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A novel linear search-linear programming method for non-convex multi-objective sizing of standalone microgrids

Energy Conversion and Management 2025年 337卷

作者： Yin, Zishan Jin, Jiashu Zeng, Linghong Tang, Xiyun Wang, Zhuo Li, Xi School of Artificial Intelligence and Automation Huazhong University of Science and Technology Hubei Wuhan430074 China Key Laboratory of Imaging Processing and Intelligent Control of Education Ministry Huazhong University of Science and Technology Hubei Wuhan430074 China Belt and Road Joint Laboratory on Measurement and Control Technology Huazhong University of Science and Technology Hubei Wuhan430074 China

Both the increased utilization of photovoltaic (PV) and the consequent expansion of energy storage, leading to higher costs, are critical factors in the development of a techno-economic microgrid. To address this trade-off, optimal sizing design of a multi-energy microgrid is essential. This paper proposes a novel linear search-linear programming method for optimizing the sizing of microgrids with diverse energy storage systems, including battery energy storage systems (BESS) and hydrogen energy storage systems (HESS). The method minimizes both the non-linear and non-convex life cycle cost and the PV curtailment rate. Simulation results demonstrate the feasibility and superiority of the proposed method, achieving enhanced computational efficiency: 52 times faster for PV/HESS microgrids, 124 times for PV/BESS, and 5 times for PV/HESS/BESS. Moreover, more comprehensive and accurate optimal configurations were identified, including 4289 PV units for both the PV/BESS and PV/HESS/BESS microgrids, and 6239 PV units along with 37 fuel cell units for the PV/HESS microgrid. Based on the advanced optimization outcomes, a techno-economic analysis shows that the PV/HESS/BESS microgrid optimally combines the advantages of both HESS and BESS, substantially improving overall system performance. © 2025

关键词： Linear programming

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Adaptive Homophily Clustering: Structure Homophily Graph Learning with Adaptive Filter for Hyperspectral image

arXiv

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arXiv 2025年

作者： Ding, Yao Kang, Weijie Yang, Aitao Zhang, Zhili Zhao, Junyang Feng, Jie Hong, Danfeng Zheng, Qinghe The Key Laboratory of Intelligent Control PLA Rocket Force University of Engineering Xi’an710025 China The Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Xidian University Xi’an710071 China The Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China The School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China

Hyperspectral image (HSI) clustering has been a fundamental but challenging task with zero training labels. Currently, some deep graph clustering methods have been successfully explored for HSI due to their outstanding performance in effective spatial structural information encoding. Nevertheless, insufficient structural information utilization, poor feature presentation ability, and weak graph update capability limit their performance. Thus, in this paper, a homophily structure graph learning with an adaptive filter clustering method (AHSGC) for HSI is proposed. Specifically, homogeneous region generation is first developed for HSI processing and constructing the original graph. Afterward, an adaptive filter graph encoder is designed to adaptively capture the high and low frequency features on the graph for subsequence processing. Then, a graph embedding clustering self-training decoder is developed with KL Divergence, with which the pseudo-label is generated for network training. Meanwhile, homophily-enhanced structure learning is introduced to update the graph according to the clustering task, in which the orient correlation estimation is adopted to estimate the node connection, and graph edge sparsification is designed to adjust the edges in the graph dynamically. Finally, a joint network optimization is introduced to achieve network self-training and update the graph. The K-means is adopted to express the latent features. Extensive experiments and repeated comparative analysis have verified that our AHSGC contains high clustering accuracy, low computational complexity, and strong robustness. The code source will be available at https://***/DY-HYX. Copyright © 2025, The Authors. All rights reserved.

关键词： Adaptive filters

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Deep transfer learning-based decoder calibration for intracortical brain-machine interfaces

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Computers in Biology and Medicine 2025年第Pt A期192卷 110231-110231页

作者： Li, Xiao Dong, Xianxin Wang, Jun Mao, Haodong Tu, Xikai Li, Wei He, Jiping Li, Qiang Zhang, Peng Hubei Key Laboratory of Modern Manufacturing Quantity Engineering School of Mechanical Engineering Hubei University of Technology Wuhan430068 China Britton Chance Center for Biomedical Photonics Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Hubei Wuhan China MoE Key Laboratory for Biomedical Photonics Collaborative Innovation Center for Biomedical Engineering School of Engineering Sciences Huazhong University of Science and Technology Hubei Wuhan China The Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Hubei Wuhan China Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

