In this paper, a simulation study of the maximum power point tracking (MPPT) for a photovoltaic system using an artificial neural network is presented. Maximum power point tracking (MPPT) plays an important role in photovoltaic systems because it maximizes the power output from a PV solar system for all temperature and irradiation conditions, and therefore maximizes the power efficiency. Since the maximum power point (MPP) varies, based on the PV irradiation and temperature, appropriate algorithms must be utilized to track it in order maintain the optimal operation of the system. The software Matlab/Simulink is used to develop the model of PV solar system MPPT controller. The system simulation is elaborated by combining the models established of solar PV module and a DC/DC Boost converter. The system is studied using various irradiance shading conditions. Simulation results show that the photovoltaic simulation system tracks optimally the maximum power point even under severe disturbances conditions.

In this paper, a simulation study of the maximum power point tracking (MPPT) for a photovoltaic system using an artificial neural network is presented. Maximum power point tracking (MPPT) plays an important role in photovoltaic systems because it maximizes the power output from a PV solar system for all temperature and irradiation conditions, and therefore maximizes the power efficiency. Since the maximum power point (MPP) varies, based on the PV irradiation and temperature, appropriate algorithms must be utilized to track it in order maintain the optimal operation of the system. The software Matlab/Simulink is used to develop the model of PV solar system MPPT controller. The system simulation is elaborated by combining the models established of solar PV module and a DC/DC Boost converter. The system is studied using various irradiance shading conditions. Simulation results show that the photovoltaic simulation system tracks optimally the maximum power point even under severe disturbances conditions.

In this paper, a simulation study of the maximum power point tracking (MPPT) for a photovoltaic system using an artificial neural network is presented. Maximum power point tracking (MPPT) plays an important role in photovoltaic systems because it maximizes the power output from a PV solar system for all temperature and irradiation conditions, and therefore maximizes the power efficiency. Since the maximum power point (MPP) varies, based on the PV irradiation and temperature, appropriate algorithms must be utilized to track it in order maintain the optimal operation of the system. The software Matlab/Simulink is used to develop the model of PV solar system MPPT controller. The system simulation is elaborated by combining the models established of solar PV module and a DC/DC Boost converter. The system is studied using various irradiance shading conditions. Simulation results show that the photovoltaic simulation system tracks optimally the maximum power point even under severe disturbances conditions.

The paper proposes a new reliable fault-tolerant scheduling algorithm for real-time embedded systems. The proposed scheduling algorithm takes into consideration only one bus fault in multi-bus heterogeneous architectures, caused by hardware faults and compensated by software redundancy solutions. The proposed algorithm is based on both active and passive backup copies, to minimize the scheduling length of data on buses. In the experiments, this paper evaluates the proposed methods in terms of data scheduling length for a set of DAG benchmarks. The experimental results show the effectiveness of our technique.

The paper proposes a new reliable fault-tolerant scheduling algorithm for real-time embedded systems. The proposed scheduling algorithm takes into consideration only one bus fault in multi-bus heterogeneous architectures, caused by hardware faults and compensated by software redundancy solutions. The proposed algorithm is based on both active and passive backup copies, to minimize the scheduling length of data on buses. In the experiments, this paper evaluates the proposed methods in terms of data scheduling length for a set of DAG benchmarks. The experimental results show the effectiveness of our technique.

The coupled finite element method - finite volume method are applied to solve magnetohydrodynamic (MHD) flow equations and the thermal equation in the linear induction MHD pump taking into account the saturation of the ferromagnetic materials. This study is done using the stream-vorticity formulation. The purpose of this paper is to represent the velocity and the temperature respectively in linear and non linear cases because it is required to have the knowledge of the flow and the temperature to design an MHD pump. Additionally, the effect of the electromagnetic thrust on the flow distribution in a linear induction MHD pump is studied.

The coupled finite element method - finite volume method are applied to solve magnetohydrodynamic (MHD) flow equations and the thermal equation in the linear induction MHD pump taking into account the saturation of the ferromagnetic materials. This study is done using the stream-vorticity formulation. The purpose of this paper is to represent the velocity and the temperature respectively in linear and non linear cases because it is required to have the knowledge of the flow and the temperature to design an MHD pump. Additionally, the effect of the electromagnetic thrust on the flow distribution in a linear induction MHD pump is studied.

The coupled finite element method - finite volume method are applied to solve magnetohydrodynamic (MHD) flow equations and the thermal equation in the linear induction MHD pump taking into account the saturation of the ferromagnetic materials. This study is done using the stream-vorticity formulation. The purpose of this paper is to represent the velocity and the temperature respectively in linear and non linear cases because it is required to have the knowledge of the flow and the temperature to design an MHD pump. Additionally, the effect of the electromagnetic thrust on the flow distribution in a linear induction MHD pump is studied.

The coupled finite element method - finite volume method are applied to solve magnetohydrodynamic (MHD) flow equations and the thermal equation in the linear induction MHD pump taking into account the saturation of the ferromagnetic materials. This study is done using the stream-vorticity formulation. The purpose of this paper is to represent the velocity and the temperature respectively in linear and non linear cases because it is required to have the knowledge of the flow and the temperature to design an MHD pump. Additionally, the effect of the electromagnetic thrust on the flow distribution in a linear induction MHD pump is studied.