Investment in multi-energy complementary power grid infrastructure projects needs to solve the problems of economy

risk and multi-objective collaborative optimization. In this study

a dynamic energy flow modeling method is proposed to build an economic evaluation model covering full life cycle cost-effectiveness and internal yield

design a double-layer nested Monte Carlo simulation technology to analyze the risk coupling effect of new energy outlet and electricity price fluctuation

and develop a multi-objective optimization algorithm to jointly balance economic benefits

power supply reliability and low-carbon benefits. In typical wind-light-storage projects

the dynamic model optimizes the energy storage capacity configuration

the risk entropy mechanism triggers the energy storage frequency modulation expansion and the green electric hydrogen production collaborative defense strategy

and the carbon intensity of key nodes driven by carbon flow tracking has decreased significantly. The case verification shows that this method improves the net present value of the project and reduces the frequency of extreme risks

providing a quantifiable decision-making framework for high-proportion investment in new energy grid.