Search Results (108)

The large-scale utilization of wind and solar energy is crucial for achieving carbon neutrality targets. However, as extensive wind and solar power generation is integrated via power electronic devices, the inertia level of power systems continues to decline. This leads to a significant reduction in the system’s frequency regulation capability, posing a serious threat to frequency stability. Optimizing the system is an essential measure to ensure its safe and stable operation. Traditional optimization approaches, which separately optimize transmission and distribution systems, may fail to adequately account for the variability and uncertainty of renewable energy sources, as well as the impact of inertia changes on system stability. Therefore, this paper proposes a two-layer optimization method aimed at simultaneously optimizing the operation of transmission and distribution systems while satisfying minimum inertia constraints. The upper-layer model comprehensively optimizes the operational costs of wind, solar, and thermal power systems under the minimum inertia requirement constraint. It considers the operational costs of energy storage, virtual inertia costs, and renewable energy curtailment costs to determine the total thermal power generation, energy storage charge/discharge power, and the proportion of renewable energy grid connection. The lower-layer model optimizes the spatiotemporal distribution of energy storage units within the distribution network, aiming to minimize total network losses and further reduce system operational costs. Through simulation analysis and computational verification using typical daily scenarios, this model enhances the disturbance resilience of the transmission network layer while reducing power losses in the distribution network layer. Building upon this optimization strategy, the model employs multi-scenario stochastic optimization to simulate the variability of wind, solar, and load, addressing uncertainties and correlations within the system. Case studies demonstrate that the proposed model not only effectively increases the integration rate of new energy sources but also enables timely responses to real-time system demands and fluctuations. Full article

In large-scale warehouses, mobile robots often face energy shortages during inspection tasks, necessitating multiple charging points. Considering battery limits and multiple charging points makes path planning challenging. This paper presents a two-level solution: (i) local path planning via improved B-RRT* (adaptive Gaussian sampling + dynamic goal bias) to build a path-cost matrix, and (ii) global inspection and charging scheduling under multi-charging-point constraints. We evaluate planning time, total path length (as an energy proxy), and the number of sampling points. Experimental results demonstrate that the improved B-RRT* algorithm achieves an average reduction of 10–15% in path length, 20–30% in computation time, and 15–40% in the number of sampling points compared to the initial B-RRT* and RRT* algorithms across various warehouse environments. For global planning with up to 60 inspection targets and 3–5 charging points, a feasible charging schedule is obtained within 150–360 s on a standard desktop (Ryzen 7 5800H, 16 GB RAM), demonstrating strong practicality and scalability. Full article

Research on extreme environmental exploration using unmanned robots has recently attracted significant attention. In particular, unmanned robot exploration in vast areas such as Antarctica requires a system capable of remotely monitoring and controlling multiple robots. This paper proposes an integrated control system designed to monitor, control, and assign exploration tasks to multiple robots operating in extreme environments. This system utilizes GPS-based collaboration to support specific tasks, such as crevasse exploration and automatic battery charging, in Antarctic target areas. The system’s user interface (UI) is designed for efficiency and integrates elements such as remote control and mission execution commands tailored to the Antarctic environment. The proposed system was implemented using three robot platforms, and through performance evaluation tests in Antarctica, it achieved a cumulative driving distance of over 500 km and over 200 h of operation for over a month. The successful execution of simultaneous crevasse exploration by three robots highlights the system’s capability for coordinated multi-robot operations in extreme environments. Full article

