Search Results (61)

Deep learning-based models have achieved considerable success in partial discharge (PD) fault diagnosis for power systems, enhancing grid asset safety and improving reliability. However, traditional approaches often rely on centralized training, which demands significant resources and fails to account for the impact of noisy operating conditions on Intelligent Electronic Devices (IEDs). In a gas-insulated switchgear (GIS), PD measurement data collected in noisy environments exhibit diverse feature distributions and a wide range of class representations, posing significant challenges for trained models under complex conditions. To address these challenges, we propose a Self-Supervised Asynchronous Federated Learning (SSAFL) approach for PD diagnosis in noisy IED environments. The proposed technique integrates asynchronous federated learning with self-supervised learning, enabling IEDs to learn robust pattern representations while preserving local data privacy and mitigating the effects of resource heterogeneity among IEDs. Experimental results demonstrate that the proposed SSAFL framework achieves overall accuracies of 98% and 95% on the training and testing datasets, respectively. Additionally, for the floating class in IED 1, SSAFL improves the F1-score by 5% compared to Self-Supervised Federated Learning (SSFL). These results indicate that the proposed SSAFL method offers greater adaptability to real-world scenarios. In particular, it effectively addresses the scarcity of labeled data, ensures data privacy, and efficiently utilizes heterogeneous local resources. Full article

AC power cables play an important role in power systems, in the transmission and distribution of electrical energy. For this reason, to ensure high operational reliability, voltage withstand tests and diagnostic tests are performed at every stage of their technical life to determine the condition of cable insulation. Due to the large electrical capacitances of cable systems, modern testing methods use very low frequency (VLF) and damped oscillating (DAC) voltages. The research presented in the article analyzed the effect of the test voltage waveform parameters on the partial discharge (PD) inception conditions in spherical gaseous voids present in the XLPE insulation of AC cable model. Using COMSOL 6.1 and MATLAB R2021b, a coupled electro-thermal model of a 110 kV AC cable was implemented, for which the critical gaseous void dimensions were estimated and phase-resolved PD patterns were generated for the rated voltage and the VLF and DAC test voltages specified in the relevant standards. In the analyses for the rated voltage, the influence of internal temperature distribution, which causes modification of XLPE permittivity, was taken into account in the numerical cable model. Full article

In light of the large and fast-growing use of power electronics in electrical generation, distribution and utilization systems, and with the focus on electrified transportation, evaluating the significance of testing insulation systems for design and quality control under AC sinusoidal or power electronics waveforms is a due knowledge step. This paper has a twofold aim. One is presenting a procedure for the comparison between two insulation system solutions for partial discharge, PD, free design, referring to motorettes of a MV speed-controlled motor. The other is to carry out an evaluation of the most effective testing waveform, from AC sinusoidal to AC modulated (PWM), varying the number of inverter levels and switching the slew rate. It is shown that AC sinusoidal is effective for a qualitative evaluation of insulation system design as regards partial discharge risk, but PD inception voltage can be significantly dependent on supply voltage waveforms. Hence, if quantitative estimation of partial discharge inception voltage is requested, for design and quality control purposes, PWM waveforms as close as possible to those planned under operation should be used. Full article

Partial discharge (PD) analysis is critical for diagnosing insulation degradation in high-voltage equipment. While conventional methods struggle with multi-source PD classification due to signal overlap and noise, this study proposes a hybrid approach combining five time–frequency analysis (TFA) techniques with deep learning (GoogLeNet for simulation, ResNet50 for experiments). PD data are generated through Finite Element Method (FEM) simulations and validated via laboratory experiments. The Scatter Wavelet Transform (SWT) achieves 96.67% accuracy (F1-score: 0.967) in simulation and perfect 100% accuracy (F1-score: 1.000) in experiments, outperforming other TFAs like HHT (70.00% experimental accuracy). The Wigner–Ville Distribution (WVD) also shows strong experimental performance (94.74% accuracy, AUC: 0.947), though its computational complexity limits real-time use. These results demonstrate the SWT’s superiority in handling real-world noise and multi-source PD signals, providing a robust framework for insulation diagnostics in power systems. Full article

