In order to study the effect of AC aging on space charge characteristics of low-density polyethylene (LDPE) films, an AC electric field of 50 kV/mm (peak value) was adopted for the accelerated aging test and space charge measurements of AC aged LDPE films were carried out subsequently. The results show that no significant space charge accumulation in the LDPE samples aged under a 50 kV/mm AC electric field. It can be seen that a significant positive space charge accumulation occurs inside the sample, when DC electric fields were applied to the AC aged LDPE samples. The long-term AC aging also causes more and deeper cracks on the surface of LDPE samples. Moreover, AC aging promotes the oxidation reaction of LDPE. The longer the aging time, the higher the degree of oxidation. On this basis, the probable relationship between space charge characteristics and material physicochemical properties of LDPE during AC electrical aging is clarified.
{"title":"Space Charge Behavior in AC Electrically Aged Low-Density Polyethylene Films","authors":"Zixia Cheng, Jin-Rui Shi, Ling Zhang, Yuanxiang Zhou, Zekai Lu, Shaowei Guo","doi":"10.1109/CIEEC.2018.8745824","DOIUrl":"https://doi.org/10.1109/CIEEC.2018.8745824","url":null,"abstract":"In order to study the effect of AC aging on space charge characteristics of low-density polyethylene (LDPE) films, an AC electric field of 50 kV/mm (peak value) was adopted for the accelerated aging test and space charge measurements of AC aged LDPE films were carried out subsequently. The results show that no significant space charge accumulation in the LDPE samples aged under a 50 kV/mm AC electric field. It can be seen that a significant positive space charge accumulation occurs inside the sample, when DC electric fields were applied to the AC aged LDPE samples. The long-term AC aging also causes more and deeper cracks on the surface of LDPE samples. Moreover, AC aging promotes the oxidation reaction of LDPE. The longer the aging time, the higher the degree of oxidation. On this basis, the probable relationship between space charge characteristics and material physicochemical properties of LDPE during AC electrical aging is clarified.","PeriodicalId":329285,"journal":{"name":"2018 IEEE 2nd International Electrical and Energy Conference (CIEEC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128881938","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 : 2018-11-01DOI: 10.1109/CIEEC.2018.8745777
Xi Chen, Yongkang Zheng, Z. Jiao, Jin Qin, Daqian Shen, Q. Mo
Smart grid emphasizes identifiability, controllability, unified coordination ability, safety and stability of power grids. In the process of building smart grids, the requirements of transmission lines are mainly reflected in two aspects: state monitoring and transmission capacity of line. Realizing the monitoring of transmission line status, could timely discover hidden failure of transmission line and reduce the number of power failure, ensuring safe and stable operation of transmission lines. The excavation of the transmission capacity is reflected in timely adjustment of the current capacity to maximize the capacity of the transmission line. This paper proposed from the demand of smart grid construction, and combine the output status information of smart substation to realize the real-time status monitoring of transmission lines, and then supporting the condition maintenance of transmission lines and improving the management level of transmission assets. At the same time, through the on-line monitoring of the line temperature and the meteorological environment of the transmission line, comprehensively collect data for calculation analysis and verification to achieve the purpose of dynamic capacity-increase of the transmission line.
{"title":"Research on Real-time Condition Monitoring and Dynamic Capacity-increase of Transmission Lines","authors":"Xi Chen, Yongkang Zheng, Z. Jiao, Jin Qin, Daqian Shen, Q. Mo","doi":"10.1109/CIEEC.2018.8745777","DOIUrl":"https://doi.org/10.1109/CIEEC.2018.8745777","url":null,"abstract":"Smart grid emphasizes identifiability, controllability, unified coordination ability, safety and stability of power grids. In the process of building smart grids, the requirements of transmission lines are mainly reflected in two aspects: state monitoring and transmission capacity of line. Realizing the monitoring of transmission line status, could timely discover hidden failure of transmission line and reduce the number of power failure, ensuring safe and stable operation of transmission lines. The excavation of the transmission capacity is reflected in timely adjustment of the current capacity to maximize the capacity of the transmission line. This paper proposed from the demand of smart grid construction, and combine the output status information of smart substation to realize the real-time status monitoring of transmission lines, and then supporting the condition maintenance of transmission lines and improving the management level of transmission assets. At the same time, through the on-line monitoring of the line temperature and the meteorological environment of the transmission line, comprehensively collect data for calculation analysis and verification to achieve the purpose of dynamic capacity-increase of the transmission line.","PeriodicalId":329285,"journal":{"name":"2018 IEEE 2nd International Electrical and Energy Conference (CIEEC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121962623","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 : 2018-11-01DOI: 10.1109/CIEEC.2018.8745916
S. Bai, Lin-cui Zeng, Liyi, Xiao-Hua Wang, M. Rong
As the key equipment for a new generation of smart substations, the data measurement of electronic instrument transformers is the only basis for the protection calculations performed by the spacer device. Therefore, the accuracy of the measurement is critical to the safe operation of the entire substation. As an entry point from actual project application, this article takes dual-AD sampling data inconsistency of output protection current in the merging unit of the electronic instrument transformer, and based on the specific configuration of the project and the alarm phenomenon, a deep research and analysis was carried out to explain the causes in inconsistency between the dual ADs and the corresponding solutions from the aspects of secondary conditioning circuit, AD sampling and merging unit data processing of the electronic instrument transformer collector. This scheme has been successfully applied in engineering practice. The problem analysis and solutions proposed in this paper provide a further reference for the reliability design of electronic instrument transformers.
