Pub Date : 2017-04-23DOI: 10.1109/ISGT.2017.8085987
M. Arani, Y. Mohamed
High Voltage Direct Current (HVDC) transmission lines are increasing rapidly and Voltage Source Converter (VSC)-based is one of the most famous types used in the industry. Despites all of its merits, VSCs have not been favored in very weak grids because of stability issues. Recently, these issues have generated much attention in literature and different solutions are proposed. Among the discussed solutions, the artificial bus is one of the most straight-forward and effective methods, which enable VSC to inject or absorb its maximum nominal power. However, this method is not examined under grid disturbances. This paper studies the impact of severe faults, phase jump and frequency changes and discusses the inherent robustness of the method to fill a serious gap in the literature.
{"title":"Voltage source converter connected to very weak grids under disturbances","authors":"M. Arani, Y. Mohamed","doi":"10.1109/ISGT.2017.8085987","DOIUrl":"https://doi.org/10.1109/ISGT.2017.8085987","url":null,"abstract":"High Voltage Direct Current (HVDC) transmission lines are increasing rapidly and Voltage Source Converter (VSC)-based is one of the most famous types used in the industry. Despites all of its merits, VSCs have not been favored in very weak grids because of stability issues. Recently, these issues have generated much attention in literature and different solutions are proposed. Among the discussed solutions, the artificial bus is one of the most straight-forward and effective methods, which enable VSC to inject or absorb its maximum nominal power. However, this method is not examined under grid disturbances. This paper studies the impact of severe faults, phase jump and frequency changes and discusses the inherent robustness of the method to fill a serious gap in the literature.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123198559","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 : 2017-04-23DOI: 10.1109/ISGT.2017.8085971
S. Hosein, Patrick Hosein
Short-term electricity demand prediction is of great importance to power companies since it is required to ensure adequate capacity when needed and, in some cases, it is needed to estimate the supply of raw material (e.g., natural gas) required to produce the required capacity. The deregulation of the power industry in many countries has magnified the importance of this need. Research in this area has included the use of shallow neural networks and other machine learning algorithms to solve this problem. However, recent results in other areas, such as Computer Vision and Speech Recognition, have shown great promise for Deep Neural Networks (DNN). Unfortunately, far less research exists on the application of DNN to short-term load forecasting. In this paper, we apply DNN as well as other machine learning techniques to short-term load forecasting in a power grid. The data used is taken from periodic smart meter energy usage reports. Our results indicate that DNN performs quite well when compared to traditional approaches. We also show how these results can be used if dynamic pricing is introduced to reduce peak loading.
{"title":"Load forecasting using deep neural networks","authors":"S. Hosein, Patrick Hosein","doi":"10.1109/ISGT.2017.8085971","DOIUrl":"https://doi.org/10.1109/ISGT.2017.8085971","url":null,"abstract":"Short-term electricity demand prediction is of great importance to power companies since it is required to ensure adequate capacity when needed and, in some cases, it is needed to estimate the supply of raw material (e.g., natural gas) required to produce the required capacity. The deregulation of the power industry in many countries has magnified the importance of this need. Research in this area has included the use of shallow neural networks and other machine learning algorithms to solve this problem. However, recent results in other areas, such as Computer Vision and Speech Recognition, have shown great promise for Deep Neural Networks (DNN). Unfortunately, far less research exists on the application of DNN to short-term load forecasting. In this paper, we apply DNN as well as other machine learning techniques to short-term load forecasting in a power grid. The data used is taken from periodic smart meter energy usage reports. Our results indicate that DNN performs quite well when compared to traditional approaches. We also show how these results can be used if dynamic pricing is introduced to reduce peak loading.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115989909","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 : 2017-04-23DOI: 10.1109/ISGT.2017.8085970
Sultan S. Alkaabi, H. Zeineldin, V. Khadkikar, M. E. Moursi
This paper provides a comparative study of coordinated voltage control (CVC) strategies for on-load tap-changers (OLTCs) and voltage regulator (VRs) under active and passive network management schemes (ANM and PNM). In PNM scheme, OLTC and VR are restricted to only regulate the secondary bus voltages at fixed set-points, while in ANM scheme, control of the secondary bus voltages within the statutory voltage range is allowed, thus providing area-based voltage controls. In this paper, the dynamic model of a 33kV 16-bus United Kingdom generic distribution system (UKGDS) is firstly implemented in PSCAD/EMTDC and validated with a steady-state model, using optimal power flow (OPF)-based technique, developed in GAMS software. Secondly, the OLTC and VR controls under ANM and PNM schemes are developed with discrete tap-changers, and tested considering different load profiles and dynamic loads. The results show that the ANM scheme allows considerable utilization of OLTC and VR compared to PNM scheme, but also may increase the loading of these devices depending on load levels and voltage profile in the power network.
