Wireless sensor networks (WSNs) play a key role in extending the smart grid implementation towards residential premises and energy management applications. Efficient supply and demand balance, and consequently reducing the electricity expenses and carbon emissions, is an immediate benefit of implementing smart grids. In this paper, design and implementation of an energy management system (EMS) for efficient load management are proposed. The EMS reduces the consumption of the consumers at the peak load hours and thus reduces the carbon emissions of the household. The proposed system consists of two main parts. The first part is an Energy Management Unit (EMU) which has a graphical user interface for runtime monitoring and control. The second part is sensor nodes which measure the power consumption of the different loads and transfer it to the EMU via multi-hop network. The EMU is implemented using NI LABVIEW software and XBee-PRO ZigBee module to communicate with sensor nodes. Hardware model is implemented using Arduino Uno microcontroller, XBee-PRO ZigBee module and the ACS712 current sensor. The EMS is applied to building of Electrical Engineering Department at Assiut University as a case study

Wireless sensor networks (WSNs) play a key role in extending the smart grid implementation towards residential premises and energy management applications. Efficient supply and demand balance, and consequently reducing the electricity expenses and carbon emissions, is an immediate benefit of implementing smart grids. In this paper, design and implementation of an energy management system (EMS) for efficient load management are proposed. The EMS reduces the consumption of the consumers at the peak load hours and thus reduces the carbon emissions of the household. The proposed system consists of two main parts. The first part is an Energy Management Unit (EMU) which has a graphical user interface for runtime monitoring and control. The second part is sensor nodes which measure the power consumption of the different loads and transfer it to the EMU via multi-hop network. The EMU is implemented using NI LABVIEW software and XBee-PRO ZigBee module to communicate with sensor nodes. Hardware model is implemented using Arduino Uno microcontroller, XBee-PRO ZigBee module and the ACS712 current sensor. The EMS is applied to building of Electrical Engineering Department at Assiut University as a case study

Wireless sensor networks (WSNs) play a key role in extending the smart grid implementation towards residential premises and energy management applications. Efficient supply and demand balance, and consequently reducing the electricity expenses and carbon emissions, is an immediate benefit of implementing smart grids. In this paper, design and implementation of an energy management system (EMS) for efficient load management are proposed. The EMS reduces the consumption of the consumers at the peak load hours and thus reduces the carbon emissions of the household. The proposed system consists of two main parts. The first part is an Energy Management Unit (EMU) which has a graphical user interface for runtime monitoring and control. The second part is sensor nodes which measure the power consumption of the different loads and transfer it to the EMU via multi-hop network. The EMU is implemented using NI LABVIEW software and XBee-PRO ZigBee module to communicate with sensor nodes. Hardware model is implemented using Arduino Uno microcontroller, XBee-PRO ZigBee module and the ACS712 current sensor. The EMS is applied to building of Electrical Engineering Department at Assiut University as a case study

Wireless sensor networks (WSNs) play a key role in extending the smart grid implementation towards residential premises and energy management applications. Efficient supply and demand balance, and consequently reducing the electricity expenses and carbon emissions, is an immediate benefit of implementing smart grids. In this paper, design and implementation of an energy management system (EMS) for efficient load management are proposed. The EMS reduces the consumption of the consumers at the peak load hours and thus reduces the carbon emissions of the household. The proposed system consists of two main parts. The first part is an Energy Management Unit (EMU) which has a graphical user interface for runtime monitoring and control. The second part is sensor nodes which measure the power consumption of the different loads and transfer it to the EMU via multi-hop network. The EMU is implemented using NI LABVIEW software and XBee-PRO ZigBee module to communicate with sensor nodes. Hardware model is implemented using Arduino Uno microcontroller, XBee-PRO ZigBee module and the ACS712 current sensor. The EMS is applied to building of Electrical Engineering Department at Assiut University as a case study

