Higher Heating Values (HHV) Prediction Model from Biomass Proximate Analysis Data

The Higher Heating Values (HHV) of biomass is an important parameter in modeling biomass to energy conversion processes. There are several published models and each of them has pros and cons. In the present studies, a HHV prediction model has been proposed based on the biomass proximate analysis (volatile matter, fixed carbon and ash contents). Nearly three hundred sets of biomass proximate analysis data was extracted from literature and used in developing the simplistic empirical model. The model was then experimentally validated with 19 biomass samples collected from Semenyih area in Selangor, Malaysia and assessed at the University of Nottingham Malaysia Campus lab. The proposed model has average absolute error, average bias error and regression coefficient of 2.32%, -0.76% and 0.93 respectively. The developed model shows better result compared to those in the literature and can be used for predicting HHV of biomass with ash content in the range 0<Ash≤39.60%.