Prediction and Optimization of Unburned Carbon Reduction in Fly Ash and Bottom Ash Using Multiple Linear Regression Method

Abstract

Coal-fired thermal power plants face increasing scrutiny due to their high carbon emissions and inefficiencies stemming from unburned carbon in combustion by-products. This study presents a novel, integrated approach for optimizing combustion parameters to significantly reduce unburned carbon content in both fly ash and bottom ash, thereby enhancing combustion efficiency and environmental performance. A combination of analytical experimentation and multiple linear regression modeling was employed. The investigation focused on the effects of burner tilt, wind box pressure, primary air header pressure, and oxygen levels. The study aimed to understand how these factors influence unburned carbon levels during biomass–coal co-firing. The proposed multiple linear regression model achieved a predictive accuracy with an R² value of 0.70, root mean square error (RMSE) of 0.3161 (fly ash) and 0.4666 (bottom ash), and mean absolute error (MAE) of 0.2403 and 0.3810, respectively. Under optimized operational conditions—including a burner tilt of −7°, wind box pressure of 105 mmWC, and oxygen concentration of 2.9%—unburned carbon in fly ash was reduced from 3.0% to 1.6%, and in bottom ash from 4.6% to 2.9%. These conditions also led to a 98.75% reduction in carbon monoxide emissions, underscoring the enhanced combustion efficiency. This study is distinguished by its real-time application of statistical optimization in plant operations, the first-of-its-kind integration of biomass pellet co-firing analysis into this framework, and its potential to inform sustainable energy practices globally. The findings offer actionable pathways for coal-based thermal plants to reduce emissions, cut operational costs, and align with international decarbonization goals. These improvements translate to increased fuel utilization, reduced particulate emissions, and cost savings in ash disposal and auxiliary power consumption.