Insulator Model Research Articles

The Estimation of the Critical Flashover Voltage of Insulators Using the Computational Intelligence

Background: Electric insulation is generally a vital factor in both the technical and economic feasibility of complex power and electronic systems. Several researches focus on the behavior of insulators under polluted conditions. That they are mathematical and physical models of insulators, experiments and simulation programs. Also experiments on critical flashover voltage are timeconsuming and have more limitations such as high cost and need for especial equipment’s. Objective: This paper focused on optimized predicting of critical flashover voltage of Polluted insulators based on artificial intelligence. Methods: Fuzzy logic and artificial neural networks are used in order to have the best estimation of the critical flashover. Results: In this way the correlation index (regression coefficient) improved about 2% toward previous works with same experimental data sets. Additionally, with using the properties of nonlinear artificial neural networks we can have the perfect (R=100%) prediction of the critical flashover voltage on experimental dataset. Conclusion: In this paper two methods for the estimation of critical flashover voltage of polluted insulators using fuzzy logic and neural networks was presented. the regression coefficient R achieved by the optimal parameters is 98.4% while in previous work is 96.7%. In neural network model we have regression coefficient 100% and in previous neural network model it was 99%. our test set is the same as previous works and achieved from experiments. These results show that fuzzy proposed methods are powerful and useful tools lead to a more accurate, generalized and objective estimation of the critical flashover voltage.

Ageing and reliability of electrical insulation: the risk of hybrid AC/DC grids

With an impetuous growth of DC links and future grids that will be often hybrid, providing AC and DC supply to nearby or the same customer, an important element is often neglected, that is, electrical insulation. There are no doubts that overhead lines will step back compared to insulated cables, for known reasons of environmental impact, right of way and reliability, especially in an urban or harsh environment. On the other hand, while AC insulation systems have been investigated and used for decades, there is no analogue experience for DC polymeric insulation, nor for insulation systems subjected to power electronics supply. This study aims at enhancing the attention on this topic, focusing on insulation ageing mechanisms and models of relevance for hybrid AC/DC assets and grids. Ageing and life models for AC, DC and power electronics supply are discussed and compared to experimental data, focusing on partial discharge and space charge. It is shown how these two phenomena affect lifetime for different AC, DC and transient operating conditions. The main drivers for insulation design and material selection are discussed, showing that insulation reliability can be achieved only if operating stresses, ageing mechanisms and life models are known and accounted for properly by insulation designers.

The sound insulation and directivity of the sound radiation from double glazed windows.

The sound insulation and directivity of the radiated sound from double glazed windows have been measured by different researchers. Previously, airborne sound insulation models have been used to predict the associated measurement results with limited success. In this paper, the importance of accounting for the structure borne sound transmission between two glazing elements via the window frame on the prediction results is demonstrated. The decreased stiffness of the wall cavity as the depth is increased is the reason why sound transmission via the window frame needs to be considered. The reciprocity argument provided by Davy for the prediction of the directivity of sound radiating into a room is validated and it is shown that once the structure borne transmission is considered, an additional weighting term is not needed to compensate for the extra wall collisions which the sound experiences when radiated at grazing incidence.

Modelling of insulation in DC systems: the challenges for HVDC cables and accessories

Modelling of insulation in DC systems: the challenges for HVDC cables and accessories

Spin Hall conductivity in insulators with nonconserved spin

We study the linear response of a spin current to a small electric field in a two-dimensional crystalline insulator with non-conserved spin. We adopt the spin current operator proposed in [J. Shi et al., Phys. Rev. Lett. 96, 076604 (2006)], which satisfies a continuity equation and fits the Onsager relations. We use the time-independent perturbation theory to present a formula for the spin Hall conductivity, which consists of a "Chern-like" term, reminiscent of the Kubo formula obtained for the quantum Hall systems, and a correction term that accounts for the non-conservation of spin. We illustrate our findings on the Bernevig-Hughes-Zhang model and the Kane-Mele model for time-reversal symmetric topological insulators and show that the correction term scales quadratically with the amplitude of the spin-conservation-breaking terms. In both models, the spin Hall conductivity deviates from the quantized value when spin is not conserved.

