Predicting the higher heating value of products through solid yield in torrefaction process

Yuhang Zhu, Qiaohui Peng, Hong Wang, Wei Lin, Rui Yang, Zhiyong Qi, Dongdong Zhang and Lin Ouyang

Renewable Energy, 2024, vol. 236, issue C

Abstract: Torrefaction is a widely employed method to upgrade biomass for energy purpose. The higher heating value (HHV) serves as a vital indicator for assessing the energy potential of biomass. Nevertheless, HHV measurement is a time-consuming and costly process. HHV of raw biomass, torrefied biomass, and biochar has been extensively estimated using the results of elemental analysis and/or proximate analysis. However, these data must be repeatedly measured for each target object. To reduce the efforts required for the measurement of each object, this study proposes, for the first time, the use of solid yield (the most easily obtainable data) to predict the HHV of torrefied biomass.

Keywords: Solid yield; HHV prediction model; Torrefaction; Artificial neural network (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:236:y:2024:i:c:s0960148124015143

DOI: 10.1016/j.renene.2024.121446

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