Low-carbon power generation technologies such as wind, solar and carbon capture and storage are expected to play major roles in a decarbonized world. However, currently high cost may weaken the competitiveness of these technologies. One important cost reduction mechanism is the “learning by doing”, through which cumulative deployment results in technology costs decline. In this paper, a 14-region global energy system model (Global TIMES model) is applied to assess the impacts of technology diffusion on power generation portfolio and CO₂ emission paths out to the year 2050. This analysis introduces three different technology learning approaches, namely standard endogenous learning, multiregional learning and multi-cluster learning. Four types of low-carbon power generation technologies (wind, solar, coal-fired and gas-fired CCS) undergo endogenous technology learning. The modelling results show that: (1) technology diffusion can effectively reduce the long-term abatement costs and the welfare losses caused by carbon emission mitigation; (2) from the perspective of global optimization, developed countries should take the lead in low-carbon technologies’ deployment; and (3) the establishment of an effective mechanism for technology diffusion across boundaries can enhance the capability and willingness of developing countries to cut down their CO₂ emission.