CIESC Journal ›› 2013, Vol. 64 ›› Issue (12): 4628-4633.DOI: 10.3969/j.issn.0438-1157.2013.12.053

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Multi-objective optimization of coal gasifier using NSES

ZHANG Yu1, YAN Liexiang1, LI Guojian2, SHI Bin1   

  1. 1. College of Chemical Engineering, Wuhan University of Technology, Wuhan 430070, Hubei, China;
    2. Hubei Electric Power Survey & Design Institute, Wuhan 430040, Hubei, China
  • Received:2013-06-28 Revised:2013-07-05 Online:2013-12-05 Published:2013-12-05
  • Supported by:

    supported by the National Natural Science Foundation of China (20976142) and the High-tech Research and Development Program of China (2011AA02A206).

非支配排序进化策略求解煤气化多目标优化问题

张宇1, 鄢烈祥1, 李国建2, 史彬1   

  1. 1. 武汉理工大学化学工程学院, 湖北 武汉 430070;
    2. 湖北省电力勘测设计院, 湖北 武汉 430040
  • 通讯作者: 鄢烈祥
  • 作者简介:张宇(1988- ),男,硕士研究生。
  • 基金资助:

    国家自然科学基金项目(20976142);国家高技术研究发展计划项目(2011AA02A206)。

Abstract: Non-dominated sorting evolution strategy (NSES) is used to solve the multi-objective optimization problem of coal gasifier.The solving of the two classical test function with NSES indicates that NSES is effective comparing to NSGA-2.Aspen Plus is applied to the simulation of the coal gasifier process.On this basis,with the ratio of oxygen to coal,ratio of water to coal and gasification pressure as optimization variables,and taking the yield of effective gases and cold gas efficiency as goals,the sensitivity analysis is completed.The results show that the three variables have more or less influence on gasification indexes.NSES is used to solve that multi-objective optimization model.The two goals' compromise solution including the cold gas efficiency and yield of effective gases can be achieved based on the Pareto front.

Key words: algorithm, coal gasifier, computer simulation, multi-objective, optimization design

摘要: 应用非支配排序进化策略(non-dominated sorting evolution strategy,NSES)对煤气化多目标优化问题进行求解。通过解两个经典测试函数,并与NSGA-2算法进行比较,表明了非支配排序进化策略的有效性和优势。应用Aspen Plus流程模拟软件对煤气化过程进行了模拟计算。在此基础上,以氧煤比、水煤比、气化炉的压力为操作变量,分别对冷煤气效率和有效气产出率两个目标进行灵敏度分析。分析结果表明,3个变量对气化结果评价指标均有不同程度的影响。将非支配进化策略用于煤气化过程的多目标优化模型的求解,得到了Pareto最优前沿面,为确定冷煤气效率和有效气产出率两个目标的协调提供了依据。

关键词: 算法, 煤气化, 计算机模拟, 多目标, 优化设计

CLC Number: