Search

Planning power system (PS) towards renewable energy is crucial for reducing carbon dioxide (CO 2) emission as well as mitigating climate change. However, the inherent uncertainty and hierarchical structure of PS pose intractable challenges to the planning process. This study develops a multi-GCM-based interval bi-level programming (MIBP) method that can balance two-level decision-making conflict between CO 2 -emisison reduction and system cost minimization. MIBP can also deal with uncertainties expressed as interval values in objective functions and constraints. Then, a MIBP-PS model is formulated to plan PS for China (2021–2050), where the upper-level objective is to minimize CO 2 emission and the lower-level objective is to minimize the system cost. The major findings are: (i) the CO 2 emission for PS would reach peak value before 2030 and then reduce by [10.2, 20.4]% in 2050, which is mainly owing to the curtailment of fossil fuel; (ii) compared with the conventional model, CO 2 emission from MIBP-PS model could decrease by [3.1, 4.8]%, which shows the superiority of the developed model; (iii) the fossil-fuel power would be gradually replaced by renewable energy, and the proportion of coal-fired power would decrease by 38.8% by 2050, especially small coal-fired facilities (i.e., below 0.3 GW) should be gradually phased down. [Display omitted] [ABSTRACT FROM AUTHOR]