Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 2958-2967 |
| Journal | IET Generation, Transmission & Distribution |
| Volume | 12 |
| Issue number | 12 |
| DOIs | |
| Publication status | Published - 4 Apr 2018 |
| Externally published | Yes |
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SG parameters estimation based on synchrophasor data. / Ahmadzadeh-Shooshtari, Babak (Corresponding author); Torkzadeh, Roozbeh; Kordi, Meysam; Marzooghi, Hesamoddin; Eghtedarnia, Fariborz.
In: IET Generation, Transmission & Distribution, Vol. 12, No. 12, 04.04.2018, p. 2958-2967.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - SG parameters estimation based on synchrophasor data
AU - Ahmadzadeh-Shooshtari, Babak
AU - Torkzadeh, Roozbeh
AU - Kordi, Meysam
AU - Marzooghi, Hesamoddin
AU - Eghtedarnia, Fariborz
PY - 2018/4/4
Y1 - 2018/4/4
N2 - In this study, first, it is shown that the least-squares (LS) algorithm outperforms well known methods such as extended Kalman filter and unscented Kalman filter for synchronous generator (SG) parameters estimation using phasor measurement unit (PMU) data. However, as the LS algorithm may estimate the SG parameters inaccurately if the initial values of SG model state variables are not valid, a modified LS (MLS) algorithm, which estimates the initial values of SG model state variables alongside SG parameters, is proposed. In addition to parameters estimation of an SG classical model, the performance of this algorithm in the estimation of whole electromagnetic parameters and rotor inertia constant of an SG full-order model is evaluated. Note that conventionally, measurements of generators rotor angles were used to estimate SGs full-order model parameters; nevertheless, in the proposed MLS algorithm, online SG parameters estimation is accomplished using PMU data without relying on rotor angle measurement that is difficult to be obtained in practise. Simulation results demonstrate the effectiveness of the proposed algorithm in SG parameters estimation for various disturbances and noisy measurements. Furthermore, the effect of mechanical torque signal unavailability on the proposed algorithm capability is studied, where the efficacy of this algorithm is proven.
AB - In this study, first, it is shown that the least-squares (LS) algorithm outperforms well known methods such as extended Kalman filter and unscented Kalman filter for synchronous generator (SG) parameters estimation using phasor measurement unit (PMU) data. However, as the LS algorithm may estimate the SG parameters inaccurately if the initial values of SG model state variables are not valid, a modified LS (MLS) algorithm, which estimates the initial values of SG model state variables alongside SG parameters, is proposed. In addition to parameters estimation of an SG classical model, the performance of this algorithm in the estimation of whole electromagnetic parameters and rotor inertia constant of an SG full-order model is evaluated. Note that conventionally, measurements of generators rotor angles were used to estimate SGs full-order model parameters; nevertheless, in the proposed MLS algorithm, online SG parameters estimation is accomplished using PMU data without relying on rotor angle measurement that is difficult to be obtained in practise. Simulation results demonstrate the effectiveness of the proposed algorithm in SG parameters estimation for various disturbances and noisy measurements. Furthermore, the effect of mechanical torque signal unavailability on the proposed algorithm capability is studied, where the efficacy of this algorithm is proven.
U2 - 10.1049/iet-gtd.2017.1989
DO - 10.1049/iet-gtd.2017.1989
M3 - Article
VL - 12
SP - 2958
EP - 2967
JO - IET Generation, Transmission & Distribution
JF - IET Generation, Transmission & Distribution
SN - 1751-8687
IS - 12
ER -