ANN based temperature compensation for variations in polarization and depolarization current measurements in transformer

Nowadays, more than a quarter of the faults that occur in oil-filled transformers are due to the aging and deterioration of their oil-paper insulation. Therefore, condition assessment of the oil-paper insulation of oil-filled transformers, which are installed in the power grids, is very important. One of the non-destructive methods, which are currently used to distinguish the insulation condition, is polarization and depolarization current (PDC) technique. Factors such as oil conductivity, paper conductivity, moisture content, temperature and insulation aging alter PDC test results. This paper proposes a method based on artificial neural network (ANN) integrated genetic algorithm to modify the effect of temperature variation in the results of PDC tests. For this purpose, PDC tests are performed on two different transformers at temperatures of 22 °C, 30 °C, 40 °C, 50 °C, 60 °C and 70 °C with the help of Megger-IDAX 300 device, which is capable of performing PDC tests up to 70 °C. To achieve the desired temperatures, the transformers are placed in the thermal furnace and with special thermal cables; the terminals of the devices are connected to the transformers inside the furnace. According to the results of depolarization current, which are measured at different temperatures, the parameters of the insulation model have been estimated by using genetic algorithm (GA). The insulation model parameters corresponding to 22 °C temperature in each transformer are selected as target parameters. Insulation model parameters related to higher temperatures are applied as inputs to the artificial neural network (ANN). This is done in order to train the ANN. The purpose of artificial neural network training is to transmit parameters related to higher temperatures on target parameters. Finally, with the help of the transferred model parameters, the polarization and depolarization current curves are drawn and transferred on the target curves (curves of 22 °C). The transfer error is calculated by the mean square error (MSE) index. Comparison of the proposed model results with the traditional method, which is based on the Arrhenius equation, in correcting the effect of temperature on the PDC test results, confirms the prediction accuracy of the proposed method.

Metal-insulator phase transition and topology in a three-component system* *Project supported by the National Natural Science Foundation of China (Grant Nos. 11835011 and 11774316).

Due to the topology, insulators become non-trivial, particularly those with large Chern numbers which support multiple edge channels, catching our attention. In the framework of the tight binding approximation, we study a non-interacting Chern insulator model on the three-component dice lattice with real nearest-neighbor and complex next-nearest-neighbor hopping subjected to Λ- or V-type sublattice potentials. By analyzing the dispersions of corresponding energy bands, we find that the system undergoes a metal–insulator transition which can be modulated not only by the Fermi energy but also the tunable extra parameters. Furthermore, rich topological phases, including the ones with high Hall plateau, are uncovered by calculating the associated band’s Chern number. Besides, we also analyze the edge-state spectra and discuss the correspondence between Chern numbers and the edge states by the principle of bulk-edge correspondence. In general, our results suggest that there are large Chern number phases with C = ± 3 and the work enriches the research about large Chern numbers in multiband systems.

Novel colour image encoding system combined with ANN for discharges pattern recognition on polluted insulator model

This study introduces a novel methodology for electrical discharges recognition elaborating an algorithm based on the RGB colour image model and artificial neural network (ANN) classifier. The developed RGB-ANN algorithm aims to detect and monitor the propagation of electrical discharges until flashover, through analysis of six colours appearing in the discharges images, extracted from the flashover videos recorded on a plan glass insulator model under uniform pollution. First, more than 300 colours images are collected and divided into sets to form a large database. Using an RGB encoding system, each pixel is represented by (R, G, B) coordinates and each image is encoded by 3D matrix. For the discharge image, the coordinates of each pixel are compared to all database ones. The colour of the database having the same coordinates of the discharge image pixel is attributed to this latter. Based on the ratio of the pixels number of a given colour to the total pixels number of the discharge image, six indicators are quantified and grouped to form a feature vector. This latter is used as input of the ANN, in order to classify the evolution of discharges into five classes. As the main result, >98% of images have been well classified.

Cutting off the non-Hermitian boundary from an anomalous Floquet topological insulator

In two-dimensional anomalous Floquet insulators, non-Hermitian boundary state engineering can be used to completely separate chiral boundary states from bulk bands in the quasienergy spectrum. The topological properties of such spectrally separated boundary states are no longer restricted by the strict bulk-boundary correspondence of Hermitian systems. We show that this additional topological freedom enables one to faithfully transfer the topological properties of a boundary attached to a Floquet insulator to a non-Hermitian Floquet chain obtained by physically cutting off the boundary from the bulk. We implement this scenario for a simple model of an anomalous Floquet insulator with Hermitian and non-Hermitian boundaries, and discuss the relevance of our construction for the experimental realization of non-Hermitian topological phases that connect dimensions one and two.

A tomography-based effective thermal conductivity model for ceramic fiber insulation

Ceramic fiber insulation is widely used in thermal systems due to its high temperature limits and light weight. In high temperature applications, radiation is the main mechanism of heat transfer in these materials due to high porosity (greater than 95 %), and orientation of the fibers in the construction of the insulation. A combined radiation and conduction computational model has been developed to calculate thermal conductivity in ceramic fiber materials using the Rosseland diffusion approximation to evaluate thermal radiation transfer, and a tortuosity-weighted effective thermal conductivity to evaluate gas and solid phase conduction. Tomographic reconstructions of sample insulation material were analyzed to determine fiber size and orientation distributions as well as tortuosity and volume fraction of the solid and void fraction. The model is validated by manufacturer data. Together, the conduction and radiation model accurately predicted effective thermal conductivity of ceramic fiber materials in the temperature range of 300–1673 K. The tortuosity-weighted conduction approach allows the model to capture the directional dependence of thermal conductivity in the highly an-isotropic fibrous structure. Critical parameters of fibrous ceramics to maximize insulating properties are also identified.

