基于类噪声的解耦测辨负荷模型机理分析及应用
作者:
作者单位:

(1.国网江苏省电力有限公司,江苏 南京 210024;2.清华大学电机工程与应用电子技术系,北京 100084;3.上海电力大学电气工程学院,上海 200090)

作者简介:

通讯作者:

周晋航(1997—),男,硕士研究生,主要从事负荷辨识方面研究;E?mail:zjhyddx@163.com

中图分类号:

TM714

基金项目:

国网江苏省电力有限公司科技项目(20192001526)


Mechanism analysis and application of ambient noise decoupling load measurement and identification model
Author:
Affiliation:

(1.State Grid Corporation of Jiangsu Province Nanjing, Nanjing 210024, China;2.Department of Electrical Engineering, Tsinghua University,Beijing 100084, China; 3.Electrical Power Engineering of Shanghai University of Electric Power, Shanghai 200090,China)

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    摘要:

    负荷辨识是电力系统仿真的重要环节。为得到准确的负荷辨识动态参数,国内外学者在合理构建辨识模型方面做出了大量深入的研究。首先,在传统负荷模型基础上反推出2种基于类噪声的负荷实时动态参数辨识模型,实现测辨数据在辨识模型计算中的输入数据时序的解耦,同时避免辨识初始物理量冗余性以及辨识量误差迭代放大对参数功率响应能力造成的负面影响。再从类噪声仿真数据和实测数据上验证分析这2种测辨模型的数据功率响应能力。结果显示测辨得到负荷动态参数适用于现在的电力仿真系统,说明此研究能够为进一步研究辨识模型提供新方向,为负荷可控性提供数据基础。

    Abstract:

    Load identification is an important part of power system simulation. In order to obtain accurate load identification dynamic parameters, scholars at home and abroad have done a lot of in-depth research on the reasonable construction of identification models. Firstly, on the basis of the traditional load model, two real-time dynamic parameter identification load models based on ambient noise are deduced, which realizes the decoupling of the input data sequence of the measurement and identification data in the calculation of the identification model. At the same time, it avoids the negative impact of the identification of the initial physical quantity redundancy and the iterative amplification of the identification quantity error on the parameter power response capability. Then, the data power response capability of the two measurement and identification models is verified and analyzed from the ambient noise simulation data and the actual measurement data. The results show that the load dynamic parameters measured and identified are applicable to the current power simulation system, indicating that the research can provide a new direction for further research on the identification model and provide a data basis for load controllability.

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引用本文

徐 贤,周晋航,王 颖,等.基于类噪声的解耦测辨负荷模型机理分析及应用[J].电力科学与技术学报,2023,38(1):138-145.
XU Xian, ZHOU Jinhang, WANG Ying, et al. Mechanism analysis and application of ambient noise decoupling load measurement and identification model[J]. Journal of Electric Power Science and Technology,2023,38(1):138-145.

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  • 在线发布日期: 2023-04-10
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