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CSEE Journal of Power and Energy Systems 2024年第2期10卷 481-491页

作者： Yue Qiu Suyang Zhou Wei Gu Xiao-Ping Zhang school of electrical Engineering Southeast UniversityNanjingChina school of Electronic Electrical and System EngineeringUniversity of BirminghamU.K.

The Chinese government is deepening reformation of electricity prices during the 14th Five Year Plan period and has set a carbon emission reduction target of reaching carbon peak before *** this context,will the carbon emission target influence electricity pricing and will electricity price influence competitiveness of Chinese main industries are two questions needing to be *** paper compares China's electricity price level with the selected major countries in the world,and four typical industries are selected to evaluate their electricity burden ***,the correlation between residential electricity price and industrial electricity price and the influencing factors is analyzed,from the perspectives of scale,structure and *** to the model obtained by regression analysis,the electricity price level and corresponding residential and industrial electricity burden in 2025 and 2030 are *** Terms-Electricity burden,industrial electricity price,regression analysis,residential electricity price.

关键词： Electricity burden industrial electricity price regression analysis residential electricity price

Optimal Operation Strategy Analysis with Scenario Generation Method Based on Principal Component Analysis,Density Canopy,and K-medoids for Integrated Energy Systems

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 89-100页

作者： Bingtuan Gao Yunyu Zhu Yuanmei Li school of electrical Engineering Southeast UniversityNanjingChina

The operation of integrated energy systems(IESs)is confronted with great challenges for increasing penetration rate of renewable energy and growing complexity of energy *** generation is one of ordinary methods to alleviate the system uncertainties by extracting several typical scenarios to represent the original high-dimensional *** paper proposes a novel representative scenario generation method based on the feature extraction of panel *** original high-dimensional data are represented by an aggregated indicator matrix using principal component analysis to preserve temporal ***,the aggregated indicator matrix is clustered by an algorithm combining density canopy and *** with the proposed scenario generation method,an optimal operation model of IES is established,where the objective is to minimize the annual operation costs considering carbon trading ***,case studies based on the data of Aachen,Germany in 2019 are *** results indicate that the adjusted rand index(ARI)and silhouette coefficient(SC)of the proposed method are 0.6153 and 0.6770,respectively,both higher than the traditional methods,namely K-medoids,K-means++,and density-based spatial clustering of applications with noise(DBSCAN),which means the proposed method has better *** error between optimal operation results of the IES obtained by the proposed method and all-year time series benchmark value is 0.1%,while the calculation time is reduced from 11029 s to 188 s,which verifies that the proposed method can be used to optimize operation strategy of IES with high efficiency without loss of accuracy.

关键词： Scenario generation principal component analysis(PCA) density canopy K-medoids integrated energy system

An improved initial rotor position estimation method using high-frequency pulsating voltage injection for PMSM

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Defence Technology（防务技术） 2024年第3期33卷 19-29页

作者： Yang Jiang Ming Cheng school of electrical Engineering Southeast UniversityNanjing 210096China

High frequency pulsating voltage injection method is a good candidate for detecting the initial rotor position of permanent magnet synchronous ***,traditional methods require a large number of filters,which leads to the deterioration of system stability and dynamic *** order to solve these problems,a new signal demodulation method is proposed in this *** proposed new method can directly obtain the amplitude of high-frequency current,thus eliminating the use of filters,improving system stability and dynamic performance and saving the work of adjusting filter *** addition,a new magnetic polarity detection method is proposed,which is robust to current measurement ***,experiments verify the effectiveness of the method.

