Search Results (2,904)

With sub-millimeter deformation capture capability, InSAR technology has become an important tool for surface deformation monitoring. However, it is still limited by interferences like land subsidence and bridge deformation in long-term linear engineering monitoring, failing to accurately identify track deformation. Based on RadarSAT-2 and Sentinel-1A satellite data from 2013 to 2023, this study uses time-series InSAR technology (PS-InSAR) to accurately invert the track deformation information of the Beijing–Tianjin Intercity Railway (Beijing section) in the past decade. Key findings demonstrate (1) rigorous groundwater policies (extraction bans and artificial recharge) drove up to 48% regional subsidence mitigation in Chaoyang–Tongzhou, with synchronous track deformation exhibiting 0.6‰ spatial gradient; (2) critical differential subsidence identified at DK11–DK23, where maximum annual settlement decreased from 110 to 49.7 mm; (3) XGBoost-SHAP modeling revealed dynamic driver shifts: confined aquifer depletion dominated in 2015 (>60%), transitioned to delayed consolidation in 2018 (45%), and culminated in phreatic recovery–compressible layer coupling by 2022 (55%). External factors (tectonic/urban loads) played secondary roles. The rise in groundwater levels induces soil dilatancy, while the residual deformation in cohesive soils—exhibiting hysteresis relative to groundwater fluctuations—manifests as surface subsidence deceleration rather than rebound. This study provides a scientific basis for in-depth understanding of the differential subsidence mechanism along high-speed railways and disaster prevention and control. Full article

Partial shading condition (PSC) for photovoltaic (PV) arrays complicates the operation of PV systems at peak power due to the existence of multiple peak points on the power–voltage (P–V) characteristic curve. Identifying the global peak among multiple peaks presents challenges, as the system may become trapped at a local peak, potentially resulting in significant power loss. Power generation is reduced, and hot-spot issues might arise, which can cause shaded modules to fail, under the partly shaded case. In this paper, instead of focusing on local peaks, several effective, precise, and dependable maximum power point tracker (MPPT) systems monitor the global peak using a fuzzy logic controller. The suggested method can monitor the total of all PV array peaks using an interleaved boost converter DC/DC (IBC), not only the global peaks. A DC/DC class boost converter (CBC), the current gold standard for traditional control methods, is pitted against the suggested converter. Four PSC-PV systems employ three-phase inverters to connect their converters to the power grid. Full article

This paper proposes a Hybrid Adaptive Learning-Based Control (HALC) algorithm for voltage regulation in grid-forming inverters (GFIs), addressing the challenges posed by voltage sags and swells. The HALC algorithm integrates two key control strategies: Model Predictive Control (MPC) for short-term optimization, and reinforcement learning (RL) for long-term self-improvement for immediate response to grid disturbances. MPC is modeled to predict and adjust control actions based on short-term voltage fluctuations while RL continuously refines the inverter’s response by learning from historical grid conditions, enhancing overall system stability and resilience. The proposed multi-stage control framework is modeled based on a mathematical representation using a control feedback model with dynamic optimal control. To enhance voltage stability, Lyapunov is used to operate across different time scales: milliseconds for immediate response, seconds for short-term optimization, and minutes to hours for long-term learning. The HALC framework offers a scalable solution for dynamically improving voltage regulation, reducing power losses, and optimizing grid resilience over time. Simulation is conducted and the results are compared with other existing methods. Full article

Facing the pressure of green transformation, studying the relationship between government subsidies and the environmental performance of agricultural enterprises has significant theoretical value and practical significance for achieving sustainable agricultural development. Based on the micro data of 283 A-share listed agricultural enterprises in China from 2013 to 2023, this paper empirically analyzes the impact of government subsidies on the environmental performance of agricultural enterprises and its mechanism. The results show that there is an inverted U-shaped relationship between government subsidies and the environmental performance of agricultural enterprises, that is, when the government subsidies are within a certain scale, increasing government subsidies will have a positive impact on the environmental performance of agricultural enterprises. When the government subsidy reaches a certain scale, increasing the government subsidy will have a negative impact on the environmental performance of agricultural enterprises. External media attention (EMA) and internal control level (IC) play mediating roles in the impact of government subsidies on the environmental performance of agricultural enterprises. Heterogeneity analysis showed that for different types of subsidies, R&D subsidies and environmental protection subsidies had an inverted U-shaped impact on the environmental performance of agricultural enterprises. This study provides useful implications for improving methods of issuing government subsidies and enhancing the driving force of agricultural enterprises to carry out sustainable development actions. Full article

