Pub Date : 2022-04-01DOI: 10.1109/ACPEE53904.2022.9783764
Yao Nan, Qin Jian-Hua, Wang Zhen, Wang Hong-Chang
In the substation monitoring environment, monitoring the helmet wearing of workers is an important approach to ensure safety. Because the helmet size in entire surveillance images is often small and the characteristic information is unclear, existing target detection algorithms present the problem of missed detection and omission. A safety helmet detection dynamic model based on the critical area attention mechanism first detected the human target in the image, and then, locked the human head area through the critical area attention mechanism network. Finally, the feature map of the critical areas of the head was up-sampled many times to increase the proportion of the helmet area in the image to highlight the characteristic information of the helmet in the image. The algorithm used the dynamic model method to match the optimum up-sampling times for the helmets of different scales, which improved the recognition speed of the algorithm while ensuring the recognition accuracy. The experimental results showed that the recognition rate of algorithm for helmets was 92.68%, which is considerably higher than that of other target detection algorithms in the same field.
{"title":"Safety Helmet Detection Dynamic Model Based on the Critical Area Attention Mechanism","authors":"Yao Nan, Qin Jian-Hua, Wang Zhen, Wang Hong-Chang","doi":"10.1109/ACPEE53904.2022.9783764","DOIUrl":"https://doi.org/10.1109/ACPEE53904.2022.9783764","url":null,"abstract":"In the substation monitoring environment, monitoring the helmet wearing of workers is an important approach to ensure safety. Because the helmet size in entire surveillance images is often small and the characteristic information is unclear, existing target detection algorithms present the problem of missed detection and omission. A safety helmet detection dynamic model based on the critical area attention mechanism first detected the human target in the image, and then, locked the human head area through the critical area attention mechanism network. Finally, the feature map of the critical areas of the head was up-sampled many times to increase the proportion of the helmet area in the image to highlight the characteristic information of the helmet in the image. The algorithm used the dynamic model method to match the optimum up-sampling times for the helmets of different scales, which improved the recognition speed of the algorithm while ensuring the recognition accuracy. The experimental results showed that the recognition rate of algorithm for helmets was 92.68%, which is considerably higher than that of other target detection algorithms in the same field.","PeriodicalId":118112,"journal":{"name":"2022 7th Asia Conference on Power and Electrical Engineering (ACPEE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115392879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wind power integration makes the uncertainty of power system increasing dramatically, which brings new challenges to the calculation of Total Transfer Capability (TTC). A fast assessment method for probabilistic TTC based on Copula and deep ensemble learning is proposed. Considering wind power output uncertainties and correlation of wind speed in geographical close wind farms, Copula function is adopted to generate scenarios. Stacked Denoising Autoencoder (SDAE) is used to extract features directly from source data. Support Vector Regression (SVR) is selected as regressor and bagging ensemble strategy is applied to further improve the accuracy of the TTC estimation. The case study in simplified Shandong grid validates the effectiveness of the proposed method.
{"title":"Fast Probabilistic TTC Assessment Based on Copula Theory and Deep Ensemble Learning","authors":"Shaopeng Zhang, Jiongcheng Yan, Xin Li, Dong Yang, Huan Ma, Changgang Li","doi":"10.1109/ACPEE53904.2022.9783751","DOIUrl":"https://doi.org/10.1109/ACPEE53904.2022.9783751","url":null,"abstract":"Wind power integration makes the uncertainty of power system increasing dramatically, which brings new challenges to the calculation of Total Transfer Capability (TTC). A fast assessment method for probabilistic TTC based on Copula and deep ensemble learning is proposed. Considering wind power output uncertainties and correlation of wind speed in geographical close wind farms, Copula function is adopted to generate scenarios. Stacked Denoising Autoencoder (SDAE) is used to extract features directly from source data. Support Vector Regression (SVR) is selected as regressor and bagging ensemble strategy is applied to further improve the accuracy of the TTC estimation. The case study in simplified Shandong grid validates the effectiveness of the proposed method.","PeriodicalId":118112,"journal":{"name":"2022 7th Asia Conference on Power and Electrical Engineering (ACPEE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117162574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper analyzes the small disturbance characteristics of voltage source converter (VSC) in the frequency domain, expounds the process in which the small harmonic disturbance of the grid voltage participates in the operation of the VSC, clarifies the generation mechanism of the disturbance frequency current and the disturbance coupling frequency current. The small disturbance impedance model of VSC considering the dynamic characteristics of phase-locked loop (PLL) is established by using the harmonic linearization method. The simulation model in PSCAD/EMTDC verifies the correctness of the small disturbance impedance model. Theoretical analysis and simulation show that the converter control parameters and PLL parameters will affect the impedance characteristics of small disturbance impedance.