Impact of impulse voltage frequency on the partial discharge characteristic of electric vehicles motor insulation

The urgent need for electric vehicles is the leading research to safer operation of electric motors on high frequency impulsive voltages. For low voltage electric vehicles partial discharge (PD) inception voltage tests under impulse voltage waveforms are desired. However, measuring PD using repetitive impulse waveforms is critical in selecting generators with appropriate parameters to increase PD detection sensitivity. Here, we report on PD characteristics for such kind of voltage waveforms, demonstrated with the high frequency and thermal impact on different types of motor insulation models. The increasing frequency of impulsive voltages tends to result in PD activities with low magnitude and short delay times. In this case, some PD pulses are missed because the PD and disturbance pulses produced by power electronic devices will likely overlap. Therefore, these parameters are carefully considered to evaluate the insulation performance of EV motors.

Exciton topology and condensation in a model quantum spin Hall insulator

We study by a consistent mean-field scheme the role on the single- and two-particle properties of a local electron-electron repulsion in the Bernevig, Hughes and Zhang model of a quantum spin Hall insulator. We find that the interaction fosters the intrusion between the topological and non-topological insulators of a new insulating and magnetoelectric phase that breaks spontaneously inversion and time reversal symmetries, but not their product. The approach to this phase from both topological and non-topological sides is signalled by the softening of two exciton branches, i.e., whose binding energy reaches the gap value, that possess, in most cases, finite and opposite Chern numbers, thus allowing this phase being regarded as a condensate of topological excitons. We also discuss how those excitons, and especially their surface counterparts, may influence the physical observables.

Dynamic Pollution Prediction Model of Insulators Based on Atmospheric Environmental Parameters

Pollution-induced flashover is one of the most serious power accidents, and the pollution degree of insulators depends on atmospheric environmental parameters. The pollution models used in the power system research are usually static, but the environmental parameters are dynamic. Therefore, the study on the dynamic pollution prediction model is of great importance. In this paper, the dynamic pollution prediction model of insulators based on atmospheric environmental parameters was built, and insulators’ structure coefficients were proposed based on the model. Firstly, the insulator dynamic pollution model based on meteorological data (PM2.5, PM10, TSP (total suspended particulate), and wind speed) was proposed, and natural pollution tests were also conducted as verification tests. Furthermore, insulator structure coefficients c1, c2 (c1: pollution ratio of U210BP/170 to XP-160; c2: calculated pollution ratio of U210BP/170T to XP-160) were then obtained, and their influence factors were discussed. At last, insulator structure coefficients were calculated, and it can be seen that the calculated error of insulator structure coefficients was acceptable, with the average re (relative errors) at 9.0% (c1) and 13.5% (c2), which verifies the feasibility of the model. Based on the results in this paper, the NSDD (non-soluble deposit density) of insulators with different structures can be obtained using the insulators’ structure coefficient and the reference XP-160 insulator’s NSDD.

Anomalous levitation and annihilation in Floquet topological insulators

Anderson localization in two-dimensional topological insulators takes place via the so-called levitation and pair annihilation process. As disorder is increased, extended bulk states carrying opposite topological invariants move towards each other in energy, reducing the size of the topological gap, eventually meeting and localizing. This results in a topologically trivial Anderson insulator. Here, we introduce the anomalous levitation and pair annihilation, a process unique to periodically-driven, or Floquet systems. Due to the periodicity of the quasienergy spectrum, we find it is possible for the topological gap to increase as a function of disorder strength. Thus, after all bulk states have localized, the system remains topologically nontrivial, forming an anomalous Floquet Anderson insulator (AFAI) phase. We show a concrete example for this process, adding disorder via onsite potential "kicks" to a Chern insulator model. By changing the period between kicks, we can tune which type of (conventional or anomalous) levitation-and-annihilation occurs in the system. We expect our results to be applicable to generic Floquet topological systems and to provide an accessible way to realize AFAIs experimentally, without the need for multi-step driving schemes.