Precise time interval generation is a cornerstone of modern measurement, automation, and distributed control systems, particularly within Internet of Things (IoT) architectures. This paper presents the design, implementation, and evaluation of a low-cost and high-precision time interval generator based on Complementary Metal-Oxide Semiconductor (CMOS) logic counters (Integrated Circuit (IC) IC 7493 and IC 4017) and inverter-based crystal oscillators (IC 74LS04). The proposed system enables frequency division from 1 MHz down to 1 Hz through a cascade of binary and Johnson counters, enhanced with digitally controlled multiplexers for output signal selection. Unlike conventional timing systems relying on expensive Field-Programmable Gate Array (FPGA) or Global Navigation Satellite System (GNSS)-based synchronization, this approach offers a robust, locally controlled reference clock suitable for IoT nodes without network access. The hardware is integrated with Arduino and ESP32 microcontrollers via General-Purpose Input/Output (GPIO) level interfacing, supporting real-time timestamping, deterministic task execution, and microsecond-level synchronization. The system was validated through Python-based simulations incorporating Gaussian jitter models, as well as real-time experimental measurements using Arduino’s micros() function. Results demonstrated stable pulse generation with timing deviations consistently below ±3 µs across various frequency modes. A comparative analysis confirms the advantages of this CMOS-based timing solution over Real-Time Clock (RTC), Network Time Protocol (NTP), and Global Positioning System (GPS)-based methods in terms of local autonomy, cost, and integration simplicity. This work provides a practical and scalable time reference architecture for educational, industrial, and distributed applications, establishing a new bridge between classical digital circuit design and modern Internet of Things (IoT) timing requirements. Full article

This paper proposes the expressions for the motor airgap torque harmonics induced by a cascaded H-bridge inverter operating with failed cells. These variable frequency drive systems (VFDs), are widely used in oil and gas applications, where a torsional vibration evaluation is a critical challenge for field engineers. This paper proposes mathematical expressions that are crucial for an accurate torsional analysis during the design stage of VFDs, as required by international standards such as API 617, API 672, etc. By accurately reconstructing the electromagnetic torque from the stator voltages and currents in the (αβ0) reference frame, the obtained expressions enable the precise prediction of the exact locations of torque harmonics induced by the inverter under various real-world operating conditions, without the need for installed torque sensors. The neutral-shifted and peak-reduction fault-tolerant control techniques are commonly adopted under faulty operation of these VFDs. However, their effects on the pulsating torques harmonics in machine air-gap remain uncovered. This paper fulfils this gap by conducting a detailed evaluation of spectral characteristics of these fault-tolerant methods. The theoretical analyses are supported by MATLAB/Simulink 2024 based offline simulation and Typhoon based virtual real-time simulation results performed on a (4.16 kV and 7 MW) vector-controlled induction motor fed by a 7-level cascaded H-bridge inverter. According to the theoretical analyses- and simulation results, the Neutral-shifted and Peak-reduction approaches rebalance the motor input line-to-line voltages in the event of an inverter’s failed cells but, in contrast to the normal mode the carrier, all the triplen harmonics are no longer suppressed in the differential voltage and current spectra due to inequal magnitudes in the phase voltages. These additional current harmonics induce extra airgap torque components that can excite the lowly damped eigenmodes of the mechanical shaft found in the oil and gas applications and shut down the power conversion system due torsional vibrations. Full article

A self-diplexing, full-mode, substrate-integrated waveguide (SIW) rectangular cavity-backed antenna based on an inverted Z-shaped radiating slot with filtering characteristics is investigated in this work. The proposed design allows for individual control through the loading of four different slots, namely, a combination of horizontal and diagonal slots, called inverted Z-shaped slots. The two diagonal slots make 45° angles between them, and this flexible rotation gives the design flexibility regarding control of the bands. By combining these slots into a modified inverted Z-shaped slot, a SIW rectangular cavity is configured and energized with two separate 50 Ω microstrip feed lines to resonate at two different frequencies—11.63 GHz and 13.27 GHz—and TE₂₁₀ and TE₂₂₀ modes are obtained for X- and Ku-band wireless purposes. In an experimental analysis, reflection coefficients of S₁₁ < −10 dB were noted for both operating frequencies of 7.4% (11.23–12.09 GHz) and 3.0% (13.15–13.55 GHz), respectively. The average gain of the proposed antenna design in the two different operating conditions is 6.14 and 6.16 dBi, respectively. In addition, the proposed self-diplexing antenna attained high isolation, greater than 28 dB between both operating channels, and showed overall measured efficiency of 87.32%. Moreover, it features a single-layer structure, operates in dual bands, provides broadside linear polarization, and exhibits filtering capabilities. Full article

