塔式太阳能原位开采油页岩系统余热回收及参数优化研究

侯宏娟, 王晶, 杜琼杰, 蔡亮

太阳能学报 ›› 2023, Vol. 44 ›› Issue (1) : 126-132.

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太阳能学报 ›› 2023, Vol. 44 ›› Issue (1) : 126-132. DOI: 10.19912/j.0254-0096.tynxb.2021-1536

塔式太阳能原位开采油页岩系统余热回收及参数优化研究

  • 侯宏娟1, 王晶1, 杜琼杰2, 蔡亮3
作者信息 +

RESEARCH ON WASTE HEAT RECOVERY AND PARAMETER OPTIMIZATION OF OIL SHALE IN-SITU RECOVERY SYSTEM DRIVEN BY SOLAR TOWER HEATING

  • Hou Hongjuan1, Wang Jing1, Du Qiongjie2, Cai Liang3
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文章历史 +

摘要

为减少油页岩原位开采过程中的化石能源消耗,构建塔式太阳能聚热页岩油原位开采系统模型,对集热场蒸汽参数和油页岩开采井间距进行优化,并在此基础上展开余热回收研究以提高系统综合能效。结果表明:通过对蒸汽参数和井间距进行优化,系统热效率η可由22.4%升至33.5%,再对生产井出口的蒸汽余热进行回收利用后,系统热效率η进一步提升(升至38.4%),页岩油生产成本Cp由306.0美元/t减少到174.7美元/t。

Abstract

Solar energy introduced in oil shale mining can reduce fossil energy consumption and carbon emissions. In this paper, an oil shale in-situ recovery system driven by solar tower is proposed, the steam parameters of the solar field and the spacing between producing wells are optimized. On this basis, the research on waste heat recovery is carried out to improve the energy efficiency of the system. The results show that by optimizing steam parameters and well spacing, the thermal efficiency η of the system can be increased from 22.4% to 33.5%, based on this, by recovering the steam waste heating of the production well, the thermal efficiency η of the system is further improved: increases to 38.4%, and the shale oil production cost PC decreases from 306.0 $/t to 174.7 $/t .

关键词

太阳能 / 油页岩 / 余热回收 / 塔式太阳能聚热 / 参数优化 / 夹点分析法

Key words

solar energy / oil shale / waste heat utilization / tower solar heating / parameter optimization / pinch point analysis

引用本文

导出引用
侯宏娟, 王晶, 杜琼杰, 蔡亮. 塔式太阳能原位开采油页岩系统余热回收及参数优化研究[J]. 太阳能学报. 2023, 44(1): 126-132 https://doi.org/10.19912/j.0254-0096.tynxb.2021-1536
Hou Hongjuan, Wang Jing, Du Qiongjie, Cai Liang. RESEARCH ON WASTE HEAT RECOVERY AND PARAMETER OPTIMIZATION OF OIL SHALE IN-SITU RECOVERY SYSTEM DRIVEN BY SOLAR TOWER HEATING[J]. Acta Energiae Solaris Sinica. 2023, 44(1): 126-132 https://doi.org/10.19912/j.0254-0096.tynxb.2021-1536
中图分类号: TK519   

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基金

北京市自然科学基金(3222042); 国家重点研发计划(2021YFE0194500)

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