ملخص الدراسة:

Renewable energy sources play an important role in electric power generation. There are various renewable sources, which are used for electric power generation, such as solar energy, wind energy, geothermal etc. Solar energy is a good choice for electric power generation, which is viewed as clean and renewable source of energy for the future since the solar energy is directly converted into electrical energy by solar photovoltaic modules which is suitable for obtaining higher power output. There are two major approaches: sun tracking and maximum power point tracking to maximizing the power output of the solar arrays. These two methods need efficient intelligent controller such as Fuzzy Logic Controller (FLC). The advantage of the fuzzy logic control is that it does not strictly need any mathematical model of the plant. It is based on operator experience, and it is very easy to apply. Hence, many complex systems can be controlled without knowing the exact mathematical model of the plant. In addition, fuzzy logic simplifies dealing with nonlinearities in systems. The advantage of fuzzy logic control is that the linguistic system definition becomes the control algorithm. In this thesis: Two Sugeno fuzzy logic controllers are designed to increase the energy generation efficiency of solar cells. These controllers are, sun-tracking controller and maximum power point tracking controller with Genetic Algorithm (GA) to optimize the membership, output gain and inputs gain of the fuzzy controllers. Solar tracking system uses a stepper motor as the drive source to rotate the solar panel. The position of the sun is determined by using a tracking sensor, the sensor reading is converted from analog to digital signal, and then it passed to a fuzzy logic controller. The controller output is connected to the driver of the stepper motor to rotate PV panel in one axis until it faces the sun. The proposed sun-tracking controller is tested using Matlab/Simulink program, the results show that the Sugeno controller has a good response when compared with Mamdani controller. Maximum power point tracking system uses dc-to-dc converter to compensate the output voltage of the solar panel to keep the voltage at the value, which maximizes the output power. MPP fuzzy logic controller measures the values of the voltage, and current at the output of the solar panel. Then, calculates the power from the relation (P=V*I) to extract the inputs of the controller, and the crisp output of the controller represents the duty cycle of the pulse width modulation for controlling on/off time of MOSFET switch of a buck converter. The proposed maximum power point tracking controller for grid-connected photovoltaic system is tested using model designed by Matlab/Simulink program and the results show that the Sugeno controller with GA has a response better than Mamdani controller applied to the same system.

توثيق المرجعي (APA)