With the popularization of airplanes, high-speed railways and high-voltage transmission lines, the economic and safety problems caused by ice accretion have become increasingly serious. In the past few decades, SHS and SLIPS have made progress in anti/de-icing surfaces. However, their durability has been challenged. In recent years, liquid-like surfaces (LLS) prepared by grafting functional polymers have been proven to significantly improve the durability of anti/de-icing surfaces, thus achieving diverse, large-scale and controllable performances. Herein, we review the wetting mechanism and anti/de-icing mechanism of LLS. Then, the factors influencing the anti/de-icing performance of LLS are introduced, including their grafting density, relative molecular weight, branched structure and end groups. Subsequently, taking polymer brushes, polymer networks, storage-functional polymer networks and brush-like polymer networks as four types, the preparation methods and anti/de-icing performance of LLS are elaborated. In addition, in the case of photothermal anti/de-icing coatings, LLS can endow them with excellent transparency to meet the requirements of special application environments. Finally, the challenges and obstacles of LLS in the anti/de-icing field are discussed, and the great potential of LLS in this field in the future is prospected.

Abstract We apply polymer quantization, a quantization technique sometimes used in high energy physics, to several superconducting circuits including: transmons, transmission line resonators, and LC circuits. In the case of transmon qubits and transmission line resonators, experimental predictions are very close to what is found with canonical quantization, though in this approach constant charge offsets can be interpreted as quantization ambiguities. In the case of LC circuits, polymer quantization predicts nonlinearities which are not present in the canonical approach. Based on this analysis we design and analyze a qubit which uses a meander inductor instead of a Josephson junction. Implications for qubit performance and fabrication are discussed. Given a choice for an effective phase operator, relevant parameters such as anharmonicity, frequency, and dispersive shifts are calculated for this meander inductor based qubit.

To address the challenges of high concealability and difficulty in identifying minor damage in transmission lines, as well as low fault diagnosis accuracy under strong noise conditions, a novel fault diagnosis method for transmission lines is proposed. A data processing method based on adaptive modal filtering is proposed by combining a variational constraint model with an adaptive frequency band extraction strategy. Subsequently, by leveraging the concept of the generalized Fourier transform, pseudopeak effects near modal frequencies are suppressed, achieving thorough noise signal filtering without altering the intrinsic state characteristics of the transmission lines. For fault diagnosis, a convolutional neural network enhanced with an attention module is constructed, and a fault diagnosis model integrated with bidirectional long short-term memory (BiLSTM) is proposed. By embedding a convolutional block attention module, network weights are dynamically adjusted to enhance feature representation in both channel and spatial dimensions. Additionally, the introduction of BiLSTM strengthens the model’s ability to process time series data. Finally, the proposed method is validated on a conductor vibration test platform, demonstrating its high diagnostic accuracy and superior performance in noisy environments compared with other models.

Protecting transmission line in STATCOM integrated DFIG system using adaptive distance relay blocking scheme

Abstract Integration of electricity based on intermittent renewable sources such as solar power to a grid can have adverse effect on electric power grid. In this work, we investigated the impact of integration of solar photovoltaic (SPV) on voltage stability. Six transmission buses (Kano, Kaduna, Gwagwalada, New Haven, Birnin Kebbi and Lokoja) with shortest distance to each of the 13 proposed locations have been identified and each of the Solar PV farms was integrated to the transmission bus closest to the proposed solar farm sites. The effects of SPV integration on Transmission lines loading have been performed and the Nigeria 56-bus transmission network was used for the investigation. Voltage stability analysis was carried out using the load margin obtained from the PV curve at each of the six identified buses and effect of SPV integration on the system voltage profile was identified. Sensitivity analysis was also performed in order to obtain the impact of increasing penetration on the voltage stability. The investigation was conducted using DigSilent Power Factory and MATLAB. The result shows that the safe region of integration for the six identified transmission buses is between 10 % (365.8 MW) at Gwagwalada bus and 19 % (695 MW) of base load power at Kaduna. 1 % of SPV was integrated simultaneously at Egbin, Ikeja West, Akangba, Sakete, Kano, Aja, Alagbon, and Osogbo with voltages lesser than 0.95 pu at the base case and the result reveals that all the buses in the system are within acceptable voltage level of 0.95–1.05 pu. Highest improvement in load margin is achieved when 1 % SPV is integrated at Kaduna bus among the six transmission buses considered. Different locations affect system load margins and voltage stability differently. 1 % integration of SPV at different buses significantly improve the load margin from 1,107.7 MW (Birnin Kebbi) to 1,448.9 MW (Kaduna).