Surface soil moisture (SSM) is a critical land surface parameter affecting a wide variety of economically and environmentally important processes. Spaceborne microwave remote sensing has been extensively employed for monitoring SSM. Active microwave sensors offering high spatial resolution are typically utilized to capture dynamic fluctuations in soil moisture, albeit with low temporal resolution, whereas passive sensors are typically used to monitor the absolute values of large-scale soil moisture, but offer coarser spatial resolutions (~10 km). In this study, a passive microwave observation system using an X-band microwave radiometer mounted on a drone was established to obtain high-resolution (~1 m) radiative brightness temperature within the observation region. The region was a control experimental field established to validate the proposed approach. Additionally, machine learning models were employed to invert the soil moisture. Based on the site-based validation the trained inversion model performed well, with estimation accuracies of 0.74 and 2.47% in terms of the coefficient of determination and the root mean square error, respectively. This study introduces a methodology for generating high-spatial resolution and high-accuracy soil moisture maps in the context of precision agriculture at the field scale. Full article

With the large-scale integration of renewable energy through power electronic inverters,
modern power systems are gradually transitioning to low-inertia systems. Grid-forming
inverters are prone to power overshoot and frequency deviation when facing external
disturbances, threatening system stability. Existing methods face two main challenges in
dealing with complex disturbances: neural-network-based approaches have high computational
burdens and long response times, while traditional linear algorithms lack sufficient
precision in adjustment, leading to inadequate system response accuracy and stability. This
paper proposes an innovative coordinated adaptive control strategy for virtual inertia and
damping. The strategy utilizes a Radial Basis Function neural network for the adaptive
regulation of virtual inertia, while the damping coefficient is adjusted using a linear algorithm.
This approach provides refined inertia regulation while maintaining computational
efficiency, optimizing the rate of change in frequency and frequency deviation. Simulation
results demonstrate that the proposed control strategy significantly outperforms traditional
methods in improving system performance. In the active power reference variation
scenario, frequency overshoot is reduced by 65.4%, active power overshoot decreases by
66.7%, and the system recovery time is shortened. In the load variation scenario, frequency
overshoot is reduced by approximately 3.6%, and the maximum frequency deviation is
reduced by approximately 26.9%. In the composite disturbance scenario, the frequency
peak is reduced by approximately 0.1 Hz, the maximum frequency deviation decreases by
35%, and the power response improves by 23.3%. These results indicate that the proposed
method offers significant advantages in enhancing system dynamic response, frequency
stability, and power overshoot suppression, demonstrating its substantial potential for
practical applications. Full article

When faults occur in transmission lines of grid-forming PV systems, the LVRT control and virtual impedance function cause the fault characteristics of grid-forming inverters to differ significantly from those of synchronous generators, which deteriorates the performance of existing protection schemes. To address this issue, this paper analyzes the fault characteristics of PV transmission lines under grid-forming control objectives and the adaptability of traditional current differential protection. Subsequently, a novel pilot protection based on the Jensen–Shannon distance is proposed for transmission line of grid-forming PV systems. Initially, the post-fault current samples are modeled as discrete probability distributions. The Jensen–Shannon distance algorithm quantifies the similarity between the distributions on both line ends. Based on the calculated distance results, internal and external faults are distinguished, optimizing the performance of traditional waveform-similarity-based pilot protection. Simulation results verify that the proposed protection reliably identifies internal and external faults on the protected line. It demonstrates satisfactory performance across different fault resistances and fault types, and exhibits strong noise immunity and synchronization error tolerance. In addition, the proposed pilot protection is compared with the existing waveform-similarity-based protection schemes. Full article

The growing need for high-efficiency and reliable propulsion systems in naval applications, particularly within the evolving landscape of submarine warfare, has led to an increased interest in multiphase Permanent Magnet AC motors. This study presents a modelling and simulation approach for a 3MW, seventeen-phase Permanent Magnet AC motor designed for submarine propulsion, integrating an AI-based drive control system. Despite the advantages of multiphase motors, such as higher power density and enhanced fault tolerance, significant challenges remain in achieving precise torque and variable speed, especially for externally mounted motors operating under deep-sea conditions. Existing control strategies often struggle with the inherent nonlinearities, unmodelled dynamics, and extreme environmental variations (e.g., pressure, temperature affecting oil viscosity and motor parameters) characteristic of such demanding deep-sea applications, leading to suboptimal performance and compromised reliability. Addressing this gap, this research investigates advanced control methodologies to enhance the performance of such motors. A MATLAB/Simulink framework was developed to model the motor, whose drive system leverages an AI-optimised dual fuzzy-PID controller refined using the Harmony Search Algorithm. Additionally, a combination of Indirect Field-Oriented Control (IFOC) and Space Vector PWM strategies are implemented to optimise inverter switching sequences for precise output modulation. Simulation results demonstrate significant improvements in torque response and control accuracy, validating the efficacy of the proposed system. The results highlight the role of AI-based propulsion systems in revolutionising submarine manoeuvrability and energy efficiency. In particular, during a test case involving a speed transition from 75 RPM to 900 RPM, the proposed AI-based controller achieves a near-zero overshoot compared to an initial control scheme that exhibits 75.89% overshoot. Full article

