Complementary Characteristics Research Articles

Construction of pumped storage power stations among cascade reservoirs to support the high-quality power supply of the hydro-wind-photovoltaic power generation system

Multi-energy complementary technology has become one of the core elements to promote the structural transformation of global energy and cope with climate change. Faced with the rapid growth of wind power and photovoltaic, the uncertainty of its power generation will increase further, and it is urgent to explore more types of flexible regulation power sources to compensate for them. The construction of pumped storage power stations among cascade reservoirs is a feasible way to expand the flexible resources of the multi-energy complementary clean energy base. However, this way makes the hydraulic and electrical connections of the upper and lower reservoirs more complicated, which brings more uncertainty to the power generation. Hence, to support the high-quality power supply, this research explores the complementary characteristics of the clean energy base building different types of pumped storage power stations, and recognizes the efficient operation intervals of the giant cascade reservoir. First, a multi-dimensional uncertainty evaluation system is proposed to elaborate on the typical output scenarios of wind power and photovoltaic in more detail. Next, based on different utilization principles of wind power and photovoltaic, the multi-energy complementary operation models of the hydropower-wind-PV hybrid system, the hydropower-wind-PV hybrid system including pump stations, and the hydropower-wind-PV hybrid system including reversible hydro units are established. Further, a multi-dimensional scenarios random combination method is applied to investigate the response relationship between the operation parameters of the key reservoir and the operation indicators of the clean energy base. Finally, these above methods have been practiced in the clean energy base in the upper Yellow River basin. The main results of the research are as follows: (1) when the power output of wind-PV plants is high, the absorption rates of wind power and photovoltaic increase by 36% and 12% respectively, in hydropower-wind-PV hybrid systems with reversible hydro units and with pump stations, compared to the hydropower-wind-PV hybrid system; (2) when the power output of wind-PV plants is high, the load loss rates of the transmission channel decrease by 28.57% and 14.28% respectively, in hydropower-wind-PV hybrid systems with reversible hydro units and with pump stations, compared to the hydropower-wind-PV hybrid system; (3) for the hydropower-wind-PV hybrid system including reversible hydro units, the comprehensive utilization flow of the key reservoir respectively maintain 500-800 m3/s and 1000-1200 m3/s in the max scenario and min scenario of wind power and photovoltaic, which is beneficial to the efficient absorption of new energy and high-quality power transmission; (4) for the hydropower-wind-PV hybrid system including pump stations, the comprehensive utilization flow of the key reservoir should respectively keep 500-750 m3/s and 950-1100 m3/s in the max scenario and min scenario of wind power and photovoltaic.

Establishment and Validation of Patient-Derived Non-Small Cell Lung Cancer Organoids as In Vitro Lung Cancer Models

Background: Recent advances in the personalized treatment of non-small cell lung cancer (NSCLC) require representative in vitro model systems that reflect tumor heterogeneity and maintain the characteristic genetic aberrations. We therefore aimed to establish patient-derived NSCLC organoids that offer a reliable platform for further investigations. Methods: NSCLC organoids were cultured between May 2020 and February 2022 from surgically resected NSCLC tissue specimens. After histological and immunohistochemical validation, genetic validation was performed by targeted next-generation sequencing of tissue and organoid specimens using the Oncomine Focus Assay (ThermoFisher Scientific). Results: From 37 resected NSCLC samples, 18 primary organoid cultures were successfully established and expanded during early passages. Upon histomorphological validation, organoids showed complementary characteristics when compared to the resected parental tumor, including adenocarcinoma, squamous cell carcinoma, mucoepidermoid carcinoma, and lung carcinoid differentiation. Among nine parental tumors, traceable genetic alterations were detected, and three corresponding organoids lines retained this mutational profile, including a KRAS p.Gly12Val mutation, KRAS p.Gly12Cys mutation, and RET-fusion. Conclusions: The establishment of primary NSCLC organoids from surgically resected tissue is feasible. Histological, immunohistochemical, and genetic validation is essential to identify representative NSCLC organoids that maintain the characteristics of the parental tumor. Overall, low establishment rates remain a challenge for broad clinical applications.