Intracortical brain-machine interfaces (iBMIs) aim to establish a communication path between the brain and external devices. However, in the daily use of iBMIs, the non-stationarity of recorded neural signals necessitates frequent recalibration of the iBMI decoder to maintain decoding performance, which requires collecting and labeling a large amount of new data. To address this challenge and minimize the time needed for decoder recalibration, we proposed an active learning domain adversarial neural network (AL-DANN). This model leveraged a substantial volume of historical data alongside a small amount of current data (four samples per category) to calibrate the decoder. By incorporating domain adversarial and active learning strategies, the model effectively transferred knowledge from historical data to new data, reducing the demand for new samples. We validated the proposed method using neural signals recorded from three monkeys performing different movements in a classification task or a regression task. The results showed that the AL-DANN outperformed existing state-of-the-art methods. Impressively, it required only four new samples per category for decoder recalibration, leading to a recalibration time reduction of over 80 %. To our knowledge, this is the first study to incorporate deep transfer learning into iBMI decoder calibration, highlighting the significant potential of applying deep learning technologies in iBMIs. © 2025

关键词： Adversarial machine learning

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Brightness temperature emitted by radiometer calibration load at millimeter wave band

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INTERNATIONAL JOURNAL OF INFRARED AND MILLIMETER WAVES 2001年第4期22卷 553-569页

作者： Xiao, ZH Zhang, ZY Guo, W 1. Key Laboratory of Education Ministry of People's Republic of China for Image Processing and Intelligent Control China

In this paper, the DVRT(vector radiative transfer theory of densely distributed random discrete scatters) model to calculate the brightness temperature emitted by radiometer calibration load is presented. It takes the multiple scattering of isolation layer into account, which is neglected by the incoherent homogeneous model often used in calibration. Hence, it works much better than incoherent homogeneous model at millimeter wave band. Furthermore, the iteration of DVRT model is presented, and it proves that the incoherent homogeneous model is just the zero-order solution of DVRT model. Some numerical results are provided in the end.

关键词： DVRT model incoherent homogeneous model radiometer calibration calibration load brightness temperature

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Flocking in Multi-Agent Systems with Multiple Virtual Leaders Based Only on Position Measurements

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Communications in Theoretical Physics 2012年第5期57卷 801-807页

作者：苏厚胜 Department of Control Science and Engineering Image Processing and Intelligent Control Key Laboratory of Education Ministry of ChinaHuazhong University of Science and Technology

Most existing flocking algorithms assume one single virtual leader and rely on information on both relative positions and relative velocities among neighboring *** this paper,the problem of controlling a flock of mobile autonomous agents to follow multiple virtual leaders is investigated by using only position information in the sense that agents with the same virtual leader asymptotically attain the same velocity and track the corresponding virtual leader based on only position measurements.A flocking algorithm is proposed under which every agent asymptotically attains its desired velocity,collision between agents can be avoided,and the final tight formation minimizes all agents' global potentials.A simulation example is presented to verify and illustrate the theoretical results.

关键词： distributed control flocking multi-agent system multiple virtual leaders

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Switching mechanism for TiO_2 memristor and quantitative analysis of exponential model parameters

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Chinese Physics B 2015年第8期24卷 598-604页

作者：王小平陈敏沈轶 School of Automation Huazhong University of Science and Technology Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology

The memristor, as the fourth basic circuit element, has drawn worldwide attention since its physical implementation was released by HP Labs in 2008. However, at the nano-scale, there are many difficulties for memristor physical realization. So a better understanding and analysis of a good model will help us to study the characteristics of a memristor. In this paper, we analyze a possible mechanism for the switching behavior of a memristor with a Pt/TiO2/Pt structure, and explain the changes of electronic barrier at the interface of Pt/TiO2. Then, a quantitative analysis about each parameter in the exponential model of memristor is conducted based on the calculation results. The analysis results are validated by simulation results. The efforts made in this paper will provide researchers with theoretical guidance on choosing appropriate values for(α, β, χ, γ) in this exponential model.

关键词： memristor switching behavior electronic barrier exponential model

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Analysis and Design of Application-Layer Rateless Codes Based on Reliability and Latency Trade-Off

Analysis and Design of Application-Layer Rateless Codes Base...