{"title":"Dynamic analysis of OLTC and voltage regulator under active network management considering different load profiles","authors":"Sultan S. Alkaabi, H. Zeineldin, V. Khadkikar, M. E. Moursi","doi":"10.1109/ISGT.2017.8085970","DOIUrl":"https://doi.org/10.1109/ISGT.2017.8085970","url":null,"abstract":"This paper provides a comparative study of coordinated voltage control (CVC) strategies for on-load tap-changers (OLTCs) and voltage regulator (VRs) under active and passive network management schemes (ANM and PNM). In PNM scheme, OLTC and VR are restricted to only regulate the secondary bus voltages at fixed set-points, while in ANM scheme, control of the secondary bus voltages within the statutory voltage range is allowed, thus providing area-based voltage controls. In this paper, the dynamic model of a 33kV 16-bus United Kingdom generic distribution system (UKGDS) is firstly implemented in PSCAD/EMTDC and validated with a steady-state model, using optimal power flow (OPF)-based technique, developed in GAMS software. Secondly, the OLTC and VR controls under ANM and PNM schemes are developed with discrete tap-changers, and tested considering different load profiles and dynamic loads. The results show that the ANM scheme allows considerable utilization of OLTC and VR compared to PNM scheme, but also may increase the loading of these devices depending on load levels and voltage profile in the power network.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123585977","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 : 2017-04-23DOI: 10.1109/ISGT.2017.8085965
YooJin Kwon, H. Kim, K. Koumadi, Yong-hun Lim, Jong-in Lim
A smart grid is a fully automated power electricity network, which operates, protects and controls all its physical environments of power electricity infrastructure being able to supply energy in an efficient and reliable way. As the importance of cyber-physical system (CPS) security is growing, various vulnerability analysis methodologies for general systems have been suggested, whereas there has been few practical research targeting the smart grid infrastructure. In this paper, we highlight the significance of security vulnerability analysis in the smart grid environment. Then we introduce various automated vulnerability analysis techniques from executable files. In our approach, we propose a novel binary-based vulnerability discovery method for AMI and EV charging system to automatically extract security-related features from the embedded software. Finally, we present the test result of vulnerability discovery applied for AMI and EV charging system in Korean smart grid environment.
{"title":"Automated vulnerability analysis technique for smart grid infrastructure","authors":"YooJin Kwon, H. Kim, K. Koumadi, Yong-hun Lim, Jong-in Lim","doi":"10.1109/ISGT.2017.8085965","DOIUrl":"https://doi.org/10.1109/ISGT.2017.8085965","url":null,"abstract":"A smart grid is a fully automated power electricity network, which operates, protects and controls all its physical environments of power electricity infrastructure being able to supply energy in an efficient and reliable way. As the importance of cyber-physical system (CPS) security is growing, various vulnerability analysis methodologies for general systems have been suggested, whereas there has been few practical research targeting the smart grid infrastructure. In this paper, we highlight the significance of security vulnerability analysis in the smart grid environment. Then we introduce various automated vulnerability analysis techniques from executable files. In our approach, we propose a novel binary-based vulnerability discovery method for AMI and EV charging system to automatically extract security-related features from the embedded software. Finally, we present the test result of vulnerability discovery applied for AMI and EV charging system in Korean smart grid environment.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132662803","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 : 2017-04-23DOI: 10.1109/ISGT.2017.8085959
Zaid H. Ali, Junhui Zhao, Emad Manla, Junpeng Ma, Wensheng Song
In order to get the desired output from photovoltaic (PV) generation, it is necessary to control the power exchange with the grid. Therefore, the calculations of real and reactive power for PV inverters are important. In this study, a novel direct power control (DPC) strategy for three-level single-phase grid-connected SVPWM inverters has been developed. In this strategy, the real and reactive power control and SVPWM are considered in inner loop, while a voltage PI controller is used in outer loop to acquire constant output voltage and provide power reference to the DPC. In addition, the MPPT algorithm is integrated into the control strategy to get the maximum PV output. The performance of the proposed method is verified by simulation results obtained using Matlab/Simulink.