Distribution cabinets are of paramount importance in power supply systems. Internal partial discharge may result in power interruption or even the outbreak of fire. This paper proposes a partial discharge (PD) detection approach based on a fiber-optic Mach–Zehnder interferometer (MZI). The MZI method utilizes a fiber wound with a certain size and number of turns as the sensing element, which is mounted on the wall of the low-voltage distribution cabinet to monitor the partial discharge within the cabinet in real time. A true-type distribution cabinet partial discharge experimental platform is developed to validate the proposed method. Three 10 m long fiber-optic sensors with diameters of 50 mm, 80 mm, and 100 mm are designed and compared with a traditional piezoelectric transducer (PZT) for analysis. The experimental results indicate that the fiber-optic MZI sensor can effectively capture PD acoustic pulses, and the pulse amplitude is consistent with that of the PZT sensor. Moreover, compared with the PZT sensor, the fiber-optic MZI system possesses a higher frequency response and a longer effective detection time for PD pulses, demonstrating superior PD detection performance. The fiber-optic coil sensor with a diameter of 8 cm performed optimally in the experiment. The fiber-optic sensing method based on the MZI has significant potential application value in the partial discharge detection of power distribution cabinets, providing a theoretical basis for its application in engineering practice. Full article

HVDC cable systems are becoming an upscaled technical option, compared to AC, because of various factors, including easier interconnections, lower losses, and longer transmission distances. In addition, renewables providing direct DC energy, electrified transportation, and aerospace where DC can be favored because of higher carried specific power all point in the direction of broad future usage of HV and MV DC links. However, contrary to AC, there is little return from on-field installation as regards long-term cable reliability and aging processes. This gap must be covered by intensive research, and contributing to this research is the purpose of this paper. The focus is on key points for HVDC (and MVDC) cable reliability and sustainability, from design modeling able to account for voltage transients and extrinsic aging (such as that caused by partial discharges) to the impact of aging on insulation conductivity (which rules the electric field distribution, thus aging rate). Also, recyclable and nanostructured materials, as well as health conditions, are considered. It is shown how cable design can account for accelerated aging due to voltage transients, as well as for aging-time dependence of conductivity, and how design can be free of extrinsic aging caused by PDs. Algorithms for health condition evaluations, which have additional value in a relatively new technology such as HVDC polymeric cables, are applied to insulation system aging under partial discharges, showing how they can provide an indication of insulation degradation globally or locally (weak spots) and of possible maintenance times. All of this can effectively contribute to reducing the risk of major cable breakdown and damage under operation, which would significantly affect the return on investment (ROI). Full article

As critical infrastructure in modern distribution systems, power cables face progressive insulation degradation from partial discharge (PD), while conventional recognition methods struggle with feature extraction and model generalizability. This study develops an integrated experimental platform for PD pattern recognition in power cable systems, comprising a control console, high-voltage transformer, high-frequency current transformer, and ultra-high-frequency (UHF) signal acquisition equipment. Four distinct types of discharge-defective models are constructed and tested through this dedicated high-voltage platform, generating a dataset of phase-resolved partial discharge (PRPD) spectra. Based on this experimental foundation, an improved Swin Transformer-based framework with adaptive learning rate optimization is developed to address the limitations of conventional methods. The proposed architecture demonstrates superior performance, achieving 94.68% classification accuracy with 20 training epochs while reaching 97.52% at the final 200th epoch. Comparisons with the original tiny version of the Swin Transformer model show that the proposed Swin Transformer with an adaptive learning rate attains a maximum improvement of 6.89% over the baseline model in recognition accuracy for different types of PD defect detection. Comparisons with other deeper Convolutional Neural Networks illustrate that the proposed lightweight Swin Transformer can achieve comparable accuracy with significantly lower computational demands, making it more promising for application in real-time PD defect diagnostics. Full article

This thesis proposes an improved droop control strategy design based on active disturbance rejection control and LSTM. This strategy uses the droop control method to coordinately control the distributed generation units (DGs) in a microgrid to achieve stable operation of the microgrid system. Linear-Auto Disturbance Rejection Control (LADRC) is introduced and an improved LADRC is designed based on the error principle. A disturbance compensation link is introduced on the basis of traditional LADRC to form ILADRC and a droop control strategy is used. Instead of improving the PD controller in LADRC, an improved droop control strategy is formed, which not only achieves natural decoupling between powers, but also improves the system’s immunity and transient operation capabilities. At the same time, in order to achieve adaptive parameter tuning in the improved droop control strategy, this article introduces long short-term memory (LSTM) to form an adaptive improved droop control strategy which further improves the system’s immunity and robustness. This article builds a simulation model through the MATLAB/Simulink simulation experiment platform and tests PI control and traditional droop control. The strategy and the improved droop control strategy designed in this thesis are experimentally compared and verified, and simulation analysis and verification are conducted on the two working conditions. The simulation results clearly demonstrate the superiority of the improved droop control strategy over PI control and traditional droop control, indicating that the correctness and reliability under various working conditions are verified. Full article

