Pub Date : 2022-12-09DOI: 10.1109/SPIES55999.2022.10082255
Lixiong Sun, Q. Ye, Rongye Yang, Chaochao Yang, Qigen Zhao, Hu Zhao
In order to master the arc characteristics of high-voltage SF6 circuit breaker during the breaking process, the arc characteristics detection method of SF6 circuit breaker is studied. The physical parameters such as arc voltage, current, nozzle dynamic pressure, and after arc current are tested. The relationship between arc quenching peak, after arc current value, nozzle throat pressure change and expected short-circuit current and charging pressure is analyzed. The results show that the increase of short-circuit current is expected to reduce the dielectric recovery strength of the arc gap when the arc current crosses zero, and the increase of charging pressure is conducive to the improvement of dielectric recovery strength of the arc gap when the arc current crosses zero.
{"title":"Experimental Study on Arc Physical Parameters of High Voltage SF6 Circuit Breaker","authors":"Lixiong Sun, Q. Ye, Rongye Yang, Chaochao Yang, Qigen Zhao, Hu Zhao","doi":"10.1109/SPIES55999.2022.10082255","DOIUrl":"https://doi.org/10.1109/SPIES55999.2022.10082255","url":null,"abstract":"In order to master the arc characteristics of high-voltage SF6 circuit breaker during the breaking process, the arc characteristics detection method of SF6 circuit breaker is studied. The physical parameters such as arc voltage, current, nozzle dynamic pressure, and after arc current are tested. The relationship between arc quenching peak, after arc current value, nozzle throat pressure change and expected short-circuit current and charging pressure is analyzed. The results show that the increase of short-circuit current is expected to reduce the dielectric recovery strength of the arc gap when the arc current crosses zero, and the increase of charging pressure is conducive to the improvement of dielectric recovery strength of the arc gap when the arc current crosses zero.","PeriodicalId":412421,"journal":{"name":"2022 4th International Conference on Smart Power & Internet Energy Systems (SPIES)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124486748","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 : 2022-12-09DOI: 10.1109/SPIES55999.2022.10082120
Yajuan Wang, Bo Liu, Weichen Liang, Xuan Li, Zhi-xue Zhao, Bowen Liu
The feeder terminal unit (FTU) is the core equipment for realizing power distribution automation. In this paper, the logic function model of the feeder terminal unit is established based on the electromagnetic transient simulation platform. First of all, the functions of the feeder terminal unit are clarified, including measurement, protection and control functions. Then, the action logic of the feeder terminal unit is designed, and the power distribution terminal model is established by using the logic custom module of the electromagnetic transient simulation platform. Finally, a simple distribution network model is established to verify the rationality of the parameter configuration of the feeder terminal unit model established in this paper and the action logic of the coordination of multiple feeder terminal units. The model serves as a simulation reference for the actual feeder terminal unit to put into operation the distribution network, which is beneficial to improve the power supply reliability of the distribution network.
{"title":"Feeder Terminal Unit Model Based on Electromagnetic Transient Simulation Platform","authors":"Yajuan Wang, Bo Liu, Weichen Liang, Xuan Li, Zhi-xue Zhao, Bowen Liu","doi":"10.1109/SPIES55999.2022.10082120","DOIUrl":"https://doi.org/10.1109/SPIES55999.2022.10082120","url":null,"abstract":"The feeder terminal unit (FTU) is the core equipment for realizing power distribution automation. In this paper, the logic function model of the feeder terminal unit is established based on the electromagnetic transient simulation platform. First of all, the functions of the feeder terminal unit are clarified, including measurement, protection and control functions. Then, the action logic of the feeder terminal unit is designed, and the power distribution terminal model is established by using the logic custom module of the electromagnetic transient simulation platform. Finally, a simple distribution network model is established to verify the rationality of the parameter configuration of the feeder terminal unit model established in this paper and the action logic of the coordination of multiple feeder terminal units. The model serves as a simulation reference for the actual feeder terminal unit to put into operation the distribution network, which is beneficial to improve the power supply reliability of the distribution network.","PeriodicalId":412421,"journal":{"name":"2022 4th International Conference on Smart Power & Internet Energy Systems (SPIES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125739290","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 : 2022-12-09DOI: 10.1109/SPIES55999.2022.10082322
L. Luo, Xingmao Wen, Xinjin Luo, W. Qin
In this paper, the distribution of magnetic flux leakage and force in transformer short circuit are calculated by using two-dimensional finite element model of transformer. Based on the calculation of magnetic field and force, the blocks and disks of Transformer Winding models of three-dimensional single-coil winding are further analyzed. The factors affecting the axial stability of transformer are studied. Through finite element simulation software, the influence of three working conditions on the axial stability of winding are calculated, including the accumulation of multiple short-circuit impact, assembly defects and different design of supporting structure. This paper lays a foundation for the subsequent study of the axial stability of transformer and the cumulative effect of short circuit.
