A state space three-phase multilimb transformer model in the time domain: fast periodic steady state analysis

García, Salvador; Medína, A.

doi:10.1109/pess.2001.970364

Cited by 8 publications

(14 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In a more recent contribution, Newton methods in the time domain have been proposed for the fast time domain computation of the periodic steady state of systems containing nonlinear and time-varying components [15]. They have been applied successfully for the transient and periodic steady state analysis of the power transformer [16] and systems containing time-varying components such as arc furnaces, TCR's [17] and TSC's [18].…”

Section: Fast Periodic Steady State Solutionmentioning

confidence: 99%

Synchronous machine stability analysis using an efficient time domain methodology: unbalanced operation analysis

Rodriguez

Medína²

IEEE Power Engineering Society Summer Meeting,

Self Cite

View full text Add to dashboard Cite

This paper describes a methodology for the efficient stability analysis of the synchronous machine. The state space phase coordinates model of the synchronous machine incorporates the effects of time-varying and inter-spatial harmonic inductances. The dynamics of the synchronous machine are represented by a set of Ordinary Differential Equations (ODEs). The machine behaviour is analyzed under severe unbalanced operation conditions. The level of detail and accuracy obtained with the machine model in phase coordinates can not be achieved with conventional models based on the dq0 framework for unbalanced fault analysis. A Newton technique based on a Numerical Differentiation process is used for the acceleration of the convergence of the state variables to the Limit Cycle to obtain the machine initial conditions and the steady state previous to the fault application and after the fault is removed. The combined response obtained with methodology for swift time domain transient and periodic steady state analysis and the phase domain synchronous machine model is compared in terms of accuracy and computational efficiency against a widely used and accepted machine model of an Electro-Magnetic Transient Program (EMTP-ATP).

show abstract

Section: Fast Periodic Steady State Solutionmentioning

confidence: 99%

Synchronous machine stability analysis using an efficient time domain methodology: unbalanced operation analysis

Rodriguez

Medína²

IEEE Power Engineering Society Summer Meeting,

Self Cite

View full text Add to dashboard Cite

show abstract

“…9 time-domain simulation [17][18][19][20][21][22][23][24][25], 9 frequency-domain simulation [26][27][28][29], 9 combined frequency-and time-domain simulation [30,31], and 9 numerical (e.g., finite-difference, finite-element) simulation [1, 2, 6, 32-34].…”

Section: Of Transformersmentioning

confidence: 99%

“…2.16b,c. The incremental approach uses a polynomial [31,30], arctangent [22,23], or other functions to model the transformer magnetizing characteristic. The incremental reluctances (or inductances) are then obtained from the slopes of the inductance-magnetizing current characteristic.…”

Section: Frequency-and Time-domain Transformer Core Modeling By Saturmentioning

confidence: 99%

“…Due to the fact that the effect of hysteresis in transformers is much smaller than that of the eddy current, and to simplify the computation, most models assume a constant value for the magnetizing conductance [22,23,30]. As mentioned before, the saturation curve may be modeled using a polynomial [30,29], arctangent [22,23], or other functions.…”

Section: Time-domain Transformer Coil Modeling By Saturation Curve Anmentioning

confidence: 99%

“…As mentioned before, the saturation curve may be modeled using a polynomial [30,29], arctangent [22,23], or other functions. The slightly simplified transformer model is shown in Fig.…”

Section: Time-domain Transformer Coil Modeling By Saturation Curve Anmentioning

confidence: 99%

See 2 more Smart Citations

Harmonic Models of Transformers

2008

Power Quality in Power Systems and Electrical Machines

View full text Add to dashboard Cite

Extensive application of power electronics and other nonlinear components and loads creates single-time (e.g., spikes) and periodic (e.g., harmonics) events that could lead to serious problems within power system networks and its components (e.g., transformers). Some possible impacts of poor power quality on power transformers are 9 saturating transformer core by changing its operating point on the nonlinear ~-i curve, 9 increasing core (hysteresis and eddy current) losses and possible transformer failure due to unexpected high losses associated with hot spots, 9 increasing (fundamental and harmonic) copper losses, 9 creating half-cycle saturation in the event of even harmonics and DC current, 9 malfunctioning of transformer protective relays, 9 aging and reduction of lifetime, 9 reduction of efficiency, 9 derating of transformers, 9 decrease of the power factor, 9 generation of parallel (harmonic) resonances and ferroresonance conditions, and 9 deterioration of transformers' insulation near the terminals due to high voltage stress caused by lightning and pulse-width-modulated (PWM) converters.Pfe = Phys + Peddy = ghys (Bmax)Sf + geddy(Bmax)2f 2, (2-1) where Phys, Peddy, Bmax, and f are hysteresis losses, eddy-current losses, maximum value of flux density, and fundamental frequency, respectively. Khys is a constant for the grade of iron employed and Keddy is the eddy-current constant for the conductive material. S is the Steinmetz exponent ranging from 1.5 to 2.5 depending on the operating point of transformer core.9 Elsevier Inc. All rights reserved. I ~,H I i r 9 FIGURE 2.4 Magnetic field strength inside and outside of a conductor. / / I i \ % o 9 "% ~Ho3 / %% u / / %

show abstract

An EKF‐SVM machine learning‐based approach for fault detection and classification in three‐phase power transformers

Kazemi

Naseri

Yazdi

et al. 2021

IET Science Measure & Tech

View full text Add to dashboard Cite

In this paper, a hybrid approach for effective diagnosis of power transformers is proposed. In the proposed method, the extended Kalman filter is used for the estimation of three‐phase currents in the primary windings of the transformer. Three residual signals are defined as the differences between the measured and estimated three‐phase currents. When the transformer is healthy, the EKF perfectly estimates the primary currents and hence, the residual signals are nearly zero. However, when the transformer is faulty, the EKF cannot suitably estimate the currents due to the large model mismatch resulting from the transformer internal faults. Consequently, large residual signals are generated, which are used as the key signatures for discriminating the internal faults from energisation conditions. Besides, the proposed method uses the entries of the covariance matrix of the estimation error to locate and classify the internal faults. For these purposes, support vector machine classifiers are used. The effectiveness of the proposed method is demonstrated by a large number of simulation test cases obtained using PSCAD/EMTDC software. Also, hardware‐in‐the‐loop experiments are conducted using dSPACE1104 development platform and real‐time feasibility of the proposed method is authenticated.

show abstract

A state space three-phase multilimb transformer model in the time domain: fast periodic steady state analysis

Cited by 8 publications

References 19 publications

Synchronous machine stability analysis using an efficient time domain methodology: unbalanced operation analysis

Synchronous machine stability analysis using an efficient time domain methodology: unbalanced operation analysis

Harmonic Models of Transformers

An EKF‐SVM machine learning‐based approach for fault detection and classification in three‐phase power transformers

Contact Info

Product

Resources

About