An Application of the Multi-Objective Approach for the Evaluation of Long-Term Electrical Generation Optimum Mix: a Case Study

Abstract

This paper presents findings from optimization of a long-term generation mix for Malaysia electricity power supply. The optimization is modeled as multi-objective functions i.e. to minimize the costs of supplying electricity as well as to minimize CO2 emission. This research uses Dynamic Programming (DP) incorporates with Efficiency Multi-Criteria decision technique in modeling the multi-objective generation mix for Malaysia. Several technologies have been used for generation candidates such as coal, gas and nuclear. Analyses was first performed for base case and then sensitivity analyses was included to study the impact of uncertainty in some parameters on the generation mix; 1) nuclear as expansion plant, 2) gas price variations and 3) renewable energy development. Result shows that a balance generation mix for Malaysia in 2030 will be 30% is from coal, 31.6% from gas, 17.5% from nuclear, 6.8% from hydro and 14% from RE. Sensitivity analyses conclude that the inclusion of nuclear in the generation mix will mostly affect gas technology. On the other hand, increasing the gas price and the RE target policy will affect the development of coal and gas in the generation mix as well as increasing the total cost and CO2 emission.