Lung cancer is the leading cause of cancer mortality worldwide, with a poor prognosis driven by late diagnosis, systemic toxicity of existing therapies, and rapid development of multidrug resistance (MDR) to agents such as paclitaxel and cisplatin. MDR arises through multiple mechanisms, including overexpression of efflux transporters, alterations in apoptotic pathways, and tumour microenvironment-mediated resistance. The application of nanotechnology offers a potential solution to the aforementioned challenges by facilitating the enhancement of drug solubility, stability, bioavailability, and tumour-specific delivery. Additionally, it facilitates the co-loading of agents, thereby enabling the attainment of synergistic effects. Halloysite nanotubes (HNTs) are naturally occurring aluminosilicate nanocarriers with unique dual-surface chemistry, allowing hydrophobic drug encapsulation in the positively charged lumen and functionalisation of the negatively charged outer surface with targeting ligands or MDR modulators. This architecture supports dual-delivery strategies, enabling simultaneous administration of phytocannabinoids and chemotherapeutics or efflux pump inhibitors to enhance intracellular retention and cytotoxicity in resistant tumour cells. HNTs offer additional advantages over conventional nanocarriers, including mechanical and chemical stability and low production cost. Phytocannabinoids such as cannabidiol (CBD) and cannabigerol (CBG) show multitarget anticancer activity in lung cancer models, including apoptosis induction, proliferation inhibition, and oxidative stress modulation. However, poor solubility, instability, and extensive first-pass metabolism have limited their clinical use. Encapsulation in HNTs can overcome these barriers, protect against degradation, and enable controlled, tumour-targeted release. This review examined the therapeutic potential of HNT-based phytocannabinoid delivery systems in the treatment of lung cancer, with an emphasis on improving therapeutic selectivity, which represents a promising direction for more effective and patient-friendly treatments for lung cancer. Full article

This review systematically summarizes recent advances in ultrasound–chemical catalytic synergistic technology for controlling harmful algae blooms, focusing on the multi-mechanism cooperation of catalysts, oxidants, and nanomaterials within sonocavitation systems. The technology enhances coupling efficiency between cavitation effects and radical oxidation while leveraging interfacial regulation capabilities of catalysts (e.g., charge adsorption, carrier migration) to selectively disrupt algae cell structures and efficiently degrade extracellular organic matter. Three key innovations are highlighted: (1) development of a multi-mechanism synergistic system that overcomes traditional technical limitations through moderate pre-oxidation strategies for precise algae control; (2) first systematic elucidation of the bridging role of sonoporation in ultrasound–chemical synergy; (3) decipherment of interface-targeted regulation mechanisms that enhance oxidation efficiency. Collectively, these advances establish an engineerable new paradigm characterized by high efficiency, operational stability, and minimized ecological risks. Full article

In recent years, the generation of circularly polarized attosecond pulses has garnered significant attention due to their potential applications in ultrafast spectroscopy and, notably, in chiral-sensitive molecular detection. The traditional methods for generating such pulses often involve complex laser configurations or specially engineered targets, limiting their experimental feasibility. In this study, we present a streamlined and effective approach to producing circularly polarized attosecond pulses by employing a linearly polarized laser field in conjunction with a stereosymmetric linear molecule, 1-butyne (C₄H₆). The generation of high-order harmonics by this molecular system reveals a distinct plateau in the perpendicular polarization component, which facilitates the generation of isolated attosecond pulses with circular polarization. Through a detailed analysis of the time-dependent charge density dynamics across atomic sites, we identify the atoms primarily responsible for the emission of circularly polarized harmonics in the plane orthogonal to the driving field. Moreover, we explore the role of multi-orbital contributions in shaping the polarization properties of the harmonic spectra. Our findings underscore the importance of molecular symmetry and the electronic structure in tailoring the harmonic polarization, and they demonstrate a viable pathway for using circularly polarized attosecond pulses to probe molecular chirality. This method offers a balance between simplicity and performance, opening new avenues for practical applications in chiral recognition and ultrafast stereochemical analysis. Full article

