Reliability Analysis and Design Using Intelligent Techniques for Wind Energy Systems

Abstract

ABSTRACT newlineWind power is the most reliable and developed renewable energy source. The isolating of wind power in relation to totally installed capacity of power is increasing worldwide. The wind turbine based upon the Doubly Fed Induction Generator (DFIG) with variable-speed variable-pitch regulate scheme is the most common wind power generator in the industry of wind power. Either in grid connected mode or by standalone mode, this machine can function. A complete analysis on modelling, control, dynamic and the steady state analysis of this machine in both operation modes is essential to draw the power optimally from the wind and precisely find its functions. The main responsibility of the Maximum Power Point Tracking (MPPT) module is to draw maximum power from the wind while it is available. newlineThis thesis presents a wind energy conversion system based upon the DFIG which includes different MPPT control techniques for a grid connected system. The Grid Side Converter (GSC) provides the modulation of the Direct Current (DC) voltage and the power flow from the rotor of the DFIG to the grid.The important reason behind the research relies on effective use of MPPT techniques and the optimization of control parameters on the grid side converter, thereby making a high performance Wind Energy Conversion System (WECS). The other problems associated with the voltage regulation at the grid side are high settling and rise time, overshoot and undershoot problems, low transient response and high computational complexity. The base intention of the research is to reduce the problems stated above. These have been accomplished by using intelligent controllers and optimization algorithms. newlineIn this thesis most of the reliable MPPT control strategies are (Proportional and Integral (PI), Perturb and Observe (PandO), Fuzzy Logic Controller (FLC), Adaptive Neuro Fuzzy Inference System (ANFIS), and cuckoo, crow search optimization techniques) applied in DFIG based WECS. Cuckoo search optimization and crow search techniques are adopted, and both