4.7 Article

Effects of pressure and heating rate on coal pyrolysis: A study in simulated underground coal gasification

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ELSEVIER
DOI: 10.1016/j.jaap.2023.106179

Keywords

Underground coal gasification; Pyrolysis; Char production; Solid-state kinetic model; ANN

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This study investigates the effects of heating rate and pressure on the char formation during the pyrolysis of bituminous coal. An empirical model is developed to predict pyrolysis rates under varying heating rate and pressure conditions. The results show that the optimal heating rate for char generation is around 10 degrees C/min and pressure above 2 MPa enhances char production.
Underground coal gasification (UCG) is a promising technology which in-situ converts coal into fuel gases through controlled chemical reactions. In order to precisely control coal pyrolysis and increase the char yield, it is vital to understand the influences of operating factors such as heating rate and pressure, on coal pyrolysis. In this study, the effects of heating rate and pressure on the char formation of bituminous coal pyrolysis are investigated. The reaction mechanism of coal pyrolysis and the solid-state kinetic model are firstly reviewed. Subsequently, thermal experiments are conducted to study the effects of heating rate and pressure on coal pyrolysis characteristics. Moreover, the connection between the dominant coal pyrolysis reaction type and corresponding solid-state kinetic model is revealed. An empirical model of coal pyrolysis rate, pressure, and heating rate is also developed, which can be used to quantitatively predict pyrolysis rates under varying heating rate and pressure conditions. The results show that the optimal heating rate for char generation is at around 10 degrees C/min. On the other hand, when the pressure exceeds 2 MPa, it will enhance the char production by obstructing the physical release of volatiles and has insignificant impact on the reaction type. This study contributes to our understanding of the coal pyrolysis mechanism, and the proposed empirical model can provide valuable insights for optimizing operating parameters during UCG process.

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