关键词： Initial position detection Signal demodulation algorithm Magnetic polarity detection Filter elimination

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

H∞ Robustness for Distributed Control in Autonomous Microgrids Considering Cyber Disturbances

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 696-706页

作者： Ge Cao Guannan Lou Wei Gu Lina Sheng school of electrical Engineering Southeast UniversityNanjing 210096China

The physical connections and logical relationships between microgrids and communication networks allow microgrids to develop into typical cyber-physical systems(CPSs).With the extensive use of open communication mechanisms,the impact of cyber disturbances in public communication networks cannot be *** this paper,a parameter optimal method for a distributed secondary controller based on the robust control theory and consensus algorithm is presented to enhance the robustness of a secondary control system under data disturbance,parameter perturbation,and time ***,a distributed secondary control strategy of microgrids is demonstrated that coordinates frequency and voltage restoration and power ***,considering the impact of cyber events on the secondary control,a distributed robust controller gain design method is proposed to satisfy the H∞ performance *** solution of the distributed robust control is transformed into a linear matrix in equation problem and latency margin is simultaneously ***,a test microgrid CPS is simulated with and without time delay to investigate the impact of cyber events on system operational states and the effectiveness and robustness of the proposed method.

关键词： Cyber disturbance cyber-physical lsystem distributed control microgrid robust H∞control

Robust Interval State Estimation for Distribution Systems Considering Pseudo-measurement Interval Prediction

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 179-188页

作者： Xu Zhang Wei Yan Meiqing Huo Hui Li the school of electrical Engineering Chongqing UniversityChongqing 400044China

Interval state estimation(ISE)can estimate state intervals of power systems according to confidence intervals of predicted pseudo-measurements,thereby analyzing the impact of uncertain pseudo-measurements on ***,predicted pseudo-measurements have prediction errors,and their confidence intervals do not necessarily contain the truth values,leading to estimation biases of the *** solve this problem,this paper proposes a pseudo-measurement interval prediction framework based on the Gaussian process regression(GPR)model,thereby improving the prediction accuracy of pseudo-measurement confidence ***,a weight assignment strategy for improving the robustness of weighted least squares(WLS)ISE is *** strategy quantifies the deviation between the pseudo-measurement intervals and their estimated intervals and assigns smaller weights to the pseudo-measurement intervals with larger deviations,thereby improving the estimation accuracy and robustness of the *** paper adopts the data from the supervisory control and data acquisition(SCADA)system of the New York Independent System Operator(NYISO).It verifies the advantages of the GPR method for pseudo-measurement interval prediction by comparing it with the quantile regression and neural network *** addition,this paper demonstrates the effectiveness of the proposed weight assignment strategy through the IEEE 14-bus ***,the differences in the estimation accuracy and the bad data identification between the robust interval state estimation and deterministic state estimation are discussed.

关键词： Interval state estimation interval analysis pseudo-measurement Gaussian process regression(GPR)

Electromagnetic anisotropic homogeneous model for eddy-current field in single-phase wound core

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High Voltage 2024年第1期9卷 172-181页

作者： Lijun Zhou Woyang Li Yingyi Xia Jiawei Chen Chenqingyu Zhang Xiaohu Cai Lei Guo Dongyang Wang school of electrical Engineering Southwest Jiaotong UniversityChengduChina

The analysis of the eddy-current field in the wound core widely used in the field of transformer energy conservation is taken as the *** the homogenisation idea to consider the unique geometry of the wound core and features of its equivalent multi-stage circular cross-section magnetic boundary,a homogeneous model consisting of a columnar material with continuous homogeneous electromagnetic anisotropy is established by deriving the Maxwell equations of the magnetic quasi-static field in the columnar coordinate ***,a homogeneous fine element model for the eddycurrent field in the wound core is established and the accuracy of the model has been verified by the test *** result shows that the homogeneous model can be effectively used for the analysis of the eddy-current field in the wound core,and the error of calculating the eddy-current loss under different excitation conditions is less than 6%under the premise of extremely saving the engineering calculation cost,which will help improve the operational performance of the wound core and contribute to the energysaving goal of the high-voltage equipment.