In this article, an extension of a conventional partial discharge (PD) approach called partial discharge echo (PDE), which is applied to different classes of electrical insulation systems of power devices, is presented. Currently, high-voltage (HV) electrical insulation is attributed not only to transmission and distribution grids but also to the industrial environment and emerging segments such as transportation electrification, i.e., electric vehicles, more-electric aircraft, and propulsion in maritime vehicles. This novel PDE methodology extends the conventional and established PD-based assessment, which is perceived to be one of the crucial indicators of HV electrical insulation integrity. PD echo may provide additional insight into the surface conditions and charge transport phenomena in a non-invasive way. It offers new diagnostic attributes that expand the evaluation of insulation conditions that are not possible by conventional PD measurements. The effects of partial discharge echo in various segments of insulation systems (such as cross-linked polyethylene [XLPE] power cable sections that contain defects and a twisted-pair helical coil that represents motor-winding insulation) are shown in this paper. The aim is to demonstrate the echo response on representative electrical insulating materials; for example, polyethylene, insulating paper, and Nomex. Comparisons of the PD echo decay times among various insulation systems are depicted, reflecting dielectric surface phenomena. The presented approach offers extended quantitative assessments of the conditions of HV electrical insulation, including its detection, measurement methodology, and interpretation. Full article

This research explores the integrated management of water distribution systems (WDS) and power distribution systems (PDS) to improve their resilience to extreme scenarios. This study delves into the dynamics of a locally managed PDS as an example of extreme operational conditions. The primary objective is to minimize load shedding (LS) in the PDS through strategic load shifting in the interconnected WDS, demonstrating the potential of cooperative decision making between the two critical systems. The optimization framework offers a novel approach to managing flexible resources during emergencies by utilizing the mutual links between a WDS and a PDS. Typically, WDSs and PDSs are operated by different operators such that cooperation is limited. This study presents how communication based on limited information sharing between the two systems is sufficient to increase resilience and improve the systems’ functionality, emphasizing the advantages of cooperative decision making. This paper highlights the significance of cross-sectoral collaboration, presenting a viable pathway for managing local infrastructure systems under extreme conditions while ensuring uninterrupted service delivery to communities. Full article

New applications such as augmented reality/virtual reality (AR/VR), Internet-of-Things (IOT), autonomous mobile robot (AMR) services, etc., require high reliability and high accuracy real-time positioning and tracking of persons and devices in indoor areas. Among the different visible-light-positioning (VLP) schemes, such as proximity, time-of-arrival (TOA), time-difference-of-arrival (TDOA), angle-of-arrival (AOA), and received-signal-strength (RSS), the RSS scheme is relatively easy to implement. Among these VLP methods, the RSS method is simple and efficient. As the received optical power has an inverse relationship with the distance between the LED transmitter (Tx) and the photodiode (PD) receiver (Rx), position information can be estimated by studying the received optical power from different Txs. In this work, we propose and experimentally demonstrate a real-time VLP system utilizing long short-term memory neural network (LSTM-NN) with principal component analysis (PCA) to mitigate high positioning error, particularly at the positioning unit cell boundaries. Experimental results show that in a positioning unit cell of 100 × 100 × 250 cm³, the average positioning error is 5.912 cm when using LSTM-NN only. By utilizing the PCA, we can observe that the positioning accuracy can be significantly enhanced to 1.806 cm, particularly at the unit cell boundaries and cell corners, showing a positioning error reduction of 69.45%. In the cumulative distribution function (CDF) measurements, when using only the LSTM-NN model, the positioning error of 95% of the experimental data is >15 cm; while using the LSTM-NN with PCA model, the error is reduced to <5 cm. In addition, we also experimentally demonstrate that the proposed real-time VLP system can also be used to predict the direction and the trajectory of the moving Rx. Full article