Optimizing the surface quality of electrochemical machined Ni-based single crystal superalloy via manipulation of phase and dendrite dissolution

The transpassive dissolution behaviors of Ni-based single crystal superalloy in 10 %NaCl, 10 %NaNO3, and mixed solution are investigated by using potentiodynamic polarization, scanning electron microscopy, energy dispersive X-ray spectroscopy, and X-ray photoelectron spectroscopy. The alloy exhibits opposite yet complementary dissolution characteristics in NaCl and NaNO3 solutions. The different responses of γ/γ′ phases to Cl− and NO3− contribute to the opposite dissolution behaviors of dendrites and interdendritic regions. The surface flatness is noticeably enhanced in mixed solution due to the synchronous dissolution of the γ/γ′ phases. Our work paves the way for obtaining high-quality surface in electrochemical machining of single crystal superalloys.

Optimal Design of Wind-Solar complementary power generation systems considering the maximum capacity of renewable energy

This paper proposes constructing a multi-energy complementary power generation system integrating hydropower, wind, and solar energy. Considering capacity configuration and optimization of the complementary power generation system, a dual-layer planning model is constructed. The outer layer aims to maximize the accessible scale of wind and solar energy, while the inner layer considers the matching degree between power output and grid load. The optimization uses a particle swarm algorithm to obtain wind and solar energy integration's optimal ratio and capacity configuration. The results indicate that a wind-solar ratio of around 1.25:1, with wind power installed capacity of 2350 MW and photovoltaic installed capacity of 1898 MW, results in maximum wind and solar installed capacity. Furthermore, installed capacity increases with increasing wind and solar curtailment rates and loss-of-load probabilities. When the loss-of-load probability is set to 3 %, the impact of wind and solar curtailment rates on the installed capacity ratio is relatively small. The complementary characteristics of wind and solar energy can be fully utilized, which better aligns with fluctuations in user loads, promoting the integration of wind and solar resources and ensuring the safe and stable operation of the system.

A novel online time calibration framework via double-stage EKF for visual-inertial odometry

Abstract There is an unavoidable time offset between the camera stream and the inertial measurement unit (IMU) data due to the sensor triggering and transmission delays, which will seriously affect the accuracy of visual-inertial odometry (VIO). A novel online time calibration framework via double-stage EKF for VIO is proposed in this paper. First, the first-stage complementary Kalman filter is constructed by adapting the complementary characteristics between the accelerometer and the gyroscope in the IMU, where the rotation result predicted by the gyroscope is corrected through the measurement of the accelerometer so that the IMU can output a more accurate initial pose. Second, the unknown time offset is added to the state vector of the VIO system. The estimated pose of IMU is used as the prediction information, and the reprojection error of multiple cameras on the same feature point is used as the constraint information. During the operation of the VIO system, the time offset is continuously calculated and superimposed on the IMU timestamp to obtain the data synchronized by the IMU and the camera. The Schur complement model is used to marginalize the camera state that carries less information in the system state, avoiding the loss of prior information between images, and improving the accuracy of camera pose estimation. Finally, the effectiveness of proposed algorithm is verified using the EuRoC dataset and the real experimental data.

A novel cross fusion model with fine-grained detail reconstruction for remote sensing image pan-sharpening

ABSTRACT Pan-sharpening aims to obtain high resolution multispectral (HRMS) images by integrating the information in the panchromatic and multispectral images. Existing pan-sharpening methods have demonstrated impressive sharpening performance. However, these methods inherently overlook the complementary characteristics and interaction between diverse source images, resulting in sharpened outcomes accompanied by distortion. To solve the above problems, we construct a novel cross fusion model with fine-grained detail reconstruction from the perspective of frequency-domain. The motivation of the model is twofold: (1) to reconstruct spatial detail representations from diverse source images, laying the foundation for the generation of fine details in the subsequent fused images; and (2) to enhance the interaction between diverse source features during the fusion process in order to attain high-fidelity fusion outcomes. Based on the theoretical model, we develop a frequency-spectral dual domain cross fusion network (CF2N) utilizing the deep learning technique. Consequently, the CF2N consist of two main stages, namely frequency-domain dominated detail reconstruction (FD2R) and frequency-spectral cross fusion (FSCF). Specifically, a more reasonable reconstruction of fine frequency details in HRMS can be achieved by performing adaptive weighted fusion of frequency details in the FD2R stage. Furthermore, the FSCF module, which seamlessly integrates frequency- and spectral-domain details in a highly interactive cross fusion manner. As a result, the CF2N possesses the capability to attain high frequency-spectral fidelity results with excellent interpretability. Extensive experiments show the superior performance of ours over state of the art, while maintaining high efficiency. All implementations of this work will be published at our website.

