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<p>Considering the differences in economic development, electricity demand, renewable energy resource profile, and renewable energy development goals in different regions of China, we establish a multi-objective optimization model of China’s renewable energy development plan under the carbon peak goal, with objectives encompassing the minimization of power generation costs, maximization of carbon emission reduction, and minimization of inter-regional transmission and distribution. The multi-objective particle swarm optimization and multi-criteria decision-making method are adopted to obtain the optimal solution. The results show that if the carbon peak goal is to be achieved by 2030, the cumulative installed capacity of renewable energy in China will increase from 1.213&#xa0;billion kilowatts in 2022 to 2.2&#xa0;billion kilowatts in 2030. Among the 30 regions studied, Shandong and Inner Mongolia have the largest new installed capacity, with 124 and 78&#xa0;million kW, respectively. Meanwhile, Jiangsu and Guangdong face the most notable gaps between local renewable energy generation and consumption targets, with 125.6 and 119.3&#xa0;billion kWh, respectively. In alignment with China’s 14th Five-Year Plan, the installed capacity of renewable energy in the country needs to undergo a compound annual growth rate of 8.1% and 8.6%, correspondingly, to achieve the carbon peak goal by 2028 or 2026.</p>

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Renewable energy development planning under carbon peak target: a multi-objective optimization framework considering regional differences in China

  • 期刊论文

  • 发表日期：

    2026年2月23日

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  • Libo Zhang,
  • Yikai Wu,
  • Huan Zhang,
  • Qunwei Wang,
  • Dequn Zhou

摘要

Considering the differences in economic development, electricity demand, renewable energy resource profile, and renewable energy development goals in different regions of China, we establish a multi-objective optimization model of China’s renewable energy development plan under the carbon peak goal, with objectives encompassing the minimization of power generation costs, maximization of carbon emission reduction, and minimization of inter-regional transmission and distribution. The multi-objective particle swarm optimization and multi-criteria decision-making method are adopted to obtain the optimal solution. The results show that if the carbon peak goal is to be achieved by 2030, the cumulative installed capacity of renewable energy in China will increase from 1.213 billion kilowatts in 2022 to 2.2 billion kilowatts in 2030. Among the 30 regions studied, Shandong and Inner Mongolia have the largest new installed capacity, with 124 and 78 million kW, respectively. Meanwhile, Jiangsu and Guangdong face the most notable gaps between local renewable energy generation and consumption targets, with 125.6 and 119.3 billion kWh, respectively. In alignment with China’s 14th Five-Year Plan, the installed capacity of renewable energy in the country needs to undergo a compound annual growth rate of 8.1% and 8.6%, correspondingly, to achieve the carbon peak goal by 2028 or 2026.