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Integrated energy microgrid bi-level game scheduling optimization taking into account electricity-heat-hydrogen enriched compressed natural gas coupling and shared energy storage

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International Journal of Electrical Power and Energy systems 2025年 169卷

作者： Wang, Changgang Sun, Xiaoning Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China School of Electrical Engineering Northeast Electric Power University Jilin132012 China

Hydrogen-enriched compressed natural gas (HCNG) is a promising technology capable of significantly reducing carbon emissions in conventional gas units. Its integration into microgrids enhances the coupling and complementarity of diverse energy sources. Shared energy storage systems, which play a crucial role in improving energy utilization, have garnered increasing attention in recent research. However, the deployment of HCNG technology involves multiple stakeholders, posing challenges in balancing their respective benefits. To address this, we propose a novel scheduling method for Integrated Energy Management that accounts for electricity-heat-HCNG coupling and shared energy storage services. First, we model the proton exchange membrane electrolyzer and HCNG energy coupling device, incorporating HCNG loads on the demand side to enhance hydrogen production and utilization efficiency. Additionally, tiered carbon trading mechanisms, integrated demand response strategies, and shared energy storage are introduced to optimize carbon reduction on both the demand and storage sides while effectively constraining energy emissions. The strategic interactions between integrated energy microgrid operators and load aggregators are modeled using a Stackelberg game approach, and the existence and uniqueness of equilibrium solutions are rigorously proven. Finally, the proposed model is solved using the Black-winged Kite algorithm in conjunction with the CPLEX *** studies demonstrate the effectiveness of the proposed method, showing revenue increases of 9.15% for integrated energy microgrid operators and 8.29% for load aggregators, alongside a reduction in carbon emissions by 8.76%. © 2025 The Author(s)

关键词： Energy utilization

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Energy-carbon pricing-guided collaborative optimization for local integrated energy communities with multi-vector electrification consumers

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Applied Energy 2025年 392卷

作者： Xi, Yufei Zuo, Lujie Chen, Meng Zhang, Jiansheng Cheng, Lin Lestas, Ioannis State Key Laboratory of Power System Operation and Control Tsinghua University Beijing100084 China Department of Energy and Power Engineering Tsinghua University Beijing100084 China Department of Engineering University of Cambridge CambridgeCB2 1PZ United Kingdom

The integration of multi-energy services and CO2 reduction measures is crucial for advancing the transition to low-carbon energy. This study proposes a novel Integrated Energy Community (IEC) framework that synergizes Electric Vehicles (EVs), Power-to-Chemical (P2C), and Power-to-Heat (P2H) electrification consumers to optimize renewable energy utilization and carbon management. The framework incorporates Electrochemical CO2 Reduction (ECO2R) and Carbon Capture and Storage (CCS) technologies, enabling carbon trading and chemical product commercialization. Meanwhile, an energy-carbon pricing-guided collaborative optimization model is developed, utilizing Nash bargaining game theory to coordinate electricity, gas, and heat operations under limited communication. Case studies validate the model's effectiveness, with numerical results demonstrating its superior performance in operational efficiency, renewable energy utilization, and carbon reduction compared to conventional community systems. © 2025 The Author(s)

关键词： Energy utilization

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Efficient Trajectory Generation Based on Traversable Planes in 3D Complex Architectural Spaces

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arXiv 2025年

作者： Zhang, Mengke Tian, Zhihao Xia, Yaoguang Xu, Chao Gao, Fei Cao, Yanjun The State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China Huzhou Institute Zhejiang University Huzhou Key Laboratory of Autonomous System Huzhou313000 China China Tobacco Zhejiang Industrial Co. Ltd. Hangzhou310024 China

With the increasing integration of robots into human life, their role in architectural spaces where people spend most of their time has become more prominent. While motion capabilities and accurate localization for automated robots have rapidly developed, the challenge remains to generate efficient, smooth, comprehensive, and high-quality trajectories in these areas. In this paper, we propose a novel efficient planner for ground robots to autonomously navigate in large complex multi-layered architectural spaces. Considering that traversable regions typically include ground, slopes, and stairs, which are planar or nearly planar structures, we simplify the problem to navigation within and between complex intersecting planes. We first extract traversable planes from 3D point clouds through segmenting, merging, classifying, and connecting to build a plane-graph, which is lightweight but fully represents the traversable regions. We then build a trajectory optimization based on motion state trajectory and fully consider special constraints when crossing multi-layer planes to maximize the robot’s maneuverability. We conduct experiments in simulated environments and test on a CubeTrack robot in real-world scenarios, validating the method’s effectiveness and practicality. Copyright © 2025, The Authors. All rights reserved.