Innovative Strategies for Combining Solar and Wind Energy with Green Hydrogen Systems

The integration of wind and solar energy with green hydrogen technologies represents an innovative approach toward achieving sustainable energy solutions. This review examines state-of-the-art strategies for synthesizing renewable energy sources, aimed at improving the efficiency of hydrogen (H2) generation, storage, and utilization. The complementary characteristics of solar and wind energy, where solar power typically peaks during daylight hours while wind energy becomes more accessible at night or during overcast conditions, facilitate more reliable and stable hydrogen production. Quantitatively, hybrid systems can realize a reduction in the levelized cost of hydrogen (LCOH) ranging from EUR 3.5 to EUR 8.9 per kilogram, thereby maximizing the use of renewable resources but also minimizing the overall H2 production and infrastructure costs. Furthermore, advancements such as enhanced electrolysis technologies, with overall efficiencies rising from 6% in 2008 to over 20% in the near future, illustrate significant progress in this domain. The review also addresses operational challenges, including intermittency and scalability, and introduces system topologies that enhance both efficiency and performance. However, it is essential to consider these challenges carefully, because they can significantly impact the overall effectiveness of hydrogen production systems. By providing a comprehensive assessment of these hybrid systems (which are gaining traction), this study highlights their potential to address the increasing global energy demands. However, it also aims to support the transition toward a carbon-neutral future. This potential is significant, because it aligns with both environmental goals and energy requirements. Although challenges remain, the promise of these systems is evident.

Endgroup engineering of the third component for high-efficiency ternary organic solar cells

In this study, we carefully designed and synthesized three A-D-A type molecules, namely YF-C8-CN, YF-C8-S, and YF-C8-O. These molecules feature a 2,2′-bithiophene core, which bears two 2,4,6-tripropylbenzene steric hindrance groups, as the central electron-donating unit, and utilize rhodanine (Rh), thiazolidinedione, and dicyanoyl-modified benzotriazole (BTA) respectively as the electron acceptor unit (A-unit). We investigated their impact as the third component on the performance of ternary organic solar cells (OSCs). Our studies indicate that YF-C8-S, with rhodanine terminal groups, exhibits complementary absorption characteristics and cascaded energy levels when combined with the host binary system (D18:eC9-4F). Compared to YF-C8-CN and YF-C8-O, ternary OSCs based on YF-C8-S demonstrate significantly higher exciton diffusion and charge transport efficiency, favorably impacting the short-circuit current density (JSC) and fill factor (FF) of the OSCs. Furthermore, devices based on YF-C8-S exhibit reduced non-radiative energy loss, contributing to an enhanced open-circuit voltage (VOC). Consequently, ternary OSCs based on YF-C8-S achieve a remarkable efficiency of 19.12%, positioning it among the highest reported values. This comprehensive research on the third component of the YF-C8 series underscores their significant potential for fabricating high-performance ternary OSCs.

A method for evaluating the regulation capacity of thermostatically controlled load group based on state complementary control strategy

