Podrobná bibliografie
| Název: |
基于运行数据与智能优化算法辨识的汽轮机动态参数模型. (Chinese) |
| Alternate Title: |
Steam Turbine Dynamic Parameter Model Identified based on Operational Data and Intelligent Optimization Algorithms. (English) |
| Autoři: |
王辉, 郝晓光, 张文彬, 胡博杰 |
| Zdroj: |
Journal of Engineering for Thermal Energy & Power / Reneng Dongli Gongcheng; 2025, Vol. 40 Issue 10, p191-200, 10p |
| Abstract (English): |
To address the limitation of fixed parameter models in primary frequency regulation simulations of power grid, which fail to accurately reflect the impact of load variations on the dynamic response of steam turbines, a steam turbine dynamic parameter model identified based on operational data and intelligent optimization algorithms was proposed. Aiming at the model construction, dynamic operational data under different load conditions were divided into multiple intervals, and a multi-start strategy-based particle swarm optimization (PSO) algorithm was employed to identify parameters for each interval. Subsequently, it fitted the variation curves of each identified parameter with respect to unit load conditions to obtain the dynamic parameters of steam turbine model in actual operation. A 330 MW unit was selected as a case study, under load conditions ranging from 50% to 100% of rated power, and parameter identification was conducted at 5% load intervals. The established dynamic parameter model was then validated through simulations. The results demonstrate that under 91%, 70% and 53% rated load conditions, the determination coefficients (R) of the proposed model are 0.9989, 0.995 8 and 0.985 5, respectively, all of which surpass those of classical fixed parameter models. These results verify that the proposed model effectively enhances simulation accuracy under varying load conditions, providing a more reliable basis for power grid frequency regulation and safe operation of the system. [ABSTRACT FROM AUTHOR] |
| Abstract (Chinese): |
为解决当前电网一次调频仿真中固定参数模型无法准确反映负荷变化对汽轮机动态响应影响的问题, 提出基于运行数据与智能优化算法辨识的汽轮机动态参数模型。针对模型构建, 将不同负荷工况的动态运行数据划分为多个区间, 采用多启动策略的粒子群优化算法分别进行参数辨识, 并拟合各个参数随机组负荷工况变化的曲线, 从而获取能够准确反映实际运行中汽轮机模型的动态参数。选取某 330MW 机组为实例, 在 50% ~100% 负荷工况范围内, 以每 5% 负荷变化为间隔进行参数辨识, 构建汽轮机动态参数模型并进行仿真验证。结果表明: 在 91%, 70% 和 53% 额定负荷工况下, 所建模型的判定系数分别为 0.9989, 0.9958 和 0.9855, 均优于固定参数的经典模型, 验证了本文模型能够有效提高汽轮机在不同负荷工况下的仿真精度, 为电网频率调节与系统安全运行提供更可靠的依据。 [ABSTRACT FROM AUTHOR] |
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Copyright of Journal of Engineering for Thermal Energy & Power / Reneng Dongli Gongcheng is the property of Journal of Engineering for Thermal Energy & Power and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Databáze: |
Complementary Index |
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