基于Logistic和学习曲线模型的中国电源结构预测  

Forecast of Power Source Structure in China Based on the Logistic & Learning Curve Model

作　　者：袁晓玲[1] 范玉仙[1] 

机构地区：[1]西安交通大学经济与金融学院,陕西西安710061

出　　处：《湖南大学学报（社会科学版）》2013年第4期51-55,共5页Journal of Hunan University(Social Sciences)

基　　金：国家社会科学基金重点项目"电网智能化对我国能源供用方式和能源产业格局的影响及发展战略研究"(12AZD103)

摘　　要：可再生能源发电是缓解电力短缺、化石能源过度消耗和环境污染多重压力的重要突破口。Logistic模型和学习曲线模型能很好地刻画新能源发电技术创新过程中累积产量不断接近最大生产极限的过程以及发电成本降低的过程。预测结果显示,未来40年风电和太阳能发电发展速度较快,其中风电的装机容量从2040年开始超过水电,但以火电为主的电源结构将持续。Promoting the Renewable Energy power is one of the ways to abate resources shortage, wan- ton depletion of chemistry and oil energy and environmental pollution. Logistic ~ Learning Curve Model can precisely describe the process that cumulative production is near to maximum limit and that the power cost is reduced. The results are as follows： wind power and solar power generation will develop quickly in the next 40 years, and from 2040, installed capacity of wind power begins to dominate hydropower, but fossil power remains the mainstay of power generation.

关 键 词：LOGISTIC模型 学习曲线模型 电源结构 可再生能源 

分 类 号：F124.5[经济管理—世界经济]