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Peer-to-peer trading price and strategy optimization considering different electricity market types, tariff systems, and pricing models

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ENERGY AND BUILDINGS 2023年 300卷

作者： Zhang, Ruixiaoxiao Lee, Minhyun Zhao, Dongqi Kang, Hyuna Hong, Taehoon Hong Kong Polytech Univ Dept Bldg & Real Estate Hung Hom Kowloon Hong Kong Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Educ Minist Wuhan Hubei Peoples R China Yonsei Univ Dept Architecture & Architectural Engn Seoul South Korea

This study investigated the peer-to-peer (P2P) trading price and strategy based on market-driven methods within a residential microgrid consists of two prosumers (i.e., P1 and P2) and one consumer (i.e., C1), which establishes a diverse microgrid trading market in terms of peer characteristics (e.g., system configurations and electrical load profile). Five cases are proposed in this study considering different electricity market types (i.e., peer-to-grid and P2P markets), retail tariff systems (i.e., progressive and time-of-use (ToU) tariff systems) as well as market-driven P2P trading pricing models (i.e., uniform and individual pricing models). Peer electrical load data are collected from three typical four-person households in Hong Kong along with their domestic electrical appliance utilization pattern. The results indicate that the individual pricing model has led to the dynamics of P2P electricity trading price than the uniform pricing model, and P2P trading is more economically efficient under the ToU tariff system. The maximum electricity bill saving of the entire microgrid can be achieved by 31.33% in summer and by 43.02% in winter. Besides, it is observed that the installation of battery energy storage system (BESS) has facilitated the self-consumption ratio of the renewable energy system to 91.98% in summer and 100% in winter. This implies that the BESS plays a pivotal role in improving the flexibility in managing the P2P trading strategy, and enhancing the efficiency in electricity dispatching within the microgrid. This study contributes to the novelty in science since it provides a comprehensive framework that can adapt to changing market conditions.

关键词： Peer-to-Peer energy trading Time-of-Use Energy storage system Photovoltaic system Price optimization

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Low-Rank Optimal Transport for Robust Domain Adaptation

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1667-1680页

作者： Bingrong Xu Jianhua Yin Cheng Lian Yixin Su Zhigang Zeng IEEE the School of Automation Wuhan University of TechnologyWuhan 430070China Intelligent Transportation Systems Research Center Wuhan University of TechnologyWuhan 430063 Chongqing Research Institute Wuhan University of TechnologyChongqingChina the School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074 the Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074China

When encountering the distribution shift between the source(training) and target(test) domains, domain adaptation attempts to adjust the classifiers to be capable of dealing with different domains. Previous domain adaptation research has achieved a lot of success both in theory and practice under the assumption that all the examples in the source domain are welllabeled and of high quality. However, the methods consistently lose robustness in noisy settings where data from the source domain have corrupted labels or features which is common in reality. Therefore, robust domain adaptation has been introduced to deal with such problems. In this paper, we attempt to solve two interrelated problems with robust domain adaptation:distribution shift across domains and sample noises of the source domain. To disentangle these challenges, an optimal transport approach with low-rank constraints is applied to guide the domain adaptation model training process to avoid noisy information influence. For the domain shift problem, the optimal transport mechanism can learn the joint data representations between the source and target domains using a measurement of discrepancy and preserve the discriminative information. The rank constraint on the transport matrix can help recover the corrupted subspace structures and eliminate the noise to some extent when dealing with corrupted source data. The solution to this relaxed and regularized optimal transport framework is a convex optimization problem that can be solved using the Augmented Lagrange Multiplier method, whose convergence can be mathematically proved. The effectiveness of the proposed method is evaluated through extensive experiments on both synthetic and real-world datasets.