Wireless sensor networks (WSNs) play a key role in extending the smart grid implementation towards residential premises and energy management applications. Efficient supply and demand balance, and consequently reducing the electricity expenses and carbon emissions, is an immediate benefit of implementing smart grids. In this paper, design and implementation of an energy management system (EMS) for efficient load management are proposed. The EMS reduces the consumption of the consumers at the peak load hours and thus reduces the carbon emissions of the household. The proposed system consists of two main parts. The first part is an Energy Management Unit (EMU) which has a graphical user interface for runtime monitoring and control. The second part is sensor nodes which measure the power consumption of the different loads and transfer it to the EMU via multi-hop network. The EMU is implemented using NI LABVIEW software and XBee-PRO ZigBee module to communicate with sensor nodes. Hardware model is implemented using Arduino Uno microcontroller, XBee-PRO ZigBee module and the ACS712 current sensor. The EMS is applied to building of Electrical Engineering Department at Assiut University as a case study

Abstract –This paper proposes an accurate model for DC photovoltaic pumping system. The system model begins with the photovoltaic module (PVM).The boost converter is used as an interfacing circuitry between the PVM and the motor. The DC motor is a permanent magnet (PM) type which coupled with a centrifugal pump. The boost converter is controlled using three different maximum power point tracking (MPPT) algorithms to extract the available power under changing conditions of radiation. Optimal duty cycle required to drive the boost converter is obtained using graphical steady state analysis. Further the system is built using Matlab/Simulink and tested with different atmospheric conditions.

Abstract –This paper proposes an accurate model for DC photovoltaic pumping system. The system model begins with the photovoltaic module (PVM).The boost converter is used as an interfacing circuitry between the PVM and the motor. The DC motor is a permanent magnet (PM) type which coupled with a centrifugal pump. The boost converter is controlled using three different maximum power point tracking (MPPT) algorithms to extract the available power under changing conditions of radiation. Optimal duty cycle required to drive the boost converter is obtained using graphical steady state analysis. Further the system is built using Matlab/Simulink and tested with different atmospheric conditions.

Abstract –This paper proposes an accurate model for DC photovoltaic pumping system. The system model begins with the photovoltaic module (PVM).The boost converter is used as an interfacing circuitry between the PVM and the motor. The DC motor is a permanent magnet (PM) type which coupled with a centrifugal pump. The boost converter is controlled using three different maximum power point tracking (MPPT) algorithms to extract the available power under changing conditions of radiation. Optimal duty cycle required to drive the boost converter is obtained using graphical steady state analysis. Further the system is built using Matlab/Simulink and tested with different atmospheric conditions.

Abstract. This study aims to analyze the flow characteristics and the thermal features of foil thrust bearing. The flow in the gas film is modeled with 2D compressible Reynolds equation including effects of centrifugal forces in the gas film. The Couette Approximation is adopted for the analysis of temperature distribution in the gas film, and the small perturbations method is used to calcu-late its dynamic force coefficients. The results show that the Couette Approxi-mation can be used to calculate the temperature distribution in foil thrust bearing with reasonable accuracy and the analysis of the fluid flow reveals that most of the side-leakage occurs in the low-temperature converging region removing less than 5% of the heat generated in the gas film. Furthermore, with the proper control of cooling flow rate through the bump foils, more than 70% of the heat generated in the gas film can be removed.

Abstract: This study aims to tailor the bearing stiffness for enhancing the load carrying capacity of foil thrust bearings. New architectures for the bump foil are introduced with structural stiffness tailored in radial and circumferential directions to ensure a converging gas film under high axial loads while maintaining a reasonable bearing compliance to accommodate thermal as well as mechanical distortions. The flow in the gas film is modeled with 2-D compressible Reynolds equation including effects of centrifugal forces in the gas film. The Couette Approximation technique is used to calculate the temperature distribution in the gas film and small perturbations method is used to calculate its dynamic coefficients. Enhanced load capacity could be obtained with the introduced bump foil designs.