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Optimization approach for greenhouse gas to green energy for a low carbon region of Iskandar Malaysia

Ahmed, Saeed Isa and Johari, Anwar and Hashim, Haslenda and Mat, Ramli and Lim, Jeng Shiun and Jusoh, Mazura and Alkali, Habib and Hafshar, Siti Shamsi (2015) Optimization approach for greenhouse gas to green energy for a low carbon region of Iskandar Malaysia. Jurnal Teknologi, 75 (6). pp. 7-16. ISSN 2180-3722

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Official URL: http://dx.doi.org/10.11113/jt.v75.5157

Abstract

Landfill gas (LFG) like any other greenhouse gases (GHG) is a threat to the environment; hence its mitigation through effective utilization is necessary. The objective of this study is to estimate the amount of LFG captured using IPCC methodology and then develop optimization model for the LFG utilization for green energy production for Iskandar Malaysia. Of the three MSW Scenarios considered, the most appropriate was Scenario MIX, giving projection of MSW to landfill ranging from 600,000 tons in 2010 to 711,000 tons in 2035 for Iskandar Malaysia. From this, a mean annual LFG capture of 21,672 tons was estimated. The Mixed Integer Programing model considered Scenario ST as the more appropriate of the two LFG Scenarios, favoring combined heat and power generation with steam turbines over other options. The optimal result yielded a mean annual electricity and steam generation of 20,588 MWh (2.3 MW) and 150 million MJ respectively. The mean electricity generation represents 0.16% and 0.02% of the maximum electricity demand for Iskandar Malaysia and Peninsular Malaysia respectively. Additionally, GHG emission reduction of 12,000 tons CO2 equivalent was achieved. The findings revealed the potentials in LFG capture from the case study in terms of green energy and GHG emission reduction for sustainable development.

Item Type:Article
Uncontrolled Keywords:greenhouse gas, green energy
Subjects:T Technology > TP Chemical technology
Divisions:Chemical Engineering
ID Code:56194
Deposited By: Fazli Masari
Deposited On:05 Dec 2016 00:13
Last Modified:01 Nov 2017 04:16

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