Pathway Evolution Modeling of Provincial Power Systems Under Multi-Scenario Carbon Constraints: An Empirical Analysis of Guangdong, China

China’s energy system is transitioning from a state of coal-dependent, low-electrification to a low-carbon, high-electrification paradigm. Carbon emissions have become a central constraint that directly influences generation expansion and transmission investment decisions. This study develops a bottom-up optimization framework integrating dynamic carbon trajectories into a coupled generation–transmission–storage expansion model. Distinct carbon emission trajectories are established on the basis of Guangdong’s allocated carbon budget, and the analysis evaluates the resulting power system structures and transition pathways under each scenario. Results show that Guangdong’s clean energy transition relies on external power imports, nuclear power, and variable renewable energy (VRE), collectively accounting for 87% of generation by 2060. Flexibility requirements expand substantially, with storage capacity rising from 10% of installed VRE in 2030 to 26% in 2060. Critically, under identical cumulative carbon budgets, an accelerated decarbonization pathway achieving earlier peak emissions demonstrates a pivotal economic trade-off: it imposes modestly higher near-term operation costs but delivers significant long-term savings by avoiding prohibitively expensive end-of-period abatement measures. Specifically, advancing the emissions peak from 2030 to 2025 reduces cumulative system costs over the planning horizon by CNY 53.7 billion and lowers the 2060 levelized cost of electricity by 5.2%.