Electric heating load (EHL) is a type of thermostatically controlled load whose power consumption mode can be flexibly adjusted, as long as the customers’ thermal comfort is ensured. The key to unlocking the regulatory potential of EHL lies in characterizing and harnessing its post-aggregation regulatory capacity, given its inherent dispersion and heterogeneity. Firstly, the second-order equivalent thermal parameter (ETP) model, grounded in the thermal equilibrium of the room, is employed to analyze the operational characteristics and to construct a model for aggregating load group. Secondly, leveraging the analysis of individual EHL regulation capacity, the temperature state characteristic quantity is introduced as a sorting index. Considering the dynamic properties of baseline power over time, a control strategy is proposed, based on state complementary characteristics among EHLs, for a more comprehensive and dynamic system management. Finally, the key indexes for reporting and implementation phases are identified to evaluate the regulation capacity of load group. The case study evidences that the newly introduced control strategy and evaluation method can provide more stable regulation power support for power grid dispatching, and more deeply harness the regulation capacity to maximize its potential value. In addition, this paper also discusses the influence of related factors such as the number, the rated power, the inside temperature control interval, the inside temperature setting value and the outside temperature on the regulation ability of the EHL group, offering a robust framework for the dispatching center to devise well-informed and rational regulation instructions.

5G network performance using novel MIMO mixed FSO/MMW communication systems under pointing errors effect: test analysis using image transmission

Abstract Millimeter waves (MMW) enable high data rates over short distances; free-space optical (FSO) provides high-capacity optical wireless transmissions; and multiple-input multiple-output (MIMO) maximizes antenna utilization. These are the three leading technologies that work harmoniously to deliver 5G’s superior performance. This collaborative effort results in 5G’s ability to offer high connection capacities, low latency, and rapid speeds, creating new opportunities for industrial and internet of things applications. In this paper, the proposed system combines FSO links and MMW radio frequency (RF) links to enhance the performance of mixed FSO/RF systems. FSO experiences turbulence and pointing errors (PE), while MMW undergoes fading. Using both FSO and MMW provides diversity against channel fading. Furthermore, both the FSO and MMW links utilize MIMO technology to combat fading through spatial diversity. The FSO link is modeled with a Gamma-Gamma Turbulence model and PE. The MMW link is modeled with Rayleigh fading. By combining these two types of links with MIMO, the system can achieve improved performance compared to using either FSO or MMW alone. The dual nature of the system provides robustness against different types of channels fading effects. Overall, the goal is to enhance performance by capitalizing on the complementary channel characteristics of optical and RF links and exploiting MIMO’s spatial diversity benefits. In the present work, closed-form formulas accounting for the influence of PE are generated for the bit error rate (BER). This article also explores the MIMO mixed FSO/MMW system with multiple modulation techniques under various turbulence situations. The suggested system is ultimately verified by transmitting images with suitable fixed BER.

Complementary Analysis and Performance Improvement of a Hydro-Wind Hybrid Power System

Hydropower as a flexible regulation resource is a rare choice to suppress the ever-increasing penetration of wind power in electrical power systems. The complementary characteristics and performance improvement of a hydro–wind hybrid power system based on a mathematical model of the hybrid power system is studied in this paper. This established model takes into account the stochastic variation in wind speeds in the wind power subsystem and the hydraulic–mechanical–electrical coupling characteristics of the hydropower subsystem. The complementary analysis is conducted based on the evaluation variables outputted by the established model, such as the wind power, hydro-regulation power, hydraulic power, and frequency. To make full use of the regulation capability of the hydropower system, the optimization of parameter settings is also carried out to improve complementary performances of the hybrid power system. The results from the complementary analysis show the detailed characteristics of hydro–wind coordinated operation under different types of real wind speeds. Here, 95% of installed hydro-capacity is used to complement the power shortage of the intermittent wind energy under the low wind speed. Alternatively, only around 66% of the installed hydro-capacity can be utilized to cope with the fluctuation in wind power under the medium and high wind speeds before the optimization of parameter settings. The recommended values and change rules of the control, hydraulic, and electrical parameters for the hydropower system are subsequently revealed from the analysis of parameter settings to contribute to a stable and safe hybrid power system. The results show that the optimized parameter can increase the maximal regulating capacity of the hydropower system by nearly 9 MW, approximately a sixth of the total installed hydropower capacity. The method and results obtained in this paper provide theoretical and technical guidance for the safe and economical operation of power stations.

