Prediction models for chemical exergy of biomass on dry basis from ultimate analysis using available electron concepts

Hongliang Qian, Weiwei Zhu, Sudong Fan, Chang Liu, Xiaohua Lu, Zhixiang Wang, Dechun Huang and Wei Chen

Energy, 2017, vol. 131, issue C, 251-258

Abstract: Prediction models, based on ultimate analysis of biomass on dry basis (db) which is leveraged to predict chemical exergy, were proposed in this study. A new concept — chemical exergy per equivalent of available electrons transferred to oxygen (reductance degree) of model 1 was established. The result shows that chemical exergy per reductance degree of model 1 is relatively constant for the values of most biomass (db) beyond the±1% relative error range. A modified reductance degree of biomass was presented, whereas oxygen (O) content was neglected due to its inaccurate value and the high p-value for the coefficient of O variable. Chemical exergy per modified reductance degree of models 2 and 3 was approximated to be nearly a constant. Thus, two theoretical prediction models (model 2 and model 3) for the biomass (db) with and without sulfate (920.08(C/3 + H + S/8), 920.72(C/3 + H)) were established, respectively. The coefficients of the two models are of almost the same value, which indicates that the S content has also a negligible effect on chemical exergy. Model 3 (920.72(C/3 + H)) is also herein proposed for prediction of exergy of biomass. The average relative errors of model 1, model 2 and model 3 are 2.882%, 0.643% and 0.634%, respectively.

Keywords: Chemical exergy; Biomass; Ultimate analysis; Prediction model (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:131:y:2017:i:c:p:251-258

DOI: 10.1016/j.energy.2017.05.037

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