A finite-element analysis approach to determine the parasitic capacitances of high-frequency multiwinding transformers for photovoltaic inverters

Shadmand, Mohammad B.; Balog, Robert S.

doi:10.1109/peci.2013.6506044

Cited by 22 publications

(5 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The iron cores are removed to measure the parasitic capacitances of the secondary windings directly. And their parasitic capacitances can be measured by using the frequency resonance point method proposed in [4], [14], [27], [34], [35]. As shown in Fig.…”

Section: Fem Results Analytical Results and Experimental Resultsmentioning

confidence: 99%

Investigation on the Parasitic Capacitance of High Frequency and High Voltage Transformers of Multi-Section Windings

Deng

Wang

et al. 2020

IEEE Access

View full text Add to dashboard Cite

Resonant converters are widely used in high voltage applications thanks to the soft switching technologies. The high frequency and high voltage (HFHV) transformer is the most complicated and important part to boost the voltage by tens or hundreds of times, and the parasitic capacitance of the transformers is critical to the performances of resonant converters. To reduce the parasitic capacitance, the multi-section winding technique is usually employed in HFHV transformers. However, the parasitic capacitance values calculated by the classical methods are not consistent with the experimental results of HFHV transformers, and they are usually designed and optimized with low efficiency. This paper proposes a new analytic method for calculating the parasitic capacitance of HFHV transformers of multi-section windings, which is verified with good accuracy by experimental results.

show abstract

Section: Fem Results Analytical Results and Experimental Resultsmentioning

confidence: 99%

Investigation on the Parasitic Capacitance of High Frequency and High Voltage Transformers of Multi-Section Windings

Deng

Wang

et al. 2020

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Step1: Data acquisition. The transformer vibration signals of different fault types, locations, and severities are obtained through experiments and COMSOL finite element simulation software [38][39][40][41][42][43].…”

Section: Proposed Methodsmentioning

confidence: 99%

“…The simulation model is established using COMSOL finite element software [38][39][40][41][42][43], which performs a multifield coupling calculation of the external circuit, magnetic field, and structural force field.…”

Section: Simulation Model Establishmentmentioning

confidence: 99%

Adaptive Transfer Learning Based on a Two-Stream Densely Connected Residual Shrinkage Network for Transformer Fault Diagnosis over Vibration Signals

Liu

Wang

2021

Electronics

View full text Add to dashboard Cite

Vibration signal analysis is an efficient online transformer fault diagnosis method for improving the stability and safety of power systems. Operation in harsh interference environments and the lack of fault samples are the most challenging aspects of transformer fault diagnosis. High-precision performance is difficult to achieve when using conventional fault diagnosis methods. Thus, this study proposes a transformer fault diagnosis method based on the adaptive transfer learning of a two-stream densely connected residual shrinkage network over vibration signals. First, novel time-frequency analysis methods (i.e., Synchrosqueezed Wavelet Transform and Synchrosqueezed Generalized S-transform) are proposed to convert vibration signals into different images, effectively expanding the samples and extracting effective features of signals. Second, a Two-stream Densely Connected Residual Shrinkage (TSDen2NetRS) network is presented to achieve a high accuracy fault diagnosis under different working conditions. Furthermore, the Residual Shrinkage layer (RS layer) is applied as a nonlinear transformation layer to the deep learning framework to remove unimportant features and enhance anti-interference performance. Lastly, an adaptive transfer learning algorithm that can automatically select the source data set by using the domain measurement method is proposed. This algorithm accelerates the training of the deep learning network and improves accuracy when the number of samples is small. Vibration experiments of transformers are conducted under different operating conditions, and their results show the effectiveness and robustness of the proposed method.

show abstract

“…Therefore, they draw constant power from the grid and exhibit negative incremental impedance property which causes stability issues for the entire system. This has resulted to the formation of a new research area in academia concerning the stability analysis and controller design methods for dc distribution power systems [13][14][15][16][17]. In contrary to conventional control design methods that only consider the stability of individual converters in the dc power system, the new research efforts are focused on the analysis of the converters in the system considering the interactions between them and the network.…”

Section: Introductionmentioning

confidence: 99%

Improving performance of a DC-DC cascaded converter system using an extra feedback loop

Ahmadi

Ferdowsi

2013

2013 IEEE Energy Conversion Congress and Exposition

View full text Add to dashboard Cite

This paper introduces the extra feedback method as a technique to improve the performance of a cascaded converter system and stabilize its operation. In this paper, first, the block diagram representation of the small-signal model of a single converter is presented. The open-loop and closed-loop transfer functions of this converter are provided in this stage as well. Next, the presented model is expanded to the block diagram model of a cascaded converter system comprised of two dc-dc converters. Then, the extra feedback method which is the main contribution of the paper is introduced. Some design guidelines for applying this method to an experimental cascaded converter system are provided in this part as well. Finally, some experimental results are provided to verify the theoretical outcomes.

show abstract

A finite-element analysis approach to determine the parasitic capacitances of high-frequency multiwinding transformers for photovoltaic inverters

Cited by 22 publications

References 24 publications

Investigation on the Parasitic Capacitance of High Frequency and High Voltage Transformers of Multi-Section Windings

Investigation on the Parasitic Capacitance of High Frequency and High Voltage Transformers of Multi-Section Windings

Adaptive Transfer Learning Based on a Two-Stream Densely Connected Residual Shrinkage Network for Transformer Fault Diagnosis over Vibration Signals

Improving performance of a DC-DC cascaded converter system using an extra feedback loop

Contact Info

Product

Resources

About