Clinical, laboratory and neuroimaging profile of patient's cohort with septo-optic dysplasia treated at a pediatric university hospital

ObjectivesSepto-optic dysplasia (SOD) is a relatively rare clinical condition. However, there has been a significant increase in its incidence over the years. Diagnosis is clinical and made when there are at least 2 components of the classic triad: Optic nerve hypoplasia (ONH), midline malformation, and pituitary dysfunction. This study aims to describe the clinical and complementary exam characteristics of patients with SOD. MethodsA retrospective study of review of medical records of 48 patients cohort (24 female) with SOD followed to 2023. ResultsThe average age at diagnosis was 3.90 ± 3.85 years. Maternal age was ≤ 25 years at the time of delivery in 50% (24/48) of cases. Visual and developmental impairment was observed in 21 (43.7%) and nystagmus in 15 patients. Fourteen of them developed short stature. Regarding the diagnostic criteria for SOD: 92.6% (38/41) had ONH (78.9% bilaterally), 95.3% (41/43) had structural midline abnormalities, 85.7% (24/28) had hypothalamic-pituitary region alterations, and 73% had at least one hormonal deficiency, of which 2/3 had multiple pituitary dysfunctions. The most frequent deficiencies were thyroid-stimulating hormone and growth hormone, and the average age at diagnosis of the first dysfunction was 4.25 ± 3.71 years. ConclusionClinical manifestations that most led to early suspicion were developmental delay, nystagmus and visual impairment. More than 1/3 of the patients had the complete triad and 2/3 developed multiple pituitary deficiencies, with TSH deficiency being the most prevalent followed by GH deficiency. Patients with ONH or midline structural changes should undergo endocrine evaluation.

Research on the collaborative operation strategy of shared energy storage and virtual power plant based on double layer optimization

Large-scale access to distributed energy resources leads to new energy consumption problems and safe operation risks in the power system. Virtual power plants and shared energy storage are effective ways to promote the flexible consumption of distributed energy resources and improve the reliability and economy of power system operation. Based on the concept of sharing economy and considering the complementary characteristics of source and load resources between different virtual power plants, this paper focuses on the optimisation of shared energy storage and multi-virtual power plant operation. Firstly, distributed wind power, distributed photovoltaic and flexible load resources are aggregated into virtual power plants to analyze the cooperative operation mode of shared energy storage and multi-virtual power plant systems. Secondly, a two-layer decision model for shared energy storage configuration and multi-VPP system operation optimisation is constructed, with the upper model solving the optimal energy storage configuration scheme by maximising the revenue of the shared energy storage operator, and the lower model optimising the multi-VPP system operation strategy by minimising the total operation cost, the maximum amount of new energy consumed, and the minimum amount of carbon emission as the multi-objective optimisation strategy. Finally, a simulation analysis is carried out, and the results show that compared with the independent operation mode of each virtual power plant, the model proposed in this paper increases the annual profit of the shared energy storage operator by 7180¥, reduces the operating cost of the VPP system by 7.08 %, improves the rate of renewable energy consumption by 0.82 %, and reduces the annual carbon emission by 54.91 t, which realizes the mutual benefits of the virtual power plant and the shared energy storage.

Hierarchical collaboration for referring image segmentation

In the field of referring segmentation, top-down methods and bottom-up methods are the two prevailing approaches. Both of these methods inevitably exhibit certain drawbacks. Top-down methods are susceptible to Polar Negative (PN) errors due to their limited understanding of multi-modal fine-grained features. Bottom-up methods lack macro-level object positional information, making them susceptible to Inferior Positive (IP) errors. However, we find that the two approaches are highly complementary in addressing their respective weaknesses, but combining them directly through a simple average does not yield complementary advantages. Therefore, we proposed a hierarchical collaboration approach to explore the complementary characteristics of the existing two methods from the perspectives of fusion and interaction, aiming to achieve more precise segmentation results. We proposed the Complementary Feature Interaction (CFI) module, which enables top-down methods to access fine-grained information and allows bottom-up approaches to obtain object positional information interactively. Regarding integration, Gaussian Scoring Integration (GSI) models the Gaussian performance distributions of two branches and performs weighted integration by sampling confidence scores from these distributions. We integrate various top-down and bottom-up methods within the proposed architecture and conduct experiments on three standard datasets. The experimental results demonstrate that our method outperforms the state-of-the-art independent segmentation algorithms. On the RefCOCO validation, test A and test B datasets, our proposed method achieved IoU scores of 77.51, 79.12, and 72.79, respectively. Extensive experiments demonstrate that our method can significantly improve segmentation accuracy when fusing different sub-methods.

