Characterization of Magnetic Losses in the Transformer Tank Steel

Azzabi, Lotfi; Høidalen, Hans Kristian; Agheb, E.; Nysveen, Arne

doi:10.1109/tmag.2015.2512929

Cited by 8 publications

(5 citation statements)

References 11 publications

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“…These losses are proportional to the enclosed area within the static hysteresis loop (depicted by the red line in Figure 3), with evolution contingent on past or historical values. In contrast, eddy losses are considered dynamic as their value per cycle exhibits frequency dependence [48,49]. Static hysteresis is responsible for the residual flux.…”

Section: Inrush Current and Residual Fluxmentioning

confidence: 99%

Field Programmable Gate Array-Based Smart Switch to Avoid Inrush Current in PV Installations

Martínez-Figueroa,

Córcoles,

Bogarra

2024

Sensors

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This paper introduces an FPGA-based implementation of a smart switch designed to avoid inrush currents occurring during the connection of single-phase transformers utilized in grid-connected photovoltaic (PV) systems. The magnitude of inrush currents is notably impacted by the residual flux within the transformer core and the precise moment of energization relative to the wave cycle. Alternative methods frequently hinge on intricate procedures to estimate residual flux. This challenge is adeptly circumvented by the innovative smart control system proposed herein, rendering it a cost-effective solution for grid-connected PV systems. The proposed solution for mitigating inrush current remains effective, even in the face of challenges with current and voltage sensors. This resilience arises from the system’s ability to learn and adapt by leveraging information acquired from the network.

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Section: Inrush Current and Residual Fluxmentioning

confidence: 99%

Field Programmable Gate Array-Based Smart Switch to Avoid Inrush Current in PV Installations

Martínez-Figueroa,

Córcoles,

Bogarra

2024

Sensors

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“…On the other hand, by depending on the amplitude of the leakage magnetic field, the so developed eddy losses can become quite significant, which implies in loss of efficiency as well as in the occurrence of hot spots. Thus, although such these issues have been addressed and published for the steady-state operation of power transformers [1][2][3][4], the evaluation of the losses within these structural parts has not been equally diffused for the transient state, as in the case of inrush currents or GICs events. Moreover, the influence of power harmonics on these losses, as in the case of a transformer supplying a variable frequency driver (VFD) that is becoming more and more frequent has become a very significant issue for transformer designers to consider.…”

Section: Introductionmentioning

confidence: 99%

Alternative model for computing transformer tank induced losses in the time domain

Oliveira¹,

Sadowski²,

Cabral³

2020

IET Electric Power Applications

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In the performance evaluation of power transformers, the occurrence of eddy currents and their effects on the transformer tank have been widely modelled and studied for the cases of power frequency in the steady state. Nonetheless, for the cases when harmonic components are present (zero‐sequence flux) or for transient conditions (inrush or geomagnetically induced current (GIC) events) there is much to do. With this aim, this work presents the proposal in using temporal modelling for evaluating eddy currents in transformer tank walls in practical cases of sinusoidal, harmonic and transient excitations. Obtained results are compared with consolidated commercially available software based on finite elements for showing how good this proposition is.

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“…The research on the eddy current loss and temperature rise in transformer structural parts is significant in the design of transformer [1][2][3]. Owing to the compact structure of large capacity power transformer, the eddy current loss in mental structure caused by the leakage magnetic field might lead to the appearance of local overheating in structural parts, if the design is not proper [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%