This is an evidence from a high-income economy in Southeast Asia and a support for scientific planning of the energy sector in ensuring air pollution and climate change mitigation. A comparative analysis of the energy options for electricity generation in the nation was made considering availability, cost and greenhouse gases emission - CO2, N2O and CH4, using a two-stage method comprising multi-objective optimization and TOPSIS. The renewable (RE) and non-renewable energy (NRE) options available were assessed through the lifecycle approach to determine the lifecycle greenhouse gas emission (LCGHG) and levelized cost of energy (LCOE) per MWh of electricity. Considering historical electricity consumption, annual GDP and population growth from 1965, energy consumption for the year 2035 was forecasted using support vector machine regressor in Weka. Future plans in energy diversification pathways were examined through various scenario multi-objective optimizations with a constraint on resource availability and energy target using genetic algorithm in MATLAB. The outputs were ranked using TOPSIS method. Results showed that greenhouse gases emission could be reduced by 10.3 percent compared to business as usual scenario while the energy mix could attain 10 percent renewable energy in the grid at a relatively lower generation cost.
Keywords: Cost; Greenhouse gas; Lifecycle; Multi-objective optimization; Renewable energy; TOPSIS.
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