Multi-objective optimization and 4E analysis of a multigeneration system for hydrogen production using WHR in cement plants

被引:0
|
作者
Dashtizadeh, Ebrahim [1 ]
Houshfar, Ehsan [1 ]
机构
[1] Univ Tehran, Coll Engn, Sch Mech Engn, POB 11155-4563, Tehran, Iran
关键词
Waste heat recovery; Cement industry; Alkaline electrolyzer; Artificial Neural Network (ANN); RO Desalination; ORGANIC RANKINE-CYCLE; WASTE HEAT-RECOVERY; EXERGY; ENERGY;
D O I
10.1016/j.rineng.2024.103845
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The cement industry is notorious for its significant energy consumption and CO2 emissions. This research focuses on enhancing energy efficiency by implementing a waste heat recovery system in cement plants. A unique power generation setup is proposed, combining a steam Rankine cycle with a reheating process and an organic Rankine cycle utilizing methanol as the working fluid. Through optimization using artificial neural networks and genetic algorithms for exergy and economic considerations, a multigeneration cycle is developed. This system not only produces 21.48 MW of electricity, meeting all the plant's power needs and supplying water through reverse osmosis but also facilitates hydrogen production, freshwater generation, oxy-fuel combustion, and natural gas blending with hydrogen. By incorporating a hydrogen production process, this cycle reduces methane consumption by 2361.6 tonnes and minimizes the energy demand of the air separation unit by 1200 MWh annually. This innovative multigeneration cycle achieves exergy and energy efficiencies of 63.39% and 27.46%, respectively, with a payback period of 3.59 years and a net present value of $51.63 million. Furthermore, it slashes CO2 emissions by 62550 tonnes each year.
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页数:17
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