{"title":"Research on Inconsistent Acquisition of Dual AD in Protection Current of Electronic Instrument Transformer","authors":"S. Bai, Lin-cui Zeng, Liyi, Xiao-Hua Wang, M. Rong","doi":"10.1109/CIEEC.2018.8745916","DOIUrl":"https://doi.org/10.1109/CIEEC.2018.8745916","url":null,"abstract":"As the key equipment for a new generation of smart substations, the data measurement of electronic instrument transformers is the only basis for the protection calculations performed by the spacer device. Therefore, the accuracy of the measurement is critical to the safe operation of the entire substation. As an entry point from actual project application, this article takes dual-AD sampling data inconsistency of output protection current in the merging unit of the electronic instrument transformer, and based on the specific configuration of the project and the alarm phenomenon, a deep research and analysis was carried out to explain the causes in inconsistency between the dual ADs and the corresponding solutions from the aspects of secondary conditioning circuit, AD sampling and merging unit data processing of the electronic instrument transformer collector. This scheme has been successfully applied in engineering practice. The problem analysis and solutions proposed in this paper provide a further reference for the reliability design of electronic instrument transformers.","PeriodicalId":329285,"journal":{"name":"2018 IEEE 2nd International Electrical and Energy Conference (CIEEC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116208289","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 : 2018-11-01DOI: 10.1109/CIEEC.2018.8745954
Jin Liu, Yanbo Chen, Q. Zhou, M. Lei, Binjun Yan, Xin Liu
Modern power system is becoming increasingly larger AC-DC hybrid system, and its operating mode is more and more complex. Occasional incidents may cause overload problems, voltage problems, and cascading failures. These problems may damage the system stability. Therefore, in the normal state of the system, it is important to study the state transition and its harm to the system through security analysis. Besides, adopting certain control measures to reduce the risk of the system, such as the coordination of prevention and emergency control, is of great significance to both the safety and the economy of the system. In this premise, this paper proposes a risk-based two-layer optimization model for coordination on prevention control and emergency control of quasi-steady state AC-DC system. By introducing a continuous derivable function, the non-derivable constraints in the traditional model are replaced by continuous derivable constraints. The method can greatly improve the computational efficiency of the model. According to the characteristic of the two-layer optimization model, the first layer optimization problem is solved by the golden section method, and the second layer optimization problem is solved by the active and reactive power alternating approach method. Finally, the effectiveness of the proposed method is verified with simulation example.
