Search Results (154)

In the construction and operation of smart grids, real-time monitoring of electrical signals is crucial for achieving efficient and stable power transmission, so it is necessary to develop current and voltage sensors with high stability, mass manufacturing and light weight. This study presents a current and voltage sensor based on fully printed technology for electrical signal monitoring of transmission lines. The current sensor is supported and insulated by polyimide, and successfully fabricates the 3D induction coil through screen printing and high-precision inkjet printing processes, achieving a sensitivity of 0.00823 mV/A and a linearity of 0.999 in 0–60 A. The voltage sensor is made of polyimide film as the substrate, and a pair of silver sensing electrodes are prepared by screen printing process, achieving a sensitivity of 0.00369 μA/V and a linearity of 0.999 in 0–1200 V, with stable output over a continuous operation of 24 h. The overall size of the current and voltage sensor is 1.5 cm × 2 cm, the weight is 1.8 g, the cost is about USD 0.462, and it has the advantages of low cost, lightweight, good linearity, high stability, simple structure, and scalable preparation. This work provides a new sensor fabrication method for current and voltage monitoring in transmission lines. Full article

High-current-carrying capability with minimum thermal elongation is one of the key reasons for using high-temperature low-sag (HTLS) conductors in modern power systems. However, their higher operational temperature can significantly affect corona discharge characteristics. Corona is one of the key factors in transmission line design considerations. Corona discharge is the leading cause of audible noise, radio interference, and corona loss in power transmission systems. The influence of conductor temperature on corona discharge characteristics is investigated in this paper using experimental methods and computational simulations. A simulation framework has been developed in COMSOL Multiphysics using the physics of plasmas and electrostatics to simulate corona plasma dynamic behavior and electric field distribution. The results show that the conductor temperature enhances the ionization by electron impact, enhances the production of positive and negative ions, changes the electric field distribution, and increases the electron temperature. This analysis emphasizes that temperature-dependent conditions affect the inception and intensity of corona discharge. Additionally, an experimental model was developed to evaluate corona voltage–current characteristics under varying temperature conditions. The study presents both simulation results and a newly developed model for predicting corona current at high conductor temperatures. Full article

Cement poles serve as supporting components for transmission lines and are widely used in medium- and low-voltage transmission networks. The main rebar is the primary load-bearing structure of the pole, and the accurate measurement of its diameter and embedment depth is crucial for quality control and safety assessment. However, existing non-destructive testing methods lack the accuracy of quantifying the internal main rebar of cement poles, and the measurement process is complex, cumbersome, and inefficient. To address this issue, this paper proposes a magnetic rotation-based detection method for measuring the diameter and embedment depth of the main rebar within cement poles. A specially designed H-type magnetic excitation structure is proposed, coupled with a detection technique utilizing rotating permanent magnets. The magnetic induction intensity data were acquired at seven distinct rotation angles using sensors, and the collected data were subsequently combined with a CNN-LSTM model to invert the diameter and embedment depth of the main rebar. The experimental results indicate that the method significantly improved the measurement accuracy compared with the condition of fixed magnetic excitation, with reductions in root mean square error (RMSE) of 46.71% and 35.57% for the diameter and embedment depth measurements, respectively. This method provides a robust, efficient, and accurate solution for quantifying the main rebar within cement poles, addressing the challenge associated with the quality assessment and health monitoring of these structures. Full article

This paper proposes a transient energy auxiliary supply circuit architecture based on resonant switched-capacitor principles, aimed at optimizing the system’s transient response to meet the growing power supply demands. This paper first introduces the relevant principles of resonant switched-capacitor converters. Based on this, a transient energy path topology based on resonant principles is designed to achieve bidirectional, fast, and low electromagnetic interference energy transmission. Corresponding system coordination control strategies and high-precision switch control based on delay lines are proposed for the designed circuit topology. A circuit model is built in SIMPLIS (V8.20a) software for system simulation, and a prototype is built based on FPGA to verify circuit functionality and performance. Experimental results demonstrate that the resonant energy auxiliary circuit can operate in conjunction with a six-phase Buck circuit prototype. Under test conditions of a 500 kHz operating frequency, 6.5 V input voltage, and 0.75 V output voltage, the overshoot voltage is reduced by more than 17% across the entire operating range. When the load steps from 200 A to 20 A, the overshoot voltage is reduced to only 85 mV, a decrease of 27.97%, while the recovery time is 28.8 µs, a reduction of 37.66%. These results confirm that the auxiliary circuit can significantly improve the system’s transient response under large load steps, meeting the design requirements. Full article