关键词： Flight paths

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Incipient fault diagnosis method for silicon single crystal growth assisted by deep learning

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CrystEngComm 2025年第21期27卷 3480-3491页

作者： Liu, Yu-Yu Liu, Ding Ren, Jun Chao Wu, Shi Hai School of Automation and Information Engineering Xi'an University of Technology Xi'an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China

In this study, an accurate diagnostic classification algorithm based on a deep belief network and entropy value (C-DBN-E) incorporating signal decomposition, entropy theory and deep belief network (DBN) network is proposed to address the problem of tiny faults that may occur during the growth of silicon single crystals (SSC). The study is divided into three stages: feature selection, fault feature extraction and fault pattern classification. In the feature selection stage, the recursive feature elimination (RFE) method based on support vector machine (SVM) is employed to rank features according to their importance and eliminate redundant features. In the subsequent feature extraction stage, the adaptive decomposition theory is introduced to select components that contain a greater number of fault features for signal reconstruction. The deep features of the reconstructed signal are then mined in depth using a DBN and supplemented with energy entropy and multi-scale arrangement entropy as supplementary features to further refine the capture of tiny fault information. Finally, all the features are integrated and inputted into the SVM classifier to enable accurate classification of micro-fault modes in SSC growth. The effectiveness of the method in distinguishing micro-faults in the SSC growth process is verified by simulation results. This study is of great significance in solving the problem of fault diagnosis in the SSC growth system, which is expected to contribute to the improvement of work performance and the reduction of accident risk and economic loss. © 2025 The Royal Society of Chemistry.

关键词： Image reconstruction

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High-spatial-resolution phase-chaos Brillouin optical correlation domain sensor: theoretical analysis and experimental demonstration

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Journal of Lightwave Technology 2025年第12期43卷 5957-5966页

作者： Niu, Lintao Wang, Yahui Tian, Yixiu Ma, Jinglian Zhang, Mingjiang Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan030024 China Taiyuan University of Technology College of Physics and Optoelectronic Engineering Taiyuan030024 China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan030032 China

The predicaments of micro-scale gain motivation and its high signal-to-noise ratio (SNR) extraction primarily restrict the practical measurement of a superior spatial resolution (SR) for stimulated Brillouin scattering sensors. A high-SNR phase-chaos laser Brillouin optical correlation domain analysis (PCL-BOCDA) is introduced to breakthrough the physical bottlenecks. The fundamental principle of gain excitation scale based on PCL linewidth is proposed, and a novel SR evolvement model is constructed. The significant impact of edge effects on SR measurement is thoroughly analyzed, and this approach is theoretically capable of achieving higher SR benefiting from the narrower gain range and feebler accumulation noise. Experiments with different linewidth PCLs are conducted and the results are confirmed to the simulated ones. Ultimately, an SR of 4.8 mm with a relative error of 4.3% is achieved over a 1.14 km sensing distance, representing a tenfold improvement over previous results. This advancement provides a competent approach for high-SR sensors and their application. © 1983-2012 IEEE.

关键词： Stimulated Brillouin scattering

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Water and sediment characteristics in pressurized pipelines under complex terrain conditions

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Physics of Fluids 2025年第2期37卷

作者： Nan, Junhu Li, Wei Tao, Ran College of Energy and Power Engineering Lanzhou University of Technology Lanzhou730050 China Key Laboratory of Advanced Pumps Valves and Fluid Control System of the Ministry of Education Lanzhou University of Technology Lanzhou730050 China China Communications Hydraulic Engineering Company Limited Nanjing210012 China

