Optimal design of subsidy to stimulate renewable energy investments: The case of China

This paper proposes a real options model for estimating the optimal subsidy for renewable energy power generation project by using stochastic process to describe the market price of electricity, CO2 price and investment cost. Two indicators, i.e., project value and threshold value, are used to derive the optimal subsidy. The least squares Monte Carlo simulation method is used to solve the model. The proposed model is used to empirically evaluate the optimal level of subsidy for solar photovoltaic power generation in China. The results show that carbon emission trading scheme helps reduce subsidy. Unit generating capacity, market price of electricity, CO2 price and the volatility of investment cost are negatively related with subsidy, whereas investment cost and the volatility of electricity price and CO2 price are positively related with subsidy. It is suggested that Chinese governments take some measures, e.g., promoting technological progress, establishing a nationwide carbon emission trading market, promoting the competition in renewable energy industry as well as maintaining the stability of CO2 price and electricity price, to reduce the required subsidy.