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用于可再生电力消纳的沼气直接甲烷化研究

Study on direct methanation of biogas for utilization of renewable electricity
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摘要 利用甲烷化反应将沼气中的二氧化碳转化为甲烷可以同时实现绿氢的消纳和可再生能源的高效利用。本文将沼气直接甲烷化和高温固体氧化物电解池(SOEC)电解水制氢过程耦合,以实现可再生电力的消纳与生物沼气能源的利用。首先,对比了Pt基镍硅催化剂和Ru基镍铈催化剂的CO_(2)甲烷化活性,二者均能高选择性地在400℃、0.1 MPa下实现模拟沼气中CO_(2)的甲烷化,Pt基镍硅催化剂由于更低的贵金属用量具有一定的成本优势。其次,通过二段甲烷化工艺优化,使用Pt基镍硅催化剂在2620 h^(-1)空速下单程转化率超过95%,甲烷选择性接近100%。最后,建立了SOEC电解水制氢与沼气直接甲烷化的工艺计算模型,系统理论能效为70.6%;通过热交换网络的设计,系统理论能效提高到85.4%,能效提升显著。 The methanation of CO_(2) in biogas could simultaneously realize the consumption of green hydrogen and utilization of renewable energy efficiently.In this study,direct methanation of biogas is coupled with hydrogen production using high-temperature solid oxide electrolysis cell(SOEC),which is aimed for renewable electricity consumption and biogas upgrading.Firstly,the CO_(2) methanation activity of Pt-based Ni/SiO_(2) and Ru-based Ni/Ce_(0.9)Zr_(0.1_O_(2) catalysts is studied,which realize the conversion of CO_(2) in model biogas with high selectivity at 400°C and 0.1 MPa.The Pt-based Ni/SiO_(2) shows cost efficiency due to the low usage of noble metal.Secondly,using two-stage methanation process,the CO_(2) conversion of over 95% and CH_(4) selectivity of about 100%is achieved at space velocity of 2620 h^(-1) with Pt-based Ni/SiO_(2) catalyst.Finally,a simulation model with hydrogen production via SOEC and biogas direct methanation is built with theoretical system energy efficiency of 70.6%.A heat exchange network is designed to improve the energy efficiency to 85.4%.
作者 马芳平 张柳 曾庆 彭放 胡强 吴可荆 MA Fang-ping;ZHANG Liu;ZENG Qing;PENG Fang;HU Qiang;WU Ke-jing(Dadu River Hydropower Development Co.,Ltd.,Chengdu 610041,China;Institute of New Energy and Low-carbon Technology,Sichuan University,Chengdu 610207,China;Sichuan Energy Internet Research Insititute,Tsinghua University,Chengdu 610042,China)
出处 《化学研究与应用》 CAS CSCD 北大核心 2022年第8期1819-1827,共9页 Chemical Research and Application
基金 四川省科技计划项目(2020YFG0314)资助。
关键词 沼气 CO_(2)甲烷化 催化剂 绿氢 系统模拟 biogas CO_(2)methanation catalyst green hydrogen system modeling
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