SG parameters estimation based on synchrophasor data
Babak Ahmadzadeh-Shooshtari,Roozbeh Torkzadeh,Meysam Kordi,Hesamoddin Marzooghi,Hesamoddin Marzooghi,Fariborz Eghtedarnia +5 more
TL;DR: It is shown that the least-squares (LS) algorithm outperforms well known methods for synchronous generator (SG) parameters estimation using phasor measurement unit (PMU) data, and a modified LS (MLS) algorithm, which estimates the initial values of SG model state variables alongside SG parameters, is proposed.
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Abstract: 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.
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Citations
Field Current Waveform-Based Method for Estimation of Synchronous Generator Parameters Using Adaptive Black Widow Optimization Algorithm
Mihailo Micev,Martin Ćalasan,Dragan S. Petrovic,Ziad M. Ali,Nguyen Vu Quynh,Shady H. E. Abdel Aleem +5 more
TL;DR: A novel method for identification of synchronous generator parameters that is based on sudden short-circuit test data and a novel metaheuristic algorithm, called the adaptive black widow optimization algorithm, which tends to minimize the normalized sum of squared errors between simulation and experimental results.
Two Novel Approaches for Identification of Synchronous Machine Parameters from Short-Circuit Current Waveform
TL;DR: Two novel approaches for identifying the synchronous generator parameters are presented, using an experimentally obtained armature current during the short-circuit test as input data and a novel hybrid metaheuristic algorithm to identify the SGs parameters.
15
A novel comprehensive optimal PMU placement considering practical issues in design and implementation of a wide-area measurement system
Moossa Khodadadi Arpanahi,Roozbeh Torkzadeh,Arash Safavizadeh,Ali Ashrafzadeh,Fariborz Eghtedarnia +4 more
TL;DR: In this article , a line-wise observability concept is proposed for a range of WAMS-based applications such as restoration management, model validation of power system components, and dynamic line rating (DLR) monitoring.
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Two Novel Approaches for Identification of Synchronous Machine Parameters From Short-Circuit Current Waveform
TL;DR: In this article , two novel approaches for identifying the synchronous generator (SG) parameters are presented using an experimentally obtained armature current during the short-circuit test as input data.
6
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