Simulation and optimization of rice husk gasification using intrinsic reaction rate based CFD model

被引：22
作者：
Gao, Xiaoyan [1 ]
Xu, Fei [2 ]
Bao, Fubing [1 ]
Tu, Chengxu [1 ]
Zhang, Yaning [3 ,4 ]
Wang, Yingying [4 ]
Yang, Yang [5 ]
Li, Bingxi [3 ]
机构：
[1] China Jiliang Univ, Coll Metrol & Measurement Engn, Hangzhou 310018, Zhejiang, Peoples R China
[2] Ansys Inc, Elect Business Unit, Austin, TX 78746 USA
[3] Harbin Inst Technol, Sch Energy Sci & Engn, Harbin 150001, Heilongjiang, Peoples R China
[4] Taizhou Huangyan Architecture & Engn Qual Supervi, Taizhou 318020, Peoples R China
[5] Corning Inc, Mfg Technol & Engn Div, Corning, NY 14831 USA
来源：
RENEWABLE ENERGY | 2019年 / 139卷
基金：
中国国家自然科学基金;
关键词：
Rice husk; Gasification; Sensitivity analysis; Multi-objective optimization; Pareto optimal solution; BIOMASS GASIFICATION; BED GASIFICATION; FIXED-BED; GAS;
D O I：
10.1016/j.renene.2019.02.108
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
Entrained flow gasification processes of rice husk were simulated and optimized in this study using an intrinsic reaction rate based CFD model. A detailed sensitivity analysis was conducted to characterize the effects of operation parameters on the gas composition, gas production and cold gas efficiency. Gasification temperature, average particle diameter, ER (equivalence ratio) and CO2/biomass (mass ratio of carbon dioxide to biomass) are important operation parameters affecting the gasification process, and they were investigated in this study. Three-objective optimization of rice husk gasification was performed base on the response surface methodology (RSM) to maximize CO content, gas production, and cold gas efficiency, and the Pareto optimal solutions were obtained from NSGA-II (non-dominated sorting genetic algorithm) to instruct gasification operation. With standard TOPSIS (technique for order preference by similarity to ideal situation), the optimal solutions with CO concentration of 25.15%, gas production of 1.96 Nm(3)/kg and cold gas efficiency of 65.34% were obtained. (C) 2019 Published by Elsevier Ltd.
引用
收藏
页码：611 / 620
页数：10
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