详细信息
Heat Integration for Phenols and Ammonia Recovery Process of Coal Gasification Wastewater Considering Optimization of Process Parameters ( SCI-EXPANDED收录 EI收录)
文献类型:期刊文献
英文题名:Heat Integration for Phenols and Ammonia Recovery Process of Coal Gasification Wastewater Considering Optimization of Process Parameters
作者:Ye, Qiliang[1];Zeng, Jiang[1];Li, Yuan[1];Yuan, Peiqing[1];Wang, Fuchen[2]
机构:[1]East China Univ Sci & Technol, Sch Chem Engn, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Shanghai Engn Res Ctr Coal Gasificat, Shanghai 200237, Peoples R China
年份:2022
卷号:15
期号:23
外文期刊名:ENERGIES
收录:;EI(收录号:20225013229065);WOS:【SCI-EXPANDED(收录号:WOS:000896329100001)】;
基金:This research was funded by the National Natural Science Foundation of China (Grant No. 22178113). And The APC was funded by Qiliang Ye.
语种:英文
外文关键词:coal gasification wastewater; heat exchanger network; heat integration; genetic algorithm
摘要:A heat integration optimization method that considers the changes in process parameters is proposed to find the global optimal process scheme for a coal chemical company's phenols and ammonia recovery process. The phenols and ammonia recovery process is simulated by Aspen Plus, and a programming method for heat exchanger networks synthesis that can simultaneously optimize process parameters and heat integration is constructed by Matlab. Taking the total annual cost as the objective function, the following process parameters are optimized: the hot feed temperature and cold/hot feed ratio of sour water stripper, the temperature of three-step partial condensation system, the feed temperature and column pressure of both solvent distillation column and solvent stripper. The result shows that, compared with the heat integration process under original process parameters, the new heat integration process saves 14.3% energy consumption and reduces the total annual cost by about 15.1%. The new heat integration process provides guidance for the optimization of the phenols and ammonia recovery process. The proposed heat integration optimization method based on changing process parameters is an effective and practical tool that offers good application prospects.
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