This paper present a Mixed Integer Linear Programming (MILP) model that was developed and implemented in General Algebraic Modeling System (GAMS) for the optimal planning of electricity generation schemes to achieve the renewable energy (RE) target as well as satisfy emission reduction target. The model applied two case studies on a new economic region in Malaysia known as Iskandar Malaysia. The optimization results show that, in order to achieve 40% carbon emission reduction and meeting the demand of 1997 MW by 2015 for Iskandar Malaysia, electricity generation from RES such as municipal solid waste (MSW) (103 MW), and biomass bubbling fluidized bed (BBFB) (mesofiber — 215 MW, EFB — 426 MW, and Kernel — 131 MW) are required with the remaining demand met by fossil fuels.