Search Results (1,699)

This paper presents the design and fabrication of a wideband low-noise amplifier (LNA) covering C-band, using the 0.15 µm GaAs pHEMT process. To achieve both low noise performance and wide matching characteristics, a two-stage cascaded architecture is implemented. In the first stage, circular inductors and an inductive source degeneration technique are employed to minimize the noise figure (NF) while ensuring wideband input matching. Furthermore, an RC feedback structure is incorporated to effectively enhance the stability of the amplifier. The proposed LNA operates under a supply voltage of 3.3 V and a gate bias of 0.35 V, with a total DC power consumption of 69.3 mW. The fabricated MMIC occupies a total chip area of 1.98 mm², including the probing pads. Measurement results demonstrate that the LNA achieves an NF of 0.81–1.09 dB and a gain of over 20.1 dB in the frequency range of 3.3–8.0 GHz. The input and output return losses are maintained over 10 dB and 9.7 dB, respectively. Full article

Deep learning-powered Street View Imagery (SVI) analytics provides a critical mechanism for smart city perception within the framework of Sustainable Development Goal 11 (SDG 11), effectively bridging the gap left by traditional remote sensing in fine-grained street-level observation. Over the years, deep learning-based semantic segmentation of urban streetscapes has become the dominant paradigm. However, when scaling to megacity measurements, current research faces the dual bottlenecks of “computational redundancy” and the “geographical domain shift” caused by the blind application of pre-trained models based on Western datasets. To address these challenges, this study is the first to systematically quantify the performance trade-off between Multi-Task Learning (MTL) and Single-Task Learning (STL) in megacity scenarios. Using this as a baseline, we constructed and validated a “low-computation, high-robustness” framework for streetscape semantic perception and spatial measurement. Relying on an integrated ResNeXt101-FPN MTL architecture and an ultra-low-cost fine-tuning strategy to overcome geographical domain shift, we extracted and analyzed the spatial heterogeneity of five core semantic elements—vegetation, sky, building, road, and vehicle—across the road network within Beijing’s 5th Ring Road. The results indicate the following: (1) We explicitly defined the computation-accuracy trade-off of MTL and STL in megacity perception. While utilizing only 1/5 of the parameters of STL, the MTL framework achieved a 5.34-fold increase in inference speed with a negligible 0.1% loss in overall mean Intersection over Union (mIoU); however, a 27.13% decrease in boundary segmentation accuracy was observed. (2) We established a low-cost, localized correction paradigm to overcome domain shift. Utilizing a minimal annotation cost (only 200 local images) significantly improved cross-domain adaptability, boosting the overall mIoU by 8.92% and significantly mitigating the geographical domain shift problem. (3) Multi-dimensional measurement and spatial analysis revealed a significant spatial decoupling pattern in Beijing’s streetscapes. The visual proportion of vegetation exhibited a pronounced “north-high, south-low” spatial differentiation, whereas built environment elements (e.g., building and road) displayed a typical “center-periphery” concentric gradient. This objectively reflects the spatial inequality of urban street greenery resources and the monocentric development characteristics of the built environment. The proposed framework therefore serves as a low-cost, AI-driven computational paradigm for smart city perception in resource-constrained regions. Furthermore, the revealed spatial heterogeneity offers data-driven insights for formulating sustainable urban renewal policies aligned with SDG 11. Full article

Multiple-fault events can initiate overload propagation and cascading outages, resulting in severe load loss and reduced system resilience. Therefore, beyond conventional protection concepts based on the (n − 1) criterion, there is also a need to address multiple-fault events to minimize loss of load. This paper presents an optimized overload tripping scheme to mitigate cascading outages in high-voltage grids under multiple-fault conditions, where selected line switches or circuit breakers are opened in a controlled manner to isolate limited grid sections, minimize interrupted load, and prevent further overload propagation. The method combines inverse definite minimum time relay modeling with a heuristic graph-search algorithm implemented in pandapower to identify feasible switching actions that minimize load loss while preventing overload propagation. The approach is demonstrated on SimBench high-voltage urban and mixed benchmark grids under double-line fault scenarios. In the urban grid, the proposed scheme reduces the maximum load loss from 34.0% to 2.4%, while in the mixed grid, the reduction is from 50.3% to 5.2%. A SAIFI-inspired resilience proxy is introduced to quantify the reduction in customer/load interruptions, showing a resilience improvement factor of about 3.6 for cascading scenarios. In addition, thermal inertia analysis indicates that corrective switching must be completed within approximately 5 min to remain within line-temperature limits. The analysis is based on quasi-steady-state power-flow and relay simulations; transient stability effects are outside the scope of this study. The results demonstrate that the optimized overload tripping scheme is a promising adaptive protection strategy for improving grid resilience under severe contingency conditions. Full article

