A novel 3-layer mixed cultural evolutionary optimization framework for optimal operation of syngas production in a Texaco coal-water slurry gasifier

doi:10.1016/j.cjche.2015.03.005

›› 2015, Vol. 23 ›› Issue (9): 1484-1501.DOI: 10.1016/j.cjche.2015.03.005

• 过程系统工程与过程安全 • 上一篇下一篇

A novel 3-layer mixed cultural evolutionary optimization framework for optimal operation of syngas production in a Texaco coal-water slurry gasifier

Cuiwen Cao¹, Yakun Zhang¹, Teng Yu¹, Xingsheng Gu¹, Zhong Xin², Jie Li³

1 Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China;
2 State Key Laboratory of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China;
3 State Key Laboratory of Multiphase Complex Systems, Institute of Processing Engineering, Chinese Academy of Sciences, Beijing 100190, China

收稿日期:2014-09-04 修回日期:2015-01-11 出版日期:2015-09-28 发布日期:2015-10-24
通讯作者: Cuiwen Cao, Jie Li
基金资助:
Supported by the National Natural Science Foundation of China (61174040, U1162110, 21206174), and Shanghai Commission of Nature Science (12ZR1408100).

A novel 3-layer mixed cultural evolutionary optimization framework for optimal operation of syngas production in a Texaco coal-water slurry gasifier

Cuiwen Cao¹, Yakun Zhang¹, Teng Yu¹, Xingsheng Gu¹, Zhong Xin², Jie Li³

1 Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China;
2 State Key Laboratory of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China;
3 State Key Laboratory of Multiphase Complex Systems, Institute of Processing Engineering, Chinese Academy of Sciences, Beijing 100190, China

Received:2014-09-04 Revised:2015-01-11 Online:2015-09-28 Published:2015-10-24
Supported by:
Supported by the National Natural Science Foundation of China (61174040, U1162110, 21206174), and Shanghai Commission of Nature Science (12ZR1408100).

摘要/Abstract

摘要： Optimizing operational parameters for syngas production of Texaco coal-water slurry gasifier studied in this paper is a complicated nonlinear constrained problem concerning 3 BP (Error Back Propagation) neural networks. To solve this model, a new 3-layer cultural evolving algorithmframeworkwhich has a population space, amediumspace and a belief space is firstly conceived. Standard differential evolution algorithm (DE), genetic algorithm (GA), and particle swarm optimization algorithm (PSO) are embedded in this framework to build 3-layer mixed cultural DE/GA/ PSO (3LM-CDE, 3LM-CGA, and 3LM-CPSO) algorithms. The accuracy and efficiency of the proposed hybrid algorithms are firstly tested in 20 benchmark nonlinear constrained functions. Then, the operational optimization model for syngas production in a Texaco coal-water slurry gasifier of a real-world chemical plant is solved effectively. The simulation results are encouraging that the 3-layer cultural algorithm evolving framework suggests ways in which the performance of DE, GA, PSO and other population-based evolutionary algorithms (EAs) can be improved, and the optimal operational parameters based on 3LM-CDE algorithm of the syngas production in the Texaco coalwater slurry gasifier shows outstanding computing results than actual industry use and other algorithms.

关键词: 3-Layermixed cultural evolutionary framework, Optimal operation, Syngas production, Coal-water slurry gasifier

Abstract: Optimizing operational parameters for syngas production of Texaco coal-water slurry gasifier studied in this paper is a complicated nonlinear constrained problem concerning 3 BP (Error Back Propagation) neural networks. To solve this model, a new 3-layer cultural evolving algorithmframeworkwhich has a population space, amediumspace and a belief space is firstly conceived. Standard differential evolution algorithm (DE), genetic algorithm (GA), and particle swarm optimization algorithm (PSO) are embedded in this framework to build 3-layer mixed cultural DE/GA/ PSO (3LM-CDE, 3LM-CGA, and 3LM-CPSO) algorithms. The accuracy and efficiency of the proposed hybrid algorithms are firstly tested in 20 benchmark nonlinear constrained functions. Then, the operational optimization model for syngas production in a Texaco coal-water slurry gasifier of a real-world chemical plant is solved effectively. The simulation results are encouraging that the 3-layer cultural algorithm evolving framework suggests ways in which the performance of DE, GA, PSO and other population-based evolutionary algorithms (EAs) can be improved, and the optimal operational parameters based on 3LM-CDE algorithm of the syngas production in the Texaco coalwater slurry gasifier shows outstanding computing results than actual industry use and other algorithms.

Key words: 3-Layermixed cultural evolutionary framework, Optimal operation, Syngas production, Coal-water slurry gasifier

Cuiwen Cao, Yakun Zhang, Teng Yu, Xingsheng Gu, Zhong Xin, Jie Li. A novel 3-layer mixed cultural evolutionary optimization framework for optimal operation of syngas production in a Texaco coal-water slurry gasifier[J]. , 2015, 23(9): 1484-1501.

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A novel 3-layer mixed cultural evolutionary optimization framework for optimal operation of syngas production in a Texaco coal-water slurry gasifier

A novel 3-layer mixed cultural evolutionary optimization framework for optimal operation of syngas production in a Texaco coal-water slurry gasifier

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