Optimization of Operation Strategy of Multi-Islanding Microgrid Based on Double-Layer Objective

The shared energy storage device acts as an energy hub between multiple microgrids to better play the complementary characteristics of the microgrid power cycle. In this paper, the cooperative operation process of shared energy storage participating in multiple island microgrid systems is researched, and the two-stage research on multi-microgrid operation mode and shared energy storage optimization service cost is focused on. In the first stage, the output of each subject is determined with the goal of profit optimization and optimal energy storage capacity, and the modified grey wolf algorithm is used to solve the problem. In the second stage, the income distribution problem is transformed into a negotiation bargaining process. The island microgrid and the shared energy storage are the two sides of the game. Combined with the non-cooperative game theory, the alternating direction multiplier method is used to reduce the shared energy storage service cost. The simulation results show that shared energy storage can optimize the allocation of multi-party resources by flexibly adjusting the control mode, improving the efficiency of resource utilization while improving the consumption of renewable energy, meeting the power demand of all parties, and realizing the sharing of energy storage resources. Simulation results show that compared with the traditional PSO algorithm, the iterative times of the GWO algorithm proposed in this paper are reduced by 35.62%, and the calculation time is shortened by 34.34%. Compared with the common GWO algorithm, the number of iterations is reduced by 18.97%, and the calculation time is shortened by 22.31%.

A novel shape sensing approach based on the coupling of Modal Virtual Sensor Expansion and iFEM: Numerical and experimental assessment on composite stiffened structures

Shape sensing, i.e. the reconstruction of the displacement field of a structure from discrete strain measurements, is becoming crucial for the development of a modern Structural Health Monitoring framework. Nevertheless, an obstacle to the affirmation of shape sensing as an efficient monitoring system for existing structures is represented by its requirement for a significant amount of sensors. Two shape sensing methods have proven to exhibit complementary characteristics in terms of accuracy and required sensors that make them suitable for different applications, the inverse Finite Element Method (iFEM) and the Modal Method (MM). In this work, the formulations of these two methods are coupled to obtain an accurate shape sensing approach that only requires a few strain sensors. In the proposed procedure, the MM is used to virtually expand the strains coming from a reduced number of strain measurement locations. The expanded set of strains is then used to perform the shape sensing with the iFEM. The proposed approach is numerically and experimentally tested on the displacement reconstruction of composite stiffened structures. The results of these analyses show that the formulation is able to strongly reduce the number of required sensors for the iFEM and achieve an extremely accurate displacement reconstruction.

Complementary resistive switching characteristics of solid electrolyte chalcogenide AgxTe nanoparticles for high-density crossbar random access memory

Silver telluride (AgxTe) is a member of the chalcogenide family that comprises materials extensively used as solid electrolytes. Because of its high-ionic conductivity, low-optical bandgap, and excellent thermoelectric properties, AgxTe has been studied in many research fields, including optoelectronics and energy harvesting. Herein, AgxTe is proposed as the active channel for resistive random access memory (RRAM) showing complementary resistive switching (CRS) characteristics. AgxTe-based RRAM devices with an Ag/AgxTe/Au structure are fabricated on a glass substrate. AgxTe nanoparticles are synthesized using the colloidal method, and AgxTe thin films are prepared via spin coating of the synthesized nanoparticles dispersed in deionized water. The fabricated AgxTe-based RRAM device exhibits CRS characteristics without any additional built-in selectors or antiserial arrangement. This is attributed to the formation of the inversion of CF geometry and allows the fabrication of high-density crossbar arrays. The AgxTe RRAM device annealed at 200 °C exhibits a resistance on/off ratio of approximately 102 as well as stable retention (∼104 s) and endurance (∼103 cycles). This investigation proposes a new application of AgxTe, as a solid electrolyte, and a new strategy for the development of high-density crossbar RRAM architectures, for the first time.

