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The price of wind power in China during its expansion: Technology adoption, learning-by-doing, economies of scale, and manufacturing localization

机译:扩大中的中国风电价格:技术采用,边做边学,规模经济和制造本地化

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摘要

Using the bidding prices of participants in China's national wind project concession programs from 2003 to 2007, this paper built up a learning curve model to estimate the joint learning from learning-by-doing and learning-by-searching, with a novel knowledge stock metric based on technology adoption in China through both domestic technology development and international technology transfer. The paper describes, for the first time, the evolution of the price of wind power in China, and provides estimates of how technology adoption, experience in building wind farm projects, wind turbine manufacturing localization, and wind farm economies of scale have influenced the price of wind power. The learning curve model presented includes several important control variables, namely, wind resource indicators and steel prices. The results indicate that joint learning from technology adoption and learning-by-doing through cumulative installed capacity, wind turbine manufacturing localization, and wind farm economies of scale comprise the three most significant factors associated with reductions in the price of wind power in China during the period under consideration. The two types of learning investigated are associated with a 4.1%-4.3% price reduction per doubling of installed capacity, providing an estimate of the evolution of the price of wind power, a technology widely used in other markets, which in China has benefited from technology leapfrogging, established supply chains, and operational experience in other countries. Because of the change of bidding rules in 2007, our estimates can be interpreted as the lower bound of the true joint learning rates. Our model also indicates that most learning about the installation and operation of wind farms was common to the whole industry (i.e., we found little evidence for intra-firm learning). The policies that have contributed to the growth of the Chinese knowledge stock through the promotion of technology adoption are also discussed.
机译:利用2003年至2007年中国国家风电项目特许权项目参与者的竞标价格,建立了一种学习曲线模型,以一种新颖的知识量度标准来估计边做边学和边学边学习的联合学习。以通过国内技术开发和国际技术转让在中国采用技术为基础。本文首次描述了中国风电价格的演变,并提供了对技术采用,风电场项目建设经验,风机制造本地化以及风电场规模经济如何影响价格的估计。风能。提出的学习曲线模型包括几个重要的控制变量,即风能指标和钢价。结果表明,从技术采用和通过累积装机容量,风力涡轮机制造本地化以及风电场规模经济中的边做边学中获得的共同学习是与中国风电价格下降相关的三个最重要因素。正在考虑的时期。所研究的两种学习方式与每增加一倍的装机容量可降低4.1%-4.3%的价格有关,从而估计了风电价格的演变,风电是一种在其他市场广泛使用的技术,在中国,该技术已从中受益技术的飞跃发展,已建立的供应链和其他国家的运营经验。由于2007年竞标规则的变化,我们的估算可以解释为实际联合学习率的下限。我们的模型还表明,关于风电场安装和运行的大多数知识是整个行业共有的(即,我们发现很少有公司内部学习的证据)。还讨论了通过促进技术采用为中国知识储备增长做出贡献的政策。

著录项

  • 来源
    《Energy economics》 |2012年第3期|p.772-785|共14页
  • 作者

    Yueming Qiu; Laura D. Anadon;

  • 作者单位

    Stanford University, Atmosphere/Energy Program, The Jerry Yang and Akiko Yamazaki, Environment & Energy Building, 473 Via Ortega, Stanford, CA 94305, USA,Harvard University, John F. Kennedy School of Government, Belfer Center for Science and International Affairs, 79 John F. Kennedy Street, Cambridge, MA 02138, USA;

    Harvard University, John F. Kennedy School of Government, Belfer Center for Science and International Affairs, 79 John F. Kennedy Street, Cambridge, MA 02138, USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    wind power; learning curve; china; technology adoption; learning-by-doing; learning-by-searching;

    机译:风力;学习曲线;中国;技术采用;边干边学;边学边学;

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