A scheme of load frequency control (LFC) is proposed based on the deep deterministic policy gradient (DDPG) and active disturbance rejection control (ADRC) for multi-region interconnected power systems considering the renewable energy sources (RESs) and energy storage (ES). The dynamic models of multi-region interconnected power systems are analyzed, which provides a basis for the subsequent RES access. Superconducting magnetic energy storage (SMES) and capacitor energy storage (CES) are adopted due to their rapid response capabilities and fast charge–discharge characteristics. To stabilize the frequency fluctuation, a first-order ADRC is designed, utilizing the anti-perturbation estimation capability of the first-order ADRC to achieve effective control. In addition, the system states are estimated using a linear expansion state observer. Based on the output of the observer, the appropriate feedback control law is selected. The DDPG-ADRC parameter optimization model is constructed to adaptively adjust the control parameters of ADRC based on the target frequency deviation and power deviation. The actor and critic networks are continuously updated according to the actual system response to ensure stable system operation. Finally, the experiment demonstrated that the proposed method outperforms traditional methods across all performance indicators, particularly excelling in reducing adjustment time (45.8% decrease) and overshoot (60% reduction). Full article

As an innovative plant protection method in precision agriculture, electrostatic spray technology can increase the droplet coverage area by over 30% coMpared to conventional spraying. This technology not only achieves higher droplet deposition density and coverage but also enables water and pesticide savings while reducing environmental pollution. This study, combining theoretical analysis with experimental validation, reveals the critical role of electrode material selection in induction-based electrostatic spray systems. Theoretical analysis indicates that the Fermi level and work function of electrode materials fundamentally determine charge transfer efficiency, while corrosion resistance emerges as a key parameter affecting system durability. To elucidate the effects of different electrode materials on droplet charging, a coMparative study was conducted on nickel, copper, and brass electrodes in both pristine and moderately corroded states based on the corrosion classification standard, using a targeted mesh-based charge-to-mass measurement device. The results demonstrated that the nickel electrode achieved a peak charge-to-mass ratio of 1.92 mC/kg at 10 kV, which was 8.5% and 11.6% higher than copper (1.77 mC/kg) and brass (1.72 mC/kg), respectively. After corrosion, nickel exhibited the smallest reduction in the charge-to-mass ratio (19.2%), significantly outperforming copper (40.2%) and brass (21.6%). Droplet size analysis using a Malvern Panalytical Spraytec spray particle analyzer (measurement range: 0.1–2000 µm) further confirmed the atomization advantages of nickel electrodes. The volume median diameter (Dv50) of droplets produced by nickel was 4.2–8 μm and 6.8–12.3 um smaller than those from copper and brass electrodes, respectively. After corrosion, nickel showed a smaller increase in droplet size spectrum inhomogeneity (24.5%), which was lower than copper (30.4%) and brass (25.8%), indicating superior droplet uniformity. By establishing a multi-factor predictive model for spray droplet size after electrode corrosion, this study quantifies the correlation between electrode characteristics and spray performance metrics. It provides a theoretical basis for designing weather-resistant electrostatic spray systems suitable for agricultural pesticide application scenarios involving prolonged exposure to corrosive chemicals. This work offers significant technical support for sustainable crop protection strategies. Full article

In this study, we propose a novel approach for dynamic micro-vibration measurement based on an interferometric system utilizing a fractional optical vortex (FOV) beam as the reference and a Gaussian beam as the measurement path. The reflected Gaussian beam encodes the vibration information of the target, which is extracted by analyzing the rotational behavior of the petal-like interference pattern formed through coaxial interference with the FOV beam. When the topological charge (TC) of the FOV beam is less than or equal to one, a single-petal structure is generated, significantly reducing the complexity of angular tracking compared to traditional multi-petals OAM-based methods. Moreover, using a Gaussian beam as the measurement path mitigates spatial distortions during propagation, enhancing the overall robustness and accuracy. We systematically investigate the effects of TC, CCD frame rate, and interference contrast on measurement performance. Experimental results demonstrate that the proposed method achieves high angular resolution with a minimum angle deviation of 18.2 nm under optimal TC conditions. The system exhibits strong tolerance to environmental disturbances, making it well-suited for applications requiring non-contact, nanometer-scale vibration sensing, such as structural health monitoring, precision metrology, and advanced optical diagnostics. Full article

