With the sustainable development of the economy and energy

electric power industry is faced with more uncertainty challenges

while conventional power generation decision-making methods are not able to meet the requirement for solving new problems. The current problems facing the power generation investment assessment are analyzed

on the basis of which

the generation portfolios are assessed. Firstly

under given elastic conditions of demand

the amount of change of load due to the change of generation cost is determined

with the intermittent renewable energy sources regarded as negative load correction. As an improvement on the conventional load duration curve

the impact of demand elasticity and intermittent energy is considered. Secondly

the Monte Carlo simulation method is used to simulate the uncertainties

including capital cost

load

fuel and carbon price to have the uncertainties merged into power generation investment portfolio assessment. Finally

a case study is analyzed with the example of Guangdong Province

the effective boundary

generation cost

CO2 emission and cost risk are obtained therefrom. The research results show that the carbon emissions policy is helpful to the development of clean energy

while the nuclear power will have greater development potential in the current policy environment. The proposed methodology is proved effective. This work is supported by National Soft Science Research Program (No. 2012GXS4B064) and National Natural Science Foundation of China (No. 71271082).