关键词： Domain adaptation low-rank constraint noise corruption optimal transport

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Selection of Cancer Biomarkers from Microarray Gene Expression Data Utilizing the Bi-Objective Optimization Method

Selection of Cancer Biomarkers from Microarray Gene Expressi...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Jiang, Hanjing Lin, Jianqing Zhu, Huachao Huang, Yabing Huazhong University of Science and Technology Key Lab. of Image Information Processing and Intelligent Control of Education Ministry of China Institute of Artificial Intelligence School of Artificial Intelligence and Automation Wuhan430074 China Wuhan University School of Computer Science Wuhan430064 China Renmin Hospital of Wuhan University Department of Pathology Wuhan430060 China

ISBN: (纸本)9798350337488

Cancer-associated biomarker genes play an indispensable role in the intricate tapestry of cancer development and manifestation. The expression of biomarkers in different types of tumor cells has beneficial implications for shedding light on the development of various cancers, guiding clinical diagnosis, and treatment. Microarray technology enables the expression levels of thousands of genes in samples to be sequenced simultaneously. However, sparse and high-dimensional microarray data present a formidable challenge in identifying biomarker genes. This study presents EREF-NSGA2, a novel method for cancer biomarker selection from microarray data, employing a hybrid gene selection approach. Firstly, the combination of the wrapper and embedded gene selection methods is proposed to filter the microarray data, which efficiently decreases the search space of the algorithm. After that, the improved NSGA-II algorithm is used to search the genes subset obtained from the previous step to reach the optimal subset of cancer biomarker genes. The proposed EREF-NSGA2 is compared with other reported methods on six cancer benchmark gene expression datasets. A detailed biological analysis is performed to analyze the relationship between the selected genes and the cancer data sets they belong to. To summarize, EREF-NSGA2 proves its effectiveness in selecting a feature subset comprising the fewest genes while maintaining the highest classification accuracy. © 2023 IEEE.

关键词： Bi-objective optimization Cancer biomarker Gene selection NSGA-II

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Short-term hybrid prognostics of fuel cells: A comparative and improvement study

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RENEWABLE ENERGY 2024年 237卷

作者： Sheng, Chuang Fu, Jun Qin, Hongchuan Zu, Yanmin Liang, Yezhe Deng, Zhonghua Wang, Zhuo Li, Xi Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Educ Minist Wuhan 430074 Peoples R China Shenzhen Huazhong Univ Sci & Technol Res Inst Shenzhen 518055 Peoples R China Jingchu Univ Technol Sch Elect & Informat Engn Jingmen 448000 Peoples R China Accelink Technol Co Ltd Wuhan 430000 Peoples R China

Accurately predicting the performance degradation trend of fuel cells helps take measures in advance and prolong the stack's service life, leading to a novel hybrid forecasting approach. The first grey model prediction method based on residual exponential smoothing optimization (ES-R-GM) can capture the voltage deterioration trend. We explore the integration of two different ES techniques, specifically the double ES (ES2) and cubic ES (ES3), to investigate their effect on enhancing the predictive accuracy of the GM model. The second method of the adaptive network fuzzy inference system (ANFIS) can characterize local nonlinear behavior. We utilize the simulated annealing (SA) algorithm to optimize ANFIS results under different fuzzy rule selection strategies. The outcomes of the two prediction methods mentioned above are combined to create a hybrid prediction using the data fusion method and the moving window technique. Various hybrid methods are evaluated under general conditions and further detailed optimization. The data collected from the experimental platform confirms the suggested hybrid framework. The results show that the hybrid ES3-R-GM + ANFIS-SC method outperformed the single models in final prediction accuracy and can effectively track both global trends and local changes. Simultaneously, it takes less time to calculate than the literature. Moreover, when applied to consistent public datasets, the hybrid approach maintains its robustness and accuracy compared with other hybrid prognostic methods.