{"title":"Study On Small Disturbance Characteristics Of Ac Side Of Grid-connected VSC","authors":"Runze Bai, Yuanxin Zhang, Zehong Yu, Yongqiang Zhu","doi":"10.1109/ACPEE53904.2022.9783997","DOIUrl":"https://doi.org/10.1109/ACPEE53904.2022.9783997","url":null,"abstract":"This paper analyzes the small disturbance characteristics of voltage source converter (VSC) in the frequency domain, expounds the process in which the small harmonic disturbance of the grid voltage participates in the operation of the VSC, clarifies the generation mechanism of the disturbance frequency current and the disturbance coupling frequency current. The small disturbance impedance model of VSC considering the dynamic characteristics of phase-locked loop (PLL) is established by using the harmonic linearization method. The simulation model in PSCAD/EMTDC verifies the correctness of the small disturbance impedance model. Theoretical analysis and simulation show that the converter control parameters and PLL parameters will affect the impedance characteristics of small disturbance impedance.","PeriodicalId":118112,"journal":{"name":"2022 7th Asia Conference on Power and Electrical Engineering (ACPEE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117240835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Electric vehicles as controllable loads connected to the grid can improve the utilization of wind and PV and thus reduce the amount of renewable energy curtailment, but if they are not regulated, they can cause harm to the operation of the grid. This article adopts an algorithm called cuckoo search which has global convergence is used to perform a two-stage optimization of the system load. In the first stage, the amount of wind and solar power curtailment is optimized, and it is obvious that the amount of new energy consumption increases from 5423kW to 5842kW, but the power consumption in peak hours increases significantly, forming a phenomenon of "peaking on peak". Compared with the first stage, the peak load curve is smoothed out during the second stage and the valley load curve is filled, and the difference between the highest and lowest value of the electricity load is reduced from 254 kW to 198 kW. The results show that this optimization method not only increases the amount of new energy consumption, but also stabilizes the load fluctuations in order to mitigate the impact of large-scale electric vehicle charging on the electric grid.
{"title":"Orderly charging of electric vehicles considering new energy consumption and system peak-to-valley differences","authors":"Chen Yiyao, Xue Yingnan, Wu Yingying, Liang Yaojun, Wang Qianchun, Duan Xinhui","doi":"10.1109/ACPEE53904.2022.9784024","DOIUrl":"https://doi.org/10.1109/ACPEE53904.2022.9784024","url":null,"abstract":"Electric vehicles as controllable loads connected to the grid can improve the utilization of wind and PV and thus reduce the amount of renewable energy curtailment, but if they are not regulated, they can cause harm to the operation of the grid. This article adopts an algorithm called cuckoo search which has global convergence is used to perform a two-stage optimization of the system load. In the first stage, the amount of wind and solar power curtailment is optimized, and it is obvious that the amount of new energy consumption increases from 5423kW to 5842kW, but the power consumption in peak hours increases significantly, forming a phenomenon of \"peaking on peak\". Compared with the first stage, the peak load curve is smoothed out during the second stage and the valley load curve is filled, and the difference between the highest and lowest value of the electricity load is reduced from 254 kW to 198 kW. The results show that this optimization method not only increases the amount of new energy consumption, but also stabilizes the load fluctuations in order to mitigate the impact of large-scale electric vehicle charging on the electric grid.","PeriodicalId":118112,"journal":{"name":"2022 7th Asia Conference on Power and Electrical Engineering (ACPEE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117345530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-01DOI: 10.1109/ACPEE53904.2022.9783909
Zitong Wang, Gengfeng Li, Yao Xiao, Shunyu Tang, Mengjie Teng
Scheduling a multi-regional unit commitment is an efficient way to operate the power system economically. The conventional unit commitment models, which adopts the DC power flow, fail to take the network loss and voltage drop constraints into account. This paper proposes a novel AC power flow model to fill this gap. The proposed model first achieves convexity by decomposing the nonlinear part of the network loss into the voltage amplitude part and the phase angle part, and then is formulated into two sets of linear inequalities. After that, this paper integrates it into a multi-regional unit commitment. Considering the independence and parallelism of operation between regions, the established unit commitment is solved via a parallel decentralized solution, where the simplicial decomposition method (SDM), the nonlinear block Gauss-Seidel (GS) method, and the augmented Lagrangian method (ALM) (abbreviated as SDM-GS-ALM) are integrated. Finally, the efficiency and applicability of the multi-regional unit commitment with convex AC power flow constraints are verified on IEEE Test Systems.