This study pioneers the development of a synergistic Ag-doped molecularly imprinted TiO₂ photocatalyst (MIP-Ag-TiO₂) through a multi-strategy engineering approach, integrating molecular imprinting technology with plasmonic metal modification via a precisely optimized sol–gel protocol. Breaking from conventional non-selective photocatalysts, our material features an engineered surface architecture that combines selective molecular recognition sites with enhanced charge separation capabilities, specifically tailored for the targeted degradation of recalcitrant salicylic acid (SA) contaminants. Advanced characterization (XRD, EPR, FT-IR, TEM-EDS) reveals unprecedented structure–activity relationships, demonstrating how template molecule ratios (Ti:SA = 5:1) and calcination parameters (550 °C) collaboratively optimize both adsorption selectivity and quantum efficiency. The optimized MIP-Ag-TiO₂ achieves breakthrough performance metrics: 98.6% SA degradation efficiency at 1% Ag doping, coupled with a record selectivity coefficient R = 7.128. Mechanistic studies employing radical trapping experiments identify a dual •OH/O_2⁻-mediated degradation pathway enabled by the Ag-TiO₂ Schottky junction. This work establishes a paradigm-shifting “capture-and-destroy” photocatalytic system that simultaneously addresses the critical challenges of selectivity and quantum yield limitations in advanced oxidation processes, positioning molecularly imprinted plasmonic photocatalysts as next-generation smart materials for precision water purification. Full article

Wireless power transfer (WPT) systems are critical for enabling safe and efficient charging of inspection drones in flammable oilfield environments, yet existing solutions struggle with multi-target compatibility and reactive power losses. This study proposes a novel frequency-regulated LCC-S topology that achieves both constant current (CC) and constant voltage (CV) charging modes for heterogeneous drones using a single hardware configuration. By dynamically adjusting the operating frequency, the system minimizes the input impedance angle (θ < 10°) while maintaining load-independent CC and CV outputs, thereby reducing reactive power by 92% and ensuring spark-free operation in explosive atmospheres. Experimental validation with two distinct oilfield inspection drones demonstrates seamless mode transitions, zero-phase-angle (ZPA) resonance, and peak efficiencies of 92.57% and 91.12%, respectively. The universal design eliminates the need for complex alignment mechanisms, offering a scalable solution for multi-drone fleets in energy, agriculture, and disaster response applications. Full article

Against the backdrop of the steady advancement of the national rural revitalization strategy and the dual-carbon goals, the low-carbon transformation of rural energy systems is of critical importance. This study first proposes a comprehensive architecture for rural energy supply systems, incorporating four key dimensions: investment, system configuration, user demand, and policy support. Leveraging the abundant wind, solar, and biomass resources available in rural areas, a low-carbon optimization model for rural energy system operation is developed. The model accounts for diverse load characteristics and the integration of elevated water towers, which serve both energy storage and agricultural functions. The optimization framework targets the multi-energy demands of rural production and daily life—including electricity, heating, cooling, and gas—and incorporates the stochastic nature of wind and solar generation. To address renewable energy uncertainty, the Fisher optimal segmentation method is employed to extract representative scenarios. A representative rural region in China is used as the case study, and the system’s performance is evaluated across multiple scenarios using the Gurobi solver. The objective functions include maximizing clean energy benefits and minimizing carbon emissions. Within the system, flexible resources participate in demand response based on their specific response characteristics, thereby enhancing the overall decarbonization level. The energy storage aggregator improves renewable energy utilization and gains economic returns by charging and discharging surplus wind and solar power. The elevated water tower contributes to renewable energy absorption by storing and releasing water, while also supporting irrigation via a drip system. The simulation results demonstrate that the proposed clean energy system and its associated operational strategy significantly enhance the low-carbon performance of rural energy consumption while improving the economic efficiency of the energy system. Full article

