Unified Semi-Empirical Models for Predicting or Estimating the Heating Value of Coal and Related Properties – Theoretical Basis and Thermochemical Implications. Issue 8 (2nd August 2020)

• Record Type: Journal Article
• Authors: Go, Alchris Woo; Agapay, Ramelito C.; Ju, Yi-Hsu; Conag, Angelique T.
• Is Part Of: Combustion science and technology. Volume 192:Issue 8(2020)
• Page Start: 1449
• Page End: 1474
• Publication Date: 2020-08-02
• Subjects: Coal -- elemental analysis -- heating value -- predictive models -- proximate analysis -- regression; Combustion -- Periodicals; Combustion engineering -- Periodicals; 541.36105
• DOI: 10.1080/00102202.2019.1617705
• Languages: English
• ISSNs: 0010-2202

Abstract

ABSTRACT: As coal will continue to be a major energy resource, it is important to have the means of quickly and accurately estimating properties related to its combustion like that of its calorific value, theoretical air requirement, and elemental composition. Most of the existing models widely used in predicting the higher heating value (HHV) of coal generally lack the theoretical basis and/or miss to account for the thermochemical implications of the predictive parameters. In this work, a semi-empirical model is derived based on first principles and accounting for the technical limitations involved in the determination of HHV of coal. A wide range of coal sample data set (n = 8500) was used in generating, testing, and validating of the new and existing models. Some of the hidden relationships and influence of nitrogen content, ash, and moisture to the determined HHV are elucidated in the process of deriving the HHV models. Furthermore, empirical relationships based on proximate analysis of coal and HHV, along with mass and energy balances, would allow a reasonably accurate estimation of the theoretical air requirement, lower heating value (LHV), and major elemental components (C, H, and O) in a given coal sample. Mean absolute errors of predicted or estimated quantities are well below 5%, which in most cases are less than 1% depending on the source of coal. The usefulness of a model lies not only in its ease of use and accuracy, but also in the extent of providing a theoretically sound representation of the actual phenomenon involved.