Naggar Hassan Saad - Academia.edu (original) (raw)

Naggar Hassan Saad

Uploads

Papers by Naggar Hassan Saad

Research paper thumbnail of Steady state performance of axial laminations switched reluctance motor

This paper presents the steady state operation of the axial laminations switched reluctance motor... more This paper presents the steady state operation of the axial laminations switched reluctance motor (ALSRM). The performance of the motor is studied under constant speed operation and different values of both the switching turn on and off angles. The response of the motor is obtained at low, high, and very high speed in order to illustrate the performance of the

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Speed Regulation of Switched Reluctance Motor Using lead-Lag Compensator Controller

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Direct Torque Control Induction Motor Drive using Adaptive Fuzzy Torque Ripple Minimization

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Enhancing the maximum power point tracking techniques for photovoltaic systems

Renewable and Sustainable Energy Reviews, 2014

ABSTRACT The development of maximum power point tracking (MPPT) is continuing in order to increas... more ABSTRACT The development of maximum power point tracking (MPPT) is continuing in order to increase the energy transfer efficiency of the solar photovoltaic system. This paper provides a review of the conventional maximum power point tracking techniques that is enhanced by the presentation of a new technique. The new method is based on a genetic neural algorithm in order to predict the closest point to the maximum power point (MPP), which will be the kickoff point of the search process. Not only does the new technique start the search process from the nearest point to the MPP, but also the developed search algorithm is very fast. Consequently, the time taken to reach the MPP is reduced. In order to determine the new MPPT performance, a complete photovoltaic generator system is modeled and simulated using the MATLAB/SIMULINK package. Simulation results show that the new technique reaches the MPP in less than 100 sample times compared to tens of thousands of samples for conventional methods. Furthermore, the new technique reaches directly the target MPP with small deviation from the intended values. Consequently, the new technique has a significant improvement in energy extraction efficiency from the photovoltaic array to the load, in addition to higher tracking speed and system stability compared to the conventional ones.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Adaptive Neural Controller for Maximum Power Point Tracking Of Ten Parameter Fuel Cell Model

DESCRIPTION Nonlinear characteristic and internal behavior of the Proton Exchange Membrane (PEM) ... more DESCRIPTION Nonlinear characteristic and internal behavior of the Proton Exchange Membrane (PEM) Fuel Cells under different load conditions is of paramount importance. This paper presents an adaptive neural controller based on a back-propagation algorithm for maximum power control of PEM fuel cell system. The system consists of a buck-boost converter connected to the fuel cell. The adaptive neural controller receives the error and change of error signals as inputs during load changes and generates the DC-DC converter duty cycle. By using the inference, the duty ratio of the buck-boost converter is controlled so that the fuel cell can provide the maximum power. The ANN controller monitors also the temperature, the pressure and the cell voltage. In this paper the dynamic model for proton exchange membrane fuel cells using ten parameter model is used. The model has been implemented in MATLAB/SIMULINK. Both the double-layer charging effect and the thermodynamic characteristic inside the...

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Backstepping Nonlinear Control Strategy for Dynamic Voltage Restorer Using Multilevel Inverter

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Speed control of axial lamination switched reluctance motor provided with digital pole placement controller

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Low voltage ride through of doubly-fed induction generator connected to the grid using sliding mode control strategy

Renewable Energy, 2015

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Artificial neural controller for maximum power point tracking ofphotovoltaic system

Maximum power point tracking (MPPT) is necessary for photovoltaic (PV) systems to collect the max... more Maximum power point tracking (MPPT) is necessary for photovoltaic (PV) systems to collect the maximum photovoltaic array power under variations in the insolation and temperature. This paper presents an artificial neural controller for maximum power point tracking of photovoltaic system based on back- propagation algorithm. The tracking algorithm changes the duty cycle of the DC-DC converter so that PV module voltage equals the voltage corresponding to the MPPT at any given insolation level and temperature conditions.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Calculation of Voltage Thresholds for Source Schedulaing in a Hybrid Renweable Nanogrid