Ensuring the reliability and safety of electrical power systems requires the efficient detection of defects in high-voltage transmission line insulators, which play a critical role in electrical isolation and mechanical support. Environmental factors often lead to insulator defects, highlighting the need for accurate detection methods. This paper proposes an enhanced defect detection approach based on a lightweight neural network derived from the YOLOv11n architecture. Key innovations include a redesigned C3k2 module that incorporates multidimensional dynamic convolutions (ODConv) for improved feature extraction, the introduction of Slimneck to reduce model complexity and computational cost, and the application of the WIoU loss function to optimize anchor box handling and to accelerate convergence. Experimental results demonstrate that the proposed method outperforms existing models like YOLOv8 and YOLOv10 in precision, recall, and mean average precision (mAP), while maintaining low computational complexity. This approach provides a promising solution for real-time, high-accuracy insulator defect detection, enhancing the safety and reliability of power transmission systems. Full article

This paper explores the use of a solid state transformer (SST) to mitigate the $E_{3A}$ component of a high-altitude electromagnetic pulse (HEMP) insult using external energy storage optimal control techniques. In lieu of conventional passive blocking devices or feedback-controlled energy storage devices, a novel implementation of Hamiltonian error tracking is utilized to develop a feedback control law for the variable converter ratio in an SST. The findings of the simulations performed in this paper suggest that additional energy storage is not necessary to protect an individual load from a HEMP insult. The simulations performed examine the response of a single-phase SST connected to a single voltage source on a long transmission line on the one side and a single linear resistor on the other. The control law is specifically developed for the late-time, low-frequency portion of a HEMP insult, namely the $E_{3A}$ components. The Hamiltonian error-based converter ratio control law is compared with nonlinear optimal feedforward controls to show that the HSSPFC is an external energy storage optimal controller. Full article

This article proposes a novel tube foundation intended for use under transmission line poles. The glass fibre reinforcement polymer (GFRP) piles were driven into sand. A steel tube pole, approximately 6 m high, was mounted on the foundation. The analysed foundations were designed as a monopile to be implemented in the construction of low- and medium-voltage overhead transmission lines. Experimental field tests of innovative piles made of the composite material were carried out on a 1:1 scale. The aim of this work was to develop an isotropic material model treating the GFRP composite as homogeneous. This approach does not fully reproduce the anisotropic behaviour of the composite, but it allows for the engineering design of structures made of the composite material. Laboratory tests in the form of a static tensile test on the samples and a tensile test on the rings cut from a hollow section were performed. The results of the experimental tests and FEM models of the GFRP rings and monopile embedded in sand were compared. The ultimate limit state (ULS) and serviceability limit state (SLS) of the analysed pile were assessed as 14.4 and 9.6 kNm, respectively. The developed numerical model, based on FEM, allows for the load-bearing capacity of the monopile made of GFRP to be reliably determined. From an engineering point of view, the developed numerical model of the GFRP material can be used to calculate the pile load-bearing capacity using engineering software that has limited capabilities in defining material models. Full article

This article presents research on the possibilities of using information and communication technologies in monitoring systems for electrical networks with isolated neutral, aimed at improving and automating production functions in the energy sector. This aligns with the digitalization policy of Kazakhstan’s economy and is part of similar programs in the field of the electric power industry. This article explores an approach to organizing a digital monitoring system for emergency conditions, specifically single-phase ground faults in medium-voltage lines within the range of 6–35 kV, including the new voltage class of 20 kV. A version of such a system is proposed, based on a combination of a server, a wireless information network, and remote digital voltage measurement nodes. This wireless information and communication network is designed to detect the locations of single-phase ground faults (SPGF) using specialized zero-sequence voltage sensors installed at various points along the power transmission lines, along with wireless signal transmission channels to the dispatcher’s server. To ensure protection against industrial interference, based on the results of practical environment modeling, a transmission technology most resistant to external noise is selected. This article proposes the selection of equipment necessary for implementing wireless transmission technology and develops two versions of a digital voltmeter design based on low-power programmable microcontrollers. The proposed technical solutions require further experimental validation, and therefore, the authors plan to conduct additional research and practical experiments in the future. Full article

