Feed-In Tariff for Onshore Wind Power in China

ABSTRACT

This article estimated the cost of onshore wind power in China by employing levelized cost of the electricity model. The analytical framework has enough precision for appraising the effectiveness of feed-in tariff (FIT) policy. Results show that the existing FIT policy is attractive to investors, but serious curtailment and turbine quality issues could make wind power unprofitable. Meanwhile, rapid learning-by-doing in turbine price has substantially lowered the cost of wind power and made it competitive with coal power in 2013. Our estimate results indicate that it is necessary and the right time to reform the FIT policy for the newly commissioned wind farms.

KEY WORDS:

• China
• feed-in tariff
• wind power

Acknowledgments

The authors appreciate the comments of anonymous reviewers and the assistance of the journal’s editor, which significantly improved the quality of the article.

Funding

The work reported in the article was funded by the Fundamental Research Funds for the Central Universities, the Beijing Higher Education Young Elite Teacher Project (YETP0707), and the Major Program of the National Social Science Fund of China (15ZDB165). The usual caveats apply.

Notes

^1. A recent policy consultation by NDRC (the ministry in charge of tariff policy in China) to lower the FIT level by 4 cents in resource zone I—III regions and by 2 cents in resource zone IV regions for the wind farms commissioned after 30 June 2015 is a clue that the review on the FIT policy by the Chinese government is underway and the government has already realized that current FIT levels are too high and not beneficial to the sustainable development of wind power in China.

Additional information

Funding

The work reported in the article was funded by the Fundamental Research Funds for the Central Universities, the Beijing Higher Education Young Elite Teacher Project (YETP0707), and the Major Program of the National Social Science Fund of China (15ZDB165). The usual caveats apply.