基于学习曲线的CO_2捕集和可再生能源发电成本

Cost of carbon capture and storage and renewable energy generation based on the learning curve method

为研究CO2捕集与封存技术(CCS,carbon captureand storage)和风电、太阳能发电技术未来成本变化,该文利用年限平均法计算了不同技术的发电成本及构成;在对不同发电技术未来装机容量合理假设的基础上,利用学习曲线模型分析了中国光伏和风电技术的学习率,并分析了其未来发电成本的变化以及达到商业化所需要的社会投入成本;在分析CCS电站时,利用自下而上的方法,将捕集电站分解为不同的子系统,考察了其未来的发展。研究结果表明:风电技术为近期首选的减排技术,而光伏发电技术在长期具备竞争力;如果EOR(enhanced oil recovery)技术能够大规模推广,CCS技术也将具备充分的竞争力。

The future costs of carbon capture and storage（CCS） power plants,wind and PV（photovoltaic） plants were estimated using the straight-line method.The analyses use reasonable assumptions about the future capacities of these different power generation technologies and estimate of the learning rates for the PV and wind power systems using the learning curve method to estimate their future costs.This study also uses the bottom-up method to estimate future CCS developments by breaking down the power plants into sub-systems,each of which is assumed to be analogous to those in other power plants.The results show that wind power is the best choice to reduce emissions in the short time with photovoltaics more competitive in the long-term.If enhanced oil recovery can be improved more in the future CCS systems will also be competitive.