammonia injection rates in combined heat and power (CHP) ...