{"title":"Research on Axial Stability of Power Transformer Windings","authors":"L. Luo, Xingmao Wen, Xinjin Luo, W. Qin","doi":"10.1109/SPIES55999.2022.10082322","DOIUrl":"https://doi.org/10.1109/SPIES55999.2022.10082322","url":null,"abstract":"In this paper, the distribution of magnetic flux leakage and force in transformer short circuit are calculated by using two-dimensional finite element model of transformer. Based on the calculation of magnetic field and force, the blocks and disks of Transformer Winding models of three-dimensional single-coil winding are further analyzed. The factors affecting the axial stability of transformer are studied. Through finite element simulation software, the influence of three working conditions on the axial stability of winding are calculated, including the accumulation of multiple short-circuit impact, assembly defects and different design of supporting structure. This paper lays a foundation for the subsequent study of the axial stability of transformer and the cumulative effect of short circuit.","PeriodicalId":412421,"journal":{"name":"2022 4th International Conference on Smart Power & Internet Energy Systems (SPIES)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125973685","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 : 2022-12-09DOI: 10.1109/SPIES55999.2022.10082212
Xiaoqing Ji, Zhaoxia Li, Xiaoyan Jiang, Dechang Yang
Accurate short-term wind power output prediction is of great significance to the operation and dispatch of power systems. To improve the accuracy of short-term wind power output prediction, a prediction model based on the temporal graph convolutional network is proposed. First of all, a temporal convolutional network is used to mine the temporal features of wind power output. Moreover, a graphical convolutional network is utilized to capture the relevant features between wind power output and meteorological data. Furthermore, a hybrid structure is presented, in which the temporal and relevant features are converted into the actual wind power output values in the future. The simulation results show that the proposed method has good adaptability in the short-term wind power prediction tasks for different seasons and time-scales. Meanwhile, for noise-laden prediction scenarios, it has significant advantages compared with the existing methods.
{"title":"Short-Term Wind Power Output Prediction Based on Temporal Graph Convolutional Networks","authors":"Xiaoqing Ji, Zhaoxia Li, Xiaoyan Jiang, Dechang Yang","doi":"10.1109/SPIES55999.2022.10082212","DOIUrl":"https://doi.org/10.1109/SPIES55999.2022.10082212","url":null,"abstract":"Accurate short-term wind power output prediction is of great significance to the operation and dispatch of power systems. To improve the accuracy of short-term wind power output prediction, a prediction model based on the temporal graph convolutional network is proposed. First of all, a temporal convolutional network is used to mine the temporal features of wind power output. Moreover, a graphical convolutional network is utilized to capture the relevant features between wind power output and meteorological data. Furthermore, a hybrid structure is presented, in which the temporal and relevant features are converted into the actual wind power output values in the future. The simulation results show that the proposed method has good adaptability in the short-term wind power prediction tasks for different seasons and time-scales. Meanwhile, for noise-laden prediction scenarios, it has significant advantages compared with the existing methods.","PeriodicalId":412421,"journal":{"name":"2022 4th International Conference on Smart Power & Internet Energy Systems (SPIES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125989477","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 : 2022-12-09DOI: 10.1109/SPIES55999.2022.10081994
Waqas Hassan, E. Semshikov, M. Negnevitsky, Md. Alamgir Hossain
Traditional offshore microgrids such as drilling rigs and oil and gas platforms rely on diesel generators to provide their electricity needs. With the recent developments in offshore wind, solar and wave generation, and the maturity growth of the energy storage technology, the offshore microgrids are transitioning away from diesel generation. When the majority of the energy sources and loads is DC-native or rely on conversion to DC, setting up the network as a DC microgrid becomes a viable option. Using DC coupling in offshore microgrids eliminates the problems of harmonic distortion, low inertia and overcomplicated control. However, with the high penetration of intermittent generation, the provision of DC microgrid stability becomes a challenging task. This is particularly acute within practical DC microgrids since, at this stage, there are not many off-the-shelf DC components. This paper describes the experimental lab facilities set up for offshore DC microgrid research and investigates the stability issues presented in the renewable energy-based DC microgrid.
