摘要
“十四五”规划提出“2025年能源强度和碳排放强度分别下降13.5%和18%”,考虑“十四五”期间劳动力供给和劳动生产率约束,构建节能减排约束下的经济增长优化模型,对“十四五”期间产业结构、能源结构、各产业能源强度、各产业劳动生产率、劳动力供给数量进行预测,为经济增长优化模型参数的设置提供依据。采用遗传算法对经济增长优化模型进行求解,优化结果表明,中国“十四五”期间能源强度和碳排放强度可分别降低19%和24%,在满足节能减排约束的前提下,最优年均经济增长率为6.4%。实现这一优化结果,需要不断调整优化产业结构、能源结构,大力提升生产性服务业,提高第三产业比重至65%,增强第二产业实力,降低比重至29%,降低煤炭消费比重至50%,提高天然气、非化石能源消费比重分别至12%、19%。
In view of the goal of "reducing energy intensity by 13.5% and carbon emission intensity by 18% in 2025" proposed in the 14 th Five-Year Plan, and considering the labor supply and productivity constraints, an economic growth optimization model under the constraints of energy conservation and emission reduction was established. The industrial structure, energy structure, energy intensity, labor productivity and labor supply quantity are predicted, which provides the basis for setting the parameters of the economic growth optimization model. Finally, the genetic algorithm is used to solve the economic growth optimization model. The optimization results show that, during the 14 th Five-Year Plan period, China’s energy intensity and carbon emission intensity can be reduced by 19% and 24% respectively, and the optimal annual economic growth rate will be 6.4% under the constraints of the energy conservation and emission reduction. To achieve this result, the industrial structure and energy structure need to be adjusted and optimized continuously during the 14 th Five-Year Plan period, including raising the tertiary industry proportion to 65%, reducing the secondary industry proportion to 29%, decreasing coal consumption share to 50%, and increasing natural gas and non-fossil energy consumption share to 12% and 19% respectively.
作者
张省
王金营
Zhang Xing;Wang Jinying(Department of Economic Management,North China Electric Power University,Baoding Hebei 071003,China;College of Economics,Hebei University,Baoding Hebei 071002,China)
出处
《河北经贸大学学报》
CSSCI
北大核心
2022年第5期45-56,共12页
Journal of Hebei University of Economics and Business
基金
河北省社会科学基金项目“‘十四五’时期河北省能源消费结构目标优化及政策模拟”(HB20GL027)。
关键词
经济增长优化
节能减排
数学规划
遗传算法
economic growth optimization
energy conservation and emission reduction
mathematical programming
Genetic Algorithm