关键词： Solid oxide fuel cell Hybrid prediction Exponential smoothing Moving window method

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Cluster Space control Method of Manned-Unmanned Aerial Team for Target Search Task

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2023年第7期70卷 2545-2549页

作者： Huo, Mengzhen Duan, Haibin Zeng, Zhigang Beihang Univ Sch Automat Sci & Elect Engn State Key Lab Virtual Real Technol & Syst Beijing 100083 Peoples R China Peng Cheng Lab Dept Math & Theories Virtual Real Fundamental Res Lab Shenzhen 518000 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Educ Minist China Wuhan 430074 Peoples R China

This brief proposed a cluster space control method to help the operator of manned aerial vehicles (MAVs) to coordinate with unmanned aerial vehicles (UAVs) more efficiently. The operator of the MAV could change the states of the whole heterogeneous team only by issuing a single command. To verify its application performance, the method is employed to conduct search tasks under a complex environment with static and dynamic unknown targets. The receding horizon control (RHC) and backstepping control methods are utilized to complete the search task. Simulation results show the feasibility and efficiency of the proposed method and give a strong foundation for man-machine coordination in related fields.

关键词： Heterogeneous manned-unmanned aerial team cluster space control receding horizon control target search task

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Safety Protection Analysis with Formal Verification for Process control System Under Cyberattacks

Safety Protection Analysis with Formal Verification for Proc...

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第35届中国过程控制会议

作者： Xuqing Liang Chunjie Zhou Yu-Chu Tian Xin Du Peihang Xu School of Artificial Intelligence and Automation Huazhong University of Science and Technology The Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Computer Science Queensland University of Technology

The safety protection of process control systems plays a crucial role in the overall safety of critical *** have increased the complexity of existing safety protection analysis. Traditional safety analysis methods fall short in accounting for cyberattack factors, making it challenging to conduct safety protection analysis under cyberattacks. To address this issue, this paper presents a new safety protection analysis method that considers multiple safety factors explicitly including cyberattacks using formal verification. The method consists of three main components: exhaustive system safety specifications,formal models, and system safety validation. The system safety specification component adds a cyberattack factor to system safety requirements based on the system theory process analysis(STPA) method. The formal model component considers the system's dynamic operation process, and safety protection behaviors under typical attack behaviors. The system safety validation component validates the effectiveness of system safety protection under cyberattacks by the UPPAAL tool, from the perspective of whether system safety constraints are triggered and whether the change curve of process variables is compliant. Finally, the effectiveness of the presented approach is carried out for a simplified fluid catalytic cracking(FCC) fractionating system.

关键词： Safety protection analysis Formal verification Cyberattacks System theory process analysis(STPA)

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Task Allocation and Path Planning for Multiple Destinations Oriented Towards Task Updates

Task Allocation and Path Planning for Multiple Destinations ...

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International Conference on Industrial Artificial Intelligence (IAI)

作者： Yong Yang Dingxin He Huantao Mao Hong Chen Hongtao Wu Zhi-Wei Liu School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Ministry of Education Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798350356618

ISBN: (纸本)9798350356625

This study addresses the complexities of orchestrating multi-target transportation tasks within multi-agent systems, constrained by load capacity. The primary objective is to engineer an advanced path planning framework that assures collision avoidance and optimal load distribution. Diverging from conventional single-path strategies, this research incorporates load factors and requires continuous dynamic multi-target point and path planning to ensure agents can efficiently navigate through a series of predetermined key points. To address this complex requirement, a two-stage multi-agent task allocation and path planning method is proposed. First, an initial solution is obtained using a suboptimal algorithm, followed by optimization iterations using the large neighborhood search algorithm to improve task allocation. In the second stage, an accelerated algorithm based on priority search is used to plan optimal paths for each agent in a predetermined order. The proposed algorithm's effectiveness is comprehensively evaluated through a series of experimental evaluations and comparisons with the commercial solver Gurobi within a limited time. The results show that the proposed method achieves optimality in both running time and minimum path cost while ensuring the load balance of agents.

