Issue |
MATEC Web Conf.
Volume 131, 2017
UTP-UMP Symposium on Energy Systems 2017 (SES 2017)
|
|
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Article Number | 04002 | |
Number of page(s) | 6 | |
Section | Economic, environmental, social and policy aspects of energy | |
DOI | https://doi.org/10.1051/matecconf/201713104002 | |
Published online | 25 October 2017 |
Proximate Analysis and Calorific Value Prediction using Linear Correlation Model for Torrefied Palm Oil Wastes
Faculty of Chemical & Natural Resources Engineering, University Malaysia Pahang, Lebuhraya Tun Razak, 26300, Gambang, Pahang, Malaysia
* Corresponding author: raishanrashid@gmail.com
Torrefaction is one of the pretreatment processes to upgrade the chemical and physical properties of biomass for power production. In this study, four types of palm oil wastes were selected. The wastes, which consisted of oil palm frond (OPF), palm kernel shell (PKS), palm mesocarp fibre (PMF), and empty fruit bunch (EFB), were subjected to torrefaction process at different temperatures of 240°C, 270°C, 300°C, and 330°C for 30 min residence time. Based on the analysis of torrefied palm oil wastes, it was observed that there is a linear relationship between the properties of torrefied palm oil wastes and torrefaction temperature. Based on this, linear correlation model as a function of mass loss was developed to predict the energy yield (EY), calorific value (HHV), and proximate analysis. A reliable correlation model (R2 > 0.90) for predicting calorific value (HHV), fixed carbon (FC), and volatile matter (VM) was obtained, indicating the developed linear model is indeed reliable. Meanwhile, an acceptable coefficient of determination (R2 ≈ 0.75) was obtained when the linear model is used to estimate the energy yield (EY) and ash content (ASH). These developed linear correlation models are cost effective and can be used as a tool to predict the properties of palm oil wastes and to assess the suitability of biomass in torrefaction process.
© The authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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