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Steady state performance of axial laminations switched reluctance motor

This paper presents the steady state operation of the axial laminations switched reluctance motor... more This paper presents the steady state operation of the axial laminations switched reluctance motor (ALSRM). The performance of the motor is studied under constant speed operation and different values of both the switching turn on and off angles. The response of the motor is obtained at low, high, and very high speed in order to illustrate the performance of the

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Speed Regulation of Switched Reluctance Motor Using lead-Lag Compensator Controller

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Direct Torque Control Induction Motor Drive using Adaptive Fuzzy Torque Ripple Minimization

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Enhancing the maximum power point tracking techniques for photovoltaic systems

Renewable and Sustainable Energy Reviews, 2014

ABSTRACT The development of maximum power point tracking (MPPT) is continuing in order to increas... more ABSTRACT The development of maximum power point tracking (MPPT) is continuing in order to increase the energy transfer efficiency of the solar photovoltaic system. This paper provides a review of the conventional maximum power point tracking techniques that is enhanced by the presentation of a new technique. The new method is based on a genetic neural algorithm in order to predict the closest point to the maximum power point (MPP), which will be the kickoff point of the search process. Not only does the new technique start the search process from the nearest point to the MPP, but also the developed search algorithm is very fast. Consequently, the time taken to reach the MPP is reduced. In order to determine the new MPPT performance, a complete photovoltaic generator system is modeled and simulated using the MATLAB/SIMULINK package. Simulation results show that the new technique reaches the MPP in less than 100 sample times compared to tens of thousands of samples for conventional methods. Furthermore, the new technique reaches directly the target MPP with small deviation from the intended values. Consequently, the new technique has a significant improvement in energy extraction efficiency from the photovoltaic array to the load, in addition to higher tracking speed and system stability compared to the conventional ones.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Adaptive Neural Controller for Maximum Power Point Tracking Of Ten Parameter Fuel Cell Model

DESCRIPTION Nonlinear characteristic and internal behavior of the Proton Exchange Membrane (PEM) ... more DESCRIPTION Nonlinear characteristic and internal behavior of the Proton Exchange Membrane (PEM) Fuel Cells under different load conditions is of paramount importance. This paper presents an adaptive neural controller based on a back-propagation algorithm for maximum power control of PEM fuel cell system. The system consists of a buck-boost converter connected to the fuel cell. The adaptive neural controller receives the error and change of error signals as inputs during load changes and generates the DC-DC converter duty cycle. By using the inference, the duty ratio of the buck-boost converter is controlled so that the fuel cell can provide the maximum power. The ANN controller monitors also the temperature, the pressure and the cell voltage. In this paper the dynamic model for proton exchange membrane fuel cells using ten parameter model is used. The model has been implemented in MATLAB/SIMULINK. Both the double-layer charging effect and the thermodynamic characteristic inside the...

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Backstepping Nonlinear Control Strategy for Dynamic Voltage Restorer Using Multilevel Inverter

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Speed control of axial lamination switched reluctance motor provided with digital pole placement controller

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Low voltage ride through of doubly-fed induction generator connected to the grid using sliding mode control strategy

Renewable Energy, 2015

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Artificial neural controller for maximum power point tracking ofphotovoltaic system

Maximum power point tracking (MPPT) is necessary for photovoltaic (PV) systems to collect the max... more Maximum power point tracking (MPPT) is necessary for photovoltaic (PV) systems to collect the maximum photovoltaic array power under variations in the insolation and temperature. This paper presents an artificial neural controller for maximum power point tracking of photovoltaic system based on back- propagation algorithm. The tracking algorithm changes the duty cycle of the DC-DC converter so that PV module voltage equals the voltage corresponding to the MPPT at any given insolation level and temperature conditions.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Calculation of Voltage Thresholds for Source Schedulaing in a Hybrid Renweable Nanogrid

Bookmarks Related papers MentionsView impact

Log In