Three‐dimensional electric field simulation and flashover path analysis of ice‐covered suspension insulators

Flashover of ice-covered insulators seriously affects the safe operation of transmission lines. It is necessary to study the electric field distribution for flashover analysis of ice-covered insulators. The electric field of ice-covered insulators was mostly calculated by a two-dimensional (2D) axisymmetric model that cannot be well corresponded to actual icing situations. In this study, a 3D electric field simulation model of ice-covered suspension insulators under moderate icing condition with applied DC voltage was established. Two characteristic parameters, Eav and Emax were proposed to measure electric field distortion degree. Based on the simulation results, the effects of water film conductivity, icicle length, icicle deviation angle, and icicle distribution on Eav and Emax were studied. The results showed that icicles have a significant influence on the electric field distribution of insulators. Eav increases with the increase of icicle length and decreases with the increase of icicle deviation angle. Emax increases with the increase of the icicle length, icicle spacing and adjacent icicle length difference. When the icicle deviation angle is 45°, Emax is the largest. Lastly, the possible flashover paths were analysed based on the simulation results, which would provide a theoretical basis for building a flashover model of ice-covered insulators.

A Phenomenological Model of Mott's Insulator–Metal Phase Transition in 3D and 2D Boron‐Doped Diamond

A phenomenological model of Mott's insulator–metal phase transition in boron‐doped diamond is suggested and developed. It is shown that the transition critical boron atom concentration in 3D samples at room temperature calculated on its base coincides with the experimental data. It allows to use the model for the evaluation of the transition critical sheet boron atom concentration for an experimentally much less investigated case of 2D boron‐doped diamond. This gives a value of 3.3 × 1013 cm−2 at room temperature in agreement with experimental data on so‐called delta layers. The latter are thin boron‐doped layers embedded in intrinsic diamond and can be used for the creation of the conductive channels of high‐speed diamond field‐effect transistors.

Absence of equilibrium edge currents in theoretical models of topological insulators

The low energy sector of 2D and 3D topological insulators (TIs) exhibits propagating edge states, which has speculated the existence of equilibrium edge currents or edge spin currents. We demonstrate that if the low energy sector of TIs is regularized in a straightforward manner into a square or cubic lattice, then the current from the edge states is in fact canceled out exactly by that from the valence bands, rendering no edge current. This result serves as a warning that for any equilibrium property of topological insulators, the contribution from the valence bands should not be overlooked. In these regularized lattice model, there is a finite edge current only if the Dirac point of the edge states is shifted away from the chemical potential, for instance by doping, impurities, edge confining potential, surface band bending, or gate voltage. The edge current in small quantum dots as a function of the gate voltage is quantized, and the edge current can flow out of the gated region up to the decay length of the edge state.

Experimental Studies on the Partial Discharge of Insulation for High Tc Superconducting Cable

Partial discharge (PD) is the main factor that can cause failure of the cold dielectric insulation system of superconducting cables. Nine insulation model cables with different insulating materials and wrapping styles are prepared. PD experiments under liquid nitrogen and room temperature are carried out on these model cables. Assuming that the lifetime of superconducting cable is 35 years, 40 thermal cycles from 77 –323 K are carried out on three model cables. Experimental results show that the PD is 100 times lower in liquid nitrogen than at room temperature for both polypropylene-laminated paper (PPLP) and polyimide (PI). Compared with model cables that used PI, the ones that used PPLP show much higher inception electric field. And no decay in partial discharge inception electric filed (PDIE) is found during the thermal cycles. The study will be helpful to the insulation system design for superconducting cable.

Topological protection in non-Hermitian Haldane honeycomb lattices

Topological phenomena in non-Hermitian systems have recently become a subject of great interest in the photonics and condensed-matter communities. In particular, the possibility of observing topologically-protected edge states in non-Hermitian lattices has sparked an intensive search for systems where this kind of states are sustained. Here, we present the first study on the emergence of topological edge states in two-dimensional Haldane lattices exhibiting balanced gain and loss. In line with recent studies on other Chern insulator models, we show that edge states can be observed in the so-called broken $\mathcal{P}\mathcal{T}$-symmetric phase, that is, when the spectrum of the gain-loss-balanced system's Hamiltonian is not entirely real. More importantly, we find that such topologically protected edge states emerge irrespective of the lattice boundaries, namely zigzag, bearded or armchair.

De‐noising of time‐domain spectroscopy data for reliable assessment of power transformer insulation

Polarisation-depolarisation current (PDC) measurement and its analysis is a popular technique for assessing the condition of transformer insulation. Owing to the low magnitude of PDC, recording noise-free PDC data from in-situ power transformers is a challenge. Once the relaxation current data get affected by noise, it becomes difficult to formulate insulation model (as recorded data loses its characteristic shape). This further makes the data difficult to analyse and predict insulation condition. In this study, two de-noising techniques are discussed (one is based on Wavelet Transform while the other is based on Stockwell Transform) for eliminating low-frequency non-stationary noise from recorded PDC data. Comparison between these two techniques suggests de-noising using Stockwell Transform is advantageous over wavelet analysis. The proposed methodology is first tested on data recorded from the sample prepared in the laboratory and then on data measured from real-life in-service power transformer.