参数可观测性分析及其在电力负荷模型中的应用

JU Ping

您当前的位置：

首页 >

文章列表页 >

参数可观测性分析及其在电力负荷模型中的应用

更新时间：2025-08-13

- 参数可观测性分析及其在电力负荷模型中的应用
- Automation of Electric Power Systems Vol. 40, Issue 5, Pages: 32-37(2016)
- 作者机构：
  
  河海大学能源与电气学院,江苏省,南京市,211100
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2016
- 稿件说明：
移动端阅览
JU Ping. [J]. Automation of electric power systems, 2016, 40(5): 32-37.
DOI：

JU Ping. [J]. Automation of electric power systems, 2016, 40(5): 32-37. DOI：

摘要

给出了参数可观测性概念

指出如果输入激励的功率谱能够覆盖研究对象的振荡频率

则能够在输出信号中观测到这些振荡频率

从而也就可以观测到其对应的模式和参数。提出基于参数的功率谱灵敏度来定量分析参数可观测性

基于输出功率谱实测值与计算值误差平方和的最小化来优化辨识参数。以一个二阶系统为例

分析了输入激励类型、系统幅频特性尤其是系统阻尼对参数可观测性的影响。针对电力负荷传递函数模型

分析了负荷模型的频域特性

通过两种不同频谱分布的激励信号

验证了参数可观测性方法的正确性。

Abstract

The concept of parameter observability is given

which indicates that if the power spectrum of input excitation can cover the oscillation frequency of the system

then the frequency can be observed via the output. So the corresponding modality and parameters can be identified. The power spectral sensitivity based on parameters is proposed to quantitatively analyze the parameter observability. Parameters are identified by minimizing the sum of square error between the measured and the calculated values of power spectrum. By taking a second-order system as an example

the factors of parameter observability are analyzed upon input excitation

the amplitude-frequency characteristic of system

especially the system damping. Finally

the frequency-domain characteristics of the power load model are studied

and the correctness of the concept proposed is verified by parameter identification using two different kinds of excitation signals. This work is supported by National Natural Science Foundation of China (No. 51137002

No. 51190102

No. 51377046).

关键词

Keywords

references

Views

2541

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Frequency Response Estimation Method Considering Low Voltage Ride-through Recovery Difference of Wind Farms Under Large Disturbance

Integrated Identification Method for Parameters of Doubly-fed Wind Turbines Based on General Modeling in Frequency Domain

Data-driven Parameter Identification for Low-frequency Dynamic Model of Power System with High Proportion of Converters

Related Author

YAO Zenghui

DONG Wenkai

HAN Zijiao

JIA Qi

XIE Xiaorong

CHENG Hao

LYU Yazhou

LI Wei

Related Institution

State Grid Liaoning Electric Power Co., Ltd.

Department of Electrical Engineering, Tsinghua University

Southwest Branch of State Grid Corporation of China

NARI Nanjing Control Systems Co., Ltd.

School of Electrical Engineering, Dalian University of Technology

⁰