A d-q model for the self-commutated synchronous machine considering the effects of magnetic saturation

Iglesias, I.J.; García-Tabarés, L.; Tamarit, J.

doi:10.1109/60.182661

Cited by 49 publications

(16 citation statements)

References 5 publications

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“…The set of space vectors (underlined variables) that may be selected as state-space variables is given with (5) where and denote current and flux linkage, respectively, while indices , and stand for stator, excitation and damper winding, respectively. Three space vectors are needed for any particular model.…”

Section: B Classification Of the Modelsmentioning

confidence: 99%

“…The magnetizing curve for the q-axis is usually not available and one then assumes that the degree of q-axis and d-axis saturation is the same. This approach leads to single saturation factor representation of saturation [3], [5], [10], [14], that requires conversion of an anisotropic synchronous machine into its isotropic equivalent [5], [7], [14]. Single saturation factor Manuscript method was adopted in [12], [13] for derivation of alternative models of the anisotropic synchronous machines and conversion of the anisotropic to isotropic machine was performed as defined in [14].…”

Section: Impact Of Dynamic Cross-saturation On Accuracy Of Saturated mentioning

confidence: 99%

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Impact of dynamic cross-saturation on accuracy of saturated synchronous machine models

Levi

Leví

2000

IEEE Trans. On energy Conversion

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Cross-saturation effect in synchronous machines has been a subject of considerable attention in recent years. Inclusion of the cross-saturation in the machine model has two consequences. The first one, called here 'steady-state cross-saturation', consists of dependence of the steady-state d-q axis magnetizing inductances on the currents in both axes. The second one, termed here 'dynamic cross-saturation', is the existence of nonzero elements in the system matrix, that describe cross coupling between d-and q-axis. Dynamic cross-saturation appears in all the saturated machine models, regardless of the selected set of state-space variables, with the exception of the winding flux linkage state-space model. The aim of this paper is to compare behavior of various models when dynamic cross-saturation is neglected. It is shown that the impact of dynamic cross-saturation on accuracy depends on the selected set of state-space variables. In majority of cases omission of dynamic cross-saturation leads to very inaccurate results. However, it is found that for one particular class of models omission of dynamic cross-saturation has practically no impact on accuracy. These models therefore fully describe the complete saturation effect by means of only continuous variation of the d-q axis magnetizing inductances.

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Section: B Classification Of the Modelsmentioning

confidence: 99%

Section: Impact Of Dynamic Cross-saturation On Accuracy Of Saturated mentioning

confidence: 99%

Impact of dynamic cross-saturation on accuracy of saturated synchronous machine models

Levi

Leví

2000

IEEE Trans. On energy Conversion

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“…The saturation and cross-coupling effects, due to saturation, can be accounted for by variable inductances [1,2] or by energy functions [3], while the LSRM dynamic models can be extended by accounting for the magnetic anisotropy [4,5] and even slotting effects [6].…”

Section: Introductionmentioning

confidence: 99%

Dynamic two-axis model of a linear synchronous reluctance motor based on current and position-dependent characteristics of flux linkages

Štumberger

Dolinar

2006

Journal of Magnetism and Magnetic Materials

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“…The detailed description and model equation derivation of EESGs can be found in most power system and electrical machine references [18]- [19]. Only the most important aspects of the modeling will be presented here.…”

Section: A Eesg Modelmentioning

confidence: 99%

Stator winding fault diagnosis in synchronous generators for wind turbine applications

Ibrahim¹,

Watson²

2016

5th IET International Conference on Renewable Power Generation (RPG) 2016

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Abstract-Wind turbine manufacturers have introduced to the market a variety of innovative concepts and configurations for generators to maximize energy capture, reduce costs and improve reliability of wind energy. For the purpose of improving reliability and availability, a number of diagnostic methods have been developed. Stator current signature analysis (SCSA) is potentially an effective technique to diagnose faults in electrical machines, and could be used to detect and diagnose faults in wind turbines. In this study, an investigation was conducted into the application of SCSA to detect stator inter-turn faults in an excited synchronous generator and a permanent magnet synchronous generator. It was found from simulation results that, owing to disruption of magnetic field symmetry and imbalance between the current flowing in the shorted turn and the corresponding diametrically opposite turn in the winding, certain harmonic components in the stator current clearly increased as the number of shorted turns increased. The findings are helpful to detect faults involving only a few turns without ambiguity, in spite of the difference in the configuration of the generators. As expected, because of the different type, configuration and operational condition of the two generators studied, detecting faults through the generator current signature requires a particular approach for each generator type.

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A d-q model for the self-commutated synchronous machine considering the effects of magnetic saturation

Cited by 49 publications

References 5 publications

Impact of dynamic cross-saturation on accuracy of saturated synchronous machine models

Impact of dynamic cross-saturation on accuracy of saturated synchronous machine models

Dynamic two-axis model of a linear synchronous reluctance motor based on current and position-dependent characteristics of flux linkages

Stator winding fault diagnosis in synchronous generators for wind turbine applications

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