In ultrasound systems, a protection circuit must be used to protect the receiver electronics from the high-voltage pulses generated by the transmitter and to minimize the signal loss and distortion of the low-voltage echoes generated by the transducer. Especially for certain ultrasound applications, such as intravascular ultrasound, particle manipulation, and cell stimulation, proper performance of the ultrasound transducers is desirable due to their low sensitivity. As the operating frequency of the ultrasound transducer increases, the size of the transducer decreases, increasing the amplitude of the transmitted signals to achieve proper acoustic performance. In such environments, a protection circuit can be used to protect the receiver electronics in ultrasound systems. To design suitable protection circuits, transistors, resistors, capacitors, and inductors are used, and the parameters of insertion loss, noise, total harmonic distortion, and recovery time of the protection circuits must be carefully considered. Various approaches have been developed to protect circuits such as transmission lines, transformers, bridge diodes, and metal-oxide-semiconductor field-effect transistor devices. Certain protection circuits are beneficial for impedance matching and area reduction. Other protection circuits have been designed to increase bandwidth, reduce insertion loss, or improve the signal-to-noise ratio for different ultrasound applications. Therefore, this review article may be useful for academic ultrasound researchers or circuit designers in selecting appropriate protection circuit types for specific ultrasound transducer applications. Full article

Asynchronous interconnected systems connected by High-Voltage Direct Current (HVDC) transmission lines struggle with frequency support between interconnected areas, increasing the risk of frequency instability and resulting in low efficiency in frequency resource utilization. This study establishes a frequency dynamic analysis model for asynchronous interconnected power grids and develops an HVDC frequency controller for frequency control in these systems. It analyzes the control effects of HVDC frequency under two scenarios: without Automatic Generation Control (AGC) and with AGC. The research conducts an in-depth study on the system stability and frequency control parameter optimization for HVDC-asynchronous interconnected systems, significantly improving the system’s response speed and accuracy under various conditions through parameter optimization. Furthermore, the introduction of AGC demonstrates good adaptability, and a comparative analysis of HVDC frequency control effects under different AGC control modes is conducted. Finally, case studies validate the effectiveness and robustness of the proposed optimization scheme for frequency stability control in asynchronous interconnected systems under various fault scenarios. Full article

The efficiency of helical locomotion in snake-like robots along high-voltage transmission lines is often hindered by low motion efficiency, high joint signal noise, and challenges in traversing obstacles. This study aims to address these issues by proposing a gait generation method that leverages a standardized Central Pattern Generator (CPG). We modify the traditional Hopf-CPG model by incorporating constraint functions and a frequency-tuning mechanism to regulate the oscillator, which allows for the generation of asymmetric waveform signals for deflection joints and facilitates rapid convergence. The method begins by determining initial and obstacle-crossing state parameters, such as deflection angles and helical radii of the snake-like robot, using the backbone curve method and the Frenet–Serret framework. Subsequently, a CPG neural network is constructed based on Hopf oscillators, with a limit cycle convergent speed adjustment factor and amplitude bias signals to establish a fully connected matrix model for calculating multi-joint output signals. Simulation analysis using Simulink–CoppeliaSim evaluates the robot’s obstacle-crossing ability and the optimization of deflection joint signal noise. The results indicate a 55.70% increase in the robot’s average speed during cable traversal, a 57.53% reduction in deflection joint noise disturbance, and successful crossing of the vibration damper. This gait generation method significantly enhances locomotion efficiency and noise suppression in snake-like robots, offering substantial advantages over traditional approaches. Full article

