The risk of failures on multi-circuit transmission lines on the same tower becomes higher and the fault types are more complex. Sometimes maybe we need to analyze the influence of faults between different lines and the phase-to-phase faults on one line in such a system especially when the voltage grades are high and the transferred power is big. Knowing the severity of the different fault types in advance can help us to better analyze such systems and save simulation time. However, by now the related researches are rare. This paper derived the equations of the transferred power by four-circuit transmission lines on the same tower during different faults in a simple system based on the symmetrical component method, Equal Area Criterion and some assumptions. According to the equations the paper compared the severity of the different types of faults and get some conclusions. A simple test case is used to testify the correctness of the equations and the conclusions.
{"title":"Comparison of the Influence of Different Types of Faults on Four-Circuit Transmission Lines on the Same Tower","authors":"Yujiao Sun, Liang Cheng, Jun-hui Huang, Qun Zhang, Yichao Huang, Yuanming Huang","doi":"10.1109/CIEEC.2018.8745923","DOIUrl":"https://doi.org/10.1109/CIEEC.2018.8745923","url":null,"abstract":"The risk of failures on multi-circuit transmission lines on the same tower becomes higher and the fault types are more complex. Sometimes maybe we need to analyze the influence of faults between different lines and the phase-to-phase faults on one line in such a system especially when the voltage grades are high and the transferred power is big. Knowing the severity of the different fault types in advance can help us to better analyze such systems and save simulation time. However, by now the related researches are rare. This paper derived the equations of the transferred power by four-circuit transmission lines on the same tower during different faults in a simple system based on the symmetrical component method, Equal Area Criterion and some assumptions. According to the equations the paper compared the severity of the different types of faults and get some conclusions. A simple test case is used to testify the correctness of the equations and the conclusions.","PeriodicalId":329285,"journal":{"name":"2018 IEEE 2nd International Electrical and Energy Conference (CIEEC)","volume":"52 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":"123262837","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}
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}
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}
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.2018.8745832
Shengwei Gao, Xin Lu, Xiaoming Liu
For dual active-bridge full-bridge DC-DC converter, the traditional single-phase-shifting control is simple, but there is a backflow power, and only when the input voltage and output voltage match, the converter has higher efficiency. Therefore, in order to reduce the current stress and the reflux power, and improve the conversion efficiency, a dual phase-shifting control strategy with the minimum reflux power control satisfying the soft-switching condition is proposed. In this paper, the working mode, power characteristics and soft switching range of the dual phase-shifting control are analyzed firstly, and the best phase-shifting combination for realizing the minimum return power in the soft switching range is selected. Finally, the system model is established with the help of the simulation tool of MATLAB, which verifies the effectiveness and superiority of the control strategy.
{"title":"Minimum reflux power control of bidirectional DC-DC converter based on dual phase shifting","authors":"Shengwei Gao, Xin Lu, Xiaoming Liu","doi":"10.1109/CIEEC.2018.8745832","DOIUrl":"https://doi.org/10.1109/CIEEC.2018.8745832","url":null,"abstract":"For dual active-bridge full-bridge DC-DC converter, the traditional single-phase-shifting control is simple, but there is a backflow power, and only when the input voltage and output voltage match, the converter has higher efficiency. Therefore, in order to reduce the current stress and the reflux power, and improve the conversion efficiency, a dual phase-shifting control strategy with the minimum reflux power control satisfying the soft-switching condition is proposed. In this paper, the working mode, power characteristics and soft switching range of the dual phase-shifting control are analyzed firstly, and the best phase-shifting combination for realizing the minimum return power in the soft switching range is selected. Finally, the system model is established with the help of the simulation tool of MATLAB, which verifies the effectiveness and superiority of the control strategy.","PeriodicalId":329285,"journal":{"name":"2018 IEEE 2nd International Electrical and Energy Conference (CIEEC)","volume":"89 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113962514","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.2018.8745949
Yudun Li, Binchao Zhao, Hao Bai
Simulating wind speed has important implications in wind energy research. This paper provides a wind speed simulation approach based on Markov sequence model and Archimedean Copula for planning purposes. Firstly, a Markov Sequence model is presented to describe the transfer rule of wind speed time series (WSTS). Secondly, an Archimedean Copula function (AMC) is applied to capture the temporal dependence between wind speeds of adjacent times and then obtain the transition kernel. Finally, conditional sampling technique is used to generate the wind speed of next hour. The advantage of the model lies in avoiding the loss of information of wind speed data during the discretization procedure by replacing the discrete transition matrix with the transition kernel and characterizing different dependence structure with Archimedean Copula function. A case study proves that the model can offer satisfactory fit for both probability distribution and temporal dependence. The model is applied to a reliability test system. The results show that the model can be used to evaluate the reliability of power systems with wind energy.
