Search Results (208)

This paper addresses the economic–environmental dispatch (EED) problem in DC power grids integrating thermoelectric and photovoltaic generation. A multi-objective optimization model is developed to minimize both fuel costs and CO₂ emissions while considering power balance, voltage constraints, generation limits, and thermal line capacities. To overcome the non-convexity introduced by quadratic voltage products in the power flow equations, a convex reformulation is proposed using second-order cone programming (SOCP) with auxiliary variables. This reformulation ensures global optimality and enhances computational efficiency. Two test systems are used for validation: a 6-node DC grid and an 11-node grid incorporating hourly photovoltaic generation. Comparative analyses show that the convex model achieves objective values with errors below 0.01% compared to the original non-convex formulation. For the 11-node system, the integration of photovoltaic generation led to a 24.34% reduction in operating costs (from USD 10.45 million to USD 7.91 million) and a 27.27% decrease in CO₂ emissions (from 9.14 million kg to 6.64 million kg) over a 24 h period. These results confirm the effectiveness of the proposed SOCP-based methodology and demonstrate the environmental and economic benefits of renewable integration in DC networks. Full article

Urban environments present substantial obstacles to GPS positioning accuracy, primarily due to multipath interference and limited satellite visibility. To address these challenges, we propose a novel weighting approach, referred to as the HK model, that enhances real-time GPS positioning performance by leveraging the variability of the signal-to-noise ratio (SNR), without requiring auxiliary sensors. Analysis of 24 h observational datasets collected across diverse environments, including open-sky (OS), city streets (CS), and urban canyons (UC), demonstrates that multipath-affected non-line-of-sight (NLOS) signals exhibit significantly greater SNR variability than direct line-of-sight (LOS) signals. The HK model classifies received signals based on the standard deviation of their SNR and assigns corresponding weights during position estimation. Comparative performance evaluation indicates that relative to existing weighting models, the HK model improves 3D positioning accuracy by up to 22.4 m in urban canyon scenarios, reducing horizontal RMSE from 13.0 m to 4.7 m and vertical RMSE from 19.5 m to 6.9 m. In city street environments, horizontal RMSE is reduced from 11.6 m to 3.8 m. Furthermore, a time-sequential analysis at the TEHE site confirms consistent improvements in vertical positioning accuracy across all 24-hourly datasets, and in terms of horizontal accuracy, in 22 out of 24 cases. These results demonstrate that the HK model substantially surpasses conventional SNR- or elevation-based weighting techniques, particularly under severe multipath conditions frequently encountered in dense urban settings. Full article

In response to the problems of wire detachment, insulation layer damage, and low construction efficiency in the traditional hand tied wire fixing method for 10 kV overhead lines, this paper develops a new type of 10 kV overhead line fixing device. The device mainly consists of a buckle type base and an infinitely adjustable gripper. The base is quickly installed through mechanical interlocking buckles, supplemented by auxiliary buckles to enhance stability, and the edge arc design improves operational safety. The clamp is equipped with a raised diamond-shaped structure to increase the friction coefficient and meshing strength. Combined with an arc-shaped inner surface and an infinitely adjustable screw, it can adapt to insulated wires of different diameters. The fixed device has a simple structure, easy installation, and advantages such as firm fixation and adaptability to overhead lines of different diameters. The fixed device of the overhead power line has been subjected to finite element mechanical simulation and electronic universal testing machine tension and pressure testing, and can meet the on-site mechanical performance, effectively improving the construction efficiency and safety of the overhead power line in the distribution network. Full article

To improve the ability of line-commutated converters (LCCs) to resist commutation failure (CF) when a fault occurs on the AC side, a novel sub-module-based LCC topology actively resistant to CF is proposed in this paper. The control strategy and the parameters of the proposed sub-module are elaborately designed. The proposed LCC topology can actively resist CF by providing an auxiliary commutation voltage to the AC side, and the sub-module is conducive to the rapid recovery of the thyristor’s forward blocking ability. Additionally, the initial capacitor voltage of the sub-module is designed optimally based on the commutation mechanism. The proposed LCC system can effectively improve the ability to resist CF by increasing the commutation margin of the LCC system. Furthermore, the capacitors are charged and discharged during fault time, so the capacitor voltages do not drop too low and, thus, are better at resisting CF. Matlab/Simulink simulation results verify that the proposed LCC quickens the commutation process, promotes commutation performance, and enhances the immunity of LCCs to CF. Full article

