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Power Quality Disturbance Identification Basing on Adaptive Kalman Filter andMulti-Scale Channel Attention Fusion Convolutional Network

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Energy engineering 2024年第7期121卷 1865-1882页

作者： Feng Zhao Guangdi Liu Xiaoqiang Chen Ying Wang school of automation and electrical engineering Lanzhou Jiaotong UniversityLanzhou730070China

In light of the prevailing issue that the existing convolutional neural network(CNN)power quality disturbance identification method can only extract single-scale features,which leads to a lack of feature information and weak anti-noise performance,a new approach for identifying power quality disturbances based on an adaptive Kalman filter(KF)and multi-scale channel attention(MS-CAM)fused convolutional neural network is *** and composite-disruption signals are generated through *** adaptive maximum likelihood Kalman filter is employed for noise reduction in the initial disturbance signal,and subsequent integration of multi-scale features into the conventional CNN architecture is *** multi-scale features of the signal are captured by convolution kernels of different sizes so that the model can obtain diverse feature *** attention mechanism(ATT)is introduced to adaptively allocate the extracted features,and the features are fused and selected to obtain the new main *** Softmax classifier is employed for the classification of power quality ***,by comparing the recognition accuracy of the convolutional neural network(CNN),the model using the attention mechanism,the bidirectional long-term and short-term memory network(MS-Bi-LSTM),and the multi-scale convolutional neural network(MSCNN)with the attention mechanism with the proposed *** simulation results demonstrate that the proposed method is higher than CNN,MS-Bi-LSTM,and MSCNN,and the overall recognition rate exceeds 99%,and the proposed method has significant classification accuracy and robust classification *** achievement provides a new perspective for further exploration in the field of power quality disturbance classification.

关键词： Power quality disturbance kalman filtering convolutional neural network attention mechanism

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Research on Carbon Emission for Preventive Maintenance of Wind Turbine Gearbox Based on Stochastic Differential Equation

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Energy engineering 2024年第4期121卷 973-986页

作者： Hongsheng Su Lixia Dong Xiaoying Yu Kai Liu school of automation and electrical engineering Lanzhou Jiaotong UniversityLanzhou730070China

Time based maintenance(TBM)and condition based maintenance(CBM)are widely applied in many large wind farms to optimize the maintenance issues of wind turbine gearboxes,however,these maintenance strategies do not take into account environmental benefits during full life cycle such as carbon emissions ***,this article proposes a carbon emissions computing model for preventive maintenance activities of wind turbine gearboxes to solve the *** on the change of the gearbox state during operation and the influence of external random factors on the gearbox state,a stochastic differential equation model(SDE)and corresponding carbon emission model are established,wherein SDE is applied to model the evolution of the device state,whereas carbon emission is used to implement carbon emissions *** simulation results indicate that the proposed preventive maintenance cannot ensure reliable operation of wind turbine gearboxes but reduce carbon emissions during their *** with TBM,CBM minimizes unit carbon emissions without influencing reliable operation,making it an effective maintenance method.

关键词： Stochastic differential equation(SDE) condition-based maintenance(CBM) carbon emissions

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Application of DSAPSO Algorithm in Distribution Network Reconfiguration with Distributed Generation

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Energy engineering 2024年第1期121卷 187-201页

作者： Caixia Tao Shize Yang Taiguo Li school of automation and electrical engineering Lanzhou Jiaotong UniversityLanzhou730070China

With the current integration of distributed energy resources into the grid,the structure of distribution networks is becoming more *** complexity significantly expands the solution space in the optimization process for network reconstruction using intelligent ***,traditional intelligent algorithms frequently encounter insufficient search accuracy and become trapped in local *** tackle this issue,a more advanced particle swarm optimization algorithm is *** address the varying emphases at different stages of the optimization process,a dynamic strategy is implemented to regulate the social and self-learning *** Metropolis criterion is introduced into the simulated annealing algorithm to occasionally accept suboptimal solutions,thereby mitigating premature convergence in the population optimization *** inertia weight is adjusted using the logistic mapping technique to maintain a balance between the algorithm’s global and local search *** incorporation of the Pareto principle involves the consideration of network losses and voltage deviations as objective functions.A fuzzy membership function is employed for selecting the *** analysis is carried out on the restructuring of the distribution network,using the IEEE-33 node system and the IEEE-69 node system as examples,in conjunction with the integration of distributed energy *** findings demonstrate that,in comparison to other intelligent optimization algorithms,the proposed enhanced algorithm demonstrates a shorter convergence time and effectively reduces active power losses within the ***,it enhances the amplitude of node voltages,thereby improving the stability of distribution network operations and power supply ***,the algorithm exhibits a high level of generality and applicability.