At present, Unmanned Aerial Vehicles (UAVs) combined with deep learning have become an important means of transmission line inspection; however, the current approach has the problems of high demand for manual operation, low inspection efficiency, inspection results that do not reflect the distribution of defects on transmission towers, and the need for a large number of manually annotated captured images. In order to achieve the UAV understanding the structure of transmission towers and identifying the defects in the parts of transmission towers, a three-granularity pose estimation framework for multi-type high-voltage transmission towers using Part Affinity Fields (PAFs) is presented here. The framework classifies the structural critical points of high-voltage transmission towers and uses PAFs to provide a basis for the connection between the critical points to achieve the pose estimation for multi-type towers. On the other hand, a three-fine-grained prediction incorporating an intermediate supervisory mechanism is designed so as to overcome the problem of dense and overlapping keypoints of transmission towers. The dataset used in this study consists of real image data of high-voltage transmission towers and complementary images of virtual scenes created through the fourth-generation Unreal Engine (UE4). In various types of electrical tower detection, the average keypoint identification AF of the proposed model exceeds 96% and the average skeleton connection AF exceeds 93% at all granularities, which demonstrates good results on the test set and shows some degree of generalization to electricity towers not included in the dataset. Full article

This paper presents a new method for fault location in transmission lines with series compensation, using data from voltage and current measurements at both terminals, applied to artificial neural networks. To determine the fault location, we present the proposal of using current phasors, obtained from the oscillography recorded during the short circuit, as the input to the neural network for training. However, the method does not rely on the internal voltage values of the sources or their respective equivalent Thevenin impedances to generate training files for the neural network in a transient simulator. The source data are not known exactly at the time of the short circuit in the transmission line, leading to greater errors when neural networks are applied to real electrical systems of utility companies, which reduces the dependency on electrical network parameters. To present the new method, a conventional fault location algorithm based on neural networks is initially described, highlighting how the dependency on source parameters can hinder the application of the artificial neural network in real cases encountered in utility electrical systems. Subsequently, the new algorithm is described and applied to simulated and real fault cases. Low errors are obtained in both situations, demonstrating its effectiveness and practical applicability. It is noted that the neural networks used for real cases are trained using simulated faults but without any data from the terminal sources. Although we expect the findings of this paper to have relevance in transmission lines with series compensation, the new method can also be applied to conventional transmission lines, i.e., without series compensation, as evidenced by the results presented. Full article

Deep-sea offshore wind power generation has gained increasing attention in the past decade. The low cost and high efficiency of the DC grid system make it more competitive when the transmission distance is over 100 km. As the key enabler of the DC grids, DC converters are necessitated to interconnect the DC lines with different voltage levels. Instead of using auxiliary circuits, this paper proposes a low-cost isolated modular multilevel DC converter (IMMDC) with unipolar-to-bipolar conversion topology to fit into the DC grids with different configurations. Moreover, the proposed DC-current-injection-based fault-tolerant scheme can maintain around 50% power transmission capability even under single pole open-circuit fault conditions for a certain period, enhancing the power supply continuity. The modularity and scalability of the proposed IMMDC topology can fit into different DC grid systems. The effectiveness and feasibility of the proposed topology and control strategy are verified using a 50 kV/±300 kV/100 MW MATLAB/Simulink 2022b simulation model. Full article

High-voltage overhead power lines serve as the carrier of power transmission and are crucial to the stable operation of the power system. Therefore, it is particularly important to detect and remove foreign objects attached to transmission lines, as soon as possible. In this context, the widespread promotion and application of smart robots in the power industry can help address the increasingly complex challenges faced by the industry and ensure the efficient, economical, and safe operation of the power grid system. This article proposes a bionic-based UAV pose estimation and target perception strategy, which aims to address the lack of pattern recognition and automatic tracking capabilities of traditional power line inspection UAVs, as well as the poor robustness of visual odometry. Compared with the existing UAV environmental perception solutions, the bionic target perception algorithm proposed in this article can efficiently extract point and line features from infrared images and realize the target detection and automatic tracking function of small multi-rotor drones in the power line scenario, with low power consumption. Full article