This paper presents a microcontroller-based technique for accurately measuring resistive sensors over a wide dynamic range using an adaptive constant current source. Unlike conventional voltage dividers or fixed-current methods—often limited by reduced resolution and saturation when sensor resistance varies across several decades—the proposed system dynamically adjusts the excitation current to maintain optimal Analog-to-Digital Converter (ADC) input conditions. The measurement circuit employs a fixed reference resistor and an inverting amplifier configuration, where the excitation current is generated by one or more pulse-width modulated (PWM) signals filtered through low-pass RC networks. A microcontroller selects the appropriate PWM channel to ensure that the output voltage remains within the ADC’s linear range. To support multiple sensors, an analog switch enables sequential measurements using the same dual-PWM current source. The full experimental implementation uses four op-amps to support modularity, buffering, and dual-range operation. Experimental results show accurate measurement of resistances from 1 kΩ to 100 kΩ, with maximum relative errors of 0.15% in the 1–10 kΩ range and 0.33% in the 10–100 kΩ range. The method provides a low-cost, scalable, and digitally controlled solution suitable for embedded resistive sensing applications without the need for high-resolution ADCs or programmable gain amplifiers. Full article

Grid-forming (GFM) inverters have recently seen wider adoption in microgrids and inverter-based-resource (IBR)-penetrated grids, and are primarily used to establish grid voltage under a wide array of conditions. In the existing literature, GFM control is almost exclusively applied using voltage-source inverters (VSIs). However, due to the inherent limitations of available semiconductor devices’ current ratings, inverter-side current must be limited in VSIs, particularly during grid-fault conditions. These limitations complicate the real-world application of GFM functionality in VSIs, and complex control methodologies and tuning parameters are required as a result. In the following study, GFM control is instead applied to a buck-type current-source inverter (CSI) using a combination of linear droop-control and finite-control-set (FCS) mode-predictive control (MPC) that will be referred to herein as hybrid model-predictive control (HMPC). The resulting inverter features a simple topology, inherent current limiting capabilities, and a relatively simple and intuitive control structure. Verification was performed on a 1MVA/630V system via MATLAB/Simulink, and the simulation results demonstrate strong performance in voltage establishment, power regulation, and low-voltage ride through under-grid-fault conditions, highlighting its potential as a competent alternative to VSIs in GFM applications, and lacking the inherent limitations and/or complexity of existing GFM control methodologies. Full article

This paper presents an annual, real-world evaluation of the performance and economics of a residential photovoltaic (PV) system coupled with a battery energy storage system (BESS) in southern Poland. The system, monitored with 5 min resolution, operated under time-of-use (TOU) electricity tariffs. Seasonal variation was significant; self-sufficiency exceeded 90% in summer, while winter conditions increased grid dependency. The hybrid system reduced electricity costs by over EUR 1400 annually, with battery operation optimized for high-tariff periods. Comparative analysis of three configurations—grid-only, PV-only, and PV + BESS—demonstrated the economic advantage of the integrated solution, with the shortest payback period (9.0 years) achieved with financial support. However, grid voltage instability during high PV production led to inverter shutdowns, highlighting limitations in the infrastructure. This study emphasizes the importance of tariff strategies, environmental conditions, and voltage control when designing residential PV-BESS systems. Full article

High penetration of photovoltaic (PV) generation presents new challenges for voltage regulation in distribution networks (DNs), primarily due to output intermittency and constrained reactive power capabilities. This paper introduces a distributed voltage control method leveraging reactive power compensation from PV inverters. Instead of relying on centralized computation, the proposed method allows each inverter to make local decisions using real-time voltage measurements and delayed communication with neighboring PV nodes. To account for practical asynchronous communication and feedback delay, a Distributed Online Primal–Dual Push–Sum (DOPP) algorithm that integrates a fixed-step delay model into the push–sum coordination framework is developed. Through extensive case studies on a modified IEEE 123-bus system, it has been demonstrated that the proposed method maintains robust performance under both static and dynamic scenarios, even in the presence of fixed feedback delays. Specifically, in static scenarios, the proposed strategy rapidly eliminates voltage violations within 50–100 iterations, effectively regulating all nodal voltages into the acceptable range of [0.95, 1.05] p.u. even under feedback delays with a delay step of 10. In dynamic scenarios, the proposed strategy ensures 100% voltage compliance across all nodes, demonstrating superior voltage regulation and reactive power coordination performance over conventional droop and incremental control approaches. Full article