When a fault occurs in the power grid to which the Virtual Synchronous Generator (VSG) is connected, it leads to overcurrent phenomena, which threatens the safety of the inverter and easily results in device damage. Although existing direct current limiting unit (CLU) control strategies can restrict the fault current, the input active power command far exceeds the power output, causing the virtual rotor to continuously accelerate. This leads to power angle divergence and a subsequent loss of synchronization. To address the conflict between direct current-limiting control and system transient stability, this paper proposes a control strategy based on the Particle Swarm Optimization (PSO) algorithm to modify the active power command, building upon existing direct current-limiting VSG control. During grid faults, the output current is constrained to its maximum value, leading to a reduction in the system’s output power. By leveraging the PSO algorithm, the proposed strategy decreases the active power command to minimize the power mismatch between the command and the output. This maximizes the system’s transient stability by minimizing the rotor acceleration torque and effectively suppressing excessive power angle deviation. Meanwhile, the active power command reduction is introduced as a penalty term to maximize the active power output capability during the fault period. Simulation results demonstrate that, compared to VSG with only direct current-limiting control, the proposed strategy significantly enhances the transient stability and transmission efficiency of the VSG under long-term fault conditions across various grid voltage sag scenarios. Furthermore, it ensures a seamless transition from the fault state to normal operation during short-term faults. Full article

Optimal allocation of distributed generation (DG) and feeder reconfiguration are critical strategies for improving the operational efficiency and voltage stability of modern radial distribution networks under increasing penetration of renewable resources. However, the simultaneous optimization of DG placement, sizing, and network topology constitutes a highly nonlinear multi-objective problem subject to electrical, operational, and radiality constraints. Unlike existing studies that treat DG allocation and feeder reconfiguration as separate or weakly coupled problems, this work introduces a unified mixed-integer nonlinear optimization framework that captures their strong interdependency. In addition, a hybrid Big Bang–Big Crunch (HBB-BC) algorithm is proposed, combining stochastic contraction with adaptive learning mechanisms to improve convergence robustness in highly nonlinear search spaces. This contribution addresses the limitations of conventional metaheuristics in handling coupled topology–generation optimization problems and provides a scalable solution for modern active distribution networks. We propose a coordinated optimization framework for optimal DG placement and feeder reconfiguration aimed at minimizing real power losses while enhancing voltage stability and reducing both operational cost and environmental impact. The problem is formulated as a constrained multi-objective optimization model and solved using an improved hybrid Big Bang–Big Crunch metaheuristic algorithm which integrates exploration and exploitation mechanisms to achieve fast convergence and robust global search performance. The proposed method is validated on both IEEE 33-bus and IEEE 69-bus radial distribution systems under multiple operational scenarios. The results demonstrate that the coordinated optimization consistently achieves significant performance improvements across different network scales, confirming the robustness and scalability of the proposed framework. Full article

Picosecond laser drilling is characterized by a minimal heat-affected zone (HAZ) and superior surface quality, making it widely utilized for fabricating film-cooling holes in aeroengine turbine blades. However, maintaining consistent drilling quality remains a significant challenge. This study conducts picosecond laser trepanning drilling experiments on a GH4169 nickel-based superalloy to investigate the quality of inclined holes. Due to its excellent high-temperature resistance, creep resistance, and corrosion resistance, GH4169 is a primary material for turbine blades. A control variable method was employed to evaluate the effects of power ratio (60–95%), number of scanning passes (5–40), and defocus amount (−0.2 mm to 0.2 mm) on the quality of inclined holes with tilt angles of 7° and 15° and a sample thickness of 0.5 mm. Entrance diameter, exit diameter, and taper angle were utilized as the key quality indicators. The results indicate that due to the distribution of laser energy flux, both the geometric dimensions and taper angles of 15° inclined holes are significantly larger than those of 7° holes. As the power ratio increases, the entrance and exit diameters exhibit non-linear expansion; a “topographic stability window” is achieved at a 75% power ratio due to the equilibrium in energy coupling. An increase in the number of scanning passes leads to larger diameters; however, excessive scanning slows down the expansion of the exit diameter due to multiple reflection losses within the hole and the accumulation of slag, thereby intensifying taper evolution. The defocus amount exerts a bidirectional regulatory effect: positive defocusing increases the entrance diameter while decreasing the exit diameter, whereas negative defocusing facilitates the expansion of the exit. Optimal hole wall quality is observed at zero defocusing. This work provides data support for parameter optimization and the selection of inclination angles in subsequent laser machining of inclined holes. Full article

