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【目的】碳排放的精确计量有利于碳减排活动的开展,在估算燃煤电厂的CO2排放量时,对其气体辐射特性计算方法中,逐线法计算精度高但耗时严重,统计窄谱带法计算效率高但精度有限。为解决二者精度与效率难以兼顾的问题,本文对计算方法进行改进。【方法】本文提出一种融合逐线法(line by line,LBL)高精度、统计窄谱带法(statistical narrow band,SNB)高效率优势的自适应LBL-SNB混合计算方法。将光谱范围等分为若干区域,依据各区域内谱线的总强度筛选出高强度波段,在强波段±10 cm-1范围内采用LBL计算,对相邻强波段间的谱线采用SNB计算;在保证关键谱线计算精度的前提下提升整体计算效率,可通过调整强波段筛选比例,灵活平衡计算精度与速度。【结果】研究表明,在压力1.01×105 Pa、温度1 500 K和纯CO2的条件下,计算2 200～2 400 cm-1范围内CO2辐射特性时,LBL-SNB模型(阈值为10%)耗时217.83 s,仅为传统逐线法的12.16%,且随着阈值参数的增大,其吸收系数计算结果与LBL模型的一致性显著提升。在上述相同条件下,模拟3种不同变化趋势的入射光谱(单调递减、单调递增及固定不变)透过CO2气层后的辐射传输特性,其中LBL-SNB模型占用内存64 016字节,SNB模型占用内存624字节,LBL模型占用内存320 016字节,LBL-SNB模型内存使用仅为LBL模型的20%,说明LBL-SNB混合计算方法在内存节省方面具有显著优势。【结论】LBL-SNB模型在继承LBL模型对强谱线信息精准计算优势的同时,大幅降低了内存消耗,相较于SNB模型展现出更高的计算精度,在光谱辐射特性研究中具有很好的应用价值,有助于推动煤电领域碳计量的发展。
Abstract：[Objective] The accurate measurement of carbon emissions is conducive to the development of carbon emission reduction activities. When estimating the CO2 emissions of coal-fired power plants, the line-by-line method has high calculation accuracy but serious time-consuming, and the statistical narrow-band method has high calculation efficiency but limited accuracy. In order to solve the problem that the accuracy and efficiency of the two are difficult to balance, this paper improves the calculation method. [Methods] To address this trade-off between accuracy and efficiency, an adaptive LBL-SNB hybrid computational method is proposed, combining the high precision of LBL with the computational efficiency of SNB. The method divides the spectral range into equal sub-regions and evaluates the total line intensity within each sub-region. [Results] The results show that under the conditions of pressure 1.01×105 Pa, temperature 1 500 K and pure CO2 condition, the LBL-SNB model( threshold 10%) takes 217.83 s to calculate the CO2 radiation characteristics in the range of 2 200 ～ 2 400 cm-1. The calculation time of this model is only 12.16% of that of the traditional line-by-line method. With the increase of threshold parameters, the consistency between the calculation results of the absorption coefficient and the LBL model is significantly enhanced. Under the same conditions above, the radiative transfer characteristics of three different trends of incident spectra(monotonically decreasing, monotonically increasing and fixed) through the CO2 gas layer are simulated and calculated. Among them, the LBL-SNB model occupies 64 016 bytes of memory, the SNB model occupies 624 bytes of memory, and the LBL model occupies 320 016 bytes. The memory usage of the LBL-SNB model is only 20% of that of the LBL model, indicating that the LBL-SNB hybrid calculation method has certain advantages in memory saving. [Conclusion] The LBL-SNB model inherits the advantages of the LBL model for accurate calculation of strong spectral line information, and greatly reduces the memory consumption. Compared with the SNB model, the LBL-SNB model shows higher calculation accuracy, and has good application value in the study of spectral radiation characteristics, which is helpful to promote the development of carbon measurement in the field of coal and electricity.
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Basic Information:
DOI：10.19944/j.eptep.1674-8069.2025.06.004
China Classification Code:TP18;X773
Citation Information:
[1]张佳桢,许思源,柳华蔚.基于LBL-SNB混合算法的CO_2辐射特性计算[J].电力科技与环保,2025,41(06):900-908.DOI:10.19944/j.eptep.1674-8069.2025.06.004.
Fund Information:
国家自然科学基金项目(52106219); 冲压发动机技术全国重点实验室支持项目(WDZC6142703202412)