الفهرس 
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Abstract
ABSTRACT
Renewable energy resources are considered the savior of electricity generation as depletion of conventional energy resources. Photovoltaic energy is one form of solar energy resources. The Solar panel or photovoltaic technology has developed a lot and has become much more efficient and more affordable for residential and commercial customers that advancement helps with the penetration of the PV technology into the grid.
Modeling the PV module is essential in order to use it in the PV system simulation process. This model is useful for dynamic analysis and for predicting their behavior under different operating conditions. Because the data provided by PV manufacturers is insufficient, various unknown parameters exist in the PV mathematical model. Single and double diode models are the equivalent circuit models utilized to represent the non-linear I-V relationship. The two models are introduced to achieve a higher level of accuracy.
By adjusting PV model parameters, the fitness function has been assessed by reducing the Root-Mean-Square error between calculated and measured current experimental data.
This optimization is executed through several nature inspired meta-heuristic optimization techniques known as the Crow Search Algorithm (CSA) and the Water Cycle Algorithm (WCA).
The simulation findings that are performed out under different environmental circumstances using the MATLAB software verify the PV models and the efficacy of the CSA, WCA-based PV models is evaluated by contrasting and these simulation results have been compared to the experimental results outcomes of a Kyocera KC200GT PV module and contrasting this model’s absolute current error.
The designed PV system includes a PV array linked to the electric grid via a DC enhance converter, a DC-link capacitor, a grid-side inverter, a step-up transformer, and transmitting lines to improve photovoltaic system performance and enhance low voltage ride through capacity in all abnormal operating conditions. The DC-DC converter employs a voltage control strategy that satisfies maximum power point tracking operation. The voltage at the point of common connection and the DC link voltage at the grid side inverter are both controlled using the control systems are based on Proportional Integral controllers.
The fitness function has been optimized using a new swarm intelligence technique called Emperor Penguin Optimizer in comparison to old methods such as the Genetic Algorithm for getting PI controller parameters, which ensures the controllers’ best design. The proposed control system is being tested under faulty conditions to ensure its validity.
The Matlab/Simulation software was used to simulate the System in this study.
Throughout the thesis it was noticed the study of the photovoltaic cell system connected to the electrical grid when tracking the PowerPoint and the use of new methodologies with the control of the control photovoltaic systems and optimizing the voltage crossing moments of solar cells and electric grid, the results showed that the rapid control system works in height and the outstanding of the controllers by Emperor Penguin Optimizer works with high performance under fault conditions.