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Study on supercritical CO_2 coal-fired boiler based on improved genetic algorithm

机译：基于改进遗传算法的超临界CO_2燃煤锅炉研究

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摘要

Supercritical CO2 coal-fired power generation technology is a new potential power generation technology due to its advantages of high efficiency, simple system and less carbon emission. In this study, a new global optimization model was designed with an improved genetic algorithm to optimize the supercritical CO2 boiler and evaluate its economy, aiming at levelized cost of energy (LCOE). Besides, the weighted mass method and thermodynamic calculation were adopted to accurately evaluate the cost of supercritical CO2 boiler. According to the optimization results, the heat absorption distribution and triangular distribution for the tube diameters of supercritical CO2 boiler from the furnace to the tail flue were given. The economic analysis of supercritical CO2 unit shows that the LCOE of empirical unit decreases by 9.26% compared to the conventional unit, and the optimized unit further decreases by 1.13%. In the cost of supercritical CO2 unit, the cost of boiler, recuperator and precooler is higher than that of the conventional unit. And the increased cost of heating surfaces at tail flue mainly accounts for the increased equipment cost of boiler. Finally, the sensitivity analysis shows that the regions that has high coal price is more suggested for the development of supercritical CO2 unit, and the unit also has excellent economic advantages under low load condition.
机译：超临界CO2燃煤发电技术是一种新的潜在发电技术，因为它具有高效率，简单的系统和较少的碳排放的优点。在本研究中，设计了一种新的全局优化模型，设计了一种改进的遗传算法，优化超临界CO2锅炉并评估其经济，旨在稳定能量（LCoE）成本。此外，采用了加权质量法和热力学计算来精确评估超临界CO2锅炉的成本。根据优化结果，给出了从炉子到尾烟道的超临界CO2锅炉管直径的吸热分布和三角形分布。超临界CO2单元的经济分析表明，与常规单位相比，实证单位的LCOE降低了9.26％，优化的单元进一步降低了1.13％。在超临界CO2单元的成本中，锅炉，恢复器和前冷的成本高于传统单元的成本。尾部烟道中加热表面的成本增加主要占锅炉设备成本增加的占。最后，敏感性分析表明，对于超临界二氧化碳单位的开发，更有建议具有高煤价格的地区，该装置在低负荷条件下也具有优异的经济优势。

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  • 来源
    《Energy Conversion & Management》 |2020年第10期|113163.1-113163.14|共14页
  • 作者

    Zhu Meng; Zhou Jing; Su Sheng; Xu Jun; Li Aishu; Chen Lei; Wang Yi; Hu Song; Jiang Long; Xiang Jun;

  • 作者单位

    Huazhong Univ Sci & Technol Sch Energy & Power Engn State Key Lab Coal Combust Wuhan 430074 Peoples R China;

    Huazhong Univ Sci & Technol Sch Energy & Power Engn State Key Lab Coal Combust Wuhan 430074 Peoples R China;

    Huazhong Univ Sci & Technol Sch Energy & Power Engn State Key Lab Coal Combust Wuhan 430074 Peoples R China;

    Huazhong Univ Sci & Technol Sch Energy & Power Engn State Key Lab Coal Combust Wuhan 430074 Peoples R China;

    Huazhong Univ Sci & Technol Sch Energy & Power Engn State Key Lab Coal Combust Wuhan 430074 Peoples R China;

    Huazhong Univ Sci & Technol Sch Energy & Power Engn State Key Lab Coal Combust Wuhan 430074 Peoples R China;

    Huazhong Univ Sci & Technol Sch Energy & Power Engn State Key Lab Coal Combust Wuhan 430074 Peoples R China;

    Huazhong Univ Sci & Technol Sch Energy & Power Engn State Key Lab Coal Combust Wuhan 430074 Peoples R China;

    Huazhong Univ Sci & Technol Sch Energy & Power Engn State Key Lab Coal Combust Wuhan 430074 Peoples R China;

    Huazhong Univ Sci & Technol Sch Energy & Power Engn State Key Lab Coal Combust Wuhan 430074 Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Supercritical CO2; Coal-fired boiler; Genetic algorithm; Global optimization; LCOE; Economic analysis;

    机译：超临界二氧化碳;燃煤锅炉;遗传算法;全局优化;LCoE;经济分析;

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