Abstract

Cost evolution has an important influence on the commercialization and large-scale application of power technology. Many researchers have analyzed the quantitative relationship between the cost of power technology and its influencing factors while establishing various forms of technical learning curve models. In this paper, we focus on the positive effects of the policy on research and development (R&D) learning by summarizing and comparing four energy technology cost models based on learning curves. We explore the influencing factors and dynamic change paths of power technology costs. The paper establishes a multi-stage dynamic two-factor learning curve model based on cumulative R&D investment and the installed capacity. This work presents the structural changes of the influencing factors at various stages. Causality analysis and econometric estimation of learning curves are performed on wind power and other power technologies. The conclusion demonstrates that a “learn by researching” approach had led to cost reduction of wind power to date, but, in the long term, the effect of “learn by doing” is greater than that of “learn by researching” when R&D learning is saturated. Finally, the paper forecasts the learning rates and the cost trends of the main power technologies in China. The work presented in this study has implications on power technology development and energy policy in China.

Highlights

  • The energy system has developed a wide variety of clean energy solutions

  • This study demonstrated that strengthening research and development (R&D) investments was more helpful to improving technical performance, with respect to increasing the use of technology, while some researchers believe that the single-factor equation missed an important variable named R&D investment, by comparing the estimation learning rate of single-factor and two-factor equations, so the learning rate of “learn by doing” was overestimated, causing information distortion in a certain degree

  • Ref. [24] thinks that the promotion of global technologies follows two laws, one of the laws being that the new technology transforms from the available phase (production to 1000 terajoules (TJ)) to the mature phase (1% of the total energy supply) with an annual average growth rate of 26% in about 30 years, the other being that when the technology has become mature, it begins to increase in a slow linear way. They pointed out that the technologies always need R&D and demonstration projects by the government before the technologies reach a certain scale, and the technology costs will become even more important and the government should support the technologies by the market mechanism, until the costs are reduced to the extent that they can compete with other technologies

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Summary

Introduction

The energy system has developed a wide variety of clean energy solutions. Due to the high cost of emerging technologies, compared with the established ones, most of the emerging power technology is still in the R&D and demonstration phases; it is not achieving large-scale commercial applications in the market. [24] thinks that the promotion of global technologies follows two laws, one of the laws being that the new technology transforms from the available phase (production to 1000 terajoules (TJ)) to the mature phase (1% of the total energy supply) with an annual average growth rate of 26% in about 30 years, the other being that when the technology has become mature, it begins to increase in a slow linear way They pointed out that the technologies always need R&D and demonstration projects by the government before the technologies reach a certain scale, and the technology costs will become even more important and the government should support the technologies by the market mechanism, until the costs are reduced to the extent that they can compete with other technologies.

Factors Analysis and Selection of Learning Curve Model
Staged Dynamic Two-Factor Learning Curve Model of Power Technology
Learning Curve of Wind Power
C Adjusted-R-squared
Findings
Conclusions
Full Text
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