文献类型：期刊文献

英文题名：Learning rates and cost reduction potential of indirect coal-to-liquid technology coupled with CO2 capture

作者：Zhou, Li[1];Duan, Maosheng[1];Yu, Yadong[2];Zhang, Xiliang[1]

机构：[1]Tsinghua Univ, Inst Energy Environm & Econ, Beijing 100084, Peoples R China;[2]East China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China

年份：2018

卷号：165

起止页码：21

外文期刊名：ENERGY

收录：;WOS:【SSCI(收录号:WOS:000455171600003)，SCI-EXPANDED(收录号:WOS:000455171600003)】；

基金：We are grateful for financial support for this study from the National Natural Science Foundation of China Program (No. 21306099 and No. 71690243). The comments from the anonymous referees are greatly appreciated.

语种：英文

外文关键词：Carbon capture and storage; Coal to liquid; Cost curve; Learning rate; ETS

摘要：Coal-to-liquids (CTL) and CO2 capture and storage (CCS) have attracted increasing attention in energy supply systems, but few empirical studies and industrial data are available regarding the learning rates and future cost curves. In this study, methods and equations for estimating the learning rates of indirect CTL technology coupled CO2 capture (CC) were introduced. Thermal efficiency was considered as the system efficiency and CO2 emission were obtained from Aspen Plus simulation. Economic parameters were estimated using a cost estimation model. The results showed that when the cumulative production of oil reaches 100 million tons, the oil cost for FT with CC may decrease by 5.9%-21.2%, whereas that for FT without CC may decrease by 6.3%-22.4%. CO2 emission reduction costs may decrease by approximately 8.9%-32.3%. FT with CC technology may not be economical compared with FT without CC for some time. The price of CO2 emissions in national ETS might be not enough to stimulate companies to adopt CCS. We also discussed the effects of the technological maturity and the overall performance improvements. Improvement of technological R&D was needed in some key technologies such as coal gasification and FT synthesis, as well as industrial demonstrations. (C) 2018 Elsevier Ltd. All rights reserved.