A multi-period optimization model for optimal planning of China's power sector with consideration of carbon mitigation—The optimal pathway under uncertain parametric conditions

Optimal planning of power industry considering carbon mitigation for a long-term future is complex, involving many technical alternatives and infinite possible plants installations, retrofitting, and decommissions. Previously the authors built a multi-period superstructure optimization planning model of China's power sector, gaining the optimal pathway of China's power sector with fixed parametric input during 2010–2050. With that model, this paper attempted to optimize pathway of China's power sector under uncertainty, in which the most influential parameters were uncertain. A levelized optimal pathway of China's power sector was gained, reliability of which was verified by comparing it with optimal results for the stochastic samples. The levelized optimal pathway showed that in the presence of carbon tax, carbon emissions of the power sector were reduced significantly by developing low-carbon technologies including nuclear power, renewables, as well as carbon capture and sequestration (CCS), and CCS would be key to reduce carbon emissions from coal power.

► We studied the optimal development pathway of China's power sector under uncertainty.
► A superstructure optimization model for optimal planning of power sector was applied.
► Real-life plants capacity composition of China's power sector was used as the basis.
► We used Monte Carlo method to deal with the uncertainties with the input parameters.
► Optimal pathway under uncertainty was gained, and reliability verified by comparison.