The rapid electrification of transportation, driven by stringent decarbonization targets and supportive policies, poses significant challenges for distribution system operators (DSOs). When numerous electric vehicles (EVs) charge concurrently, local transformers risk overloading—a problem that current tariff-based strategies do not adequately address. This paper introduces an aggregator-based coordination mechanism that shifts EV charging from congested to underutilized periods using a rule-based scheduling algorithm. Unlike conventional methods that depend on complex real-time pricing signals or optimization-heavy solutions, the aggregator approach uses a simple yet effective “laxity” measure to prioritize charging flexibility. To assess technical and economic viability, a multi-agent simulation was developed to replicate residential user behavior and DSO constraints under the use of a 400 kVA low-voltage transformer. The results indicate that overloads are completely eliminated with minimal inconvenience to users, whose increased charging costs are offset by the aggregator at an annual total of under DKK 6000—significantly lower than the cost of infrastructure reinforcement. This study contributes by (i) quantifying the compensation needed to prevent large-scale overloads, (ii) presenting a replicable, computationally feasible, rule-based aggregator model for DSOs, and (iii) comparing aggregator solutions to costly transformer upgrades, underscoring the aggregator’s role as a viable tool for future distribution systems. Full article

In line with the strategic plan for emerging industries in China, renewable energy sources like wind power and photovoltaic power are experiencing vigorous growth, and the number of electric vehicles in use is on a continuous upward trend. Alongside the optimization of the distribution network structure and the extensive application of energy storage technology, the active distribution network has evolved into a more flexible and interactive “source–grid–load–storage” diversified structure. When electric vehicles are plugged into charging piles for charging and discharging, it inevitably exerts a significant impact on the control and operation of the power grid. Therefore, in the context of the extensive integration of electric vehicles, delving into the charging and discharging behaviors of electric vehicle clusters and integrating them into the optimization of the active distribution network holds great significance for ensuring the safe and economic operation of the power grid. This paper adopts the two-stage “constant-current and constant-voltage” charging mode, which has the least impact on battery life, and classifies the electric vehicle cluster into basic EV load and controllable EV load. The controllable EV load is regarded as a special “energy storage” resource, and a corresponding model is established to enable its participation in the coordinated control of the active distribution network. Based on the optimization and control of the output behaviors of gas turbines, flexible loads, energy storage, and electric vehicle clusters, this paper proposes a two-layer coordinated control model for the scheduling layer and network layer of the active distribution network and employs the improved multi-target beetle antennae search optimization algorithm (MTTA) in conjunction with the Cplex solver for solution. Through case analysis, the results demonstrate that the “source–grid–load–storage” coordinated control of the active distribution network can fully tap the potential of resources such as flexible loads on the “load” side, traditional energy storage, and controllable EV clusters; realize the economic operation of the active distribution network; reduce load and voltage fluctuations; and enhance power quality. Full article

Due to the excellent concealment and high mobility, multiple small spherical underwater robots are essential for near coast defending missions. The formation of multiple small spherical underwater robots is particularly effective for tasks such as patrolling, reconnaissance, surveillance, and capturing sensitive targets. Moreover, some tasks need higher flexibility and mobility, such as reconnaissance, surveillance, or target encirclement at fixed locations. For this purpose, this paper proposes a position-based formation mechanism which is easily deployed for multiple spherical robots. A position planning method during the formation process is designed. This method creatively integrates the virtual linkage strategy with an improved consensus algorithm and the artificial potential field (APF) method. The virtual linkage strategy is in charge of computing the global formation desired target positions for robots according to the predefined position of the virtual leader joint. The improved consensus algorithm and APF are responsible for planning the local desired positions between two formation desired target positions, which is able to prevent collisions and excessive communication distance between robots. In order to verify the effectiveness of the proposed formation mechanism, adequate simulations and experiments are conducted. Thereby, the proposed formation frame offers great potential for future practical marine operations of the underwater multi-small robot systems. Full article