Successful deployment of renewable fuel production requires substantial cost reduction along the entire value chain of the underlying manufacturing routes.To improve their performance,renewable fuel production technol...Successful deployment of renewable fuel production requires substantial cost reduction along the entire value chain of the underlying manufacturing routes.To improve their performance,renewable fuel production technologies should follow a cost-reducing learning curve.In this article,we adopt recent evidence that learning-by-doing is directly influenced by the technology unit size and explore three scenarios for microwave plasma CO_(2)conversion in which the learning rate varies between 10%,15%,and 20%.Our projections reveal that the total investments required to deploy this CO_(2)conversion technology at an exajoule scale decline from 83 down to 23 billion euros under a 10%increase in the value of the learning rate.The CO_(2) production costs in 2050 amount to 247–346€(2019)/t CO_(2),in which the range is determined by the value of the learning rate.Even under substantial learning until 2050 the levelized CO production cost is unlikely to become competitive with conventional natural gas-based CO_(2) production processes,except when a CO_(2)tax is applied of up to 150€(2019)/t CO_(2).To optimally exploit effects of learning-by-doing,we recommend developing several CO production technologies simultaneously with multiple unit sizes,so as to improve the chance of ultimately selecting the process with the highest learning rate.展开更多
基金the Ministry of Economic Affairs and Climate Policy of the Netherlands for its support enabling the research underlying this publication。
文摘Successful deployment of renewable fuel production requires substantial cost reduction along the entire value chain of the underlying manufacturing routes.To improve their performance,renewable fuel production technologies should follow a cost-reducing learning curve.In this article,we adopt recent evidence that learning-by-doing is directly influenced by the technology unit size and explore three scenarios for microwave plasma CO_(2)conversion in which the learning rate varies between 10%,15%,and 20%.Our projections reveal that the total investments required to deploy this CO_(2)conversion technology at an exajoule scale decline from 83 down to 23 billion euros under a 10%increase in the value of the learning rate.The CO_(2) production costs in 2050 amount to 247–346€(2019)/t CO_(2),in which the range is determined by the value of the learning rate.Even under substantial learning until 2050 the levelized CO production cost is unlikely to become competitive with conventional natural gas-based CO_(2) production processes,except when a CO_(2)tax is applied of up to 150€(2019)/t CO_(2).To optimally exploit effects of learning-by-doing,we recommend developing several CO production technologies simultaneously with multiple unit sizes,so as to improve the chance of ultimately selecting the process with the highest learning rate.