This study selects the pipelines of the SGN as the research object and combines the experimental study with numerical simulation to investigate the water and sediment characteristics in pressurized pipelines under complex terrain conditions and determine the critical non-silting velocity under different flow rates. The results show that the sediment concentration and particle size gradually settle along the length of the pipeline, and the sediment particle size at the sampling position is 0.724-180 μm, with a sediment concentration ranging 1.09-6.28 kg/m3. The sediment in the inverted siphon pipeline is susceptible to siltation mainly at the bend below the rising section and the rising section. The sediment concentration in the radial direction of the pipeline is smaller at the upper layer and larger at the lower layer. As the flow rate increases, the sediment concentration in the lower layer of the horizontal section of the inverted siphon gradually decreases, while that in the lower layer of the descending and ascending sections gradually increases. Excess sediment concentration at the bottom of the pipeline under low flow conditions makes the high-velocity zone move upward. The flow velocity decreases in the lower layer and increases in the middle and upper layers. The critical non-silting velocity of sediment in the pipeline under sediment particle size of 1-500 μm is 1.20 m/s. The time-averaged pressure in the pipeline under water-sediment conditions is slightly greater than that under clear water conditions. The increase in sediment concentration at the bottom of the pipeline causes the fluctuation frequency and amplitude of pulsation pressure at the section center of the pipeline to be uneven and the frequency more dispersed. The research results may provide reference for the operation and design of similar projects. © 2025 Author(s).

关键词： Siphons

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Selection for Schottky Barrier Diodes with Various On-Resistance in Full-SiC Voltage Source Converters

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IEEE Transactions on Industry Applications 2025年

作者： Chen, Yuzhi Li, Chi Liu, Jianwei Wu, Yifan Liu, Zicheng Zheng, Zedong Tsinghua University State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Beijing 100084 China Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Wuhan 430074 China

In Silicon Carbide based voltage source converters (VSCs), pairing Schottky barrier diodes (SBDs) presents trade-offs. While SBDs reduce the freewheeling loss and mitigate the adverse effects of bipolar conduction, their junction capacitance also contributes to increased switching loss. This paper proposes a systematic selection strategy for SBDs aimed at enhancing converter efficiency, using on-resistance as the design variable. A three-phase VSC with 1.2 kV MOSFETs and four sets of 1.2 kV SBDs is demonstrated as the case study. The static and switching characteristics for MOSFET/SBD pair are measured and analyzed over a wide temperature range. VSC efficiency is evaluated in both inverter and rectifier modes under different operating conditions. It appears that VSC using SBDs with 126% of the MOSFETs' resistance exhibits an overall superior performance. A 4 kW full-SiC VSC prototype is developed to validate the proposed selection strategy. Compared to other SBDs, using the recommended selection enhances VSC efficiency by up to 2% (± 0.5%) under light loads while maintaining high performance under medium and heavy loads. Compared to freewheeling by the body diode, using the recommended selection enhances VSC efficiency by an average of 0.4% (± 0.1%) across nearly the entire load range. © 1972-2012 IEEE.

关键词： efficiency on-resistance Schottky barrier diodes selection strategy SiC MOSFETs voltage source converter

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3D bioprinting of a dermal scaffold for full-thickness skin tissue regeneration

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Bio-Design and Manufacturing 2025年第1期8卷 68-84,I0039-I0041页

作者： Lu Han Zixian Liu Meng Li Zhizhong Shen Jianming Wang Shengbo Sang Shanxi Key Laboratory of Micro Nano Sensors&Artificial Intelligence Perception College of Electronic Information and Optical EngineeringTaiyuan University of TechnologyTaiyuan 030024China Key Laboratory of Advanced Transducers and Intelligent Control System of the Ministry of Education Taiyuan University of TechnologyTaiyuan 030024China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan 030024China Shanxi Research Institute of 6D Artificial Intelligence Biomedical Science Taiyuan 030031China General Hospital of TISCO Taiyuan 030809China

