Electromechanical Transient Modeling and Control Strategy of Decentralized Hybrid HVDC Systems

Wang, Guoteng; Xiao, Huangqing; Liang, Xiao; Zhang, Zheren; Xu, Zheng

doi:10.3390/en12152856

Cited by 5 publications

(3 citation statements)

References 22 publications

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“…First-order derivatives are calculated based on the assumption that all variables are uncorrelated, as is customary. Equation ( 14) repeats the ADM i expression, making explicit the terms that are then derived in (15) to (19) with respect to the applicable input data, namely m lo,i and m dc,i . The derivative sensitivity coefficients for the three FDM i terms are calculated in (20) to (22), and then the overall derivatives with respect to the applicable input data (m lo,i and m hi,i ) are shown in (23) and (24).…”

Section: Law Of Propagation Of Uncertainty and First-order Derivativesmentioning

confidence: 99%

“…Going back to the objective of this section, the calculated sensitivity coefficients (see (15) through (24)) may be used to derive the uncertainty of the output quantity GDM described by (11) and (12). We may assume that the elements of the input data vectors are independent.…”

Section: Law Of Propagation Of Uncertainty and First-order Derivativesmentioning

confidence: 99%

“…Several validation methods have been proposed in various fields of science; for example, those applied to economics, crystallography, and electromagnetics, and they have been reviewed, discussed, and quantitatively assessed and confronted for some test cases [9]. The relatively recent Feature Selective Validation (FSV) method [10] is a complex and complete validation tool with wide applicability to several fields of engineering, with particular emphasis on electronic and electrical engineering: pure EMC applications were presented in 2010 from studying reverberating chambers [11], and near-and far field radiation from heatsinks [12]; a thorough validation of a railway line model against experimental data is discussed in [13], with considerations on the influence of second-order system elements; counterfeiting detection via electromagnetic fingerprint is instead evaluated in [14]; finally, the modeling of a high voltage direct current system is discussed in [15]. Older examples can be found, especially in the field of microelectronics, when models of semiconductor devices began to appear at different levels of complexity [1], and are now widely available resources in many desktop circuit simulators.…”

Section: Introductionmentioning

confidence: 99%

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Uncertainty and Sensitivity of the Feature Selective Validation (FSV) Method

Bongiorno¹,

Mariscotti

2022

Electronics

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The FSV method is a recognized validation tool that initially assesses the similarity between data sets for electromagnetic measurements and models. Its use may be extended to many problems and applications, and in particular, with relation to electrical systems, but it should be characterized in terms of its uncertainty, as for measurement tools. To this aim, the Guide to the Expression of Uncertainty in Measurement (GUM) is applied for the propagation of uncertainty from the experimental data to the Feature Selective Validation (FSV) quantities, using Monte Carlo analysis as confirmation, which ultimately remains the most reliable approach to determine the propagation of uncertainty, given the significant FSV non-linearity. Such non-linearity in fact compromises the accuracy of the Taylor approximation supporting the use of first-order derivatives (and derivative terms in general). MCM results are instead more stable and show sensitivity vs. input data uncertainty in the order of 10 to 100, highly depending on the local data samples value. To this aim, normalized sensitivity coefficients are also reported, in an attempt to attenuate the scale effects, redistributing the observed sensitivity values that, however, remain in the said range, up to about 100.

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Section: Law Of Propagation Of Uncertainty and First-order Derivativesmentioning

confidence: 99%

Section: Law Of Propagation Of Uncertainty and First-order Derivativesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Uncertainty and Sensitivity of the Feature Selective Validation (FSV) Method

Bongiorno¹,

Mariscotti

2022

Electronics

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High Frequency Model of Power Transformer Bushing for Very Fast Transient Studies

Messadi,

Zouaghi,

Ferdjallah-Kherkhachi

et al. 2023

IEEE Access

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Fast and very fast transient overvoltages generally appear during switching operations within electrical substations. The oscillatory nature of such phenomena with frequencies that can reach several tens of megahertz tends to degrade the lifetime of high voltage equipment such as bushings and transformers, inducing partial discharges activity or breakdown of the insulation system. According to several case studies, bushings are one of the most sensitive parts to such overvoltages, indeed, a failure in a bushing will in most cases lead to a failure of the transformer, often catastrophically. Generating such overvoltages with a very high frequency character and considerable amplitude can be very difficult, moreover, studying the effect of such overvoltages on the insulated bushings is not easy, even experimentally. Therefore, a simulation of the fast transients in the system can be very useful to understand the consequences of such phenomena. In this context, this document aims to propose a model of high voltage capacitive graded oil impregnated paper (OIP) bushing based on a distributed electrical circuit. The equivalent circuit is constructed based on the geometric design and electrical properties of the materials. The model was developed and implemented using Matlab/Simulink® software, and was validated with experimental measurements based on impedance sweep frequency analysis. The modeling results are in a good agreement with the experimental ones. INDEX TERMSBushing, distributed circuit model, high voltage, high frequency, impedance analysis, numerical modeling, overvoltage, power transformer, very fast transient.

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