A Simple Prediction Model for Higher Heat Value of Biomass

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• 作者：Hongliang Qian ; Xiaojing Guo ; Sudong Fan ; Kiros Hagos ; Xiaohua Lu ; Chang Liu ; Dechun Huang
• 刊名：Journal of Chemical & Engineering Data
• 出版年：2016
• 出版时间：December 8, 2016
• 年：2016
• 卷：61
• 期：12
• 页码：4039-4045
• 全文大小：294K
• ISSN：1520-5134

文摘

A simple prediction model, based on ultimate analysis of biomass which is leveraged to predict higher heating value (HHV), was proposed in this paper. In the literature there are two facts offering some bases for the study. One is that oxygen (O) content is not an accurate value in the calculation of the reductance degree as well as the heat of combustion per unit of oxygen consumed of the biomass, and as a result, the determination of HHV turns out to be inaccurate, too. The other is that the O variable does not contribute to the overall physical interpretation of the HHV from the perspective of mathematics (the p-value), and therefore, a modified reductance degree of biomass was presented, whereas O content was neglected. According to the modified reductance degree, HHV per gram of oxygen consumed of one biomass was identified to be nearly a constant. Thus, two theoretical prediction models for the biomass with and without sulfate (HHV′ = 873.52(C/3 + H + S/8), HHV″ = 874.08(C/3 + H)) were established. The comparison between mean absolute error (MAE) of Thornton’s method and 15 recently established empirical correlations shows that the MAE of the two prediction models is the least, which serves as strong evidence for the good HHV predictive capability of the two models, and their easy-to-operate quality as well. Furthermore, the coefficients of the two models are almost the same value, which indicates that the S content also has negligible effect on HHV. The final model that we proposed is model 2 (HHV″ = 874.08(C/3 + H)).