Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
贝叶斯优化下电厂除灰助吹系统数值模拟节能研究. (Chinese) |
| Alternate Title: |
Numerical Simulation on Energy Saving of Ash Removal and Aided Blowing System in Power Plants Under Bayesian Optimization. (English) |
| Συγγραφείς: |
陈泽旭, 李海广, 张超 |
| Πηγή: |
Power Generation Technology; Jun2026, Vol. 47 Issue 3, p555-562, 8p |
| Θεματικοί όροι: |
Power plants, Energy conservation, Computer simulation, Computational fluid dynamics, Surrogate-based optimization, Mathematical optimization |
| Abstract (English): |
[Objectives] Current studies on energy saving of ash removal systems mainly rely on equipment modifications combined with numerical simulation, but their timeliness is limited. In contrast, the Bayesian optimization algorithm can efficiently explore the parameter space, improve the analysis efficiency of energy saving research in ash removal system, shorten the optimization process time, promote the timeliness of numerical simulation, and enhance the efficiency of ash removal system by optimizing the parameters of aided blowing, thereby achieving energy saving and consumption reduction, and improving the economic performance of power plants. Therefore, this study is conducted. [Methods] The computational particle fluid dynamics (CPFD) is used to conduct numerical simulation of the modified ash removal system, and the Bayesian optimization algorithm is employed to perform iterative calculation of different aided blowing parameters (aided blowing speed, aided blowing distance, aided blowing angle, and aided blowing position z). [Results] A total of 30 iterative cycles of optimization on the aided blowing parameters of ash removal system of power plants are carried out through the Bayesian optimization algorithm and CPFD. The energy consumption of the system is the lowest when the aided blowing distance is 2.4 m, the aided blowing speed is 2 m/s, the valve position is z1, and the aided blowing angle is 48° . [Conclusions] The system with valve optimization achieves an energy saving of 24% compared to the system without valve optimization, and an energy saving of 54.4% compared to the system without valves, demonstrating significant optimization performance. [ABSTRACT FROM AUTHOR] |
| Abstract (Chinese): |
【目的】目前对于除灰系统节能研究的方法主要为 设备改造结合数值模拟分析, 但时效性不高, 而贝叶斯 优化算法能高效探索参数空间, 可提升除灰系统节能研 究的分析效率, 缩短优化过程时间, 提高数值模拟时 效性。通过优化助吹参数提高除灰系统效率, 可实现节能 降耗, 提升电厂经济性, 因此展开相关研究。【方法】采 用 (computational particle fluid dynamics, CPFD) 对改造后除 灰系统进行数值模拟, 结合贝叶斯优化算法对不同助吹参 数 (助吹速度、助吹距离、助吹角度、助吹位置 z ) 进行迭代 计算。【结果】使用贝叶斯优化算法与 CPFD 对电厂除灰 助吹参数进行 30 次迭代优化。当助吹距离为 2.4 m 、助吹 速度为 2 m / s 、阀门位置 z 1、助吹角度为 48°时, 系统的能 耗最低。【结论】有阀门并进行优化的系统相比有阀门未 优化系统节能 24%, 比无阀门系统节能 54.4%, 优化效果 显著。 [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: |
Complementary Index |