Power Cable System Research Articles

Power cable monitoring method based on UHF‐RFID and deep learning in edge computing environment

AbstractThis research addresses the challenge faced by most existing prediction methods in handling nonlinear data of cables. Furthermore, it proposes a novel power cable monitoring method utilizing UHF‐RFID and deep learning within an edge computing environment, specifically targeting the currently suboptimal wireless monitoring of cables. First, based on edge computing, a power cable monitoring system is designed to migrate the analysis of massive data to the edge of the network to improve the monitoring efficiency. Then, the temperature sensing chip and RFID chip were integrated to design a UHF‐RFID temperature tag, which was fixed at the cable temperature measurement point to achieve passive wireless monitoring of the cable. Finally, the parameters of the GRNN model are optimized using the beetle antennae search algorithm, and the EEMD decomposed data is input into the BAS‐GRNN model for learning to output temperature prediction results. Based on the establishment of an experimental platform, the method was demonstrated, and results showed that the maximum error between the UHF‐RFID temperature tag temperature measurement results and the thermocouple was within 0.3°C, and the average relative error of the proposed method was only 0.01, which can meet the accuracy requirements of actual monitoring of power cables.

Finite Element Method Based Design of a Computer Application Interface for Thermal Analysis of Underground Power Cable System

The aim of thermal analysis of underground power cable studies is to optimize electrical and physical parameters of cable system and to transfer maximum power with minimum losses. For such problems, finite element method is mostly preferred, since they have complex geometry and requires multi-disciplinary (thermal and electrical) study. However, design, calculation and analysis of the problem is quite challenging since it requires advanced knowledge in related areas. Therefore, it becomes difficult particularly for engineers and students to study on thermal analysis of underground cables which has an important role in power system. In this context, it is aimed to design an application to perform thermal analysis of a typical medium voltage underground cable system. The application is designed using Comsol Multiphysics and allows users to perform two-dimensional, time-dependent thermal analyses. It also provides users to set several thermal, electrical and physical parameters as inputs and allows to compare thermal distribution results at desired points and regions. In the study, a series of thermal analyses are performed and results are presented for a sample loading scenario to indicate performance of the application. Besides, the application designed is used as a training material in a seminar in Yildiz Technical University, Electrical Engineering Department. Results showed that the application can be used as a useful tool for engineering education.

An analysis of parameters affecting ampacity in aircraft bipolar MVDC power cables via coupled electrical, thermal, and computational fluid dynamic modelling

AbstractThe next generation of aircraft, including more electric aircraft and all‐electric aircraft, require electric power systems with high power density and low system mass specifications. Increasing the voltage of the system to the range of a few kV, medium voltage (MV), is a reasonable approach to achieving high‐power‐density and low‐system‐mass EPSs for aircraft applications. Higher voltages, however, pose many challenges for aviation MV power cables such as arcs and arc tracking, partial discharges (PDs), and thermal management. In this regard, thermal management is more challenging since heat transfer by convection is greatly reduced at wide‐body aircraft's cruising altitudes due to the reduced air pressure. In this paper, a finite element method (FEM) model is developed in COMSOL Multiphysics for an aircraft bipolar MVDC (±5 kV) power cable. Using the model, the maximum permissible cable current at a low pressure of 18.8 kPa (at an altitude of 12.2 km from sea level, the usual cruising altitude for wide‐body aircraft) is calculated. Also, an analytical model is developed based on analytical and proven empirical correlations governing conductive, radiative, and convective heat transfers at the steady state to estimate the ampacity of the bipolar cable system at reduced pressure. It was shown that the proposed analytical model can be used for atmospheric pressure and systems with a larger number of poles, expanding its range of applications. The results of the FEM and analytical models correlate at wide ranges of parameters such as ambient temperature, duct size, distance between the positive and negative pole cables, and the overall diameter of the cables. The influence of horizontal and vertical arrangement of poles is included in the analytical model. The results of this study can be used to design bipolar MVDC power cable systems for the envisaged wide‐body AEA.

Improving power cable partial discharge pattern recognition through gustafson-kessel fuzzy clustering techniques

Existing methods for recognizing partial discharge patterns in power cables do not utilize fuzzy clustering of the discharge signals, resulting in poor quality and low recall and precision of the pattern recognition. To address this, we propose a new approach for partial discharge pattern recognition in cables using Gustafson-Kessel(GK) Fuzzy Clustering. The method involves acquiring signals from a power cable partial discharge monitoring system and then processing the signals with GK fuzzy clustering. The clustered discharge signals are filtered with wavelet packet transforms before input into an improved adaptive resonance theory(ART) neural network for final pattern recognition. Experiments demonstrate the new technique achieves up to 98.7% recall and 85.6% precision for discharge pattern recognition, with discharge signal Signal Noise Ratio(SNR) between 55 dB and 62 dB and maximum recognition accuracy reaching 98%. The proposed fuzzy clustering-based pattern recognition approach significantly enhances partial discharge diagnostics for power cable monitoring.

