Islanding detection is an essential function for safety and reliability in grid-connected distributed generation (DG) systems. Several methods for islanding detection are proposed, but most of them may fail under mult...Islanding detection is an essential function for safety and reliability in grid-connected distributed generation (DG) systems. Several methods for islanding detection are proposed, but most of them may fail under multi-source configurations, or they may produce important power quality degradation which gets worse with increasing DG penetration. This paper presents an active islanding detection algorithm for Voltage Source Inverter (VSI) based multi-source DG systems. The proposed method is based on the Voltage Positive Feedback (VPF) theory to generate a limited active power perturbation. Theoretical analyses were performed and simulations by MATLAB /Simulink /SimPowerSystems were used to evaluate the algorithm’s performance and its advantages concerning the time response and the effects on power quality, which turned out to be negligible. The algorithm performance was tested under critical conditions: load with unity power factor, load with high quality factor, and load matching DER’s powers.展开更多
Energy consumption reduction efforts in the residential buildings sector represent socio-economical, technological and environmental preoccupations which justify advanced scientific research. These lead to use inverse...Energy consumption reduction efforts in the residential buildings sector represent socio-economical, technological and environmental preoccupations which justify advanced scientific research. These lead to use inverse models to describe thermal behavior and to evaluate the energy consumption of buildings. Their principal goal is to provide supporting evidence of enhanced energy performances and predictions. More specifically, research questions are related to building thermal modeling which is the most appropriate in a smart grid context. In this context, the models are reviewed according to three categories. The first category is based on physical and basic principle modeling (white-box). The second offers a much simpler structure which is the statistical models (black-box). The black-box is used for prediction of energy consumption and heating/ cooling demands. Finally, the third category is a hybrid method (grey-box), which uses both physical and statistical modeling techniques. In this paper, we propose a detailed review and simulation of the main thermal building models. Our comparison and simulation results demonstrate that the grey-box is the most effective model for management of buildings energy consumption.展开更多
Grid connected voltage source inverters (VSIs) are essential for the integration of the distributed energy resources. Hysteresis current control (HCC) is a commonly employed method for power control of VSIs. This cont...Grid connected voltage source inverters (VSIs) are essential for the integration of the distributed energy resources. Hysteresis current control (HCC) is a commonly employed method for power control of VSIs. This control method, in contrast with voltage control, provides good dynamics, good stability and implicit over current protection. However, the most important concern of digital implementation of HCC is related with the sampling period of the measured currents. This paper presents a predictive hysteresis current control (HCC) for grid connected voltage source inverter and its FPGA implementation. Simulation and experimental results are provided to verify the validity of the proposed implementation.展开更多
As a part of the Smart Grid concept, an efficient energy management at the residential level has received increasing attention in lately research. Its main focus is to balance the energy consumption in the residential...As a part of the Smart Grid concept, an efficient energy management at the residential level has received increasing attention in lately research. Its main focus is to balance the energy consumption in the residential environment in order to avoid the undesirable peaks faced by the electricity supplier. This challenge can be achieved by means of a home energy management system (HEMS). The HEMS may consider local renewable energy production and energy storage, as well as local control of some particular loads when peaks mitigation is necessary. This paper presents the modeling and comparison of two residential systems;one using conventional electric baseboard heating and the other one supported by Electric Thermal Storage (ETS);the ETS is employed to optimize the local energy utilization pursuing the peak shaving of residential consumption profile. Simulations of the proposed architecture using the Energetic Macroscopic Representation (EMR) demonstrate the potential of ETS technologies in future HEMS.展开更多
文摘Islanding detection is an essential function for safety and reliability in grid-connected distributed generation (DG) systems. Several methods for islanding detection are proposed, but most of them may fail under multi-source configurations, or they may produce important power quality degradation which gets worse with increasing DG penetration. This paper presents an active islanding detection algorithm for Voltage Source Inverter (VSI) based multi-source DG systems. The proposed method is based on the Voltage Positive Feedback (VPF) theory to generate a limited active power perturbation. Theoretical analyses were performed and simulations by MATLAB /Simulink /SimPowerSystems were used to evaluate the algorithm’s performance and its advantages concerning the time response and the effects on power quality, which turned out to be negligible. The algorithm performance was tested under critical conditions: load with unity power factor, load with high quality factor, and load matching DER’s powers.
文摘Energy consumption reduction efforts in the residential buildings sector represent socio-economical, technological and environmental preoccupations which justify advanced scientific research. These lead to use inverse models to describe thermal behavior and to evaluate the energy consumption of buildings. Their principal goal is to provide supporting evidence of enhanced energy performances and predictions. More specifically, research questions are related to building thermal modeling which is the most appropriate in a smart grid context. In this context, the models are reviewed according to three categories. The first category is based on physical and basic principle modeling (white-box). The second offers a much simpler structure which is the statistical models (black-box). The black-box is used for prediction of energy consumption and heating/ cooling demands. Finally, the third category is a hybrid method (grey-box), which uses both physical and statistical modeling techniques. In this paper, we propose a detailed review and simulation of the main thermal building models. Our comparison and simulation results demonstrate that the grey-box is the most effective model for management of buildings energy consumption.
文摘Grid connected voltage source inverters (VSIs) are essential for the integration of the distributed energy resources. Hysteresis current control (HCC) is a commonly employed method for power control of VSIs. This control method, in contrast with voltage control, provides good dynamics, good stability and implicit over current protection. However, the most important concern of digital implementation of HCC is related with the sampling period of the measured currents. This paper presents a predictive hysteresis current control (HCC) for grid connected voltage source inverter and its FPGA implementation. Simulation and experimental results are provided to verify the validity of the proposed implementation.
文摘As a part of the Smart Grid concept, an efficient energy management at the residential level has received increasing attention in lately research. Its main focus is to balance the energy consumption in the residential environment in order to avoid the undesirable peaks faced by the electricity supplier. This challenge can be achieved by means of a home energy management system (HEMS). The HEMS may consider local renewable energy production and energy storage, as well as local control of some particular loads when peaks mitigation is necessary. This paper presents the modeling and comparison of two residential systems;one using conventional electric baseboard heating and the other one supported by Electric Thermal Storage (ETS);the ETS is employed to optimize the local energy utilization pursuing the peak shaving of residential consumption profile. Simulations of the proposed architecture using the Energetic Macroscopic Representation (EMR) demonstrate the potential of ETS technologies in future HEMS.