Dermal substitutes have provided a template for the regeneration and reconstruction of the ***,the healed skin tissue often exhibits abnormal morphology and functionality,including scarring and *** this study,a composite bioink composed of methacrylated gelatin(GelMA)and chitosan oligosaccharide(COS)was proposed for printing a dermal scaffold using digital light processing(DLP)*** GelMA/COS bioink exhibited suitable porosity,swelling,degradation rate,and mechanical *** inclusion of COS demonstrated antibacterial effects against both Gram positive and Gram-negative bacteria,while simultaneously fostering the proliferation of human dermal fibroblasts(HDFs).Additionally,the application of COS could effectively reduce the expression levels of fibrosis-related genes,such as collagen I,collagen III,and fibronectin *** three-dimensionally printed cell-laden dermal scaffold exhibited excellent shape fidelity and high cellular viability,facilitating the extension of HDFs along the scaffold and the simultaneous secretion of extracellular matrix ***,the HDF-laden dermal scaffold transplanted into full-thickness skin defect sites in nude mice was shown to accelerate wound closure,reduce inflammation,and improve wound ***,the DLP-printed dermal scaffold provides an appealing approach for effectively treating full-thickness skin defects in clinical settings.

关键词： 3D printing Dermal scaffold Photo-cross-linking Skin tissue regeneration

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Improved CNP-Based Task Allocation for Large-Scale UAVs with Timing Constraints

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Journal of Aerospace engineering 2025年第4期38卷

作者： Tang, Yifan Dou, Liqian Zhang, Xiuyun Zhang, Ruilong Zhang, Zheyu Zhang, Lun School of Electrical and Information Engineering Tianjin Univ. Tianjin300072 China System Solution Research Laboratory Beijing Aerospace Automatic Control Institute Beijing100854 China Tianjin Key Laboratory of Avionics Integrated Mission Management Tianjin Aerospace Institute of Computing Technology Tianjin300308 China

For task allocation for multiple uncrewed aerial vehicles (UAVs) with time -series constraints, a time sequence task allocation method based on an improved contract net protocol (CNP) algorithm is proposed considering the influence of task requirements, timing constraints, and execution time of tasks. A novel reward function with time discounting was designed, and the optimization model of time-series task allocation was established with the goal of maximizing the reward of task execution. To adapt to the requirements of task execution time and multi-UAV cooperation, three stages - task release, bidding, and winning of the contract network protocol algorithm - are improved. Then the improved algorithm is used to solve the problem and the optimal task execution sequence is generated for each UAV. Simulation results verified the effectiveness and real-time performance of the proposed method, which can execute all the tasks in less time according to the timing requirements. © 2025 American Society of Civil Engineers.

关键词： Unmanned aerial vehicles (UAV)

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Approximately Invertible Neural Network for Learned Image Compression

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IEEE transactions on image processing : a publication of the IEEE Signal Processing Society 2025年 PP卷 PP页

作者： Yanbo Gao Shuai Li Meng Fu Chong Lv Zhiyuan Yang Xun Cai Hui Yuan Mao Ye School of Software Shandong University Jinan China Shandong University-WeiHai Research Institute of Industrial Technology Shandong University Weihai China School of Control Science and Engineering Shandong University Jinan China Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan China University of Electronic Science and Technology of China Chengdu Sichuan China

Learned image compression has attracted considerable interests in recent years. An analysis transform and a synthesis transform, which can be regarded as coupled transforms, are used to encode an image to latent feature and decode the feature after quantization to reconstruct the image. Inspired by the success of invertible neural networks in generative modeling, invertible modules can be used to construct the coupled analysis and synthesis transforms. Considering the noise introduced in the feature quantization invalidates the invertible process, this paper proposes an Approximately Invertible Neural Network (A-INN) framework for learned image compression. It formulates the rate-distortion optimization in lossy image compression when using INN with quantization, which differentiates from using INN for generative modelling. Generally speaking, A-INN can be used as the theoretical foundation for any INN based lossy compression method. Based on this formulation, A-INN with a progressive denoising module (PDM) is developed to effectively reduce the quantization noise in the decoding. Moreover, a Cascaded Feature Recovery Module (CFRM) is designed to learn high-dimensional feature recovery from low-dimensional ones to further reduce the noise in feature channel compression. In addition, a Frequency-enhanced Decomposition and Synthesis Module (FDSM) is developed by explicitly enhancing the high-frequency components in an image to address the loss of highfrequency information inherent in neural network based image compression, thereby enhancing the reconstructed image quality. Extensive experiments demonstrate that the proposed A-INN framework achieves better or comparable compression efficiency than the conventional image compression approach and state-of-the-art learned image compression methods.

关键词： Image coding Transforms Decoding Neural networks Quantization (signal) Image reconstruction Noise Entropy Optimization Transform coding

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