{"title":"Stability Assessment of Renewable Energy-Based DC Microgrids for Offshore Applications","authors":"Waqas Hassan, E. Semshikov, M. Negnevitsky, Md. Alamgir Hossain","doi":"10.1109/SPIES55999.2022.10081994","DOIUrl":"https://doi.org/10.1109/SPIES55999.2022.10081994","url":null,"abstract":"Traditional offshore microgrids such as drilling rigs and oil and gas platforms rely on diesel generators to provide their electricity needs. With the recent developments in offshore wind, solar and wave generation, and the maturity growth of the energy storage technology, the offshore microgrids are transitioning away from diesel generation. When the majority of the energy sources and loads is DC-native or rely on conversion to DC, setting up the network as a DC microgrid becomes a viable option. Using DC coupling in offshore microgrids eliminates the problems of harmonic distortion, low inertia and overcomplicated control. However, with the high penetration of intermittent generation, the provision of DC microgrid stability becomes a challenging task. This is particularly acute within practical DC microgrids since, at this stage, there are not many off-the-shelf DC components. This paper describes the experimental lab facilities set up for offshore DC microgrid research and investigates the stability issues presented in the renewable energy-based DC microgrid.","PeriodicalId":412421,"journal":{"name":"2022 4th International Conference on Smart Power & Internet Energy Systems (SPIES)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124769701","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 : 2022-12-09DOI: 10.1109/SPIES55999.2022.10082007
Jinwen Li, Zhongwei Deng, Xiaosong Hu
Battery health monitoring is critical for the safe management and sustainable maintenance of electrical equipment. The uncertainty of battery usage scenarios and the huge cost of aging experiments make it a challenge to construct accurate and general-purpose battery lifetime prediction models. In this paper, based on the multi-output Gaussian process (MOGP) with transfer learning, the battery aging data under different working conditions can be applied to accurately predict the capacity trajectory. The performance of the two dominant MOGP models, symmetric and asymmetric, in battery capacity prediction, is thoroughly analyzed, and compared with other machine learning algorithms. Two different types of batteries with different working conditions are used to verify the performance of the models. Considering the performance of the model for different aging degrees, the battery degradation is divided into two stages: early stage and late stage. The MOGPs are proved to be the best performer. The asymmetric MOGP is suitable for the rapid prediction of batteries in the late aging stage, while the symmetrical MOGP can accurately predict the change of capacity trajectory and has high robustness to batteries at different aging stages. The average mean absolute errors (MAEs) of the symmetrical MOGP with three outputs for the early prediction of different batteries are only 0.027Ah and 0.017Ah, respectively.
{"title":"Battery Capacity Trajectory Prediction with Multi-output Gaussian Process","authors":"Jinwen Li, Zhongwei Deng, Xiaosong Hu","doi":"10.1109/SPIES55999.2022.10082007","DOIUrl":"https://doi.org/10.1109/SPIES55999.2022.10082007","url":null,"abstract":"Battery health monitoring is critical for the safe management and sustainable maintenance of electrical equipment. The uncertainty of battery usage scenarios and the huge cost of aging experiments make it a challenge to construct accurate and general-purpose battery lifetime prediction models. In this paper, based on the multi-output Gaussian process (MOGP) with transfer learning, the battery aging data under different working conditions can be applied to accurately predict the capacity trajectory. The performance of the two dominant MOGP models, symmetric and asymmetric, in battery capacity prediction, is thoroughly analyzed, and compared with other machine learning algorithms. Two different types of batteries with different working conditions are used to verify the performance of the models. Considering the performance of the model for different aging degrees, the battery degradation is divided into two stages: early stage and late stage. The MOGPs are proved to be the best performer. The asymmetric MOGP is suitable for the rapid prediction of batteries in the late aging stage, while the symmetrical MOGP can accurately predict the change of capacity trajectory and has high robustness to batteries at different aging stages. The average mean absolute errors (MAEs) of the symmetrical MOGP with three outputs for the early prediction of different batteries are only 0.027Ah and 0.017Ah, respectively.","PeriodicalId":412421,"journal":{"name":"2022 4th International Conference on Smart Power & Internet Energy Systems (SPIES)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128693889","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}
Power equipment inspection aims to discover and eliminate equipment defects and potential safety hazards timely and ensure the safe operation of equipment. Now a large number of graph structure data have emerged in the equipment inspection field to improve the organization, management, and cognitive ability of knowledge. As a key step in the inspection business, equipment defect grading is used to determine the severity that affects the safe operation of equipment, so the accuracy and generalization ability of the model are required to be high. The pooling operation of traditional graph neural networks has the problem of information loss. Therefore, this paper introduces the multi-scale mechanism to improve the accuracy and generalization ability of the model and realize the accurate grading of equipment defects. By conducting experiments on NCI-1 and CEPRI_EQUIP datasets and comparing the proposed algorithm with baseline methods, the significant performance of the proposed algorithm is verified.