{"title":"Risk-Based Coordination Research on Prevention Control and Emergency Control of Quasi-Steady State AC-DC System","authors":"Jin Liu, Yanbo Chen, Q. Zhou, M. Lei, Binjun Yan, Xin Liu","doi":"10.1109/CIEEC.2018.8745954","DOIUrl":"https://doi.org/10.1109/CIEEC.2018.8745954","url":null,"abstract":"Modern power system is becoming increasingly larger AC-DC hybrid system, and its operating mode is more and more complex. Occasional incidents may cause overload problems, voltage problems, and cascading failures. These problems may damage the system stability. Therefore, in the normal state of the system, it is important to study the state transition and its harm to the system through security analysis. Besides, adopting certain control measures to reduce the risk of the system, such as the coordination of prevention and emergency control, is of great significance to both the safety and the economy of the system. In this premise, this paper proposes a risk-based two-layer optimization model for coordination on prevention control and emergency control of quasi-steady state AC-DC system. By introducing a continuous derivable function, the non-derivable constraints in the traditional model are replaced by continuous derivable constraints. The method can greatly improve the computational efficiency of the model. According to the characteristic of the two-layer optimization model, the first layer optimization problem is solved by the golden section method, and the second layer optimization problem is solved by the active and reactive power alternating approach method. Finally, the effectiveness of the proposed method is verified with simulation example.","PeriodicalId":329285,"journal":{"name":"2018 IEEE 2nd International Electrical and Energy Conference (CIEEC)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122415216","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 : 2018-11-01DOI: 10.1109/CIEEC.2018.8745921
Xian Wang, Zhengxiang Song, Yingsan Geng, Jianhua Wang
Liquid metal battery is a new battery with high current charging and discharging capability, low cost and long service life. It has a large capacity and is suitable to be used in power grid. An accurate online identification of battery model parameters is the basis of the state of charge and state of health estimation. However, there is presently no published literature for the on-line estimation of the parameters in the liquid metal battery model. To improve the suitability of liquid metal battery model under various scenarios, such as fluctuating and SoC variation, dynamic model with parameters updated on-time is developed, based on second order RC model, using bias compensation recursive least squares method with forgetting factor (FF-BCRLS). Open circuit voltage (OCV) of this device is also estimated as a parameter of the model. Three designed working scenarios are adopted to examine the performance of the algorithm and general recursive least squares method is used as a comparison. The root mean square error and the mean relative error of the estimation using this algorithm is less than 0.01 V and 0.16%, both less than that using general RLS algorithm. The parameters of the battery, internal resistance, polarization capacitances and resistances, and OCV, are proved to be obtained easily and accurately and time-varying by this algorithm, and the maximum estimation error of the OCV is about 0.07 V. The algorithm has of high accuracy and good adaptability to different battery conditions.
{"title":"On-line Identification of Liquid Metal Battery Model Using Bias Compensation Recursive Least Squares Method with Forgetting Factor","authors":"Xian Wang, Zhengxiang Song, Yingsan Geng, Jianhua Wang","doi":"10.1109/CIEEC.2018.8745921","DOIUrl":"https://doi.org/10.1109/CIEEC.2018.8745921","url":null,"abstract":"Liquid metal battery is a new battery with high current charging and discharging capability, low cost and long service life. It has a large capacity and is suitable to be used in power grid. An accurate online identification of battery model parameters is the basis of the state of charge and state of health estimation. However, there is presently no published literature for the on-line estimation of the parameters in the liquid metal battery model. To improve the suitability of liquid metal battery model under various scenarios, such as fluctuating and SoC variation, dynamic model with parameters updated on-time is developed, based on second order RC model, using bias compensation recursive least squares method with forgetting factor (FF-BCRLS). Open circuit voltage (OCV) of this device is also estimated as a parameter of the model. Three designed working scenarios are adopted to examine the performance of the algorithm and general recursive least squares method is used as a comparison. The root mean square error and the mean relative error of the estimation using this algorithm is less than 0.01 V and 0.16%, both less than that using general RLS algorithm. The parameters of the battery, internal resistance, polarization capacitances and resistances, and OCV, are proved to be obtained easily and accurately and time-varying by this algorithm, and the maximum estimation error of the OCV is about 0.07 V. The algorithm has of high accuracy and good adaptability to different battery conditions.","PeriodicalId":329285,"journal":{"name":"2018 IEEE 2nd International Electrical and Energy Conference (CIEEC)","volume":"18 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120837611","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 : 2018-11-01DOI: 10.1109/CIEEC.2018.8745906
Liu Chaoqun, Wu Xiaokang, Wei Bin, G. Yan
In recent years, the development of wireless charging Electric Vehicles (EV) is becoming more and more rapid, because the new energy supply mode----wireless power charging has the advantages of high space utilization, high security, more convenience, stronger user experience. The Influence of charging on life safety, as the research hotspot of EV's wireless charging, has attracted more and more attention and research at home and abroad. The electromagnetic safety evaluation in this article not only provides a theoretical foundation for the life safety analysis of EV's wireless charging, but also is conducive to the future application development. In this study, under the condition of transmission frequency and output power of 85 kHz and 11.4 kW respectively, the models of EV coil and adult body are simulated. The results of safety range and electromagnetic intensity in different positions are obtained and contrasted with International Commission for Non-Ionizing Radiation Protection (ICNIRP) standard. In order to confirm the reliability of the simulation results, we set up the experimental prototype about EV's wireless charging and do the electromagnetic exposure measurement. Finally the electromagnetic safety evaluation of EV charging system is carried out from the perspective of molecular biological experiments.
