الفهرس 
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Abstract
The electrical energy demand is increasing nowadays due to the rapid increase of population in the world. The conventional energy sources that depend on fossil fuels will be unable to face the rapid growth of electrical energy demand due to their limited availability. So the recent researches concern with the renewable energy sources especially Photovoltaic energy.
In Photovoltaic (PV) systems, DC-DC converters are used as intermediate stage between PV and load for Maximum Power Point Tracking (MPPT) purposes. Buck converters used in tracking the maximum power for photovoltaic systems suffer from some drawbacks. The Fourth order Buck Converter (FOBC) has been introduced in literature as efficient alternative that can overcome the problems of conventional buck converters.
Tracking the Maximum Power Point (MPP) needs current and voltage sensors to measure the Solar Cell Array (SCA) current and voltage continuously. Unfortunately, using a lot of sensors makes the system more expensive and more complex. The objective of the thesis is to study the performance of FOBC using enhanced control techniques that depend only on one sensor (voltage sensor) without needing any current sensors. The analysis is done using two different control techniques; Perturb and Observe (P&O) MPPT technique and ant colony Optimization (ACO) MPPT technique. The proposed control algorithms can trace the MPP without needing any initial conditions besides consuming small time to reach MPP.
The complete photovoltaic system is modeled and simulated using the MATLAB package to achieve MPPT purposes. Simulation results show that both techniques could reach MPP in small time with high accuracy using only one sensor. As a result, the system is less expensive and less complex. Moreover, changing the insolation level has no effect on reaching the actual MPP for both techniques. Moreover, if the load value changes during operation, the output power will not be affected for both techniques.