Grafting of voltage stabilizer onto EPDM surface and its inhibition effect on the breakdown of EPDM/XLPE interface

Surface discharge on the EPDM/XLPE interface is threatening the safe operation of power cable system and limiting the further improvement of its voltage level. To improve the electrical strength of EPDM/XLPE interface, the surface of EPDM was modified by grafting of voltage stabilizer 4-allyloxy-2-hydroxybenzophenone (AOHBP) based on liquid-phase impregnation and subsequent free radical grafting reaction thermally initiated by DCP. EPDM samples were modified by mixed reagents of DCP and AOHBP with different mass ratios of 1:2, 1:3 and 1:4, respectively. The SEM observation and XRD analysis results indicate that the crystals of AOHBP with a uniform distribution are covered on the surface of EPDM during the sample preparation process and then dissolved after extraction by acetone. The FTIR and ATR results show that the AOHBP molecules are successfully grafted onto the surface of EPDM samples, but there remain a lot of ungrafted reagent molecules on the surface of EPDM before solvent extraction. The grafting rate of AOHBP increases with the proportion of DCP in the mixed reagents. As for the unextracted modified EPDM samples, both the AC and DC breakdown voltage of the EPDM/XLPE interface are increased compared with pure EPDM, and further increased after the ungrafted molecules are extracted because the effect of voltage stabilizer on scavenging high-energy electrons is more efficiently utilized at a smoother interface. The interface breakdown voltage of the sample modified with 1:2 mass ratio of DCP/AOHBP mixed solution is the highest because of its highest grafting rate of voltage stabilizer. This work has proposed a new technical path to improve the electrical aging resistance of polymer insulating surface.

Research on intelligent identification algorithm for preventing external damage behavior of power cable based on machine learning

Abstract As the key carrier of power distribution line power transmission and the supporting artery of urban functioning, power cables are widely used in electric power engineering construction. The number of users is increasing, and the distribution of locations is becoming more complex. However, if a power cable failure occurs, if not eliminated in time, it will threaten the safety of the power grid, seriously affecting the production of enterprises and the lives of residents. The article first on the power cable vibration signal recognition algorithm design, extraction of power cable external damage fault signal characteristics, proposed based on PSO-SVM power cable external damage fault waveform recognition algorithm, and the design of power cable anti-external damage intelligent early warning system, to achieve a certain period according to the trend of signal changes in the vibration event to discriminate. Research results show that under the same computer operating conditions, the average running time of the algorithm proposed in this paper is only 3.43. Compared to the other two algorithms, the algorithm has the highest recognition accuracy, the fastest convergence speed, and the optimal comprehensive performance. In the external damage signal recognition and warning test, the recognition rate of the excavator passing through defense zone one and two at a distance of 3 meters is 100%, which is greater than 80%, in line with the expected effect.

Optimization of bend stiffeners of a suspended inter-array power cable between two floating offshore wind turbines

The concept of a suspended inter-array power cable assumes that the cable floats within the water column instead of being laid on the seabed. This setup requires additional equipment, such as buoyancy modules or buoys, to achieve the desired cable configuration. The implementation of buoyancy modules introduces abrupt changes in stiffness between the cable sections with clamped-on buoyancy modules and bare cable sections. Large stiffness variations can negatively impact cable bending, causing excessive curvature and fatigue damage. In order to form a smooth transition in stiffness between the buoyancy sections and the bare cable, bend stiffeners can be equipped. The study aims to optimize the bend stiffener design for a representative suspended power cable between two floating offshore wind turbines (FOWTs). The inter-array power cable system is simulated in OrcaFlex. Two parameters, including the outer diameter and the length of the bend stiffener, are adjusted to generate different cases. Eight environmental conditions are applied to the dynamic analysis of the cases. The fitness factor approach is used as a criterion to assess the overall performance of different bend stiffener designs. Adjusting the outer diameter of bend stiffeners clearly influences the maximum effective tension and the minimum bending radius by changing the stiffness profile of the bend stiffener and its submerged weight. In the investigated range of parameters, increasing the overall length of bend stiffeners is found to be less effective than adjusting the outer diameter of the bend stiffener.