{"title":"Novel direct power control of single-phase three-level SVPWM inverter for photovoltaic generation","authors":"Zaid H. Ali, Junhui Zhao, Emad Manla, Junpeng Ma, Wensheng Song","doi":"10.1109/ISGT.2017.8085959","DOIUrl":"https://doi.org/10.1109/ISGT.2017.8085959","url":null,"abstract":"In order to get the desired output from photovoltaic (PV) generation, it is necessary to control the power exchange with the grid. Therefore, the calculations of real and reactive power for PV inverters are important. In this study, a novel direct power control (DPC) strategy for three-level single-phase grid-connected SVPWM inverters has been developed. In this strategy, the real and reactive power control and SVPWM are considered in inner loop, while a voltage PI controller is used in outer loop to acquire constant output voltage and provide power reference to the DPC. In addition, the MPPT algorithm is integrated into the control strategy to get the maximum PV output. The performance of the proposed method is verified by simulation results obtained using Matlab/Simulink.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122644660","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 : 2017-04-23DOI: 10.1109/ISGT.2017.8085967
Michael Zeifman, M. Kromer, K. Roth
We present a novel framework — the SunDial system — intended to enable integration of high-penetration commercial and utility-scale photovoltaic (PV) plants by a combination of load and energy storage management. Rather than relying on controllable loads from disparate individual buildings, SunDial uses a Facility Load Aggregation and Management Engine (FLAME) that provides a single point of input for managing the electric loads in multiple commercial and/or industrial facilities. By implementing various demand response strategies, FLAME acts as a virtual energy storage resource, thus increasing the roundtrip efficiency and capacity of the Sundial's coupled battery/load-based storage system. An open standard to support broader utilization of long-duration load shifting as a means to enable grid integration of distributed renewables is also proposed. The SunDial system is planned to be deployed in Massachusetts in 2017–2019 on the National Grid distribution system. This paper presents its basic architecture, a simulation-based prototype and preliminary results based on actual loads from commercial buildings.
{"title":"Integrated system to enable high-penetration feeder-level PV: Preliminary design and simulation results","authors":"Michael Zeifman, M. Kromer, K. Roth","doi":"10.1109/ISGT.2017.8085967","DOIUrl":"https://doi.org/10.1109/ISGT.2017.8085967","url":null,"abstract":"We present a novel framework — the SunDial system — intended to enable integration of high-penetration commercial and utility-scale photovoltaic (PV) plants by a combination of load and energy storage management. Rather than relying on controllable loads from disparate individual buildings, SunDial uses a Facility Load Aggregation and Management Engine (FLAME) that provides a single point of input for managing the electric loads in multiple commercial and/or industrial facilities. By implementing various demand response strategies, FLAME acts as a virtual energy storage resource, thus increasing the roundtrip efficiency and capacity of the Sundial's coupled battery/load-based storage system. An open standard to support broader utilization of long-duration load shifting as a means to enable grid integration of distributed renewables is also proposed. The SunDial system is planned to be deployed in Massachusetts in 2017–2019 on the National Grid distribution system. This paper presents its basic architecture, a simulation-based prototype and preliminary results based on actual loads from commercial buildings.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129828469","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 : 2017-04-23DOI: 10.1109/ISGT.2017.8085977
H. Hooshyar, L. Vanfretti
Distribution grid dynamics are becoming increasingly complex due to the transition of these networks from passive to active networks. This transition requires increasing the observability and awareness of the interactions between Transmission and Distribution (T&D) grids, particularly to guarantee adequate operational security. As part of the work carried out in the EU-funded IDE4L project, a specific use case, containing PMU-based monitoring functions, has been defined to support the architecture design of a distribution grid automation system. As a result, the architecture can accommodate for synchrophasor applications that provide key dynamic information extraction and exchange between DSO and TSO. This paper presents the use case and the portion of the IDE4L architecture that accommodates for scenarios that exploit synchrophasors for monitoring applications.
{"title":"A SGAM-based architecture for synchrophasor applications facilitating TSO/DSO interactions","authors":"H. Hooshyar, L. Vanfretti","doi":"10.1109/ISGT.2017.8085977","DOIUrl":"https://doi.org/10.1109/ISGT.2017.8085977","url":null,"abstract":"Distribution grid dynamics are becoming increasingly complex due to the transition of these networks from passive to active networks. This transition requires increasing the observability and awareness of the interactions between Transmission and Distribution (T&D) grids, particularly to guarantee adequate operational security. As part of the work carried out in the EU-funded IDE4L project, a specific use case, containing PMU-based monitoring functions, has been defined to support the architecture design of a distribution grid automation system. As a result, the architecture can accommodate for synchrophasor applications that provide key dynamic information extraction and exchange between DSO and TSO. This paper presents the use case and the portion of the IDE4L architecture that accommodates for scenarios that exploit synchrophasors for monitoring applications.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124374259","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 : 2017-04-23DOI: 10.1109/ISGT.2017.8085968
Tim Chang, H. Mirzaee, F. Katiraei, Marvin Zavala-Iraheta
Current unbalance conditions are a concern to utilities and can negatively affect power quality and safe and reliable system operation if left untreated. Conventional solutions involve physical re-configuration and are typically challenging and less effective as these changes are temporary and will change as circuit and customer load habits evolve. As alternative, power electronic-based devices are promising solutions to mitigating current unbalance. This paper introduces the control theory behind one such power electronics-based Dynamic Load Balancer (DLB) and details the development of a transient software-based simulation model to allow for mitigation planning and performance evaluation in distribution circuits. The physical and software model for DLB were tested under a range of system conditions as verification of model accuracy and also evaluation of the device capabilities and performance.