{"title":"A Parallel Decentralized Solution for Multi-Regional Unit Commitment with Convex AC Power Flow Constraints","authors":"Zitong Wang, Gengfeng Li, Yao Xiao, Shunyu Tang, Mengjie Teng","doi":"10.1109/ACPEE53904.2022.9783909","DOIUrl":"https://doi.org/10.1109/ACPEE53904.2022.9783909","url":null,"abstract":"Scheduling a multi-regional unit commitment is an efficient way to operate the power system economically. The conventional unit commitment models, which adopts the DC power flow, fail to take the network loss and voltage drop constraints into account. This paper proposes a novel AC power flow model to fill this gap. The proposed model first achieves convexity by decomposing the nonlinear part of the network loss into the voltage amplitude part and the phase angle part, and then is formulated into two sets of linear inequalities. After that, this paper integrates it into a multi-regional unit commitment. Considering the independence and parallelism of operation between regions, the established unit commitment is solved via a parallel decentralized solution, where the simplicial decomposition method (SDM), the nonlinear block Gauss-Seidel (GS) method, and the augmented Lagrangian method (ALM) (abbreviated as SDM-GS-ALM) are integrated. Finally, the efficiency and applicability of the multi-regional unit commitment with convex AC power flow constraints are verified on IEEE Test Systems.","PeriodicalId":118112,"journal":{"name":"2022 7th Asia Conference on Power and Electrical Engineering (ACPEE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125846733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-01DOI: 10.1109/ACPEE53904.2022.9784027
Bin Wang, Hong Zhang, M. Cao, Zhijie Qian, Dongcheng Zhou
Distribution transformer goes deep into the load center, and its vibration and noise problems are becoming more and more prominent. Taking a distribution transformer as object of study, firstly, the vibration analysis model of transformer tank is established, the analysis of oil tank vibration mode is carried out, and obtain the vibration modes of transformer oil tank with different thickness. Secondly, combined with the characteristics of distribution transformer tank wall vibration and vibration source, the design parameters of transformer tank wall vibration absorption are analyzed; Finally, the vibration and noise test of transformer with or without vibration absorber under rated voltage is carried out on the test transformer. The research shows that the vibration mode frequency of transformer oil tank increases linearly with the thickness of tank wall. Blindly increasing the wall thickness will significantly increase the frequency of tank wall, resulting in the same frequency resonance between tank wall and vibration source. Setting single and multiple vibration absorbers on the tank wall can effectively reduce the vibration acceleration of transformer tank wall, but multiple vibration absorber systems are more sensitive to the design parameters. Therefore, Reasonably setting the design stiffness and design quality of the vibration absorber is the key to ensure the function of the tank wall vibration absorber. By adopting a reasonable design scheme, the average vibration reduction on the surface of the oil tank can exceed 20dB. The above research has a good reference for the vibration and noise control of transformer tank wall.