Enhanced Dynamic Droop Control for Microgrid Frequency and Voltage Stabilization Using Hybrid Energy Storage Systems: A SECANT Method Approach

Due to their variable and intermittent nature, the integration of renewable energy sources poses control challenges related to voltage and frequency stability in isolated microgrids. This paper proposes an enhanced dynamic droop control strategy optimized in active time along with a Hybrid Energy Storage System (HESS) comprising Battery Energy Storage System (BESS), supercapacitors (SUPCA), and Superconducting Magnetic Energy Storage (SMES) to improve microgrid stability. The Dynamic Droop Gains (DDG) are continuously tuned using the rapid-converging SECANT numerical method to enhance transient response and steady-state performance, this was achieved using MATLAB/Simulink. The HESS combines the complementary characteristics of BESS, SUPCA and SMES to balance steady power supply and temporary overload capacity. Detailed simulation studies on a microgrid test system verify that the proposed control strategy significantly enhances voltage/frequency regulation, power sharing accuracy, BESS lifespan and overall stability compared to conventional droop techniques. The SUPCA further improves the transient performance and power quality by mitigating fluctuations. The research demonstrates an innovative way to harness advanced control algorithms and emerging storage technologies for next-generation resilient and sustainable microgrids.

A CNNbased energy management strategy for a Hybrid energy storage system in electric vehicles

When approaching a large-scale performance, the choice, size, and administration of an Energy Storage System (ESS) for an Electric Vehicle (EV) are crucial. As the peak-to-average power demand ratio is relatively large, particularly for an urban ride that is frequently marked by rapid deceleration as well as acceleration, the complementary characteristics of the battery and Ultra-Capacitor (UC)render this arrangement a viable Hybrid energy storage system (HESS) for EV. Enhanced dynamic responsiveness, increased miles per charge, and extended battery life provided by the HESS increase the Electric Vehicle (EV’s) effectiveness. The primary objective of the study that has been suggested is to create a smart Energy Management Strategy (EMS) for EVs. A battery package and a properly sized Ultra-Capacitor (UC) together give the required high power along with energy density. This research proposes a CNN-based power management technique to aid in efficient EMS. Additionally, by adjusting the Convolution Neural Network (CNN) classifier’s weights through Improved Honey Badger Optimization (IHBO), the adaptive approach of the Standard HBO Algorithm, the performance of the classifier is improved. In MATLAB, the suggested CNN-based model for BESS EM is simulated and experimental assessment and analysis are done in terms of converter current and battery SoC. By contrasting the suggested approach against several standardized models, the performance analysis of the proposed work is assessed to validate its performance.

Robust maglev hybrid nanogenerator with an airflow-based motion conversion mechanism for exploiting low-frequency mechanical energy

Triboelectric nanogenerator (TENG) has been widely recognized as an efficient technology for exploiting low-frequency (LF) mechanical energy, but the sparse outputs at low frequencies and insufficient durability at high frequencies hinder its extensive applications. Herein, a robust and high-output triboelectric-electromagnetic hybrid nanogenerator (TEHG) is proposed with an ingenious airflow-based motion conversion mechanism (AMCM) and a well-designed maglev mechanism. Distinct from conventional MCMs generally constructed with complicated rigid components, the AMCM transforms LF-motions to fast rotation through a flexible bladder and air tubes. Enabled by the AMCM, the TENG part can provide power density up to 274 mW/kg at an output frequency 70 times higher than the excitation frequency. The normalized voltage of the TENG part stabilizes at 84.1 % after 8-day durability test with the specially designed maglev mechanism, which allows the TENG part to operate in intermittent (sliding) contact state under slow rotation to replenish tribo-charges with minor material wear whereas switch to non-contact state without material wear under fast rotation. By combining the complementary output characteristics of triboelectric and electromagnetic technologies, a storage capacitor can be charged to a higher voltage level within remarkably reduced time. The practical feasibility of the AMCM-TEHG was verified by arranging it on a footpath to charge a wireless digital camera and a wireless sensing system. This study provides a promising strategy for multiplying the output frequencies as well as increasing the durability of TEHGs for efficiently exploiting LF-mechanical energy.