GaN flying-capacitor-multi-level (FCML) Totem-Pole power-factor-correctors (PFCs) have been demonstrated with very high density and efficiency in the literature. However, there is still a lack of detailed discussion about flying capacitor voltage precharge during the start-up for GaN FCML Totem-Pole PFCs. To enhance the reliability during start-up, we propose a multi-path and multi-step flying capacitor precharge method. In our proposed method, the bulky DC link capacitor is precharged through the path of the auxiliary line-frequency Si diode half-bridge and the body-diodes of the Si MOSFET half-bridge. The flying capacitors which have much smaller capacitances are precharged through the path of the GaN devices and the body-diodes of the Si half-bridge. The DC link capacitor is more than 100 times higher than the flying capacitor in this topology. Therefore, by splitting the total precharging current into two paths, the precharging current through the GaN devices is almost 100 times lower than that through the body-diodes of Si MOSFETs. As a result, this method protects expensive GaN devices from high inrush current and significantly improves the reliability of the GaN devices during the voltage precharge. Detailed operation principles and experimental verifications are presented in this paper. Full article

A localized freezing technique was proposed as an auxiliary method for retrofitting the lining of a vertical shaft. The influence of the freezing temperature, lining thickness, slot height, and slot duration on the evolution of the freezing wall in the clay layer was analyzed using a hydro-thermal numerical model. Under the baseline conditions (stratum temperature of 24 °C, shaft lining thickness of 2 m, and freezing temperature of −30 °C), the freezing wall behind the slotting zone was 0.74 m at 90 d, 1.89 m at 180 d, 2.78 m at 270 d, and 3.48 m at 360 d. The average growth rate of the freezing wall during one year was negatively linearly correlated with the freezing temperature and the shaft lining thickness, with change rates of −0.00033 m/(d∙°C) and −0.00262 m/(d∙m), respectively. Using the thickness of the freezing wall behind the slotting zone to reach 1.2 m as the slotting criterion, a freezing duration of 123 days is required under typical operational parameters. The evolution of the freezing wall was simulated for a slotting duration of 15 d with a slot height of 0.5–2.0 m and for a slot height of 1.5 m with a slotting duration of 5–20 d. The freezing walls did not melt in both schemes and expanded outward. The research findings are significant for improving freezing methods for shaft linings. Full article

This paper addresses the challenge of restoring electrical service in distribution systems (DS) under contingency scenarios using a genetic algorithm (GA) implemented in MATLAB. The proposed methodology seeks to maximize restored load, considering operational constraints such as line loadability, voltage limits, and radial topology preservation. It is evaluated with simulations on the IEEE 34-bus test system under four contingency scenarios that consider the disconnection of specific branches. The algorithm’s ability to restore service is demonstrated by identifying optimal auxiliary line reconnections. The method maximizes restored load, achieving between 97% and 99% load reconnection, with an average of 98.8% across the four cases analyzed. Bus voltages remain above 0.95 pu and below the upper limit. Furthermore, test feeder results demonstrate that line loadability is mostly below 60% of the post-reconfiguration loadability. Full article

Power line detection (PLD) is a crucial task in the electric power industry where accurate PLD forms the foundation for achieving automated inspections. However, recent top-performing power line detection methods tend to generate thick and noisy edge lines, adding to the difficulties of subsequent tasks. In this work, we propose a multi-scale feature-based PLD method named LUM-Net to allow for the detection of power lines in a crisp and precise way. The algorithm utilizes EfficientNetV1 as the backbone network, ensuring effective feature extraction across various scales. We developed a Coordinated Convolutional Block Attention Module (CoCBAM) to focus on critical features by emphasizing both channel-wise and spatial information, thereby refining the power lines and reducing noise. Furthermore, we constructed the Bi-Large Kernel Convolutional Block (BiLKB) as the decoder, leveraging large kernel convolutions and spatial selection mechanisms to capture more contextual information, supplemented by auxiliary small kernels to refine the extracted feature information. By integrating these advanced components into a top-down dense connection mechanism, our method achieves effective, multi-scale information interaction, significantly improving the overall performance. The experimental results show that our method can predict crisp power line maps and achieve state-of-the-art performance on the PLDU dataset (ODS = 0.969) and PLDM dataset (ODS = 0.943). Full article

