Statistical Evaluation and Correlation Analysis of Monthly Coal Quality: Case Study in a Coal-Fired Power Plant (IPP-Kalteng-1)
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Coal quality consistency is essential for maintaining stable operation in coal-fired power plants. This study presents a statistical evaluation of monthly composite coal quality data collected in 2025 from a coal-fired power plant in Central Kalimantan (IPP-Kalteng-1), Indonesia. Key parameters—including total moisture, inherent moisture, ash content, volatile matter, fixed carbon, sulfur content, and calorific value—were analyzed in accordance with ASTM standard methods. Descriptive statistics and the coefficient of variation were applied to assess parameter stability, while Pearson correlation analysis was used to examine relationships between coal properties and calorific value. A multiple linear regression model was developed to evaluate the combined influence of total moisture, ash content, and fixed carbon. Model performance was assessed using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and the coefficient of determination (R²). Results indicate that calorific value remained stable throughout the study period, with low variability. Ash content and total moisture exhibited negative relationships with calorific value, whereas fixed carbon showed a positive effect. Although the regression model demonstrated moderate predictive accuracy (MAE = 179 kcal/kg; RMSE = 184 kcal/kg), the low R² value (0.05) suggests that additional factors influence calorific value variability.
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Copyright (c) 2026 Ikhwan Arifin, Puma Manggala V A, Subhan Hasisi
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