الفهرس 
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Abstract
The main interest of the world is oriented lately towards renewable energy sources, since most of the advanced countries are aiming to replace all fossils with renewables. This interest is raised through targeting more safe, clean as well as sustainable generated electric energy. Most of the research work has been focused mainly on both wind and solar based power systems and on developing their control and interface for more efficient, and economical operation. Developing Photovoltaics, their control and interface have received most of the interest of researchers worldwide recently. The new trend for improving its control is through the transition from traditional adaptive control methods to the new optimization control techniques.
In this thesis, a survey is primarily presented to compare all suggested control approaches considering their advantages and disadvantages with special interest directed towards various maximum power point tracking (MPPT) techniques along with their optimization Algorithms.
A survey of the system different components and main construction is also presented through studying the function of each unit and device and its effect on every part of the system. The system is then modeled and simulated on MATLAB/SIMULINK software, where the specifications of the components are wisely chosen to be close enough to the real system.
Three main studies are adopted. The first is aimed at optimizing the controller used for adjusting the output voltage of the inverter, while the second study is focused on enhancing the system’s performance, and the maximum power point tracking (MPPT) process under partial shading (PS) conditions. Here, a second order amplifier is added to the MPPT control to maximize the output power under PS through tuning its gains. In the third study, the system performance is tested under PS while tuning the duty cycle of the DC booster. After that, the system is fully optimized by tuning the amplifier and the duty cycle simultaneously.
For this purpose, three optimization algorithms have been utilized. One of them is basic and previously tested which is the Particle Swarm Optimization (PSO) algorithms. The other two are newly proposed nature-based optimization algorithms, which are the Cuttlefish Algorithm (CFA) and the Emperor Penguin Optimizer (EPO). All three algorithms resulted in quite interesting satisfying results that are discussed later at the end of the thesis.
Both static and dynamic states were considered, simulated, and tested for checking the system’s robustness. Results are recorded, and observations are reported to reach at the required conclusions.