{"title":"Hardware and software model evaluation of a dynamic load balancer for mitigation of current unbalance in distribution circuits","authors":"Tim Chang, H. Mirzaee, F. Katiraei, Marvin Zavala-Iraheta","doi":"10.1109/ISGT.2017.8085968","DOIUrl":"https://doi.org/10.1109/ISGT.2017.8085968","url":null,"abstract":"Current unbalance conditions are a concern to utilities and can negatively affect power quality and safe and reliable system operation if left untreated. Conventional solutions involve physical re-configuration and are typically challenging and less effective as these changes are temporary and will change as circuit and customer load habits evolve. As alternative, power electronic-based devices are promising solutions to mitigating current unbalance. This paper introduces the control theory behind one such power electronics-based Dynamic Load Balancer (DLB) and details the development of a transient software-based simulation model to allow for mitigation planning and performance evaluation in distribution circuits. The physical and software model for DLB were tested under a range of system conditions as verification of model accuracy and also evaluation of the device capabilities and performance.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133808981","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 : 2017-04-01DOI: 10.1109/ISGT.2017.8086020
Abdullah Alfadda, R. Adhikari, M. Kuzlu, S. Rahman
The use of solar photovoltaic (PV) in power generation has grown in the last decade. Unlike the traditional power generation methods (i.e. oil and gas), the solar output power is fluctuating and uncertain, mainly due to clouds movement and other weather factors. Therefore, in order to have a stable power grid, the electricity utilities need to forecast the solar output power, so they can prepare ahead adequately. In this work, hour-ahead solar PV power forecasting is performed using Support Vector Regression (SVR), Polynomial Regression and Lasso. The implemented regression models were tested under different feature selection schemes. These features include weather conditions (i.e. sky condition, temperature, etc.), power generated in the last few hours, day and time information. Based on the comparative results obtained, the SVR forecasting model outperforms the other two models in terms of accuracy.
{"title":"Hour-ahead solar PV power forecasting using SVR based approach","authors":"Abdullah Alfadda, R. Adhikari, M. Kuzlu, S. Rahman","doi":"10.1109/ISGT.2017.8086020","DOIUrl":"https://doi.org/10.1109/ISGT.2017.8086020","url":null,"abstract":"The use of solar photovoltaic (PV) in power generation has grown in the last decade. Unlike the traditional power generation methods (i.e. oil and gas), the solar output power is fluctuating and uncertain, mainly due to clouds movement and other weather factors. Therefore, in order to have a stable power grid, the electricity utilities need to forecast the solar output power, so they can prepare ahead adequately. In this work, hour-ahead solar PV power forecasting is performed using Support Vector Regression (SVR), Polynomial Regression and Lasso. The implemented regression models were tested under different feature selection schemes. These features include weather conditions (i.e. sky condition, temperature, etc.), power generated in the last few hours, day and time information. Based on the comparative results obtained, the SVR forecasting model outperforms the other two models in terms of accuracy.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115453759","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 : 2017-04-01DOI: 10.1109/ISGT.2017.8086062
Mahmoud Saleh, Yusef Esa, A. Mohamed
In this paper, an autonomous communication-based centralized control for DC microgrids (MG) has been developed and implemented. The proposed controller enables smooth transition between various operating modes. Finite state machine (FSM) has been used to mathematically describe the various operating modes (states), and events that may lead to mode changes (transitions). Therefore, the developed centralized controller aims at optimizing the performance of MG during all possible operational scenarios, while maintaining its reliability and stability. Results of selected cases have been presented. These results show stable transition between modes, verifying the validity and applicability of the proposed controller.
{"title":"Centralized control for DC microgrid using finite state machine","authors":"Mahmoud Saleh, Yusef Esa, A. Mohamed","doi":"10.1109/ISGT.2017.8086062","DOIUrl":"https://doi.org/10.1109/ISGT.2017.8086062","url":null,"abstract":"In this paper, an autonomous communication-based centralized control for DC microgrids (MG) has been developed and implemented. The proposed controller enables smooth transition between various operating modes. Finite state machine (FSM) has been used to mathematically describe the various operating modes (states), and events that may lead to mode changes (transitions). Therefore, the developed centralized controller aims at optimizing the performance of MG during all possible operational scenarios, while maintaining its reliability and stability. Results of selected cases have been presented. These results show stable transition between modes, verifying the validity and applicability of the proposed controller.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124424248","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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