In the deregulated economy, the maximum load forecasting is important for the electric industry. Many applications are included such as the energy generation and purchasing. The aim of the present study is to find the...In the deregulated economy, the maximum load forecasting is important for the electric industry. Many applications are included such as the energy generation and purchasing. The aim of the present study is to find the most suitable models for the peak load of the Kingdom of Bahrain. Many mathematical methods have been developing for maximum load forecasting. In the present paper, the modeling of the maximum load, population and GDP （gross domestic product） versus years obtained. The curve fitting technique used to find that models, where Graph 4.4.2 as a tool used to find the models. As well, Neuro-Fuzzy used to find the three models. Therefore, three techniques are used. These three are exponential, linear modeling and Neuro-Fuzzy. It is found that, the Neuro-Fuzzy is the most suitable and realistic one. Then, the linear modeling is the next suitable one.展开更多
The photovoltaic (PV) generator exhibits a nonlinear current-voltage (I-V) characteristic that its maximum power point (MPP) varies with solar insolation. In this paper, a maximum power point tracking (MPPT) method us...The photovoltaic (PV) generator exhibits a nonlinear current-voltage (I-V) characteristic that its maximum power point (MPP) varies with solar insolation. In this paper, a maximum power point tracking (MPPT) method using fuzzy logic control (FLC) is presented. This method is based on the concept of perturbation and observation (P & O) algorithm to track the MPP of a stand-alone PV system. The controller is used to maximize the power generated by the PV array and the simulation of the system is implemented in MATLAB. Simulation results are compared with those obtained by the conventional P & O controller. Results show that the FLC gives better and more reliable control for the stand-alone PV system feeding hybrid loads.展开更多
文摘In the deregulated economy, the maximum load forecasting is important for the electric industry. Many applications are included such as the energy generation and purchasing. The aim of the present study is to find the most suitable models for the peak load of the Kingdom of Bahrain. Many mathematical methods have been developing for maximum load forecasting. In the present paper, the modeling of the maximum load, population and GDP （gross domestic product） versus years obtained. The curve fitting technique used to find that models, where Graph 4.4.2 as a tool used to find the models. As well, Neuro-Fuzzy used to find the three models. Therefore, three techniques are used. These three are exponential, linear modeling and Neuro-Fuzzy. It is found that, the Neuro-Fuzzy is the most suitable and realistic one. Then, the linear modeling is the next suitable one.
文摘The photovoltaic (PV) generator exhibits a nonlinear current-voltage (I-V) characteristic that its maximum power point (MPP) varies with solar insolation. In this paper, a maximum power point tracking (MPPT) method using fuzzy logic control (FLC) is presented. This method is based on the concept of perturbation and observation (P & O) algorithm to track the MPP of a stand-alone PV system. The controller is used to maximize the power generated by the PV array and the simulation of the system is implemented in MATLAB. Simulation results are compared with those obtained by the conventional P & O controller. Results show that the FLC gives better and more reliable control for the stand-alone PV system feeding hybrid loads.