{"title":"Parameter analysis and experimental verification of dynamic vibration absorption design for transformer tank wall","authors":"Bin Wang, Hong Zhang, M. Cao, Zhijie Qian, Dongcheng Zhou","doi":"10.1109/ACPEE53904.2022.9784027","DOIUrl":"https://doi.org/10.1109/ACPEE53904.2022.9784027","url":null,"abstract":"Distribution transformer goes deep into the load center, and its vibration and noise problems are becoming more and more prominent. Taking a distribution transformer as object of study, firstly, the vibration analysis model of transformer tank is established, the analysis of oil tank vibration mode is carried out, and obtain the vibration modes of transformer oil tank with different thickness. Secondly, combined with the characteristics of distribution transformer tank wall vibration and vibration source, the design parameters of transformer tank wall vibration absorption are analyzed; Finally, the vibration and noise test of transformer with or without vibration absorber under rated voltage is carried out on the test transformer. The research shows that the vibration mode frequency of transformer oil tank increases linearly with the thickness of tank wall. Blindly increasing the wall thickness will significantly increase the frequency of tank wall, resulting in the same frequency resonance between tank wall and vibration source. Setting single and multiple vibration absorbers on the tank wall can effectively reduce the vibration acceleration of transformer tank wall, but multiple vibration absorber systems are more sensitive to the design parameters. Therefore, Reasonably setting the design stiffness and design quality of the vibration absorber is the key to ensure the function of the tank wall vibration absorber. By adopting a reasonable design scheme, the average vibration reduction on the surface of the oil tank can exceed 20dB. The above research has a good reference for the vibration and noise control of transformer tank wall.","PeriodicalId":118112,"journal":{"name":"2022 7th Asia Conference on Power and Electrical Engineering (ACPEE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126746003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In view of the low efficiency of the current distribution transformer fault diagnosis methods, a transformer state identification method based on improved deep belief network(DBN) is proposed in this paper. Firstly, the operation state data of distribution transformer is classified, analyzed and standardized. On this basis, the bidirectional random butterfly optimization algorithm is used to dynamically optimize the parameters of the DBN, so as to provide the efficient calculation and processing state of the whole cycle of diagnosis and analysis, and realize the accurate and effective fault identification and diagnosis of transformer. The simulation results show that the accuracy of the proposed fault identification method is 98.76% and the analysis time is 7.456s, which has good network performance.
{"title":"Fault diagnosis method of distribution transformer based on improved deep learning","authors":"Yunfeng Liu, Mengnan Li, Yi-Min Peng, Hongshan Zhao","doi":"10.1109/ACPEE53904.2022.9783871","DOIUrl":"https://doi.org/10.1109/ACPEE53904.2022.9783871","url":null,"abstract":"In view of the low efficiency of the current distribution transformer fault diagnosis methods, a transformer state identification method based on improved deep belief network(DBN) is proposed in this paper. Firstly, the operation state data of distribution transformer is classified, analyzed and standardized. On this basis, the bidirectional random butterfly optimization algorithm is used to dynamically optimize the parameters of the DBN, so as to provide the efficient calculation and processing state of the whole cycle of diagnosis and analysis, and realize the accurate and effective fault identification and diagnosis of transformer. The simulation results show that the accuracy of the proposed fault identification method is 98.76% and the analysis time is 7.456s, which has good network performance.","PeriodicalId":118112,"journal":{"name":"2022 7th Asia Conference on Power and Electrical Engineering (ACPEE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115254223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-01DOI: 10.1109/ACPEE53904.2022.9783832
Ai Maomin, An Junwei, Sun Congcong, Wang Qingze, Zhang Shouqiang, Zhang Jiaming
Distribution network overhaul without power interruption is an important means to improve power supply reliability. In this paper, in order to analyze the influencing factors of distribution network overhaul without power interruption, the research is carried out by using analytic hierarchy process (AHP). Firstly, the influencing factors of distribution network overhaul without power interruption is listed and the hierarchical evaluation index system is constructed according to the principles of comprehensiveness, independence and practicability; Then, the judgment matrix is constructed and AHP is used for calculation, and the weight coefficient of influencing factors is output to provide the basis for decision-makers to implement policies; Finally, combined with the status in a certain area, the results show that the method can judge the importance of influencing factors accurately and improve the ability of distribution network overhaul without power interruption.