{"title":"A Wind Speed Simulation Approach Based on Markov Sequence Model and Archimedean Copula","authors":"Yudun Li, Binchao Zhao, Hao Bai","doi":"10.1109/CIEEC.2018.8745949","DOIUrl":"https://doi.org/10.1109/CIEEC.2018.8745949","url":null,"abstract":"Simulating wind speed has important implications in wind energy research. This paper provides a wind speed simulation approach based on Markov sequence model and Archimedean Copula for planning purposes. Firstly, a Markov Sequence model is presented to describe the transfer rule of wind speed time series (WSTS). Secondly, an Archimedean Copula function (AMC) is applied to capture the temporal dependence between wind speeds of adjacent times and then obtain the transition kernel. Finally, conditional sampling technique is used to generate the wind speed of next hour. The advantage of the model lies in avoiding the loss of information of wind speed data during the discretization procedure by replacing the discrete transition matrix with the transition kernel and characterizing different dependence structure with Archimedean Copula function. A case study proves that the model can offer satisfactory fit for both probability distribution and temporal dependence. The model is applied to a reliability test system. The results show that the model can be used to evaluate the reliability of power systems with wind energy.","PeriodicalId":329285,"journal":{"name":"2018 IEEE 2nd International Electrical and Energy Conference (CIEEC)","volume":"227 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113988929","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.2018.8745839
Song Gao, Yong-yong Jia, Xiaotian Bi, Bin Cao, Xu Li, Daiming Yang, Liming Wang
Pollution flashover is a serious threat to the safe and stable operation of power system, and the pollution flashover voltages of insulators on the transmission lines are related to the leakage currents. In this paper, a neural network model was proposed to predict the leakage currents on the insulators, which could provide references for preventing pollution flashover. By the analysis of a large number of leakage current data obtained by the monitoring device on the insulators of operating lines, the characteristics of the leakage current is extracted, and then combined with BP neural network, the prediction model of leakage current based on the actual operation data is established. By adjusting the parameters of the BP neural network, the prediction results can be accords with the actual operation situation. The reliability of the predicted results was verified by the leakage current on the insulator surface.
{"title":"Prediction method of leakage current of insulators on the transmission line based on BP neural network","authors":"Song Gao, Yong-yong Jia, Xiaotian Bi, Bin Cao, Xu Li, Daiming Yang, Liming Wang","doi":"10.1109/CIEEC.2018.8745839","DOIUrl":"https://doi.org/10.1109/CIEEC.2018.8745839","url":null,"abstract":"Pollution flashover is a serious threat to the safe and stable operation of power system, and the pollution flashover voltages of insulators on the transmission lines are related to the leakage currents. In this paper, a neural network model was proposed to predict the leakage currents on the insulators, which could provide references for preventing pollution flashover. By the analysis of a large number of leakage current data obtained by the monitoring device on the insulators of operating lines, the characteristics of the leakage current is extracted, and then combined with BP neural network, the prediction model of leakage current based on the actual operation data is established. By adjusting the parameters of the BP neural network, the prediction results can be accords with the actual operation situation. The reliability of the predicted results was verified by the leakage current on the insulator surface.","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":"126302698","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}
Pub Date : 2018-11-01DOI: 10.1109/CIEEC.2018.8745969
Hao Zheng, Hongwei Ma, Di Wu, Jianrong Mao, Meiping Fu
The integrated energy management and control system is an important means to achieve "multiple complementarity, coordination and optimization" among different energy systems. The core purpose of the integrated energy management and control system is to improve efficiency and reduce consumption of energy by promoting the fusion of energy flow and information flow. First of all, this paper introduced the research progress of integrated energy management and control system at home and abroad. Secondly, defined the position of Multi-application scenario according to the different different customer demands. Then, described the design concept and functional architecture of the integrated energy management and control system. Finally, in this paper, the preliminary results of the system is showed.
{"title":"Architecture and Function Design of Integrated Energy Management System for Multiple Scenes","authors":"Hao Zheng, Hongwei Ma, Di Wu, Jianrong Mao, Meiping Fu","doi":"10.1109/CIEEC.2018.8745969","DOIUrl":"https://doi.org/10.1109/CIEEC.2018.8745969","url":null,"abstract":"The integrated energy management and control system is an important means to achieve \"multiple complementarity, coordination and optimization\" among different energy systems. The core purpose of the integrated energy management and control system is to improve efficiency and reduce consumption of energy by promoting the fusion of energy flow and information flow. First of all, this paper introduced the research progress of integrated energy management and control system at home and abroad. Secondly, defined the position of Multi-application scenario according to the different different customer demands. Then, described the design concept and functional architecture of the integrated energy management and control system. Finally, in this paper, the preliminary results of the system is showed.","PeriodicalId":329285,"journal":{"name":"2018 IEEE 2nd International Electrical and Energy Conference (CIEEC)","volume":"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":"129529954","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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