Suppr超能文献

考虑水轮机非线性和参数变化压力管道模型的并网水电站稳定性分析

Stability analysis of grid-connected hydropower plant considering turbine nonlinearity and parameter-varying penstock model.

作者信息

Feng Chen, Sun Na, Zheng Chuang, Zhu Yongqi, Zhang Nan, Shan Yahui, Shi Liping, Xue Xiaoming

机构信息

Jiangsu Key Laboratory of Advanced Manufacturing Technology, Huaiyin Institute of Technology, Huai'an, 223003, China.

College of Energy and Electrical Engineering, Hohai University, Nanjing, 211100, China.

出版信息

Sci Rep. 2025 Apr 25;15(1):14532. doi: 10.1038/s41598-025-98226-2.

Abstract

This paper aims to investigate the nonlinear stability and dynamic characteristics of the grid-connected hydro-turbine governing system (GCHTGS) considering the parameter-varying model (PVM) of penstock and turbine nonlinearity. Considering the inertia of fluid flow and water head loss of the penstock, a novel PVM of penstock with higher precision and simpler form is proposed, where the parameter determination process is developed to simplify the transcendental function of PVM. The accuracy of PVM has been sufficiently validated by numerical simulation. BP neural networks (BPNN) are used to establish the nonlinear model of the hydro-turbine. The NN-based differentiation method (NND) is adopted to obtain the transfer coefficients of the linear hydro-turbine model under full operating conditions (FOC). The nonlinear state space equations of GCHTGS with PVM and variable transfer coefficients are established. First, the influence of different penstock models on stability is investigated, and the comparison results show that the proposed PVM has a more precise stability region. Then the influence laws of operation conditions on the stability of GCHTGS are revealed. Finally, based on sensitivity analysis, qualitative and quantitative analyses of the effect of parameters on stability and dynamic characteristics are performed. This work establishes a more precise nonlinear GCHTGS model and provides a better understanding of the influence of hydro-turbine nonlinearity on the stability and parameter sensitivity of GCHTGS.

摘要

本文旨在研究考虑压力管道参数变化模型(PVM)和水轮机非线性的并网水轮机调节系统(GCHTGS)的非线性稳定性和动态特性。考虑到水流惯性和压力管道的水头损失,提出了一种精度更高、形式更简单的新型压力管道PVM,其中参数确定过程被开发以简化PVM的超越函数。PVM的精度已通过数值模拟得到充分验证。采用BP神经网络(BPNN)建立水轮机的非线性模型。采用基于神经网络的微分方法(NND)获得水轮机线性模型在全工况(FOC)下的传递系数。建立了具有PVM和可变传递系数的GCHTGS的非线性状态空间方程。首先,研究了不同压力管道模型对稳定性的影响,比较结果表明所提出的PVM具有更精确的稳定区域。然后揭示了运行工况对GCHTGS稳定性的影响规律。最后,基于灵敏度分析,对参数对稳定性和动态特性的影响进行了定性和定量分析。这项工作建立了一个更精确的非线性GCHTGS模型,并更好地理解了水轮机非线性对GCHTGS稳定性和参数灵敏度的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a9e/12032123/9a6db2f5a39b/41598_2025_98226_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验