Search Results (245)

This review examines the design of thermal control systems for state-of-the-art deep ultraviolet (DUV) and extreme ultraviolet (EUV) projection lithography tools. The lithographic system under investigation integrates several critical subsystems along the optical transmission chain, including the light source, reticle stage, projection optics (featuring DUV refractive lenses and EUV multilayer mirrors), immersion liquid, wafer stage, and metrology systems. Under high-power irradiation conditions with concurrent thermal perturbations, the degradation of thermal stability and gradient uniformity within these subsystems significantly compromises exposure precision. Through a systematic analysis of the thermal challenges specific to each subsystem, this review synthesizes established thermal control systems across two technical dimensions: thermal control structures and thermal control algorithms. Prospects for future advancements in lithographic thermal control are also discussed. Full article

With the rapid advancement of UAV-based remote sensing and image recognition techniques, identifying environmental risk factors from aerial imagery has emerged as a focal point in intelligent inspection during the power transmission and distribution projects construction phase. The uneven spatial distribution of risk factors on construction sites, their weak texture signatures, and the inherently multi-scale nature of UAV imagery pose significant detection challenges. To address these issues, we propose a one-stage SRW-YOLO algorithm built upon the YOLOv11 framework. First, a P2-scale shallow feature detection layer is added to capture high-resolution fine details of small targets. Second, we integrate a reparameterized convolution based on channel shuffle (RCS) of a one-shot aggregation (RCS-OSA) module into the backbone and neck’s shallow layers, enhancing feature extraction while significantly reducing inference latency. Finally, a dynamic non-monotonic focusing mechanism WIoU v3 loss function is employed to reweigh low-quality annotations, thereby improving small-object localization accuracy. Experimental results demonstrate that SRW-YOLO achieves an overall precision of 80.6% and mAP of 79.1% on the State Grid dataset, and exhibits similarly superior performance on the VisDrone2019 dataset. Compared with other one-stage detectors, SRW-YOLO delivers markedly higher detection accuracy, offering critical technical support for multi-scale, heterogeneous environmental risk monitoring during the power transmission and distribution projects construction phase, and establishes the theoretical foundation for rapid and accurate inspection using UAV-based intelligent imaging. Full article

Prefabricated construction elements are widely used in both large- and small-scale projects, serving structural and infrastructural purposes. One notable application is in power transmission poles, which ensure the safe and efficient delivery of electricity. Despite their importance, limited research exists on the structural and modal behavior of reinforced concrete power poles. This study presents a comprehensive modal analysis of such poles, focusing on how factors like modulus of elasticity, height, and lower/upper inner and outer diameters influence dynamic performance. A total of 3240 finite element models were created, with reinforced concrete poles partially embedded in the ground. Modal analyses were performed to evaluate natural frequencies, mode shapes, and modal mass participation ratios. Results showed that increasing the modulus of elasticity raised frequency values, while greater pole height decreased them. Enlarging the lower inner and upper outer radii also led to higher frequencies. Regression analysis yielded high accuracy, with R² values exceeding 90% and an average error rate of about 6%. The study provides empirical formulas that allow for quick frequency estimations without the need for detailed finite element modeling, as long as the material and geometric properties remain consistent. The approach can be extended to other prefabricated structural elements. Full article

Dynamic Line Rating (DLR) technology is presented as a key solution to optimize the transmission capacity of power lines without the need to make investments in new infrastructure. Unlike traditional methods based on static estimates, DLR allows the thermal capacity of conductors to be evaluated in real time, considering the environmental and operational conditions. This article presents a state-of-the-art analysis of this technology, including a review of the main solutions currently available on the market. Likewise, the influence of variables such as ambient temperature, wind speed and direction or solar radiation in the determination of dynamic load capacity is discussed. It also reviews various pilot and commercial projects implemented internationally, evaluating their results and lessons learned. Finally, the main technological, regulatory, and operational challenges faced by the mass adoption of DLR are identified, including aspects such as the prediction of the dynamic capacity value, combination with other flexibility options, or integration with network management systems. This review is intended to serve as a basis for future developments and research in the field. Full article

