Prediction of calorific value of biomass based on elemental analysis

Year 2018, Volume: 2 Issue: 3, 254 - 260, 15.12.2018

Ayşe Özyuğuran , Serdar Yaman , Sadriye Küçükbayrak

Abstract

Thirty nine different biomass
samples ranging from various herbaceous/woody materials to juice pulps were
used to develop linear as well as non-linear empirical equations that predict
the lower heating value (LHV) and the higher heating value (HHV) based on the
elemental analysis (C, H, N, O, and S) results of the biomass species. These
equations were interpreted with respect to their prediction performance considering
the predicted values and the experimental data. Several criteria such as mean
absolute error (MAE), average absolute error (AAE), average bias error (ABE),
and root mean square deviation (RMSD) were regarded. For the linear equations,
it was found that the lowest values of MAE were 0.3119 MJ/kg and 0.2906 MJ/kg
for HHV and LHV, respectively, and 
AAE(%) changed in the ranges of (1.6659-4.5917) for HHV and (1.8216-5.5039)
for LHV. Besides, it was determined that ABE(%) varies in the intervals of
(0.0549-0.2976) for HHV and (0.0519-0.4177) for LHV when linear equations were
tested. The best results of RMSD (0.4230 and 0.3607 for HHV and LHV,
respectively) were obtained for Equation#1 where all of the linear terms were
considered. Also, the addition of the non-linear terms to the linear equations
was also studied to check whether any further improvement can be achieved in
predictions. However, the improvements created by non-linear equations were
negligible and it was concluded that the linear empirical equations provide
satisfactory prediction performance and they may be tried to estimate the
calorific value of very wide range of biomasses.

Keywords

Biomass, Calorific value prediction, Elemental analysis

References

• 1. Klass D.L., Biomass for renewable energy, fuels, and chemicals. 1998, San Diego: Academic Press.
• 2. Channiwala S.A., and P.P. Parikh, A unified correlation for estimating HHV of solid, liquid and gaseous fuels. Fuel, 2002. 181: p. 1051-1063.
• 3. Gillespie G.D., C.D. Everard, C.C. Fagan, and K.P. McDonnell, Prediction of quality parameters of biomass pellets from proximate and ultimate analysis. Fuel, 2013. 111: p. 771-777.
• 4. Yin C.Y., Prediction of higher heating values of biomass from proximate and ultimate analyses. Fuel, 2011. 90: p. 1128-1132.
• 5. Friedl A., E. Padouvas, H. Rotter, and K. Varmuza, Prediction of heating values of biomass from elemental composition. Analytica Chimica Acta, 2005. 544: p.191-198.
• 6. Chen W.H., W.Y. Cheng, K.M. Lu, and Y.P. Huang, An evaluation on improvement of pulverized biomass property for solid fuel through torrefaction.. Applied Energy, 2011. 88: p. 3636-3644.
• 7. Titiloye J.O., M.S. Abu Bakar, and T.E. Odetoye, Thermochemical characterization of agricultural wastes from West Africa. Industrial Crops and Products, 2013. 47: p. 199-203.
• 8. Maddi B., S. Viamajala, and S. Varanasi, Comparative study of pyrolysis of algal biomass from natural lake blooms with lignocellulosic biomass. Bioresource Technology, 2011. 102: p. 11018-11026.
• 9. Chiou B.S., D. Vaenzuela-Medina, C. Bilbao-Sainz, A.K. Klamczynski, R.J. Avena-Bustillos, R.R Milczarek, W.X. Du, G.M. Glenn, and W.J. Orts, Torrefaction of pomaces and nut shells. Bioresource Technology, 2015.177: p. 58-65.
• 10. Motghare K.A., A.P. Rathod, K.L. Wasewar, and N.K. Labhsetwar, Comparative study of different waste biomass for energy application. Waste Management, 2016. 47: p. 40-45.
• 11. Ozyuguran A., A. Akturk, and S. Yaman, Optimal use of condensed parameters of ultimate analysis to predict the calorific value of biomass. Fuel, 2018. 214: p.640-646.
• 12. Setyawati W., E. Damanhuri, P. Lestari, and K. Dewi, Correlation equation to predict HHV of tropical peat based on its ultimate analysis. Procedia EngİNEERİNG, 2015. 125: p. 298-303.
• 13. Nhuchhen D.R., and P. Abdul Salam, Estimation of higher heating value of biomass from proximate analysis: A new approach. Fuel, 2012. 99: p. 55-63.
• 14. Choi H., S.I.A. Sudiarto, and A. Renggaman, Prediction of livestock manure and mixture higher heating value based on fundamental analysis. Fuel, 2014. 116: p. 772-780.
• 15. Bousdira K., L. Nouri, and J. Legrand, Chemical characterization of phoenicicole biomass fuel in Algerian oasis: Deglet nour and ghars cultivars case. Energy Fuels, 2014. 28: p. 7483-7493.
• 16. Garcia R., C. Pizarro, A.G. Lavin, and J.L. Bueno, Spanish biofuels heating value estimation. Part I: Ultimate analysis data. Fuel, 2014. 117: p. 1130-1138.