{"title":"Research on Influencing Factors of Distribution Network Overhaul without Power Interruption Based on Analytic Hierarchy Process","authors":"Ai Maomin, An Junwei, Sun Congcong, Wang Qingze, Zhang Shouqiang, Zhang Jiaming","doi":"10.1109/ACPEE53904.2022.9783832","DOIUrl":"https://doi.org/10.1109/ACPEE53904.2022.9783832","url":null,"abstract":"Distribution network overhaul without power interruption is an important means to improve power supply reliability. In this paper, in order to analyze the influencing factors of distribution network overhaul without power interruption, the research is carried out by using analytic hierarchy process (AHP). Firstly, the influencing factors of distribution network overhaul without power interruption is listed and the hierarchical evaluation index system is constructed according to the principles of comprehensiveness, independence and practicability; Then, the judgment matrix is constructed and AHP is used for calculation, and the weight coefficient of influencing factors is output to provide the basis for decision-makers to implement policies; Finally, combined with the status in a certain area, the results show that the method can judge the importance of influencing factors accurately and improve the ability of distribution network overhaul without power interruption.","PeriodicalId":118112,"journal":{"name":"2022 7th Asia Conference on Power and Electrical Engineering (ACPEE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115321654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-01DOI: 10.1109/ACPEE53904.2022.9783897
Wu Zhequan, Yin Dejun, Chen Lujun, Fu Jia
Taking permanent magnet assisted synchronous reluctance motor (PM-SynRM) as the research object, aiming at the problem of large torque ripple, Proposing a design method of motor magnetic barrier angle based on minimum torque ripple. Firstly, analyzing the source of torque ripple of permanent magnet assisted synchronous reluctance motor, and offsetting the positive and negative ripple to weaken the torque ripple. Secondly, deducing the angle between two adjacent magnetic barriers and included angle of magnetic barrier of the permanent magnet assisted synchronous reluctance motor with different slot pole matching and the number of magnetic barrier layers. Finally, designing and manufacturing the prototype according to the deduced magnetic barrier angle, and testing motor performance with bench. The test results are basically consistent with the simulation results. The results show that the magnetic barrier angle design method can minimize the torque ripple of the motor.
{"title":"Design of Magnetic Barrier Angle of Permanent Magnet Assisted Synchronous Reluctance Motor Based on Minimum Torque Ripple","authors":"Wu Zhequan, Yin Dejun, Chen Lujun, Fu Jia","doi":"10.1109/ACPEE53904.2022.9783897","DOIUrl":"https://doi.org/10.1109/ACPEE53904.2022.9783897","url":null,"abstract":"Taking permanent magnet assisted synchronous reluctance motor (PM-SynRM) as the research object, aiming at the problem of large torque ripple, Proposing a design method of motor magnetic barrier angle based on minimum torque ripple. Firstly, analyzing the source of torque ripple of permanent magnet assisted synchronous reluctance motor, and offsetting the positive and negative ripple to weaken the torque ripple. Secondly, deducing the angle between two adjacent magnetic barriers and included angle of magnetic barrier of the permanent magnet assisted synchronous reluctance motor with different slot pole matching and the number of magnetic barrier layers. Finally, designing and manufacturing the prototype according to the deduced magnetic barrier angle, and testing motor performance with bench. The test results are basically consistent with the simulation results. The results show that the magnetic barrier angle design method can minimize the torque ripple of the motor.","PeriodicalId":118112,"journal":{"name":"2022 7th Asia Conference on Power and Electrical Engineering (ACPEE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122842711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to solve the problems of low real-time and insufficient accuracy of the current substation equipment state analysis methods, this paper proposes an independent and controllable security container substation equipment state monitoring method based on cloud edge cooperation mode. This method combines edge computing technology with cloud computing technology to build a cloud edge collaborative architecture for power equipment state analysis; On the edge side, the ordered processing of data is realized based on correlation analysis method to provide reliable and complete data support; On the cloud side of the master station, dynamic power equipment state analysis is realized based on C4.5 decision tree algorithm. The simulation experiment takes SF6 circuit breaker as an example. The experimental results show that the state recognition accuracy of the proposed method is more than 95% and has good state analysis performance.
{"title":"Independent and controllable security container substation equipment condition monitoring method based on cloud edge cooperation","authors":"Yingwei Zhu, Dong Liu, Yinqiang Huang, Lixiang Ruan","doi":"10.1109/ACPEE53904.2022.9783815","DOIUrl":"https://doi.org/10.1109/ACPEE53904.2022.9783815","url":null,"abstract":"In order to solve the problems of low real-time and insufficient accuracy of the current substation equipment state analysis methods, this paper proposes an independent and controllable security container substation equipment state monitoring method based on cloud edge cooperation mode. This method combines edge computing technology with cloud computing technology to build a cloud edge collaborative architecture for power equipment state analysis; On the edge side, the ordered processing of data is realized based on correlation analysis method to provide reliable and complete data support; On the cloud side of the master station, dynamic power equipment state analysis is realized based on C4.5 decision tree algorithm. The simulation experiment takes SF6 circuit breaker as an example. The experimental results show that the state recognition accuracy of the proposed method is more than 95% and has good state analysis performance.","PeriodicalId":118112,"journal":{"name":"2022 7th Asia Conference on Power and Electrical Engineering (ACPEE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122858078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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