The YZ-ZJ DC transmission project addresses significant power transmission challenges in a specific region’s power grid, which faces unique pressures due to overlapping “growth” and “transition” periods in energy demand. This study focuses on the integration of Controllable-Line-Commutated Converters (CLCCs) into the YZ-ZJ DC transmission project at the receiving end, replacing the traditional LCCs to mitigate commutation failures during AC system faults. The main innovation lies in the development of a hybrid electromechanical–electromagnetic simulation model based on actual engineering parameters that provides a comprehensive analysis of the CLCC’s electromagnetic characteristics and system-level behavior under fault conditions. This is a significant advancement over previous research, which mainly focused on discrete electromagnetic modeling in ideal or simplified scenarios without considering the full complexity of real-world regional power grids. The research demonstrates that integrating CLCCs into the regional power grid not only prevents commutation failures but also enhances the overall reliability of the transmission system. The results show that CLCCs significantly improve fault tolerance, stabilize power transmission during faults, reduce power fluctuations in neighboring transmission lines, and enhance grid stability. Furthermore, this study confirms that the CLCC-based YZ-ZJ DC project outperforms the traditional LCC system, maintaining stable power transmission even under fault conditions. In conclusion, this study validates the feasibility of CLCCs in resisting commutation failures when integrated into a large power grid and reveals their positive impact on the regional grid. Full article

The reliability of the electro-power equipment of electrical power transmission systems is essential in ensuring an uninterrupted power supply with the necessary voltage and frequency stability. This is especially important when performing lengthy procedures requiring the serviceability of the electrical equipment used, such as those related to foundries and metallurgical processes, or with the processes of testing complex means for the remote control of electromagnetic radiation within the implementation of the Sustainable development of the Competence Center “Quantum Communication, Intelligent Security Systems and Risk Management” (QUASAR) Project, funded with the participation of the EU under the “Research, Innovation and Digitalization for Smart Transformation” Program 2021.2027 according to procedure BG16RFPR002-1.014. One of the main issues in this case is related to the availability of information regarding the technical condition of the deployed or reserve energy resources. In this connection, this study proposes methods for determining the quantity of operational equipment that is either in use or in storage, based on the reliability testing of a representative sample of it. Full article

Energy resources are abundant in high-altitude regions, and the construction of power transmission and transformation projects has important value. However, harsh natural environments can increase project costs. To address the issue of insufficient accuracy caused by the impact of extreme weather factors on cost predictions for power transmission and transformation projects in high-altitude regions, this paper first constructs a four-dimensional influencing factor system covering climate and environment, engineering scale, material consumption, and technological economy. On this basis, a hybrid deep-learning model combining an improved whale optimization algorithm (IWOA) and a convolutional neural network (CNN) is then proposed. The model improves the training accuracy of CNNs and avoids falling into local optima through the use of an SGDM optimizer, the L2 regularization method, and the Bayesian optimization method. Nonlinear convergence factors and adaptive weights are introduced to enhance the WOA’s ability to optimize the CNN’s learning rate. The case analysis results show that, compared with the comparison model, the proposed IWOA-CNN model exhibits a better convergence performance and fitting effect in the training set and a better prediction effect on the test set. Its mean absolute percentage error is as low as 1.51%, which is 10.1% lower than the optimal comparison model. The root mean square error is reduced to 5.07, and the sum of squared errors is reduced by 72.4%, demonstrating high prediction accuracy. The comparative analysis of scenarios further confirms the crucial role of climate environment; that is, the prediction accuracy of models containing a climate dimension is improved by 51.6% compared to models without such a climate dimension, indicating that the nonlinear impact of low temperatures, frozen soil, and other characteristics of high-altitude regions on costs cannot be ignored. The research results of this paper enrich the method system and application scenarios for the cost prediction for power transmission and transformation projects and provide theoretical reference for engineering predictions in other complex geographical environments. Full article

The project of the flexible direct transmission of renewable energy has become an inevitable development trend for the large-scale grid connection of renewable energy. Its two-terminal weakly fed AC system is often composed of 100% power electronic equipment, which leads to an essential transformation in fault characteristics and protection requirements. At present, in research, the traditional directional elements are limited by the negative-sequence control strategy, resulting in the decline of their sensitivity and reliability. Therefore, this paper proposes a model for identifying directional elements using composite electrical quantities that is not affected by the control strategy of the two-terminal weakly fed AC system and can reliably identify the fault direction. Firstly, the adaptability of traditional directional elements under the negative-sequence current suppression strategy on both sides of the system when faults occur in the AC line was analyzed. Secondly, based on the idea of model recognition, the model relationship of fault voltage and current in the case of ground faults and non-ground faults occurring at different locations was analyzed. Finally, a fitted voltage was constructed and the Kendall correlation coefficient was introduced to achieve fault direction discrimination. Simulation results demonstrate that the proposed pilot protection scheme can operate reliably under conditions of 300 Ω transition resistance and 25 dB noise interference. Full article