关键词： Costs Navigation Heuristic algorithms Transportation Path planning Robustness Planning Resource management Optimization Multi-agent systems

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EXPERT SYSTEMS WITH APPLICATIONS 2024年 246卷

作者： Zhou, Jian-Lan Chen, Xue-Yan Wang, Hong -Wei Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Wuhan 430074 Hubei Peoples R China Shenzhen Huazhong Univ Sci Technol Res Inst Shenzhen 518057 Peoples R China Huazhong Univ Sci & Technol Sch Management Wuhan 430074 Hubei Peoples R China

This study proposes a similarity -conformity -based clustering and decentralized feedback mechanism to manage incompatible decision -makers (DMs) in the large-scale group construction decision -making problem. Firstly, conformity is proposed to measure the consistency of the most preferred alternative of any two DMs and then extends this concept to define the similarity -conformity level of DMs. The average conformity between DMs in a subgroup represents the cohesion degree of this subgroup. Based on these concepts, a new clustering method considers the conflicts of interest among DMs and introduces the similarity -conformity to divide them into several subgroups. Then, the number of DMs in a subgroup and the cohesion degree are combined to formulate the subgroups' weights. A decentralized feedback mechanism is proposed to manage two categories of incompatible DMs in the consensus -reaching process. The proposed consensus model adjusts the incompatible DMs' opinions or subgroups' weights under four scenarios. In the proposed model, the four adjustment methods prove to be convergent, and they improve the group consensus level by ensuring the DMs' conformity and the logical consistency of preference relation. Finally, it provides an example of the alternative selection for transportation infrastructure construction. The comparative study and the sensitivity analysis are performed to verify the effectiveness of the proposed method.

关键词： Large-scale group decision -making Probabilistic linguistic preference relation Similarity -conformity level Clustering Decentralized feedback mechanism Construction decision -making

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Distributed impulsive control for secure consensus of nonlinear dynamical networks with node delay under denial-of-service attacks

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ASIAN JOURNAL OF control 2022年第2期24卷 594-604页

作者： Shi, Yu-Lun Liu, Zhi-Wei Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Minist Educ Wuhan Peoples R China

This paper investigates secure consensus problems of nonlinear dynamical networks (NDNs) with node delay under denial-of-service (DoS) attacks, which can cause a break in communication links. It will lead to packet loss. To ensure the secure consensus in this scenario, we propose an effective impulsive control which only based on sampled information from neighbor nodes. Based on the Lyapunov stability theory and the impulsive comparison principle, an upper bound of the average impulse interval is derived to ensure the exponential consensus of NDNs under DoS attacks, and the convergence rate can be estimated. Finally, a numerical example is provided to check the theory results.

关键词： comparison principle denial-of-service attacks (DoS) distributed impulsive control dynamical network time delay

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Lag quasi-synchronization of incommensurate fractional-order memristor-based neural networks with nonidentical characteristics via quantized control: A vector fractional Halanay inequality approach

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JOURNAL OF THE FRANKLIN INSTITUTE 2022年第12期359卷 6392-6437页

作者： Jia, Jia Wang, Fei Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Shandong Univ Sch Control Sci & Engn Jinan 250061 Peoples R China Qufu Normal Univ Sch Math Sci Qufu 273165 Shandong Peoples R China

This work realizes lag quasi-synchronization of incommensurate fractional-order memristor-based neural networks (FMNNs) with nonidentical characteristics via quantized control. The motivations behind this research work are threefold: (1) quantized controllers, which generate discrete control signals, can be more easily realized in computers than non-quantized controllers, and can consume smaller communication capacity;(2) incommensurate orders in a single FMNN and nonidentical characteristics in drive-response FMNNs are inescapable due to the differences among the circuit elements used to implement FMNNs;(3) convergence analysis of delayed incommensurate fractional-order nonlinear systems, which is the basis for the derivation of synchronization criterion, has not been handled perfectly. As an effective tool for convergence analysis of delayed incommensurate fractional-order nonlinear systems, especially for estimation of ultimate state bound, a vector fractional Halanay inequality is established at first. Then, a quantized synchronization controller, in which the dead-zone is introduced into some logarithmic quantizers to avoid chattering phenomenon, is designed. By means of vector Lyapunov function together with the newly derived vector fractional Halanay inequality, the synchronization criterion is proved theoretically. Lastly, numerical simulations supplementarily illustrate the correctness of the synchronization criterion. In contrast with the hypotheses in the relevant literature, the hypotheses in this paper are weaker. (C) 2022 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

关键词： Memristors

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