Glide-symmetric double-corrugated parallel-plate waveguides (GS-DCPPWs) have essential technical properties such as an electromagnetic bandgap, lower dispersion, and the ability to control the equivalent refractive index. For this reason, a fast and simple analysis and design of GS-DCPPW structures have great importance to improve related microwave systems. This paper introduces a novel design methodology based on the auxiliary functions of generalized scattering matrix (AFGSM) for the dimensional synthesis of GS-DCPPWs. We test the applicability of the AFGSM method on a variety of numerical examples to determine the passband/stopband regions of single and GS-DCPPWs before applying the design procedure. Certain design specifications are chosen, and unit cell dimensions are constructed in accordance with the proposed design technique. Three design scenarios are considered to assess the success of how well the design criteria can be met with the proposed method. The designed unit cells have been periodically connected in a various finite numbers to create periodic filters as a test application for adjusting the electromagnetic bandgap. The success of the periodic GS-DCPPW filters obtained with the proposed design strategy in meeting the specified design requirements has been tested using full-wave electromagnetic simulators (CST Microwave Studio and HFSS). The results indicate that the combined use of the equivalent transmission line circuit and the root-finding routine provided by the proposed method facilitates rapid, efficient, versatile, and approximate designs for corrugated parallel-plate waveguides. Moreover, the design methodology provides the viability of developing a minimal unit cell and a compact periodic filter performance with respect to the literature counterparts. Full article

Transformer operations are susceptible to both internal and external faults. This study primarily employed software to construct a power system simulation model featuring a step-down transformer. The simulation model comprised three single-phase transformers with ten tap positions at the secondary coil to analyze internal faults. Additionally, ten fault positions between the power transformer and the load were considered for external fault analysis. The protection scheme incorporated percentage differential protection for both the power transformer and the transmission line, aiming to explore fault characteristics. To mitigate the protection device’s sensitivity issues, the scale-dependent intrinsic entropy method was utilized as a decision support system to minimize power system protection misoperations. The results indicated the effectiveness and practicality of the auxiliary method through comprehensive failure analysis. Full article

Utilizing asymmetric Doherty technology, this paper designs a high-efficiency radio frequency (RF) power amplifier (PA) for 5G base station applications. To improve the performance of PA and narrow the gap between simulations and practices, we use compatibility methods to design the circuit, which keeps the layout dynamically adjustable. By incorporating redundant U-shaped microstrip lines, the impedance matching network can be dynamically fine-tuned during debugging based on real-time hardware conditions. Furthermore, independent debugging paths for both main and auxiliary amplifiers are designed to enable the multi-stage debugging strategy. Performing separate debugging for each branch first, followed by combined debugging ensures both amplifiers achieve optimal operation states. The proposed strategy improves debugging efficiency while achieving precise parameter optimization. To verify the feasibility of the scheme proposed in this paper, we use CGHV40030F transistors to design a Doherty PA worked at 3.5 GHz and complete the hardware implementation and tests. Simulations and practice results prove that the architecture of asymmetric Doherty increases the back-off efficiency, and the compatibility design can make debugging easy and align the practice results closely with the simulations. We observe the saturation drain efficiency of 73.5% and the back-off efficiency of 47.5% from measurements, which confirms the effectiveness of the proposed compatibility design approach. Full article