{"title":"Graph Computing Based Electric Power Equipment Defect Grading with Multi-scale Mechanism","authors":"Jiao Fei, Zhenyuan Ma, Jiannan Xu, Yuanpeng Tan, Minghui Duan, Tong Jie","doi":"10.1109/SPIES55999.2022.10082595","DOIUrl":"https://doi.org/10.1109/SPIES55999.2022.10082595","url":null,"abstract":"Power equipment inspection aims to discover and eliminate equipment defects and potential safety hazards timely and ensure the safe operation of equipment. Now a large number of graph structure data have emerged in the equipment inspection field to improve the organization, management, and cognitive ability of knowledge. As a key step in the inspection business, equipment defect grading is used to determine the severity that affects the safe operation of equipment, so the accuracy and generalization ability of the model are required to be high. The pooling operation of traditional graph neural networks has the problem of information loss. Therefore, this paper introduces the multi-scale mechanism to improve the accuracy and generalization ability of the model and realize the accurate grading of equipment defects. By conducting experiments on NCI-1 and CEPRI_EQUIP datasets and comparing the proposed algorithm with baseline methods, the significant performance of the proposed algorithm is verified.","PeriodicalId":412421,"journal":{"name":"2022 4th International Conference on Smart Power & Internet Energy Systems (SPIES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129535885","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 : 2022-12-09DOI: 10.1109/SPIES55999.2022.10082077
Chenyao Xu, M. Dong, Li Li, Ruijin Liang, Wenrui Yan
With the widespread use and development of power electronics, the study of power electronics, especially power electronics topology, has become increasingly compelling. With the study and expansion of graph theory on power electronics topology, it has become an idea to describe and reveal the topology by graph structures. We propose a framework combining the TopoDiffVAE model and reinforcement learning to reveal and learn the intrinsic connection rules of a certain class of topology and generate new topology based on them. Our model can be used not only to generate new topology, but also to accelerate the generation of other neural network-based topology.
{"title":"Power Electronics Converters Topology Derivation with Combination of TopoDiffVAE and Reinforcement Learning","authors":"Chenyao Xu, M. Dong, Li Li, Ruijin Liang, Wenrui Yan","doi":"10.1109/SPIES55999.2022.10082077","DOIUrl":"https://doi.org/10.1109/SPIES55999.2022.10082077","url":null,"abstract":"With the widespread use and development of power electronics, the study of power electronics, especially power electronics topology, has become increasingly compelling. With the study and expansion of graph theory on power electronics topology, it has become an idea to describe and reveal the topology by graph structures. We propose a framework combining the TopoDiffVAE model and reinforcement learning to reveal and learn the intrinsic connection rules of a certain class of topology and generate new topology based on them. Our model can be used not only to generate new topology, but also to accelerate the generation of other neural network-based topology.","PeriodicalId":412421,"journal":{"name":"2022 4th International Conference on Smart Power & Internet Energy Systems (SPIES)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127242649","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}
Grid-following converters may experience loss of synchronization, especially when power system becomes weak or grid fault occurs. So far, it has been found that this phenomenon is associated with Phase-Locked Loop (PLL) dynamics and several methods to analyze such issues have been proposed. However, it seems that the impact of electromagnetic transient process caused by converter current variation or grid voltage drop is not well investigated in these methods. In this article, a systematic method considering such electromagnetic transients for PLL stability assessment is presented. According to the proposed approach, the PLL performance involving the electromagnetic transient process is derived by using differential equations in time domain. Moreover, based on the nonlinear system theory, a scheme for PLL stability evaluation is designed. The effect of the electromagnetic transients on the stability of PLL system is also discussed. The accuracy of the proposed method is validated through simulation.
