Enhancement of induction generator in wind energy system

Dissertant

Ahmad, Husayn Qasim

Thesis advisor

Jalal, Kanan Ali

University

University of Technology

Faculty

-

Department

Department of Electrical Engineering

University Country

Iraq

Degree

Master

Degree Date

2013

English Abstract

Wind power is safe as well as they from one of the family members of renewable energy, the energy does not make them environmental pollutants harmful to the environment, where the world is heading now after global warming as well as pollution, for the adoption of renewable energy sources as alternative energy sources.

For these reasons, the technological advance seeks to reduce the cost of renewable energy and increase efficiency to expand their reach.

This work describes the effect of electrical parameters of the Doubly Fed Induction Generator (DFIG) for operation within power system in order to perform stability and turbine control to maximize the power generated with the lowest impact on the grid voltage and frequency during normal operation and under several disturbances, such as a transmission line earth fault.

The proposed methods consider wind turbines based on induction generator and a grid-connected converter with constant or variable speed wind turbines.

The proposed work is performed within the multiple technologies design tool MATLAB/Simulink.

The performance of DFIG under different operating conditions is investigated and an Artificial Intelligent (AI) controller is proposed to enhance the performance of induction generator parameters in wind energy system during different disturbance conditions.

The purpose of the control system is to manage the safe, automatic operation of the turbine, within a framework of optimizing generated power.

Three types of controllers are proposed in this work; the first controller is the Proportional-Integral (PI) based on classical trial and error method, the second controller is PI-controller based on Particle Swarm Optimization (PSO) technique for optimal tuning to improve the performance of the system and the third controller Artificial Neural Network (ANN) controller with gains is optimized by PSO technique.

The comparative study between the three controllers shows that Artificial Neural Network (ANN) is very effective on the stabilization of the system.

Processing becomes simpler as computational complexity is reduced.

The major advantage of ANN is that it has no mathematical model, so the computational time is reduced.

The dynamic control joins different strategies that will ensure better stability and power regulation generated by the wind turbine.

These strategies with intelligent control techniques, such as PSO and ANN, allow the increase in robustness, performance, capacity and flexibility.

Main Subjects

Electronic engineering

Topics

• Renewable energy sources
• Wind power
• Energy resources
• Electrical equipment
• Electric power systems
• Electric power generation
• Electrical generators

• APA
• MLA
• AMA

Language

English

Data Type

Arab Theses

Record ID

BIM-417972