Integrated spatial and pinch analysis of optimal industrial energy supply mix with consideration of BioCNG derived from palm oil mill effluent

Utilisation of palm oil mill effluent (POME) appears to be a promising source of bioenergy production specifically biogas. Biogas products have different spatial structure varying on the level of centrality and dispersion of palm oil mill (POM), significantly impacting the transportation and total c...

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Bibliographic Details
Main Authors: Lee, Ming Kwee, Hashim, Haslenda, Ho, Wai Shin, Ab. Muis, Zarina, Yunus, Nor Alafiza, Xu, Huijin
Format: Article
Published: Elsevier Ltd 2020
Subjects:
Online Access:http://eprints.utm.my/id/eprint/29634/
http://dx.doi.org/10.1016/j.energy.2020.118349
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Summary:Utilisation of palm oil mill effluent (POME) appears to be a promising source of bioenergy production specifically biogas. Biogas products have different spatial structure varying on the level of centrality and dispersion of palm oil mill (POM), significantly impacting the transportation and total cost of biogas production. Pinch analysis provides systematic solution to industrial energy planning. However, the current pinch analysis lacks the ability to simultaneously consider CO2 emission target and to minimise cost for bioenergy supply chain. This study presents an integrated spatial and pinch analysis to determine the least cost energy mix to satisfy industrial energy demand and GHG emission target. The selection of cost-competitive energy substitution is evaluated based on supply cost factor constructed with spatial consideration, emission reduction to cost increase (ECI) ratio and emission reduction with cost decrease (ECD) values. To demonstrate the proposed framework, a case study to meet 120 MW of industrial energy demand in the state of Johor, Malaysia was presented. The results indicated that natural gas from grid extension and bio-compressed natural gas (BioCNG) with upgrading were required to achieve 30% GHG emission reduction. The total cost of energy mix was reduced significantly from 25.16 M USD/y to 17.56 M USD/y.