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IEEE Conference on Wireless Communications and Networking

作者： Haobo Huang Yusun Fu Junpeng Yin Ningbo Artificial Intelligence Institute Shanghai Jiao Tong University Ningbo China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

With the Internet of Things (IoT) playing an increasingly crucial role in connecting diverse devices, applications have different requirements for communication and various evaluation metrics have emerged, such as Age of Information (AoI) and estimation error. Considering the fundamental trade-off between reliability and latency of the communication system, the relationship among reliability, latency, AoI and estimation error is complex. This paper proposes a remote state observation system with application-layer rateless codes to explore above relationships, addressing how to design the system for optimal performance based on varying requirements by adjusting coding parameters. By emphasizing flexible and adaptable coding strategies, we aim to convey the idea that the error-correction codes can be designed to optimize the communication system for diverse practical metrics. It is different from the traditional designs that focus on approaching the Shannon limit.

关键词： Measurement Estimation error Correlation Communication systems Reliability engineering Information age Error correction codes Internet of Things Channel coding State estimation

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A novel model and behavior analysis for a swarm of multi-agent systems with finite velocity

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Chinese Physics B 2014年第9期23卷 590-593页

作者：王良顺吴治海 Key Laboratory of Image Processing and Intelligent Control of the Ministry of Education School of AutomationHuazhong University of Science and Technology Key Laboratory for Advanced Process Control of Light Industry of the Ministry of Education School of Internet of Things EngineeringJiangnan University

Inspired by the fact that in most existing swarm models of multi-agent systems the velocity of an agent can be infinite, which is not in accordance with the real applications, we propose a novel swarm model of multi-agent systems where the velocity of an agent is finite. The Lyapunov function method and LaSalle＇s invariance principle are employed to show that by using the proposed model all of the agents eventually enter into a bounded region around the swarm center and finally tend to a stationary state. Numerical simulations are provided to demonstrate the effectiveness of the theoretical results.

关键词： multi-agent systems swarm finite velocity attraction and repulsion

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Quantum Immune Clonal Selection Algorithm for Multi-objective 0/1 Knapsack Problems

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Chinese Physics Letters 2010年第1期27卷 37-40页

作者：尚荣华焦李成李阳阳吴建设 Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Institute of Intelligent Information Processing Xidian University Xi'an 710071

Based on the concept and principles of quantum computing and the principle of the immune clonal selection, a new algorithm for multi-objective 0/1 knapsack problems is introduced. In the algorithm, for the novel representation, qubit antibodies in the antibody population are updated by applying a new chaos update strategy. A quantitative metric is used for testing the convergence to the Pareto-optimal front. Simulation results on the 0/1 knapsack problems show that the new algorithm, in most cases, is more effective.

关键词： Chinese climate network complex systems small world community

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A Game Theory-Reinforcement Learning Approach to Cooperation for UAVs

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IEEE Transactions on Vehicular Technology 2025年

作者： Tang, Changbing Pan, Linchao Chen, Jie Liu, Yang Lai, Jingang The College of Physics and Electronic Information Engineering Zhejiang Normal University Jinhua321004 China The School of Mathematical Sciences Zhejiang Normal University Jinhua321004 China The Hangzhou School of Automation Zhejiang Normal University Hangzhou311231 China The College of Electronic Engineering National University of Defense Technology Hefei230037 China The School of Artificial Intelligence and Automation the Key Laboratory of Image Processing and Intelligent Control Education Ministry of China China Huazhong University of Science and Technology Wuhan430074 China

To execute a variety of collaborative tasks, the cooperation for unmanned aerial vehicles (UAVs) with complicated interactions under dynamic environments is a challenging and critical issue. This paper studies the cooperation issue for UAVs under dynamic environments through an approach of game theory-reinforcement learning (GT-RL) approach, which combines the advantages of both game theory and reinforcement learning. First, to cope with the complicated interactions of UAVs, the cluster of UAVs is modeled as a public goods game with asymmetrical environmental feedback. Then, reinforcement learning is adopted to optimize decision-making of UAVs under unknown and dynamic environments through comparing the dynamic behaviors of UAVs, where a novel dynamics system offers a more comprehensive understanding on cooperative behavior among UAVs. Finally, the simulation results show that the GT-RL approach can effectively promote cooperation among UAVs in completing the collaborative tasks. © 1967-2012 IEEE.

关键词： Adversarial machine learning

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