الفهرس 
ABSTRACT
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Abstract
ABSTRACT:>Wind power is the most reliable and developed renewable energy source over past decades. Wind energy has numerous benefits in helping to provide a source of clean and renewable electricity for countries all over the world. The wind will never run out, unlike the earth’s fossil fuel reserves (such as coal, oil and gas), making it the ideal energy source for a sustainable power supply. Wind energy is one of the most environmentally friendly energy sources available today. Generating electricity from wind energy reduces the need to burn fossil fuel alternatives such as coal, oil and gas. The Doubly Fed Induction Generator (DFIG) based Wind Energy Conversion System (WECS) with variable speed variable pitch control scheme is the most popular wind power generator in the wind power industry. The performance and controllability of DFIG are excellent in comparison with fixed speed induction generator systems. They capture more wind energy and exhibit a higher reliability gear system. Also they supply high quality power to the grid. It saves investment on full rated power converters and soft starter or reactive power compensation devices compared to fixed speed systems. In the case of a weak grid, where the voltage may fluctuate, the DFIG may be ordered to produce or absorb an amount of reactive power to or from the grid, with the purpose of voltage control. Also, because of its ability to control reactive power and to decouple active and reactive power control by independently controlling the rotor excitation current, DFIG is preferred in wind power generation.
The present thesis applies DFIG in WECS due to its advantages. Essential features of DFIG based WECS is that they have ability to track maximum power at any wind speed below rated wind speed and to keep the output power limited at its rated for any wind speed above rated wind speed. Maximum power point tracking (MPPT) control techniques for DFIG based WECS such as Tip Speed Ratio (TSR) control using Genetic Algorithm (GA) optimization, Power Signal Feedback (PSF) using MPPT scheme curve and controlling direct axis current of rotor side converter (RSC) of DFIG using Neural Network (NN) to extract the maximum power at any wind speed below rated wind speed and under different conditions are proposed. Pitch angle control operation such as Proportional (P) only controller, Particle Swarm (PS) optimization and GA optimization of DFIG based WECS in order to keep the output power limited at its rated for any wind speed above rated wind speed and under different conditions are developed and studies.
The hysteresis band control technique and triangle carrier waveform PWM technique are applied to control and provide switch control signals for power converters of DFIG. Also, the Stator Voltage Orientation (SVO) is applied to DFIG based WECS to control the stator voltage for both Rotor Side Converter (RSC) and Grid Side Converter (GSC). Also, the steady state analysis of DFIG based WECS are presented for different wind speed and stator power factor. Furthermore a dynamic model of DFIG based WECS is developed to study the steady state analysis for different stator power factor.
Moreover, the GSC based Shunt Active Power Filter (SAPF) is designed to eliminate the current harmonic and phase shift produced by presence of nonlinear load and inductive load. Also it achieve at power grid side balanced grid currents and unity power factor. A comparison between GSC based SAPF and connecting SAPF alone at PCC from point of economic view is done. A dynamic model of an infinite power system connected to a DFIG wind turbine of fourteenth order is installed by using the eigenvalues analysis. The overall dynamic system of the DFIG wind turbine with controllers is used for improving the power system stability. Finally, STATCOM dynamic model is designed for regulation of the terminal voltage of the DFIG based WECS under different operating conditions. Further, a simulink Matlab package program is utilized to simulate the overall system for all cases.