A Novel LCOE Pricing Model for Renewable Energy with Power Purchase Agreement: A Case Study in China
To reach Carbon Peak in 2030 and Carbon Neutrality in 2060, China is developing renewable energy at a fast pace. Renewable energy enterprises will participate in the power market in an all-round way as China gradually improves its electricity market. Signing the Power Purchase Agreement (PPA) helps renewable energy companies to avoid market risk and achieve sustainable development. Therefore, a novel PPA pricing model is proposed in our research. Based on the theory of the Levelized Cost of
... gy (LCOE), our model considers system operating costs in China's dual-track electric power sector, which is both government-guided and market-oriented. First of all, key influencing factors of the PPA agreement are analyzed in view of the developments of the renewable energy and electricity markets in China. Next, the design of pricing strategies for renewable energy power plants to cope with market challenges is presented through a photovoltaic project case study. The results show that when the operating costs of the system are considered and other conditions remain unchanged, the investment payback period of the new energy power station will change from 10.8 years to 13.6 years. Furthermore, correlation degree and sensitivity coefficient (SAF) were introduced to conduct correlation analysis and sensitivity analysis of key elements that affect the pricing of the PPA. Finally, it is concluded that the utilization hours of power generation have the most significant effect on the PPA price, while the system's operating cost is the least sensitive factor. The study expands the application of LCOE, and provides a decision-making solution for the PPA pricing of renewable energy power enterprises. It is expected to help promote power transactions by renewable energy companies.