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Comprehensive Evaluation Method for Traffic Flow Data Quality Based on Grey Correlation Analysis and Particle Swarm Optimization

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Journal of Systems Science and Systems engineering 2024年第1期33卷 106-128页

作者： Wei Ba Baojun Chen Qi Li school of automation and electrical engineering Dalian Jiaotong UniversityDalian116028China Faculty of Electronic information and electrical engineering Dalian University of TechnologyDalian116023China

Nowadays,data are more and more used for intelligent modeling and prediction,and the comprehensive evaluation of data quality is getting more and more attention as a necessary means to measure whether the data are usable or ***,the comprehensive evaluation method of data quality mostly contains the subjective factors of the evaluator,so how to comprehensively and objectively evaluate the data has become a bottleneck that needs to be solved in the research of comprehensive evaluation *** order to evaluate the data more comprehensively,objectively and differentially,a novel comprehensive evaluation method based on particle swarm optimization(PSO)and grey correlation analysis(GCA)is presented in this *** first,an improved GCA evaluation model based on the technique for order preference by similarity to an ideal solution(TOPSIS)is ***,an objective function model of maximum difference of the comprehensive evaluation values is built,and the PSO algorithm is used to optimize the weights of the improved GCA evaluation model based on the objective function ***,the performance of the proposed method is investigated through parameter analysis.A performance comparison of traffic flow data is carried out,and the simulation results show that the maximum average difference between the evaluation results and its mean value(MDR)of the proposed comprehensive evaluation method is 33.24%higher than that of TOPSIS-GCA,and 6.86%higher than that of *** proposed method has better differentiation than other methods,which means that it objectively and comprehensively evaluates the data from both the relevance and differentiation of the data,and the results more effectively reflect the differences in data quality,which will provide more effective data support for intelligent modeling,prediction and other applications.

关键词： Data quality comprehensive evaluation particle swarm optimization grey correlation analysis traffic flow data

Deterministic and Robust Volt-var Control Methods of Power System Based on Convex Deep Learning

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 719-729页

作者： Qing Ma Changhong Deng the school of electrical engineering and automation Wuhan UniversityWuhanChina

Volt-var control(VVC)is essentially a non-convex optimization problem due to the non-convexity of power flow(PF)constraints,resulting in the difficulty in obtaining the optimum without convexity *** existing second-order cone method for the convexity conversion often leads to a sharp increase in PF constraints and optimization variables,which in turn increases the optimization difficulty or even leads to optimization *** paper first proposes a deterministic VVC method based on convex deep learning power flow(DLPF).This method uses the input convex neural network(ICNN)to establish a single convex mapping between state parameters and node voltage to complete the convexity conversion while the optimization variables only correspond to reactive power equipment,which can ensure the global optimum with extremely fast computation *** cope with the impact brought by the uncertainty of distributed energy and omit the additional worst scenario search of traditional robust VVC,this paper proposes robust VVC method based on convex deep learning interval power flow(DLIPF),which continues to adopt ICNN to establish another convex mapping between state parameters and node voltage *** DLIPF with DLPF,this method decreases the modeling and optimization difficulty of robust VVC *** results on 30-bus,118-bus,and 200-bus systems prove the correctness and rapidity of the proposed methods.

关键词： Volt-var control convexity conversion convex deep learning power flow

An evolutionary multiobjective method based on dominance and decomposition for feature selection in classification

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Science China(information Sciences) 2024年第2期67卷 5-19页

作者： Jing LIANG Yuyang ZHANG Ke CHEN Boyang QU Kunjie YU Caitong YUE Ponnuthurai Nagaratnam SUGANTHAN school of electrical and information engineering Zhengzhou University State Key Laboratory of Intelligent Agricultural Power Equipment school of electrical engineering and automation Henan Institute of Technology school of Electronics and information Zhongyuan University of Technology KINDI Center for Computing Research College of EngineeringQatar University