Full-waveform inversion (FWI) is a powerful interpretation method in geophysics for inferring high-resolution subsurface models by minimizing the difference between observed and simulated seismic data. In mineral exploration, FWI has shown particular promise for delineating complex ore bodies in hard-rock environments where conventional reflection seismic methods often fail. However, traditional FWI remains computationally expensive due to the iterative solution of forward and adjoint problems. The integration of deep learning, particularly the U-Net architecture, has recently emerged as a promising approach to address these computational challenges. Originally developed for biomedical image segmentation, U-Net employs a symmetric encoder–decoder structure with skip connections, enabling precise localization and efficient feature extraction from complex data. This paper proposes a modified dual-path architecture, termed DU-Net, specifically designed for the simultaneous detection and extraction of high-contrast velocity anomalies (representing potential ore bodies) and reconstruction of the background velocity model. The key innovation lies in parallel processing branches—one dedicated to anomaly segmentation and another to background reconstruction—combined with a specialized composite loss function, SeismoLoss, that independently supervises each component. This design allows the network to focus on the distinctive features of the anomaly while filtering out background complexity that typically degrades prediction quality in single-path approaches. We provide a detailed description of the DU-Net architecture and evaluate its performance on two synthetic datasets representing different styles of mineralization and host-rock complexity. Experimental results demonstrate that DU-Net achieves superior accuracy in localizing anomalous bodies and reconstructing background geology compared to the standard U-Net baseline, with a substantial reduction in boundary blurring artifacts. Full article

Addressing the challenges of topological design and the limitations of global optimization for large-scale photovoltaic (PV) plants in complex terrains, this paper proposes a topology optimization method based on mixed-integer linear programming (MILP). The innovation of the proposed method lies in its use of a MILP framework to integrate complex terrain modeling, quantification of construction difficulty, and coordinated configuration of conductor cross-sections into a single equivalent annual cost optimization model. First, equivalent mathematical models tailored to diverse environmental features—including flat, mountainous, and hilly terrains—are developed to enable accurate spatial identification. Second, aimed at minimizing the total equivalent annual cost (EAC), a MILP model is formulated. This model comprehensively incorporates physical construction difficulties and strict electrical constraints, such as active power flow balance, cable current-carrying capacity, and node voltage deviations. A high-performance solver is then utilized to achieve global optimization for radial topologies. Furthermore, the cross-sectional areas of the conductors are dynamically configured to compensate for power quality losses caused by path detours. Case studies demonstrate that the proposed method significantly reduces the EAC and enhances the overall economic benefits of PV plants while ensuring strict electrical safety across various complex environments. Full article

Cascaded H-bridge converters are the prevalent option for classic energy storage converters due to their excellent battery integration and current sharing capabilities. However, this scheme requires numerous IGBT switchings and exhibits high losses in low-voltage, high-power applications due to high current flowing through the batteries. Furthermore, the limited DC voltage regulation capability makes it difficult to obtain sufficient DC voltage for modulation when the battery is continuously discharging, resulting in shortened continuous discharge duration. To address these issues, this paper proposes a novel energy storage converter based on controllable DC buses. The proposed controllable DC bus consists of cascaded half-bridges and a bidirectional DC converter, where the former topology is designed to preserve voltage and current balancing between batteries, as well as boost the DC voltage—thereby reducing the current flowing through the batteries and minimizing losses. The latter topology is implemented to maintain DC bus voltage during battery discharge, thereby increasing the continuous operating time of the proposed energy storage converter. Moreover, the control and modulation of the proposed controllable DC bus have been optimized, and its effectiveness and performance are verified through simulation results. Full article

This work presents a high-efficiency and linear Ka-band power amplifier (PA) designed in a $0.13$ $\mathsf{\mu }$m depletion-mode GaAs pHEMT process, targeting 5G phased-array systems. To minimize passive losses, the output matching network employs an all-transmission-line architecture. Phase mismatches among output branches are compensated directly within the interstage and output matching networks via tailored distributed and capacitive components. Device-level reliability is proactively addressed by maintaining adequate voltage headroom under worst-case load mismatch, based on voltage standing wave ratio (VSWR) analysis. The amplifier achieves a peak small-signal gain of $15.8$ dB at 27 GHz. Under continuous-wave excitation at 27 GHz, it delivers $32.9$ dBm output power at the 1-dB compression point with $32.8$% power-added efficiency (PAE), reaching a peak saturated output of $33.2$ dBm and $35.9$% PAE. When driven by a 64-QAM signal with a 250 MHz symbol rate, the PA maintains an average output power of $26.3$ dBm and an average PAE of $12.2$%, with an rms EVM of $3.4$% and an SNR of $25.5$ dB. Full article