{"title":"Research on Influence of the Electric Vehicle on Life Safety During the Wireless Charging Process","authors":"Liu Chaoqun, Wu Xiaokang, Wei Bin, G. Yan","doi":"10.1109/CIEEC.2018.8745906","DOIUrl":"https://doi.org/10.1109/CIEEC.2018.8745906","url":null,"abstract":"In recent years, the development of wireless charging Electric Vehicles (EV) is becoming more and more rapid, because the new energy supply mode----wireless power charging has the advantages of high space utilization, high security, more convenience, stronger user experience. The Influence of charging on life safety, as the research hotspot of EV's wireless charging, has attracted more and more attention and research at home and abroad. The electromagnetic safety evaluation in this article not only provides a theoretical foundation for the life safety analysis of EV's wireless charging, but also is conducive to the future application development. In this study, under the condition of transmission frequency and output power of 85 kHz and 11.4 kW respectively, the models of EV coil and adult body are simulated. The results of safety range and electromagnetic intensity in different positions are obtained and contrasted with International Commission for Non-Ionizing Radiation Protection (ICNIRP) standard. In order to confirm the reliability of the simulation results, we set up the experimental prototype about EV's wireless charging and do the electromagnetic exposure measurement. Finally the electromagnetic safety evaluation of EV charging system is carried out from the perspective of molecular biological experiments.","PeriodicalId":329285,"journal":{"name":"2018 IEEE 2nd International Electrical and Energy Conference (CIEEC)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121115916","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 : 2018-11-01DOI: 10.1109/CIEEC.2018.8745825
Dawei Zhang, Weilin Li, Xiaohua Wu, Xiaofeng Lv
In order to overcome the shortcomings such as slow convergence rate and prone to sink into small locality in BP neural network, adaptive genetic algorithm and BP algorithm are combined to take shape a hybrid algorithm to train artificial neural network. In a specific implementation, firstly, an adaptive genetic algorithm is used to perform multi-point genetic optimization on the initial weight space of the neural network, and better search space is located in the solution space. On this basis, local exact search is performed using BP algorithm, ultimately the global optimum is achieved. This algorithm is simulated based on the fault diagnosis of one certain helicopter's airborne electrical control box and one certain flight control box of aircraft autopilot. The simulation conclusions indicate that the algorithm has faster convergence rate and higher diagnostic accuracy.
{"title":"Fault diagnosis method based on improved genetic algorithm and neural network","authors":"Dawei Zhang, Weilin Li, Xiaohua Wu, Xiaofeng Lv","doi":"10.1109/CIEEC.2018.8745825","DOIUrl":"https://doi.org/10.1109/CIEEC.2018.8745825","url":null,"abstract":"In order to overcome the shortcomings such as slow convergence rate and prone to sink into small locality in BP neural network, adaptive genetic algorithm and BP algorithm are combined to take shape a hybrid algorithm to train artificial neural network. In a specific implementation, firstly, an adaptive genetic algorithm is used to perform multi-point genetic optimization on the initial weight space of the neural network, and better search space is located in the solution space. On this basis, local exact search is performed using BP algorithm, ultimately the global optimum is achieved. This algorithm is simulated based on the fault diagnosis of one certain helicopter's airborne electrical control box and one certain flight control box of aircraft autopilot. The simulation conclusions indicate that the algorithm has faster convergence rate and higher diagnostic accuracy.","PeriodicalId":329285,"journal":{"name":"2018 IEEE 2nd International Electrical and Energy Conference (CIEEC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126750976","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}
Ultrasonic signal will be generated when a partial discharge occurs in the oil/paper insulation system, thereby enabling partial discharge detection of the transformer. In order to explore the ultrasonic characteristics of partial discharge of oil/paper insulation system, a partial discharge detection platform based on ultrasonic method is developed in this paper. Based on the platform, the ultrasonic signal filtering method is analyzed, and the typical defect model of oil/paper insulation is built and tested in the laboratory, obtaining partial discharge signal of typical defective. Finally, the accuracy of the waveform acquired in this paper and its effectiveness in fault diagnosis are verified by the application on the actual transformer.
