Adaptive Parameter Estimation of Power System Dynamic Model Using Modal Information

被引:31
作者
Guo, Song [1 ]
Norris, Sean [2 ]
Bialek, Janusz [2 ]
机构
[1] London Power Associates Ltd, Manchester, Lancs, England
[2] Univ Durham, Sch Engn & Comp Sci, Durham, England
基金
英国工程与自然科学研究理事会;
关键词
Dynamic power system modeling; parameter estimation; small signal analysis; synchronous generators; wide area measurements; ROBUST RLS METHODS; ONLINE ESTIMATION; ELECTROMECHANICAL MODES;
D O I
10.1109/TPWRS.2014.2316916
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A novel method for estimating parameters of a dynamic system model is presented using estimates of dynamic system modes (frequency and damping) obtained from wide area measurement systems (WAMS). The parameter estimation scheme is based on weighted least squares (WLS) method that utilizes sensitivities of the measured modal frequencies and damping to the parameters. The paper concentrates on estimating the values of generator inertias but the proposed methodology is general and can be used to identify other generator parameters such as damping coefficients. The methodology has been tested using a wide range of accuracy in the measured modes of oscillations. The results suggest that the methodology is capable of estimating accurately inertias and replicating the dynamic behavior of the power system. It has been shown that the damping measurements do not influence estimation of generator inertia. The method has overcome the problem of observability, when there were fewer measurements than the parameters to be estimated, by including the assumed values of parameters as pseudo-measurements.
引用
收藏
页码:2854 / 2861
页数:8
相关论文
共 50 条
  • [31] Adaptive parameter estimation for a general dynamical system with unknown states
    Zhang, Xiao
    Ding, Feng
    [J]. INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2020, 30 (04) : 1351 - 1372
  • [32] Parameter estimation and adaptive control of Euler-Lagrange systems using the power balance equation parameterisation
    Guadalupe Romero, Jose
    Ortega, Romeo
    Bobtsov, Alexey
    [J]. INTERNATIONAL JOURNAL OF CONTROL, 2023, 96 (02) : 475 - 487
  • [33] A new modified nonlinear Muskingum model and its parameter estimation using the adaptive genetic algorithm
    Zhang, Song
    Kang, Ling
    Zhou, Liwei
    Guo, Xiaoming
    [J]. HYDROLOGY RESEARCH, 2017, 48 (01): : 17 - 27
  • [34] PARAMETER ESTIMATION USING SPARSE RECONSTRUCTION WITH DYNAMIC DICTIONARIES
    Austin, Christian D.
    Ash, Joshua N.
    Moses, Randolph L.
    [J]. 2011 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2011, : 2852 - 2855
  • [35] Modal Analysis Applied to Dynamic Reduction of Power System Models
    Ayala, G. A. S.
    Centeno, V. A.
    [J]. IEEE LATIN AMERICA TRANSACTIONS, 2016, 14 (01) : 220 - 224
  • [36] A simple dynamic model for polymer electrolyte membrane fuel cell (PEMFC) power modules: Parameter estimation and model prediction
    Kim, Hyun-il
    Cho, Chan Young
    Nam, Jin Hyun
    Shin, Donghoon
    Chung, Tae-Yong
    [J]. INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2010, 35 (08) : 3656 - 3663
  • [37] Parameter estimation using dual fractional power filters
    Kinser, JM
    [J]. HYBRID IMAGE AND SIGNAL PROCESSING VII, 2000, 4044 : 29 - 36
  • [38] A Parameter Estimation Method for a Photovoltaic Power Generation System Based on a Two-Diode Model
    Huang, Chao-Ming
    Chen, Shin-Ju
    Yang, Sung-Pei
    [J]. ENERGIES, 2022, 15 (04)
  • [39] Online Estimation of Power System Inertia Using Dynamic Regressor Extension and Mixing
    Schiffer, Johannes
    Aristidou, Petros
    Ortega, Romeo
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2019, 34 (06) : 4993 - 5001
  • [40] Online Adaptive Parameter Estimation of a Finite Control Set Model Predictive Controlled Hybrid Active Power Filter
    Ferreira, Silvia Costa
    Foster, Joao Gabriel Luppi
    Gonzatti, Robson Bauwelz
    Pereira, Rondineli Rodrigues
    Pinheiro, Guilherme Goncalves
    Guimaraes, Bruno P. Braga
    [J]. ENERGIES, 2023, 16 (09)