Hybrid algorithms for the intelligent management of a renewable production system: Power Quality Enhancement and service continuity contribution

Abstract

Over the recent years, the world has witnessed a rapid development in the use of renewable energy in electricity consumption. Where, in 2015 the Total wind power production was reached to 432.83 MW, i.e. an increase of 17% from the previous year. In other side, the changing in the nature of loads in industrial, commercial and residential establishments connecting to the grid, led the disturbances in quality of energy which must be as a pure sinusoidal waveform with specific phases and frequency. This thesis investigates and proposes new solutions to enhance the power quality and reliability of electricity supply of wind turbine energy based on Doubly Fed Induction Generator (DFIG) system using hybrid artificial intelligence algorithms. The control scheme of the overall system consists of three controls blocks namely the Rotor Side Converter (RSC), Grid Side Converter (GSC) and the Maximum Power Point Tacking (MPPT) control which permits energy exchange between the wind energy conversion system and the grid. The problems of power quality including harmonic distortion are discussed in details and mitigation techniques based on shunt active power filtering are presented. An efficient and economical solution based on the concept of priority control is proposed. This priority control method permits to manage the priority among the previous system production controls and the harmonics currents suppression using Synchronous Reference Frame (SRF) harmonic extraction current method. In addition, and to ensure service continuity, a hybrid-intelligent Fault Tolerant Control (FTC) strategy of IGBT open-circuit for Rotor Side Converter (RSC) has been presented. The FTC strategy is based on Expert Systems and combines a simple fault detection method based on fuzzy logic inference and uses rotor current average values to detect the faulty switch in a very short period. Furthermore, to improve the performance of the closed-loop system during transients and faulty conditions, different currents controllers like conventional PI, hysteresis, PI fuzzy-adaptive controllers and PI controller optimized using Genetic Algorithms have been used. The simulation model was developed in Matlab/Simulink environment and the results demonstrate that the proposed techniques can effectively reduce the Total Harmonic Distortion (THD) in the grid currents and maintain the quality of energy within the international standards and ensure service continuity of the system during open switch IGBT fault.