基于成本分析的中国新型电力系统多能协同路径

Key Points

• This research aims to uncover the regional heterogeneity of wind and solar technology learning effects and propose cost-effective multi-energy pathways for China's new power system.
• Utilized learning curve model to quantify investment cost evolution of wind and solar energy in six regions from 2005 to 2021.
• Integrated multiple factors including resources, technology, and policies to construct an optimal dynamic optimization model covering 2022-2060.
• Investigated multi-energy collaborative pathways under different electrification and carbon reduction constraints.
• By 2060, renewable energy installed capacity is expected to reach 88.9%, predominantly in Northwest, North China, and Central China, increasing system costs by 21.0%.
• Investment costs will surpass fuel costs, with auxiliary service costs growing fastest, expected to represent 24.7% of total costs by 2060.
• China’s electricity sector could peak carbon emissions around 2029 at approximately 4.677 billion tons CO2, potentially reducing emissions by about 11.89 billion tons by 2060.