الفهرس 
صفحة العنوانOnly 14 pages are availabe for public view
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Abstract
Since the national electrical network of Egypt relies mainly on the thermal power stations that require a considerable amount of fossil fuels and pollute the environment, the supreme council of energy has planned for the renewable energy sources to generate about 20 % of the national demand. It is clear that the weather of Egypt and its geographic location make it a potential candidate to lead the region in the field of renewable energy and possibly export electric power to the neighbors. The idea is to focus more on harnessing of the renewable energy sources in order to gradually replace the conventional electrical grid aiming at minimizing the electric power cost and serve the environment.
In order to overcome the intermittent nature of renewable energy sources, two or more renewable sources are connected together forming hybrid systems. The main aim of this thesis is to investigate and improve the dynamic performance of a hybrid photovoltaic and wind turbine (PV-WT) system under various operational conditions. The hybrid energy system consists of PV and doubly-fed induction generator wind turbine, which are connected together through a DC link. In order to improve the dynamic performance, a particle swarm optimization (PSO) algorithm is proposed for tuning the controllers of system converters. The obtained optimum gains are then implemented in a simulation model using the MATLAB/SIMULINK environment. The simulation results in the case of optimized gains are compared to the results with an initial-design result in the relevant literature. The results show that the dynamic performance of the system is improved in terms of speed and steady-state error.
In this thesis, a particle swarm optimization algorithm (PSO) is proposed for tuning the PI controllers in order to get the optimum dynamic performance of a hybrid PV-WT under various operation conditions. Simulation results presents compere between optimal design and initial design in MATLAB/Simulink.