关键词： Reconfiguration of distribution network distributed generation particle swarm optimization algorithm simulated annealing algorithm active network loss

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Coordinated Frequency Control for Isolated Power Systems with High Penetration of DFIG-Based Wind Power

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CSEE Journal of Power and Energy Systems 2024年第4期10卷 1399-1414页

作者： Xin Ding Wei Lin Jian Xu Yuanzhang Sun Liangzhong Yao Beilin Mao school of electrical engineering and automation Wuhan UniversityWuhan 430072China Department of electrical engineering and Computer Science Case Western Reserve UniversityClevelandOH 44106 USA

This paper proposes a coordinated frequency control scheme for emergency frequency regulation of isolated power systems with a high penetration of wind *** proposed frequency control strategy is based on the novel nonlinear regulator theory,which takes advantage of nonlinearity of doubly fed induction generators(DFIGs)and generators to regulate the frequency of the power *** deviations and power imbalances are used to design nonlinear feedback controllers that achieve the reserve power distribution between generators and DFIGs,in various wind speed *** effectiveness and dynamic performance of the proposed nonlinear coordinated frequency control method are validated through simulations in an actual isolated power grid.

关键词： Frequency control isolated power systems nonlinear feedback nonlinear regulator theory wind power

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Neural-network-based fully distributed formation control for nonlinear multi-agent systems with event-triggered communication

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Science China(Technological Sciences) 2024年第1期67卷 209-220页

作者： ZHU GuoLiang LIU KeXin GU HaiBo LÜJinHu school of automation Science and electrical engineering Beihang UniversityBeijing 100191China Zhongguancun Laboratory Beijing 100094China

This paper investigates the consensus-based formation control problem for multi-agent systems with unknown nonlinear *** achieve the desired formation,we propose two formation controllers to achieve the desired formation,one based on system states and the other on system *** proposed controllers utilize adaptive gains to avoid global information and neural networks to estimate and compensate for *** proposed event-triggered schemes avoid continuous communication among agents and exclude the Zeno *** analysis reveals that formation errors are bounded,and numerical simulations are used to validate the effectiveness of the proposed approaches.

关键词： formation control neural network adaptive control event-triggered communication multi-agent systems

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Shape optimisation of basin insulator for DC gas insulated switchgear/gas insulated transmission lines based on artificial bee colony algorithm

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High Voltage 2024年第2期9卷 275-286页

作者： Yi Luo Shiyi Mao Ju Tang Zijun Pan Cheng Pan State Key Laboratory of Power Grid Environmental Protection School of Electrical Engineering and AutomationWuhan UniversityWuhanChina

The surface charge accumulation on the basin insulator is a particular problem in high-voltage direct current(HVDC)gas insulated switchgears(GIS)and gas insulated trans-mission lines(GIL),which restricts the development and application of extra/ultra high-voltage(EHV/UHV)*** surface charge distribution and anti-flashover performance are closely related to the insulator *** obtain the optimal basin insulator,a shape optimisation model based on artificial bee colony algorithm was established,and the minimisation objective functions based on capacitive(initial)electric field distribution and resistive(steady-state)electric field distribution were respectively *** optimisation results of the two objective functions were calculated,and the electric field and charge distribution on the surface of the insulator before and after optimisation were evaluated and compared using the simulation *** results indicated that the optimisation based on the capacitive electric field can significantly inhibit the surface charge accumulation,and the optimised insulator can significantly reduce the surface normal electric field and make the distribution of the tangential electric field more uniform,and the maximum tangential electric field can be reduced by 10%;the optimisation based on resistive electric field can achieve similar results,but requires more computational *** on the results,the‘anti-charge’basin insulator structure suitable for the DC field was given.