Traditional optical communication systems rely on single narrow-band PDs, which can expose confidential information and data to potential eavesdropping in free space. With advancements in technology, even optical communication in the UV spectrum, invisible to the sun, faces risks of interception. Consequently, broad-band PDs that combine optical encryption with algorithmic encryption hold significant promise for secure and reliable communication. This study presents a photodetector based on TiO₂–α-Ga₂O₃ heterostructures, prepared via direct oxidation and hydrothermal reaction, demonstrating self-powered UVC/UVA broad-band detection capabilities. The PD exhibits response peaks at approximately 250 and 320 nm, with R of 42.16 and 59.88 mA/W and D* of 8.21 × 10¹³ and 9.56 × 10¹³ Jones, respectively. Leveraging the superior optical response characteristics of UVC and UVA wavelengths, this device has been employed to develop a communication system designed for data transmission. The proposed system features two independent channels: one for data transmission using UVC and another for key distribution using UVA. Secure communication is ensured through specialized encryption algorithms. In summary, this work offers a straightforward, cost-effective, and practical method for fabricating self-powered UVC/UVA broad-band PDs. This PD provides new insights into the development of multi-purpose, multi-band secure optical communication devices and holds promise for integration into multifunctional optoelectronic systems in the future. Full article

During their lifespan, high-voltage (HV) electrical systems are subjected to operating conditions in which electrical, mechanical, thermal and environmental-related stresses occur. These conditions over time lead to unforeseen failures caused by various types of defects. For this reason, there are several technologies for measuring and monitoring the electrical systems, with the aim of minimizing the number of faults. The early detection of defects, preferably in their incipient state, will enable the necessary corrective actions to be taken in order to avoid unforeseen failures. These failures generally lead to human risks and material damage, lack of power supply and significant economic losses. An efficient maintenance technique for the early detection of defects consists of the supervision of the dielectrics status in the installations by means of on-line partial discharge (PD) measurement. Nowadays, there are numerous systems in the market for the measurement of PD in HV installations. The most efficient with a reasonable cost will be those that offer greater security guarantees and the best positioned in the market. Currently, technology developers and users of PD measuring systems face difficulties related to the lack of reference procedures for their complete characterization and to the technical and economic drawback of performing the characterization tests on site or in laboratory installations. To deal with the previous difficulties, in this paper a novel method for the complete and standardized characterization of PD measuring systems is presented. The applicability of this method is mainly adapted for the characterization of systems operating in on-line applications using high-frequency current transformer (HFCT) sensors. For the appropriate application of the method, an associated and necessary scale modular test platform is used. In the test platform, the real on-site measuring conditions of an HV insulated distribution line are simulated in a controlled way. Practical characterizations, showing the convenience and advantages of applying the method using the modular test platform, are also presented. Full article

Coordinated load restoration of integrated electric and heating systems (IEHSs) has become indispensable following natural disasters due to the increasingly relevant integration between power distribution systems (PDS) and district heating systems (DHS). In this paper, a coordinated reconfiguration with an energy storage system is introduced to optimize load restoration in the aftermath of natural catastrophes. By modifying the DHS network topology, it is possible to maintain an uninterrupted energy supply in unfaulty zones by shifting heat loads among sources and adjusting the operation of coupled devices. Additionally, energy storage systems with rapid response times are implemented to enhance load restoration efficiency, especially when working in conjunction with multiple energy sources. Comprehensive case analyses have been systematically conducted to demonstrate the impact of coordinated reconfiguration with energy storage systems on improving load restoration. Full article

Energy supply interruptions or blackouts caused by faults in power distribution feeders entail several damages to power utilities and consumer units: financial losses, damage to power distribution reliability, power quality deterioration, etc. Most studies in the specialized literature concerning faults in power distribution systems present methodologies for detecting, classifying, and locating faults after their occurrence. In contrast, the main aim of this study is to prevent faults by estimating the city regions whose power grid is most vulnerable to them. In this sense, this work incorporates a geographical-space study via a spatial data analysis using the local variable electrical discharge density that can increase fault risks. A geographically weighted spatial analysis is applied to data aggregated by regions to produce thematic maps with the city regions whose feeders are more vulnerable to failures. The spatial data analysis is implemented in QGIS and R programming environments. It is applied to the real data of faults in distribution power grid transformers and electrical discharges in a medium-sized city with approximately 200,000 inhabitants. In this study, we highlight a moderate positive correlation between electrical discharge density and the percentage of faults in transformers by regions in the central and western areas of the city under study. Full article