Consistency in thermal conductivity measured via lab-, field-scale test, and numerical simulation for newly developed backfill materials for underground power cable system

This study investigates the thermal properties of newly developed backfill materials (normal and prepacked concrete) for an underground power cable system (UPCS) through different methods (laboratory test, in-situ horizontal thermal response test (TRT), and numerical analysis). First, the thermal conductivities of small-scale backfill materials were measured in a laboratory using a hot disk sensor. Afterward, a 5 × 3 × 2 m full-scale backfill was prepared for the TRT. The infinite line source (ILS) model was employed to estimate the thermal conductivity of the backfill materials using data from the TRT. Finally, a numerical analysis was conducted to simulate the heat transfer process during the TRT and back-calculate the thermal conductivity of the proposed backfill materials. All tests were also conducted using conventional backfill materials, namely natural sand, for comparison with the proposed backfill materials. The results indicated that the prepacked concrete type has the highest thermal conductivity among the three backfill materials regardless of the testing method employed. In addition to a high thermal conductivity, this newly developed material also has good workability (382 mm for the grout), low bleeding, and satisfactory excavation ability for the backfill material (1.56 MPa). Furthermore, the ILS model and numerical model slightly overestimated the thermal conductivity (less than 8 %) compared to the measured values from the laboratory test involving normal and prepacked concretes; however, natural sand exhibited a significant difference (1.365 W/(mK) and 1.8 W/(mK), 32 %) owing to the influence of the water content on its thermal conductivity. In addition, thermal conductivities calculated by the ILS model and numerical simulation were in very good agreement (with the difference being lower than 3 %), demonstrating that the proposed ILS model is appropriate to use to estimate the thermal conductivity of large-scale backfill material using horizontal TRT data.

Dynamic Responses of a 1:5-Scale Ocean Current Energy Converter

The objective of this study is to numerically evaluate the dynamic responses of the Floating Kuroshio Turbine (FKT)—an ocean current energy converter—installed for field testing. In autumn 2022, the FKT was installed and tested at a 1:5 scale in the open sea area, located 1 kilometre off the LiuQiu Island coast, Taiwan. Because of unfavourable site conditions, the mooring and power cable systems for the FKT had to be customarily designed for the testing conditions. An investigation of the dynamic motions and structural responses of the mooring and cable systems was performed prior to physical testing to ensure the integrity of the testing campaign. The numerical analyses were performed using the commercial software DNV SIMA, where the prospect of the surfaced FKT and the mooring entanglement were evaluated and compared. This paper details the modelling process and the evaluation of the dynamics of the entire FKT system. Finally, the challenges and potential improvements for numerical assessments of a testing-oriented offshore marine energy system are identified and discussed.

Partial Discharge Characteristics and Mechanism of Medium Voltage Power Cable Defects under Different Voltage Stresses

Off‐line partial discharge (PD) diagnosis, which requires an additional power supply has been accepted as an essential step in ensuring the integrity of power cable systems during commissioning testing. Many types of energizing voltage sources (e.g., alternating current resonance, damped alternating current, very low frequency [VLF] sine, and VLF‐cosine rectangular) have been developed, which are used in practice. However, choosing the optimal energizing voltage waveforms for PD testing is still controversial because their capability to motivate PD activities is still unclear. Accordingly, this paper compares the PD ignition capacity of the aforementioned power sources on six well‐designed PD defects in real cable joints. The influence of test voltage frequencies and waveforms are verified. The results show that the PD inception voltage and PD magnitudes in the cable joint defects do not change significantly as a function of the sinusoidal voltage frequency and the VLF‐cosine rectangular voltage exhibits excellent PD ignition capability with a low PD inception voltage and large PD magnitude. Moreover, the dynamic behavior of space charge in a PD defect caused by a gap is analyzed in order to explain the obtained results. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Double Optical Fiber Temperature Compensation Method for Measurement of Interface Pressure Between Simulated Cable and Accessory at High Temperatures

Reliable interface pressure between cables and accessories is closely associated with the safe operation of a power cable system. Using an external optical fiber Bragg grating temperature-compensating curvature sensor, a new method for online measurement of the interface pressure between a cable and an accessory at high temperatures is proposed. On the basis of the sensing principle of a fiber Bragg grating, a mathematical pure bending model, and a model of a thick-walled cylinder, a fiber Bragg grating temperature-compensating curvature sensor is fabricated using Dow Corning Sylgard-184 silicone rubber. The interface pressures of 10 kV cable accessories with different expansion rates at different temperatures are measured. The results of the measurements show that the temperature-compensated deviation of wavelength measurements made by the fiber grating curvature sensor ranges from -2.59% to 5.50%. The interface pressure between the cable and the accessory gradually increases with an increase in temperature from 30 to 60 °C. The results are consistent with the results of measurements made using a traditional piezoelectric sensor. This method is expected to evaluate the long-term reliability of the interface pressure of cable accessories in actual complex-temperature environments.