The transmission lines we consider are constructed from the nonlinear inductors and the nonlinear capacitors. In the first part of the paper, we additionally include linear ohmic resistors. The dissipation thus being taken into account leads to the existence of shocks-the traveling waves with the different asymptotically constant values of the voltage (the capacitor charge) and the current before and after the front of the wave. For the particular values of ohmic resistances (corresponding to strong dissipation), we obtain the analytic solution for the profile of a shock wave. Both the charge on a capacitor and current through the inductor are obtained as the functions of the time and space coordinate. For the case of weak dissipation, we obtain the stationary dispersive shock waves. In the second part of the paper, we consider a nonlinear lossless transmission line. We formulate the simple wave approximation for such a transmission line, which decouples left- and right-going waves. The approximation can also be used for the lossy transmission line considered in the first part of the paper to describe the formation of the shock wave (but, of course, not the shock wave itself).

The safe and stable operation of ultra-high-voltage (UHV) transmission lines is fundamental to ensuring efficient and large-capacity power delivery. Critical fittings, as essential load-bearing components connecting towers, conductors, and insulator strings, are highly susceptible to damage under complex ice–wind conditions, thereby posing significant threats to grid security. To address the prevalent issues of jumper spacer breakage and conductor abrasion observed in field maintenance, a systematic finite element analysis model incorporating bundled conductors, jumper structures, and associated fittings was established. This model enabled comprehensive investigation of the effects of non-uniform ice accretion, wind loading, and ice-shedding impacts on the bearing characteristics of critical fittings. Through high-throughput computational simulations, a large-scale dataset capturing the bearing characteristics of jumper spacers was constructed. Based on this dataset, a damage risk assessment model under complex ice–wind conditions was developed using a multi-layer feedforward deep neural network (MLF-DNN). The results indicated that wind loading had a relatively minor influence on jumper spacers, whereas ice accretion and ice-shedding impacts were the dominant factors leading to damage. In particular, non-uniform ice-shedding readily induced unbalanced forces among sub-conductors, significantly increasing stress levels in jumper spacers and resulting in substantial risk. The proposed risk assessment model demonstrated high predictive accuracy and strong generalization capability, providing effective support for rapid evaluation and early warning of damage to fittings in UHV transmission lines under complex ice–wind environments.

