الفهرس 
CHAPTER 1 INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
There is increasing necessity for renewable replacements to traditional fossil fuel electric power generation. One of main applications of photovoltaic systems is supplying the rural areas which have not a connection to the power grid such as irrigation systems. The photovoltaic systems depend on the availability of the solar radiation and it faces several practical issues. Such as; they generate DC power and the majority loads are AC, their efficiency is low. The PV cell characteristics is nonlinear. It also depends on the atmospheric and load conditions. The PV system needs a smart controller to achieve the maximum efficiency for the various operating conditions. The Induction Motor (IM) is the horsepower of industry. It covers a large section of the motor used. Speed control of IM is a challenging because the mathematical model of the IM consists of nonlinear high-order differential equations. The thesis introduces a comparative study between two proposed MPPT techniques (modified incremental conductance and sliding mode control) and conventional MPPT techniques. The study show that the proposed techniques have less oscillations around the MPP and fast response with different variations compared with the other techniques. This increases the efficiency and stability of the system. The thesis also introduces two IM variable frequency drive systems; V/f control, and vector control to control the high-performance applications. the vector control based on PI control method was proposed and designed on MATLAB/Simulink. Then it was improved by means of PSO technique to solve the controllers’ gains tuning problems. The results of the PSO technique were better than the conventional tuning method. The error was less than 5% with PSO and around 15 % with PI controller with conventional one. Also, the raising time was less for the PSO tuning gains. A sensorless algorithm for the motor speed estimation was proposed using Artificial Neural Network (ANN) technique, the sensorless model used the motor currents and its terminal voltages to evaluate the motor speed. The system was tested using MATLAB/Simulink, and its results show that it is suitable and reliable for motor speed estimation over a wide speed range. Finally, a cost-efficient prototype for induction motor drive system was designed. The system used V/f controller for controlling the motor speed and achieving the PV maximum power point based on the fractional order open circuit voltage algorithm. The system was set up and the experimental results were taken for various operating conditions. These results show the validation and stability of the system to achieve a constant V/f ratio for all possible values.