When will wind energy achieve grid parity in China? – Connecting technological learning and climate finance

Abstract

China has adopted an ambitious plan for wind energy deployment. This paper uses the theory of the learning curve to investigate financing options to support grid parity for wind electricity. First, relying on a panel dataset consisting of information from 1207 wind projects in China’s thirty provinces over the period of 2004–2011, this study empirically estimates the learning rate of onshore wind technology to be around 4.4%. Given this low learning rate, achieving grid parity requires a policy of pricing carbon at 13€/ton CO2e in order to increase the cost of coal-generated electricity. Alternatively, a learning rate of 8.9% would be necessary in the absence of a carbon price. Second, this study assesses the evolution of additional capital subsidies in a dynamic framework of technological learning. The implicit average CO2 abatement cost derived from this learning investment is estimated to be around 16€/ton CO2e over the breakeven time period. The findings suggest that climate finance could be structured in a way to provide up-front financing to support this paradigm shift in energy transition.