With the extensive construction of high-voltage power grid projects in complex mountainous terrains, rainfall-induced slope instability poses a significant threat to the safety of transmission tower foundations. This study focuses on a power transmission and transformation project in Huizhou City, Guangdong Province. Using MIDAS GTS NX 2019 (v1.2), an unsaturated seepage-mechanics coupling model was established to systematically investigate the influence of slope ratios (1:0.75, 1:1, and 1:1.25) on slope stability under rainfall conditions and the reinforcement effects of anti-slide piles. The results demonstrate that slope ratios significantly govern slope responses. For steep slopes (1:0.75), post-rainfall matrix suction loss reached 43.2%, peak displacement attained 74.49 mm, and the safety factor decreased by 12.5%. In contrast, gentle slopes (1:1.25) exhibited superior stability. Anti-slide piles effectively controlled displacement growth (≤9.15%), but pile bending moments increased markedly with steeper slope ratios, accompanied by a notable expansion of the plastic zone at the slope toe. The study reveals a destabilization mechanism characterized by “seepage–strength degradation–displacement synergy” and recommends engineering practices adopting slope ratios of 1:1–1:1.25, combined with anti-slide piles (spacing ≤ 1.5 m) and dynamic drainage measures. These findings provide critical guidance for the design of transmission tower slopes in mountainous regions. Full article

Offshore wind power has a broad development prospect, but with the development of offshore wind farms to the deep sea, the traditional high-voltage AC transmission has been difficult to adapt to the offshore wind power transmission distance and transmission capacity needs. A flexible DC transmission system applying modular multilevel converter is a common scheme for offshore wind power, which has been put into use in actual projects, but it is still facing the problems of high cost of offshore converter station platforms and high loss of collector systems. In order to improve the economy and reliability of the medium- and long-distance offshore wind power delivery systems, this paper proposes a diode rectifier-based medium-frequency AC pooling soft-direct low-cost delivery system for medium- and long-distance offshore wind power. Firstly, the mid-frequency equivalent model of the diode converter is established, and the influence of topology and frequency enhancement on the parameters of the main circuit equipment is analysed; then, the distribution parameters and transmission capacity of the mid-frequency cable are calculated based on the finite element modelling of the marine cable, and the transmission losses of the mid-frequency AC pooling system are then calculated, including the collector losses, converter valve losses, and transformer losses, etc. Finally, an economic analysis is carried out based on a specific example, comparing with the Jiangsu Rudong offshore wind power transmission project, in order to verify the economy of the medium-frequency AC flexible and direct transmission system of the medium- and long-distance offshore wind power using diode rectifier technology. Full article

A LoRaWAN application architecture comprises three functional components: (i) nodes, which convert and wirelessly transmit data as LoRaWAN messages; (ii) gateways, which receive and forward these transmissions; and (iii) network servers, which process the received data for application delivery. The nodes convert data into LoRaWAN messages and transmit them wirelessly with the hope that one or more LoRaWAN gateway will receive the messages successfully. Then, the gateways pass on the received messages to a distant network server, where various processing steps occur before the messages are forwarded to the end application. If none of the gateways can receive the messages, then they will be lost. Although this default behaviour is suitable for some applications, there are others where ensuring messages are successfully delivered at a higher rate would be helpful. One such scenario is the application in this paper: monitoring maritime vessels and fishing equipment in offshore environments characterised by intermittent or absent shore connectivity. To address this challenge, the Custodian project was initiated to develop a maritime monitoring solution with enhanced connectivity capabilities. Two additional features are especially welcome in this scenario. The most important feature is the transmission of messages created in offshore areas to end users who are offshore, regardless of the unavailability of the ground network server. An example would be fishermen who are offshore and wish to position their fishing equipment, also offshore, based on location data transmitted from nodes via LoRaWAN, even when both entities are far away from the mainland. The second aspect concerns the potential use of gateway-to-gateway communications, through gateways on various ships, to transmit messages to the coast. This setup enables fishing gear and fishing vessels to be monitored from the coast, even in the absence of a direct connection. The functional constraints of conventional commercial gateways necessitated the conceptualisation and implementation of C-Mesh, a novel relay architecture that extends LoRaWAN functionality beyond standard protocol implementations. The C-Mesh integrates with the Custodian ecosystem, alongside C-Beacon and C-Point devices, while maintaining transparent compatibility with standard LoRaWAN infrastructure components through protocol-compliant gateway emulation. Thus, compatibility with both commercially available nodes and gateways and those already in deployment is guaranteed. We provide a comprehensive description of C-Mesh, describing its hardware architecture (communications, power, and self-monitoring abilities) and data processing ability (filtering duplicate messages, security, and encryption). Sea trials carried out on board a commercial fishing vessel in Sesimbra, Portugal, proved C-Mesh to be effective. Location messages derived from fishing gear left at sea were received by an end user aboard the fishing vessel, independently of the network server on land. Additionally, field tests demonstrated that a single C-Mesh deployment functioning as a signal repeater on a vessel with an antenna elevation of $15m$ above sea level achieved a quantifiable coverage extension of 13 km (representing a 20% increase in effective transmission range), demonstrating the capacity of C-Mesh to increase LoRaWAN’s coverage. Full article