Electrical Resistance Performance of Cable Accessory Interface Considering Thermal Effects.

Power cables are widely used in various fields of power transmission, and cable accessories are the weakest link in power cable systems due to their complex structure and multi-layer insulation coordination issues. This paper investigates the changes in electrical properties of the silicone rubber/cross-linked polyethylene (SiR/XLPE) interface at high temperatures. The physicochemical properties of XLPE material under thermal effects with different times are characterized through FTIR, DSC, and SEM tests. Finally, the mechanism of the effects of the interface state on the electrical properties of the SiR/XLPE interface is analyzed. It is found that with the increase in temperature, the changes in electrical performance of the interface do not show a monotonic downward trend, while interestingly, they can be divided into three stages. Under the thermal effects for 40 d, the internal recrystallization of XLPE in the early stage improves the electrical properties of the interface. In the later stage of thermal effects, the amorphous region inside the material is severely damaged and the molecular chains are severely broken, resulting in a decrease in the electrical properties of the interface. The results above provide a theoretical basis for the interface design of cable accessories at high temperatures.

Thermophysical Properties of Bentonite–Sand/Fly Ash-Based Backfill Materials for Underground Power Cable

The surrounding (backfill) materials around the underground power cable systems are essential for dissipating the heat away from it, during the exertion phases. The heat dissipation restrains the thermal instability and risk of progressive drying of the backfill materials, thus reducing the thermal stress on the power cable. Thermal instability indicates the reduction in thermal properties (conductivity or diffusivity) due to the migration of moisture because of heat accumulation. Thus, the backfill materials should have adequate thermal properties and water retention capacity to transfer the heat from the heat source to the surrounding area with minimal moisture migration. The bentonite has high water retention capacity, but low thermal conductivity, whereas sand/fly ash exhibits low water retention and has higher thermal conductivity than bentonite. The addition of bentonite promotes the water holding capacity and thermophysical properties of sand and fly ash. Therefore, this study presents the thermal properties of backfill materials, bentonite–fly ash (B–F) and bentonite–sand (B–S), at varying weight-percent of sand and fly ash with bentonite. Various compositions of the mixtures were compacted to varying dry densities, and water contents and thermal properties variation of backfill materials were measured using a dual thermal needle probe ‘KD2 Pro’ at room temperature. The study deals with the systematic evaluation of the volumetric specific heat capacity, thermal conductivity, and diffusivity of backfill materials against varying dry density and water content. The threshold water content (TWC) has been determined from the thermal diffusivity–water content variation curve, and it has correlated with plastic limit (PL) and optimum moisture content (OMC). Thereafter, the efficacies of two thermal conductivity prediction models have also been evaluated statistically with respect to experimental results.

Precision and Performance Evaluation of Accelerated Aging System for DC TP Power Cables

The demand and necessity of direct current (DC) has been increasing owing to large capacity and long distance power transmission. DC application of TP (thermal plastic) materials, which can increase the power transmission capacity compared to existing insulation materials, has been the primary focus of existing studies. This study presents the development of a highly reliable accelerated aging system that can implement the aging conditions of DC power cables. Moreover, we verify its reliability by testing TP model cables and analyzing the aging characteristics. Accordingly, we developed an accelerated aging system that can simulate thermal, electrical, and mechanical stresses collectively. We used the accelerated aging system to perform an accelerated aging test of the TP model cable for 40 cycles. The control precision of the accelerated aging system during the test was numerically calculated. The system was evaluated by using the conduction current and chemical characteristics of the aged TP model cables. The experimental results show that the precision of accelerated aging system is 1 % for 1 cycle. The conduction current of the aged TP model cables was increased by more than 100% before aging, thereby it is verified the performance of the system accelerates the aging of power cables. It is expected that the highly reliable accelerated aging system of power cables can be used to perform long-term reliability tests and as diagnostic technology during the development of DC power cables.

An Approach to Determine Health Index of Power Cable System

Power Cable System is a vital asset in Electrical Power System. Now a days power cables are used in transmission and distribution of electric power at MV, HV and EHV levels. Reliability and availability of power supply depends greatly on insulation condition of the power cable system. Therefore, power cable asset management is vital for taking decision on future course of action to minimize capital expenditure, maximize reliability and avoid forced outages. In this paper, how to deploy power cable asset management is discussed using Health Index based on diagnostic test data.