Feature selection in classification can be considered a multiobjective problem with the objectives of increasing classification accuracy and decreasing the size of the selected feature subset. Dominance-based and decomposition-based multiobjective evolutionary algorithms(MOEAs) have been extensively used to address the feature selection problem due to their strong global search capability. However, most of them face the problem of not effectively balancing convergence and diversity during the evolutionary process. In addressing the aforementioned issue, this study proposes a unified evolutionary framework that combines two search forms of dominance and decomposition. The advantages of the two search methods assist one another in escaping the local optimum and inclining toward a balance of convergence and diversity. Specifically, an improved environmental selection strategy based on the distributions of individuals in the objective space is presented to avoid duplicate feature subsets. Furthermore, a novel knowledge transfer mechanism that considers evolutionary characteristics is developed, allowing for the effective implementation of positive knowledge transfer between dominance-based and decomposition-based feature selection methods. The experimental results demonstrate that the proposed algorithm can evolve feature subsets with good convergence and diversity in a shorter time compared with 9 state-of-the-art feature selection methods on 20 classification problems.

关键词： evolutionary algorithms feature selection multiobjective optimization knowledge transfer classification

Dynamic thermal rating assessment of oil-immersed power transformers for multiple operating conditions

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High Voltage 2024年第1期9卷 195-205页

作者： Chen Zhang Xuzhu Dong Jiangjun Ruan Yongqing Deng school of electrical engineering and automation Wuhan UniversityWuhanHubeiChina

In this article,the dynamic thermal rating assessment method of oil-immersed power transformer with multiple operating conditions is proposed,considering the constraints of hot spot temperature(HST),top oil temperature,losses of life and the maximum allowable current of on-load tap changer(OLTC)or bushing,which can determine the dynamic load curves under different operating conditions and give the most sensitive constraints to limit the dynamic load *** improve the accuracy of HST estimation,the temperature estimation model is also improved and the thermal parameters are optimised using the HST measured by optical ***,several application examples are studied for transformers in different *** results show that the normal cyclic dynamic transformer rating(DTR)is mainly limited by the losses of life when the ambient temperature is high,and the average load factor can be increased to 0.82 with a maximum load capacity of *** main limiting factor of short-term DTR is the OLTC or bushing current constraint,and the average load factor can be increased to *** maximum load capacity of the transformer under both operating conditions is 23%and 50%higher than its rated load capacity,indicating that the transformer still has a large load potential available.

关键词： load thermal power

Leader-follower Optimal Selection Method for Distributed Control System in Active Distribution Networks

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 314-323页

作者： Jian Le Liangang Zhao Cao Wang Qian Zhou Yang Wang school of electrical engineering and automation Wuhan UniversityWuhan 430072China

Aiming at the shortcomings of a traditional centralized control in an active distribution network(AND),this paper proposes a leader-follower distributed group cooperative control strategy to realize multiple operation and control tasks for an *** distributed information exchange protocols of the distributed generation(DG)group devoted to node voltage regulation or exchange power control are developed using a DG power utilization ratio as the consensus *** these bases,this study further investigates the leader optimal selection method for a DG group to improve the response speed of the distributed control ***,a single or multiple leader selection model is established to minimize the constraints of the one-step convergence factor and the number of leaders to improve the response speed of the distributed control *** simulation results of the IEEE 33 bus standard test system show the effectiveness of the proposed distributed control *** addition,the response speed of a DG control group can be improved effectively when the single or multiple leaders are selected optimally.

关键词： Active distribution1network consensus algorithm leader-follower system mixed-integer semidefinite programming optimal distributed control

Cooperative Covert Communication in Multi-Antenna Broadcast Channels

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China Communications 2024年第6期21卷 246-260页

作者： Qiao Sen Liu Guangjie Ji Xiaopeng Liu Weiwei school of electrical and information engineering Nanjing University of Information Science and TechnologyNanjing 210044China school of automation Nanjing University of Science and TechnologyNanjing 210094China

With the gradual popularization of 5G communications,the application of multi-antenna broadcasting technology has become ***,this study aims to investigate the wireless covert communication in the two-user cooperative multi-antenna broadcast *** focus on the issue that the deteriorated reliability and undetectability are mainly affected by the transmission *** tackle this issue,we design a scheme based on beamforming to increase the reliability and undetectability of wireless covert communication in the multi-antenna broadcast *** first modeled and analyzed the cooperative multi-antenna broadcasting system,and put forward the target *** we use the SCA(successive convex approximation)algorithm to transform the target problem into a series of convex *** the convex problems are solved and the covert channel capacity is *** order to verify the effectiveness of the scheme,we conducted simulation *** simulation results show that the proposed beamforming scheme can effectively improve the reliability and undetectability of covert communication in multi-antenna broadcast channels.