At Wendelstein 7-X (W7-X), the world's largest superconducting stellarator with a five-fold symmetry and reduced neoclassical transport, a broad suite of microwave diagnostics is installed and operated. Due to the robustness of in-vessel components and transmission lines against the harsh environment in fusion devices, they are candidates for reactor plasma control.This presentation will show an overview of microwave diagnostics at W7-X. After introducing the governing equations for the propagation of microwaves in a fusion plasma e.g. the determination of the local positions where the measurements are performed, the different diagnostics are presented. The presentation will encompass the installed diagnostics, but also, the planned upgrades and show important technical details and highlighting results obtained during the last campaigns. It will cover passive microwave diagnostics for the estimation of the electron temperature profile by radiometry from the 2nd and 3rd harmonic of the electron cyclotron emission (ECE) with a temporal resolution in the MHz-range. Furthermore, the 1st–3rd harmonic ECE radiation is measured with interferometry for both, X- and O-mode polarization. Also, fluctuations of the electron temperature are measured by various methods of correlation ECE. Active probing radar applications, so-called reflectometry, are installed to measure density fluctuations and its propagation. They allow measuring the turbulence propagation for a wide wavenumber range. Under certain assumptions the radial electric field, an important quantity for the neoclassical transport is deduced from this propagation. To measure the electron density profile in the edge, a frequency modulated continuous wave reflectometer is installed in the Ion Cyclotron Resonance Heating (ICRH)-antenna. The purpose of the instrument is the measurement of the density profile to improve the coupling of the ICRH-waves into the plasma. Besides this, the measurement of the density profile in the edge with high spatial and temporal resolution is independent of the ICRH-operation. Furthermore, a microwave scattering diagnostic, the collective Thomson Scattering (CTS), uses a gyrotron as active probing beam yields direct information of the ion temperature of hydrogen or in later campaigns deuterium species and does not rely on the impurity temperature.

Performance evaluation of emerging grid infrastructure Operations: Evidence from ultra-high-voltage transmission lines in China

Emergency control is essential for ensuring transient stability in power systems after faults. This study addresses the limitations in existing methods by proposing a knowledge-generative pretrained transformer (GPT)-guided generalizable reinforcement learning (RL) approach for intelligent emergency generator tripping. This approach incorporates general electrical principles and knowledge-GPT to assist deep reinforcement learning (DRL). The general electrical principles involve identifying severely disturbed generators and selecting appropriate control actions through dynamic probability. The knowledge-GPT model extracts insights from an expert strategy knowledge base, reshaping the DRL reward structure by comparing the DRL strategy with the knowledge-GPT outputs. This paradigm is designed to leverage electrical laws and domain expertise to guide the DRL training process, thereby enhancing both training efficiency and electrical consistency. To enhance generalization capability under topological changes, message passing neural networks (NNs) are integrated into the DRL architecture, effectively simulating power flow dynamics in transmission lines. The proposed method is validated through simulations on the IEEE 39-bus system and the Northeast power grid of China, demonstrating superior control effectiveness and adaptability compared to existing approaches, offering a more robust solution for emergency control in complex power systems.

Triboelectric nanogenerator and micro thermoelectric generator−based self-powered ice weight monitoring on transmission lines

Separate and detailed characterization of signal and noise at low resonance frequencies.

<span lang="EN-US">The regular fault detection approaches are failed to detect the faults in wind integrated transmission networks due to intermittency nature of the wind energy. More reliable schemes are required to accomplish the detection of faults in presence wind. This article proposed empirical mode decomposition (EMD) based fault detection scheme to detect various faults in wind integrated transmission lines during the normal and stressed conditions of the system. The instantaneous current measurements available at either sending or receiving end are processed through EMD to decompose it into a series of intrinsic mode functions (IMFs) and IMF2 is identified as a dominated IMF with numerous case wise investigations. 1/4th cycle moving window is used to calculate the absolute sum of the IMF2 coefficients to detect the faults with the support of a predefined threshold. The efficacy of the method is tested on different types of faults during the normal condition in presence of wind and later extended to stressed conditions such as power swing. The method is reliable during the typical cases and includes remote end and high resistance faults. All the experiments are carried out in Simulink to generate the measurement data and programs are executed in MATLAB.</span>

Enhancing machine-learning-based anomaly detection in transmission lines models using robust features from neural networks

Dynamic line rating-based routing of overhead transmission lines for wind energy integration

Visual recognition of icing risk on overhead transmission lines based on improved fuzzy wavelet domain

Power system planning using optimally designed transmission lines

Adaptability analysis of distance protection in flexible low frequency ac outgoing transmission line of wind power system

Lissajous pattern based optimally compensated phase difference estimation for underground cable transmission line protection

Long-term measurement of audible noise from 750-kV AC transmission line in high-altitude area