Industrial process heat production is critical to achieving sustainability in our society. Avoiding fossil fuels and reducing electricity consumption for heat production are critical aspects of creating sustainable industries. Exploiting waste heat streams by upgrading them into useful high-temperature heat is an interesting idea for reducing the CO₂ footprint industrial processes. In line with this, the present study’s main objective is to investigate a novel thermochemical heat upgrade system based on the SrBr₂/H₂O working pair for the petrochemical industry, which is practically driven only by low-temperature waste heat streams. This innovative system, which exploits a waste heat stream of 200 °C and upgrades it to 250 °C to make it suitable for industry utilization, achieves a nominal coefficient of performance of 0.605. The examined system is compared with three other alternatives, including a natural gas boiler with 86% efficiency, a hybrid solar thermal unit with an auxiliary natural gas boiler, and a high-temperature heat pump with a coefficient of performance of two. The nominal industrial heat production is 2.2 MW for the thermochemical heat upgrade system. The dynamic investigation is conducted under the climate conditions of Denmark and Greece. The high-temperature heat pump’s annual electricity consumption is 6.94 GWh. In contrast, the annual heat consumed by the natural gas boiler is 16.12 GWh, without integrating the solar thermal unit. For the hybrid system, the maximum daily contribution of the solar thermal system is 87% for the climate conditions of Denmark, and the annual useful heat generated by the concentrating solar system is 1.30 GWh for the Danish climate conditions and 2.82 GWh for the Greek climate conditions. Full article

In coal chemical industries, the optimal allocation of gas and steam is crucial for enhancing production efficiency and maximizing economic returns. This paper proposes an optimal scheduling method using operating zone models and entropy weights for an energy system in a gas-to-methanol process. The first step is to develop mechanistic models for the main facilities in methanol production, namely desulfurization, air separation, syngas compressors, and steam boilers. A genetic algorithm is employed to estimate the unknown parameters of the models. These models are grounded in physical mechanisms such as energy conservation, mass conservation, and thermodynamic laws. A multi-objective optimization problem is formulated, with the objectives of minimizing gas loss, steam loss, and operating costs. The required operating constraints include equipment capacities, energy balance, and energy coupling relationships. The entropy weights are then employed to convert this problem into a single-objective optimization problem. The second step is to solve the optimization problem based on an operating zone model, which describes a high-dimensional geometric space consisting of all steady-state data points that satisfy the operation constraints. By projecting the operating zone model on the decision variable plane, an optimal scheduling solution is obtained in a visual manner with contour lines and auxiliary lines. Case studies based on Aspen Hysys are used to support and validate the effectiveness of the proposed method. Full article

The classification of transmission tower bolt images faces challenges such as class imbalance, sample scarcity, and the low pixel proportion of pins. Traditional classification methods exhibit poor performance in identifying key categories with small proportions, fail to leverage the correlation between transmission line fittings and bolts, and suffer from severe false positive issues. This study proposes a novel approach that dynamically integrates two sampling strategies to address the class imbalance problem while incorporating contrastive learning and category labels to enhance the discrimination of easily confused samples. Additionally, an auxiliary branch discrimination mechanism effectively exploits the correlation between fittings and bolts and, combined with a threshold-based decision process, significantly reduces the false positive rate (by 3.74%). The experimental results demonstrate that, compared to the baseline SimCLR framework with ResNet18, the proposed method improves accuracy (Acc) by 10.22%, reduces the false alarm rate by 5%, and significantly enhances classification reliability in transmission line inspections, thereby mitigating unnecessary human resource consumption. Full article

Nowadays, portrait drawing has become increasingly popular as a means of developing artistic skills and nurturing emotional expression. However, it is challenging for novices to start learning it, as they usually lack a solid grasp of proportions and structural foundations of the five senses. To address this problem, we have studied Portrait Drawing Learning Assistant System (PDLAS) for guiding novices by providing auxiliary lines of facial features, generated by utilizing OpenPose and OpenCV libraries. For PDLAS, we have also presented the exactness assessment method to evaluate drawing accuracy using the Normalized Cross-Correlation (NCC) algorithm. It calculates the similarity score between the drawing result and the initial portrait photo. Unfortunately, the current method does not assess the hair drawing, although it occupies a large part of a portrait and often determines its quality. In this paper, we present a hair drawing evaluation algorithm for the exactness assessment method to offer comprehensive feedback to users in PDLAS. To emphasize hair lines, this algorithm extracts the texture of the hair region by computing the eigenvalues and eigenvectors of the hair image. For evaluations, we applied the proposal to drawing results by seven students from Okayama University, Japan and confirmed the validity. In addition, we observed the NCC score improvement in PDLAS by modifying the face parts with low similarity scores from the exactness assessment method. Full article