Damped AC Testing and Diagnosis of Wind Farm HVAC Long-Length Cable Circuits

Many new HVAC power cable installations on wind farms, both on- and offshore, have long lengths. In contrast to traditional power cable connections of a few kilometers, the failures of those systems usually result in much higher repair and unsupplied energy costs. To support the quality assurance of newly installed cable systems as well as to create a sound basis for condition-based maintenance, this paper discusses the technical challenges of the field testing of long-length power cable systems using a damped AC testing method and also discusses the best practical applications for the testing and diagnosis of these wind farm HVAC cable systems.

A novel fault diagnosis method of power cable based on convolutional probabilistic neural network with discrete wavelet transform and symmetrized dot pattern

To accurately diagnose the XLPE power cable insulation fault, this research proposed a novel hybrid algorithm combined with Convolutional Probabilistic Neural Network (CPNN) based on Discrete Wavelet Transform (DWT) and Symmetrized Dot Pattern (SDP) analysis. First, it built seven different power cable insulation defect models to measure partial discharge signals of power cable insulation faults. Then, a discrete wavelet transform was used for noise filtering. The time-domain partial discharge signal was directly converted into the point coordinate feature image of visual polar coordinates by SDP analyses. Finally, the feature image was trained and recognized by CPNN. After the important feature information of the feature-image was extracted by convolution layer and pooling layer operations, it is applied to the power cable insulation fault state diagnosis system based on the rapid learning and highly parallel computing of Probabilistic Neural Network (PNN). The experimental results proved that the method proposed in this research could accurately diagnose the power cable insulation fault type and the recognition accuracy is higher than 96%. The proposed method has a short detection time and high diagnostic accuracy. This proves that it can be applied to detect the power cable insulation fault type.

Hybrid Methodology Based on Symmetrized Dot Pattern and Convolutional Neural Networks for Fault Diagnosis of Power Cables

This study proposes a recognition method based on symmetrized dot pattern (SDP) analysis and convolutional neural network (CNN) for rapid and accurate diagnosis of insulation defect problems by detecting the partial discharge (PD) signals of XLPE power cables. First, a normal and three power cable models with different insulation defects are built. The PD signals resulting from power cable insulation defects are measured. The frequency and amplitude variations of PD signals from different defects are reflected by comprehensible images using the proposed SDP analysis method. The features of different power cable defects are presented. Finally, the feature image is trained and identified by CNN to achieve a power cable insulation fault diagnosis system. The experimental results show that the proposed method could accurately diagnose the fault types of power cable insulation defects with a recognition accuracy of 98%. The proposed method is characterized by a short detection time and high diagnostic accuracy. It can effectively detect the power cable PD to identify the fault type of the insulation defect.

Thermal Transients in Three‐Core Power Cable Systems: First Principle Modelling and Verification

AbstractThis paper presents research related to developing a thermal model for three‐core power cable systems used in offshore wind farms. Three‐core power cable systems are a significantly more complicated thermo‐electrical system than single‐core power cables, primarily due to the geometric asymmetry and the number of heat sources. There are tools available that can model thermal transients in three‐core cable systems, but these tools demand a nontrivial level of prerequisite knowledge and training on the part of the user. Therefore, this research aimed at developing and testing a first principle model specifically tuned for thermal transients in three‐core cables. The model has been tested by comparing its predictions with empirical temperature data collected from heat cycle testing on three‐core cables at Nexans' facilities. To increase the quality of the predictions, part of the research was also to measure the thermal properties of swellable tape and filling compound (used in three‐core cables). The first principle model's predictions correspond well with the empirical data, the research results are promising. The model must be tested more thoroughly with different use cases before it can complement or replace current working methods.

Algorithm for fast calculating the energization overvoltages along a power cable based on modal theory and numerical inverse Laplace transform

Transient overvoltage caused by energization may damage the insulation in a power cable transmission system. Therefore, overvoltage along the cable should be calculated and evaluated carefully. Calculation based on traditional commercial software is time-consuming, therefore, there is a need to develop a new algorithm to improve the computational efficiency. First, coupled cable conductors are transformed into independent modes through phase-mode transformation. Then, the voltage formula of each independent mode in the complex frequency domain is obtained through Laplace transform. Finally, energization overvoltages along the cable are calculated using numerical inverse Laplace transform (NILT) and mode-phase transformation. The proposed algorithm is applied to a 330 kV cable line with a length of 9.6 km to certify the accuracy and computational efficiency. Compared with frequency dependent phase model (FDPM) in PSCAD/EMTDC, relative errors of the obtained results are less than 1%, and the maximum CPU time consumed is only about 8%. The proposed algorithm can improve the computational speed of cable energization overvoltages greatly on the premise of ensuring accuracy and may be contributing to actual applications.