关键词： beamforming covert communication multi-antenna broadcast channels OFDM

Adaptive admittance tracking control for interactive robot with prescribed performance

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Journal of Systems engineering and Electronics 2024年第2期35卷 444-450页

作者： MENG Qingrui LIN Yan school of automation Science and electrical engineering Beihang UniversityBeijing 100190China College of electrical engineering and automation Shandong University of Science and TechnologyQingdao 266590China

An adaptive control approach is presented in this paper for tracking desired trajectories in interactive manipulators. The controller design incorporates prescribed performance functions (PPFs) to improve dynamic performance. Notably, the performance of the output error is confined in an envelope characterized by exponential convergence, leading to convergence to zero. This feature ensures a prompt response from admittance control and establishes a reliable safety framework for interactions. Simulation results provide practical insights,demonstrating the viability of the control scheme proposed in this paper.

关键词： prescribed performance admittance control adaptive control robots

Distributed Cooperative Secondary Voltage Control in an Unbalanced Microgrid

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 222-234页

作者： Xiangzhen Yang Haixi Zhao Mengke Duan Yan Du Haining Wang Jian Zhang school of electrical engineering and automation Hefei University of TechnologyHefei 23009China

The negative-sequence reactive power-conductance(Q^(−)-G) droop control strategy is a conventional method to compensate for the output unbalanced voltages in an islanded ***, the conflict between unbalanced voltage compensation and negative-sequence reactive power sharing, caused bythe impedance mismatching of distribution lines and distributedgenerators, has not been solved only by Q^(−)-G droop *** this paper, a distributed cooperative secondary unbalancedvoltage control strategy is proposed to decrease the outputvoltage unbalance factor (VUF) of each droop-controlled DG,as well as to further enhance the negative-sequence reactivepower sharing effectiveness among DGs by properly shiftingup and down the Q^(−)-G droop characteristics of each *** algorithm for adaptive VUF weight coefficient is proposedto better suppress VUF under severe imbalance ***, a negative-sequence small-signal model of an MGunder an unbalanced condition, considering the communicationdelay time of the proposed SUVC, is established to analyze thesystem’s stability and transient performance under the influenceof some critical parameters. Finally, the effectiveness of theproposed strategy is validated by the simulation results froma real-time emulator of StarSim HIL.

关键词： Distributed cooperative control MG negativesequence reactive power starsim real-time platform time delay voltage unbalance compensation

Coordinated Dispatch Based on Distributed Robust Optimization for Interconnected Urban Integrated Energy and Transmission Systems

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 840-851页

作者： Wei Xu Yufeng Guo Tianhui Meng Yingwei Wang Jilai Yu the school of electrical engineering and automation Harbin Institute of TechnologyHarbin 150001China

To improve the economic efficiency of urban integrated energy systems(UIESs)and mitigate day-ahead dispatch uncertainty,this paper presents an interconnected UIES and transmission system(TS)model based on distributed robust ***,interconnections are established between a TS and multiple UIESs,as well as among different UIESs,each incorporating multiple energy *** Bregman alternating direction method with multipliers(BADMM)is then applied to multi-block problems,ensuring the privacy of each energy system operator(ESO).Second,robust optimization based on wind probability distribution information is implemented for each ESO to address dispatch *** column and constraint generation(C&CG)algorithm is then employed to solve the robust ***,to tackle the convergence and practicability issues overlooked in the existing studies,an external C&CG with an internal BADMM and corresponding acceleration strategy is ***,numerical results demonstrate that the adoption of the proposed model and method for absorbing wind power and managing its uncertainty results in economic benefits.

关键词： Distributed robust optimization distributionally robust dispatch urban integrated energy system transmission system external column and constraint generation(C&CG) internal Bregman alternating direction method with multipliers(BADMM)