{"title":"The PD Characteristics Study of Oil/Paper Insulation Typical Defects Based on Ultrasonic Method","authors":"Xin Zhang, Liuyong Qiu, Yanwei Dong, Liqing Liu, Junji Feng, Tiankai Yang","doi":"10.1109/CIEEC.2018.8745823","DOIUrl":"https://doi.org/10.1109/CIEEC.2018.8745823","url":null,"abstract":"Ultrasonic signal will be generated when a partial discharge occurs in the oil/paper insulation system, thereby enabling partial discharge detection of the transformer. In order to explore the ultrasonic characteristics of partial discharge of oil/paper insulation system, a partial discharge detection platform based on ultrasonic method is developed in this paper. Based on the platform, the ultrasonic signal filtering method is analyzed, and the typical defect model of oil/paper insulation is built and tested in the laboratory, obtaining partial discharge signal of typical defective. Finally, the accuracy of the waveform acquired in this paper and its effectiveness in fault diagnosis are verified by the application on the actual transformer.","PeriodicalId":329285,"journal":{"name":"2018 IEEE 2nd International Electrical and Energy Conference (CIEEC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127936227","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}
Prony method and auto regressive moving average (ARMA) method are two typical methods used in the low-frequency oscillation mode identification of large-scale power system. This paper applies the two methods to distribution systems with multiple DGs to identify oscillation modes. The applicability of the methods to different signals is accessed by employing them to ringdown and ambient signals simulated from a 4-DG islanded distribution system and comparing to the eigenvalues calculated by eigen-analysis of the system’s small-signal model. The results indicate that the ARMA method has better applicability in this situation while Prony method is simpler to implement in case of ringdown signals.
{"title":"Comparison of Prony and ARMA Methods for Oscillation Mode Identification in Distribution Systems Based on μPMU","authors":"Ping Ling, Zhixiong Shi, Jing Zhang, Xiangyu Wu, Yin Xu, Jinghan He, Jinli Wang","doi":"10.1109/CIEEC.2018.8745901","DOIUrl":"https://doi.org/10.1109/CIEEC.2018.8745901","url":null,"abstract":"Prony method and auto regressive moving average (ARMA) method are two typical methods used in the low-frequency oscillation mode identification of large-scale power system. This paper applies the two methods to distribution systems with multiple DGs to identify oscillation modes. The applicability of the methods to different signals is accessed by employing them to ringdown and ambient signals simulated from a 4-DG islanded distribution system and comparing to the eigenvalues calculated by eigen-analysis of the system’s small-signal model. The results indicate that the ARMA method has better applicability in this situation while Prony method is simpler to implement in case of ringdown signals.","PeriodicalId":329285,"journal":{"name":"2018 IEEE 2nd International Electrical and Energy Conference (CIEEC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127953227","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 : 2018-11-01DOI: 10.1109/CIEEC.2018.8745858
Weijie Li, Pei Zhang, S. Su, Xiangfei Meng, Changxin Ding, Yuwei Wang
Decision tree (DT) as an effective data mining method has been widely used in voltage stability assessment. The selection of decision tree’s input attributes is critical because input attributes affect the accuracy and efficiency of the decision tree. This paper compares two attribute selection methods: participation factor method and Relief-F algorithm. Participation factor method is based on modal analysis of Jacobi matrix, while Relief-F algorithm is a mathematical approach that does not require power system knowledge. Two DTs with the same number of input attributes identified by participation factor analysis and Relief-F algorithm respectively are constructed for comparison in term of accuracy and efficiency. A case study on a practical power system indicates that two methods identify similar attributes and the accuracy of two DTs are close.
{"title":"Comparison of Decision Tree Attribute Selection Methods for Static Voltage Stability Margin Assessment","authors":"Weijie Li, Pei Zhang, S. Su, Xiangfei Meng, Changxin Ding, Yuwei Wang","doi":"10.1109/CIEEC.2018.8745858","DOIUrl":"https://doi.org/10.1109/CIEEC.2018.8745858","url":null,"abstract":"Decision tree (DT) as an effective data mining method has been widely used in voltage stability assessment. The selection of decision tree’s input attributes is critical because input attributes affect the accuracy and efficiency of the decision tree. This paper compares two attribute selection methods: participation factor method and Relief-F algorithm. Participation factor method is based on modal analysis of Jacobi matrix, while Relief-F algorithm is a mathematical approach that does not require power system knowledge. Two DTs with the same number of input attributes identified by participation factor analysis and Relief-F algorithm respectively are constructed for comparison in term of accuracy and efficiency. A case study on a practical power system indicates that two methods identify similar attributes and the accuracy of two DTs are close.","PeriodicalId":329285,"journal":{"name":"2018 IEEE 2nd International Electrical and Energy Conference (CIEEC)","volume":"51 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131337626","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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