In this work, a Fabry–Perot (F–P) antenna based on metal integrated suspended lines (MISLs) at the K-band for microwave wireless power transmission (MWPT) is proposed. The antenna’s contribution lies in its adaptation of the MISL structure and its all-metal design, which achieves low loss, high gain, and high-power capability. The entire antenna structure is dielectric-free, further reducing apparent dielectric loss at high frequencies. Meanwhile, the radiation structure is surrounded by a metallic wall to minimize radiation loss. A metal partially reflective surface (PRS) on the top of the antenna, together with a metal ground plane, constitutes an air-filled resonant cavity. The reflection and transmission of electromagnetic waves in the PRS are effectively controlled to be in phase, thereby enhancing its gain by optimizing the PRS and resonant cavity dimensions. A simple slot antenna is employed as the primary source for the F–P resonant cavity. The antenna is processed layer by layer and then assembled to lower machining costs and complexity. Experimental results indicate that the proposed F–P antenna achieves an aperture efficiency over 60% and a measured peak gain of 18.4 dBi at 23.85 GHz with an aperture size of 2.86 λ₀ × 2.86 λ₀. Full article

The dual-inverter open-winding permanent magnet synchronous motor (OW-PMSM) drive system exhibits significant advantages for electric vehicles with dual energy sources, particularly in achieving coordinated energy management and efficient power allocation between the sources. Based on the dual-inverter OW-PMSM drive configuration, this paper proposes two stator current planning algorithms: one aims to minimize the electrical losses during motor operation and the other aims to maximize the power allocation range of the dual inverters, respectively. Building upon this, a geometric algorithm for stator voltage vector allocation is proposed to achieve smooth switching of the motor between the two algorithms. This enhances the tracking performance of the electromagnetic torque and d-axis current during motor operation, while ensuring that the motor operates within its steady-state range, thereby improving system stability. Finally, simulations and experiments are conducted on the proposed algorithm to verify its feasibility and advantages. Full article

This paper presents a structured planning framework for the coordinated integration of photovoltaic (PV) systems and capacitor banks (CBs) in radial distribution networks to improve steady-state voltage regulation and reduce active-power losses. The proposed methodology combines deterministic power-flow assessment, index-based candidate screening, and constrained joint placement and sizing using the Grey Wolf Optimizer (GWO) with an embedded CAPEX proxy. Compared with PV-only integration, the coordinated PV–CB strategy provides a more effective improvement in steady-state electrical performance, particularly in terms of slack-bus power factor and voltage regulation. In addition, relative to fixed coordinated PV–CB scenarios, the GWO-based formulation yields more balanced technical–economic solutions by improving power factor and voltage conditions while avoiding unnecessary overdimensioning of installed capacity. On the IEEE 15-bus system, the optimized configuration achieves a 45.9% reduction in active-power losses, improves the slack-bus power factor to 0.947, and reduces the average voltage deviation to 2.57%, with convergence reached in approximately 16 iterations. On the IEEE 34-bus system, the optimized solution yields a 49.8% loss reduction, increases the slack-bus power factor to 0.955, and reduces the average voltage deviation to 2.39%, with convergence reached in approximately 133 iterations. Using an energy price of 8.14 ctUSD/kWh, the corresponding annual loss–cost savings are approximately 19,975 USD and 78,475 USD for the IEEE 15- and 34-bus systems, respectively. The results demonstrate that the proposed GWO-based coordinated planning approach can achieve electrically effective and economically feasible solutions through the combined provision of local active-power injection and reactive-power compensation in radial distribution networks under steady-state operating conditions. Full article

This study presents a comprehensive investigation into the optimal deployment of Unified Power Flow Controllers (UPFCs) to enhance voltage stability and reduce power losses in the Sudanese national grid. With the increasing demand for electricity driven by population growth, urban expansion, and industrial development, modern power systems require advanced control strategies to ensure reliable and efficient operation. In this work, the Line Stability Index (Lmn) is employed as a key indicator to identify the most critical transmission lines prone to voltage instability. Based on this index, optimal locations for UPFC installation are determined. Furthermore, an Optimal Power Flow (OPF) framework is utilized to calculate the control parameters of the UPFC devices, aiming to minimize system losses while maintaining operational constraints. The proposed methodology is validated using a real large-scale network model of the Sudanese power system implemented in MATLAB (24b) and NEPLAN (v10) environments. The results demonstrate that installing seven UPFC devices leads to a significant improvement in voltage profiles, maintaining all bus voltages within ±5% of nominal values. Additionally, the system experiences a reduction in total active and reactive power losses by 6.96% and 0.74%, respectively. These findings highlight the effectiveness of UPFC-based control strategies in improving system stability, enhancing transmission efficiency, and supporting the integration of future energy resources. Full article

In recent years, pumps as turbines have been replacing pressure-regulating valves as a system for regulating pressure and reducing water losses in the water distribution network, as they combine leakage reduction with the production of hydroelectric power. However, when a pump as turbine is installed, it is necessary to implement real-time pressure control. This study proposes an innovative algorithm that combines the integral control with a feedforward control in order to minimize the time to reach the desired pressure under flow variation. The algorithm was tested through laboratory tests showing an effective optimization of real-time pressure control. Full article