关键词： insulator artificial charge

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Attention-Based CNN Fusion Model for Emotion Recognition During Walking Using Discrete Wavelet Transform on EEG and Inertial Signals

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Big Data Mining and Analytics 2024年第1期7卷 188-204页

作者： Yan Zhao Ming Guo Xiangyong Chen Jianqiang Sun Jianlong Qiu school of Communication engineering Hangzhou Dianzi UniversityHangzhou 310018China school of automation and electrical engineering Linyi UniversityLinyi 276000China

Walking as a unique biometric tool conveys important information for emotion *** in different emotional states exhibit distinct walking *** this purpose,this paper proposes a novel approach to recognizing emotion during walking using electroencephalogram(EEG)and inertial *** recognition of emotion is achieved by training in an end-to-end deep learning fashion and taking into account multi-modal *** wear virtual reality head-mounted display(VR-HMD)equipment to immerse in strong emotions during *** environment shows excellent imitation and experience ability,which plays an important role in awakening and changing *** addition,the multi-modal signals acquired from EEG and inertial sensors are separately represented as virtual emotion images by discrete wavelet transform(DWT).These serve as input to the attention-based convolutional neural network(CNN)fusion *** designed network structure is simple and lightweight while integrating the channel attention mechanism to extract and enhance *** effectively improve the performance of the recognition system,the proposed decision fusion algorithm combines Critic method and majority voting strategy to determine the weight values that affect the final decision *** investigation is made on the effect of diverse mother wavelet types and wavelet decomposition levels on model performance which indicates that the 2.2-order reverse biorthogonal(rbio2.2)wavelet with two-level decomposition has the best recognition *** experiment results show that the proposed method outperforms other existing state-of-the-art works with an accuracy of 98.73%.

关键词： walking multi-modal fusion virtual reality emotion recognition discrete wavelet transform attention mechanism

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Decentralized Optimal Control and Stabilization of Interconnected Systems With Asymmetric Information

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 698-707页

作者： Na Wang Xiao Liang Hongdan Li Xiao Lu the College of electrical engineering and automation Shandong University of Science and TechnologyQingdao 266000China the school of automation and electrical engineering Linyi UniversityLinyi 276000China the College of Energy Storage Technology Shandong University of Science and TechnologyQingdao 266000China

The paper addresses the decentralized optimal control and stabilization problems for interconnected systems subject to asymmetric *** with previous work,a closed-loop optimal solution to the control problem and sufficient and necessary conditions for the stabilization problem of the interconnected systems are given for the first *** main challenge lies in three aspects:Firstly,the asymmetric information results in coupling between control and estimation and failure of the separation ***,two extra unknown variables are generated by asymmetric information(different information filtration)when solving forward-backward stochastic difference ***,the existence of additive noise makes the study of mean-square boundedness an *** adopted technique is proving and assuming the linear form of controllers and establishing the equivalence between the two systems with and without additive noise.A dual-motor parallel drive system is presented to demonstrate the validity of the proposed algorithm.

关键词： Asymmetric information decentralized control forwardbackward stochastic difference equations interconnected system stalibization

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Optimal dispatching strategy for residential demand response considering load participation

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Global Energy Interconnection 2024年第1期7卷 38-47页

作者： Xiaoyu Zhou Xiaofeng Liu Huai Liu Zhenya Ji Feng Li school of electrical and automation engineering Nanjing Normal UniversityNanjing 210023P.R.China

To facilitate the coordinated and large-scale participation of residential flexible loads in demand response(DR),a load aggregator(LA)can integrate these loads for *** this study,a residential DR optimization scheduling strategy was formulated considering the participation of flexible loads in ***,based on the operational characteristics of flexible loads such as electric vehicles,air conditioners,and dishwashers,their DR participation,the base to calculate the compensation price to users,was determined by considering these loads as virtual energy *** was quantified based on the state of virtual energy storage during each time ***,flexible loads were clustered using the K-means algorithm,considering the typical operational and behavioral characteristics as the cluster ***,the LA scheduling strategy was implemented by introducing a DR mechanism based on the directrix *** simulation results demonstrate that the proposed DR approach can effectively reduce peak loads and fill valleys,thereby improving the load management performance.

关键词： Residential demand response Flexible loads Load participation Load aggregator

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Global output feedback regulation of time-varying nonlinear systems via the dual-gain method

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Science China(Information Sciences) 2024年第5期67卷 333-334页

作者： Xian-Long YIN Zong-Yao SUN Changyun WEN Institute of automation Qufu Normal University school of electrical and Electronic engineering Nanyang Technological University

Notably, owing to the limited information available, the problem of output feedback stabilization/regulation for nonlinear systems has been explored based on state *** addition, the sensors accounting for state measurement could fail to detect the system states accurately due to the limitations of manufacturing techniques and instruments.

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