关键词： anisotropic coordinate excitation

Voltage rise rate-related generalised probabilistic lifetime model of turn-to-turn insulation in inverter-fed motors

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High Voltage 2024年第1期9卷 46-55页

作者： Yan Yang Xueyang Bai Yuxing Lei Kai Liu Guangning Wu school of electrical Engineering Southwest Jiaotong UniversityChengduChina

The lifetime model of turn-to-turn insulation in inverter-fed motors is studied.A lifetime model has been built by considering the effect of inverter-generated high voltage rise rate(dv/dt up to 20 V/ns).This model is followed by the generalised probabilistic model,in which the lifetime is proportional to the nth power of the voltage rise ***,by investigating the effect of voltage rise rate on the partial discharge characteristics,it is found that the effect of voltage rise rate on the charge transport process in a voltage cycle is similar to that of the voltage *** enhanced partial discharge activity and induced charges are responsible for accelerated ageing and thus determine the final lifetime of turn-to-turn *** this case,the generalised probabilistic electric lifetime model is applicable to the voltage rise rate as well as the voltage amplitude.

关键词： lifetime inverter insulation

Dynamic Simulation of Distribution Networks Using Multi-stage Discontinuous Galerkin Method

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 185-196页

作者： Ruizhi Yu Wei Gu Weiqi Liu Peixin Li Wei Liu school of electrical Engineering Southeast UniversityNanjing 210096China. the school of electrical Engineering Southeast UniversityNanjing 210096China school of Automation Nanjing University of Science and TechnologyNanjing 210094China

Dynamic simulation plays a fundamental role in security evaluation of distribution networks(DNs).However,the strong stiffness and non-linearity of distributed generation(DG)models in DNs bring about burdensome computation and noteworthy instability on traditional methods which hampers the rapid response of simulation ***,a novel L-stable approximate analytical method with high accuracy is proposed to handle these *** method referred to as multistage discontinuous Galerkin method(MDGM),first derives approximate analytical solutions(AASs)of state variables which are explicit symbolic expressions concerning system ***,in each time window,it substitutes values for symbolic variables and trajectories of state variables are obtained *** paper applies MDGM to DG models to derive ***-truncation-error-based variable step size strategy is also developed to further improve simulation *** addition,this paper establishes detailed MDGM-based dynamic simulation *** case studies on a numerical problem,a modified 33-bus system and a practical large-scale DN,it can be seen that proposed method demonstrates fast and dependable performance compared with the traditional trapezoidal method.

关键词： Approximate analytical method distribution network distributed generation dynamic simulation multi-stage discontinuous Galerkin method variable step size

Deep Global Multiple-Scale and Local Patches Attention Dual-Branch Network for Pose-Invariant Facial Expression Recognition

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 405-440页

作者： Chaoji Liu Xingqiao Liu Chong Chen Kang Zhou school of electrical and Information Engineering Jiangsu UniversityZhenjiang212013China school of electrical Engineering Yancheng Institute of TechnologyYancheng224051China

Pose-invariant facial expression recognition(FER)is an active but challenging research topic in computer *** with the involvement of diverse observation angles,FER makes the training parameter models inconsistent from one view to *** study develops a deep global multiple-scale and local patches attention(GMS-LPA)dual-branch network for pose-invariant FER to weaken the influence of pose variation and selfocclusion on recognition *** this research,the designed GMS-LPA network contains four main parts,i.e.,the feature extraction module,the global multiple-scale(GMS)module,the local patches attention(LPA)module,and the model-level fusion *** feature extraction module is designed to extract and normalize texture information to the same *** GMS model can extract deep global features with different receptive fields,releasing the sensitivity of deeper convolution layers to pose-variant and *** LPA module is built to force the network to focus on local salient features,which can lower the effect of pose variation and self-occlusion on recognition ***,the extracted features are fused with a model-level strategy to improve recognition *** experimentswere conducted on four public databases,and the recognition results demonstrated the feasibility and validity of the proposed methods.

关键词： Pose-invariant FER global multiple-scale(GMS) local patches attention(LPA) model-level fusion