{"title":"Evaluation of Phase-Locked Loop Stability Considering Electromagnetic Transient Process","authors":"Xiaoge Liu, Chaobo Dai, Zhichang Yang, Zhanfeng Deng, Guoliang Zhao","doi":"10.1109/SPIES55999.2022.10082510","DOIUrl":"https://doi.org/10.1109/SPIES55999.2022.10082510","url":null,"abstract":"Grid-following converters may experience loss of synchronization, especially when power system becomes weak or grid fault occurs. So far, it has been found that this phenomenon is associated with Phase-Locked Loop (PLL) dynamics and several methods to analyze such issues have been proposed. However, it seems that the impact of electromagnetic transient process caused by converter current variation or grid voltage drop is not well investigated in these methods. In this article, a systematic method considering such electromagnetic transients for PLL stability assessment is presented. According to the proposed approach, the PLL performance involving the electromagnetic transient process is derived by using differential equations in time domain. Moreover, based on the nonlinear system theory, a scheme for PLL stability evaluation is designed. The effect of the electromagnetic transients on the stability of PLL system is also discussed. The accuracy of the proposed method is validated through simulation.","PeriodicalId":412421,"journal":{"name":"2022 4th International Conference on Smart Power & Internet Energy Systems (SPIES)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129086553","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 : 2022-12-09DOI: 10.1109/SPIES55999.2022.10082325
Li Ning, Hu Jia-le, Xiao Zi-Han, Shen Pan-Pan, Gong Xu-Yang, Zhao Dan
Taking the five-level Neutral Point Clamped (NPC) converter as the research object, aiming at the problem of unbalanced voltage of the DC side capacitor caused by the traditional SVPWM, the hybrid SVPWM capacitor voltage balance control strategy is adopted. In the low modulation area, a five-level DC side capacitor voltage self-balancing strategy is proposed. Through the voltage deviation and the direction of the flowing current, the real-time dynamic Select the optimal redundancy state, and propose a control strategy based on active current to achieve DC-side capacitor voltage balance in the high modulation region. By judging the direction of the active current and the deviation of the capacitor voltage, combining the relationship between the capacitor current and the phase current and all the five-stage switching sequences, the optimal switching sequence is selected so that the maximum capacitive voltage deviation is reduced to zero as much as possible. The effectiveness of the modulation method proposed in this paper is proved by experimental simulation.
{"title":"DC Capacitor Voltage Control Strategy of Five-level NPC Converter Based on Hybrid SVPWM","authors":"Li Ning, Hu Jia-le, Xiao Zi-Han, Shen Pan-Pan, Gong Xu-Yang, Zhao Dan","doi":"10.1109/SPIES55999.2022.10082325","DOIUrl":"https://doi.org/10.1109/SPIES55999.2022.10082325","url":null,"abstract":"Taking the five-level Neutral Point Clamped (NPC) converter as the research object, aiming at the problem of unbalanced voltage of the DC side capacitor caused by the traditional SVPWM, the hybrid SVPWM capacitor voltage balance control strategy is adopted. In the low modulation area, a five-level DC side capacitor voltage self-balancing strategy is proposed. Through the voltage deviation and the direction of the flowing current, the real-time dynamic Select the optimal redundancy state, and propose a control strategy based on active current to achieve DC-side capacitor voltage balance in the high modulation region. By judging the direction of the active current and the deviation of the capacitor voltage, combining the relationship between the capacitor current and the phase current and all the five-stage switching sequences, the optimal switching sequence is selected so that the maximum capacitive voltage deviation is reduced to zero as much as possible. The effectiveness of the modulation method proposed in this paper is proved by experimental simulation.","PeriodicalId":412421,"journal":{"name":"2022 4th International Conference on Smart Power & Internet Energy Systems (SPIES)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128885198","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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