Worldwide, efforts are underway to produce hydrogen from water electrolysis, moving beyond the traditional reforming of fossil fuels. Renewable energy-powered hydrogen production is possible, but the use of grid power is also being considered for large-scale production. Additionally, some demonstration projects aim to utilize electrolysis systems as auxiliary service resources to enhance stability in the grid, given the rising share of renewable energy. This study proposes a method for connecting electrolysis facilities to the grid based on voltage stability analysis. The method involves analyzing the grid power parameters required by the electrolyzer and fault scenarios where low voltage could cause system shutdowns, as observed in actual case studies. By conducting voltage stability analysis simulations that incorporate these fault scenarios, the method identifies locations where the electrolyzer can operate stably within power grids. This approach aims to ensure the stable operation of electrolysis facilities even under conditions of renewable energy loss and low-voltage occurrences in the distribution system due to potential transmission system failures. Full article

To address the issues of cumulative plastic deformation and low-cycle fatigue cracking in ultra-high voltage (UHV) disc spring hydraulic circuit breakers under long-term cyclic high-pressure loads, which lead to internal structural changes and affect closing time stability and phase-controlled closing accuracy, this paper proposes a closing time prediction model considering the low-cycle fatigue of the operating mechanism. First, a Simulink-based simulation model of the 550 kV disc spring hydraulic operating mechanism transmission system was developed to analyze the influence of structural parameter variations on closing time under no-load conditions. Then, an objective function for judging action time stability was constructed, and the stability and influence weights of each structural parameter were calculated under different mechanical dispersion requirements using a combination of adaptive surrogate models and directional importance sampling. Results show that critical parameters such as working cylinder inner diameter, working cylinder stroke, main valve stroke, and working cylinder rod diameter significantly affect closing time, contributing approximately 25%, 20%, 15%, and 10%, respectively. Finally, a dynamic-weighted closing time prediction model was designed based on different phase-controlled accuracy requirements. Compared with no-load closing tests, under mechanical dispersion conditions of ±1 ms, ±1.5 ms, and ±2 ms, the optimized model reduced maximum deviations by 12.8%, 20.4%, and 23.3%, and narrowed fluctuation ranges by 37%, 38.3%, and 38.6%, respectively, significantly improving prediction accuracy. This work is supported by the Science and Technology Project of China Southern Power Grid (No.CGYKJXM20220346). Full article

This article presents a cost-effective, robust, and reliable system for EMG/MMG (electromyography/mechanomyography). Signals indicating muscle activity have numerous applications and are the subject of many studies. However, acquiring these signals is challenging. Commercial measurement systems are often expensive, limiting their accessibility. Therefore, the primary goal of this project was to develop a simple and affordable system for simultaneous EMG and MMG data acquisition, offering efficiency comparable to commercial systems. The system consists of eight EMG/MMG probes, 16-bit analog-to-digital converters with 16 channels, and a microprocessor unit. Despite its multiple components, the system remains simple and user-friendly. This paper describes the construction of the EMG/MMG probe and analyzes the intrinsic noise of the preamplifier, as well as electromagnetic interference, particularly power line noise. The elimination of power line noise was carried out in two stages: first, using techniques known for electromagnetic compatibility (EMC), and second, by implementing a digital filter in the microprocessor system. The proposed solution enables direct data collection from eight EMG/MMG probes using any computer equipped with a USB interface. This interface facilitates both data transmission and power supply, making EMG/MMG data acquisition straightforward and efficient. Full article

China has a large number of transmission lines laid in the mountains and forests and other regions, and these transmission lines enable national strategic projects such as the west-east power transmission project. However, the occurrence of mountain fires in the corresponding areas will seriously affect these transmission projects. At the same time, these mountain fires yield fewer image samples and complex backgrounds. Based on this, this paper proposes a transmission line hill fire detection model with YOLOv11 as the basic framework, named meta-learning attention YOLO (MA-YOLO). Firstly, the feature extraction module in it is replaced with a meta-feature extraction module, and the scale of the detection head is adjusted to detect smaller-sized hill fire targets. After this, the re-weighting module learns class-specific re-weighting vectors from the support set samples and uses them to recalibrate the mapping of meta-features. To enhance the model’s ability to learn target hill fire features from complex backgrounds, adaptive feature fusion (AFF) is integrated into the feature extraction process of YOLOv11 to improve the model’s feature fusion capabilities, filter out useless information in the features, and reduce the interference of complex backgrounds in detection. The experimental results show that the accuracy of MA-YOLO is improved by 10.8% in few-shot scenarios. MA-YOLO misses fewer hill fire targets in different scenarios and is less likely to be affected by complex backgrounds. Full article