Parameter estimation of synchronous machines considering field voltage variation during the sudden short-circuit test

Faria, Victor A. D.; Bernardes, José V.; Bortoni, Edson C.

doi:10.1016/j.ijepes.2019.105421

Cited by 17 publications

(6 citation statements)

References 11 publications

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“…An ordinary least squares method was utilized in this The field winding resistance was also calculated using (10) and Figure 2. r f = 0.0014∕0.5532 = 0.0025 pu (18) After obtaining 𝜃 and r f in ( 17) and ( 18), the proposed procedure in ( 8)-( 16) and Table 1 was carried out to derive the rest of the SG parameters. The identified parameters of the case study SG are represented in Table 2.…”

Section: Pe Results Using the Proposed Test Datamentioning

confidence: 99%

“…The sudden short circuit (SSC) is another type of offline test which is performed by applying a solid three‐phase short‐circuit on SG terminals while the machine is disconnected from the grid [18]. The SG identification considering field voltage variation during the SSC test has been presented in [18]. Moreover, the authors in [17] have proposed two methods to identify SG parameters for the SSC test in off‐nominal terminal voltage.…”

Section: Introductionmentioning

confidence: 99%

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Parameter identification of small distributed hydro generators during excitation system start‐up

Arastou

Rabieyan

Karrari

et al. 2022

IET Generation Trans & Dist

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Concerning the penetration of renewable energy resources into the power grid, investigation of the power system dynamics to meet the power demand and maintain stability has gathered momentum recently. On the other hand, evaluating the generator parameters in the distributed generation (DG) units as a subsystem of a large-scale power grid is crucial for control and stability analysis purposes. To this aim, a simple and efficacious algorithm to identify the operational parameters of synchronous generators (SGs) in small hydro DGs is proposed here. The required data for the SG identification using the recommended approach is gathered during excitation system start-up while the DG is disconnected from the grid. Using the proposed test procedure, the adverse impact of magnetic saturation on estimation results can be avoided. Furthermore, a straightforward parameter estimation (PE) procedure is established here to obtain the intended parameters from the recorded data. Finally, the proposed method was applied to a 10 MW hydro DG, and the results are discussed.

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Section: Pe Results Using the Proposed Test Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Parameter identification of small distributed hydro generators during excitation system start‐up

Arastou

Rabieyan

Karrari

et al. 2022

IET Generation Trans & Dist

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“…The research presented in [5] expands the load rejection test to consider the effect of saturation. Furthermore, the short-circuit test has been presented in [6], considering field voltage variations. The authors in [7] and [8] identified the SG's parameters using simplified analytical waveforms of the field and armature shortcircuit current, respectively.…”

Section: Related Workmentioning

confidence: 99%

Artificial Neural Network-Based Nonlinear Black-Box Modeling of Synchronous Generators

Micev

Ćalasan

Radulović

et al. 2023

IEEE Trans. Ind. Inf.

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This paper deals with black-box modeling of synchronous generators based on artificial neural networks (ANN). ANN is applied to define the relationship between the excitation and terminal generator voltage values, while the Levenberg-Marquardt algorithm is used for determining the ANN's weight coefficients. The relation is made based on generator response on reference voltage step changes. The proposed approach is checked using the experimental results obtained from the measurements on a real 120 MVA generator from hydroelectric power plant Piva in Montenegro. Further, a fair comparison with the nonlinear auto-regression model with the exogenous input (NARX) and Hammerstein-Wiener (H-W) model is made. For the validation, different experiments were conducteddifferent values of step disturbances, other controller parameters, and different rotating speeds. Based on the presented results, it can be noted that the proposed ANN model is very accurate and provides a very high degree of matching with the experimental results and outperforms the other considered nonlinear models. Furthermore, the proposed test procedure and model is easy to implement and do not require disconnection of the generator from the grid or additional equipment for experimental realization. Such obtained models can be used for different testing types related to the excitation system.

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“…This has been done using load rejection tests for SG parameters, as thoroughly discussed in References 33 and 34. Micev et al 35 and Farla et al 36 recommend different methods for identifying SG parameters from the short‐circuit test; nonetheless, these methods are, in general, costly and time‐consuming. Moreover, these approaches fail to derive the full set of parameters of SG.…”

Section: Introductionmentioning

confidence: 99%

A new method to identify synchronous generator and turbine‐governor parameters of a gas unit using a closed‐loop model

Zaker

Khalili

Rabieyan

et al. 2021

Int Trans Electr Energ Syst

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Summary In this paper, an efficient three‐stage algorithm for identifying the turbine‐governor (TG) and synchronous generator (SG) parameters is proposed. Instead of considering approximate models, precise models of the TG and SG are used. In the proposed approach, d‐q axes parameters of SG, mechanical parameters of SG, and TG model parameters are estimated. For the TG model, all the main control loops are carefully modeled with respect to the real‐world system. Moreover, the robustness of the governor is enhanced by employing an anti‐windup configuration for the load‐speed controller. The well‐known seventh‐order SG model is also used. The accuracy of the model and effectiveness of the parameter identification procedure is verified by experimental data. The results show satisfactory numbers for the selected performance index in various operating points when different controllers are in effect.

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Parameter estimation of synchronous machines considering field voltage variation during the sudden short-circuit test

Cited by 17 publications

References 11 publications

Parameter identification of small distributed hydro generators during excitation system start‐up

Parameter identification of small distributed hydro generators during excitation system start‐up

Artificial Neural Network-Based Nonlinear Black-Box Modeling of Synchronous Generators

A new method to identify synchronous generator and turbine‐governor parameters of a gas unit using a closed‐loop model

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