Controller design of doubly fed induction generator for WECS

Abstract

This thesis presents the methodological aspects and algorithmic approach for controller design of a doubly fed induction generator for performance enhancement and reliability improvement of a wind energy conversion system. Recently, the doubly fed induction generator is one of the most frequently used generators in the wind energy conversion systems. The optimal control of large scale wind farm becomes a critical issue for the development of the renewable energy systems and their integration into the power grid to provide reliable, secure and efficient electrical energy. A critical review of the DFIG based WT, its control aspects for wind energy conversion system and emerging issues from last one decade have been described and demonstrated in detail. The study starts with describing widespread perception on wind energy and commonly used generator in wind energy conversion.Then it presents additional particulars on DFIGs active modes and utilization. It is followed by DFIG control methods in addition to overviews of different engaged electrical and mechanical controlling methods. The DFIG overview along with its merits and demerits, the principle of operation in synchronous / super synchronous speeds, the mathematical modeling and controller design for the DFIG driven by variable speed wind turbine, and its converter aspects have described and illustrated appropriately. The DFIG control parameters are very much essential to be optimized to enhance the performance characteristics of the WECs. In previous research in this field, the conventional techniques have improved the control parameters however; this thesis proposes to design a DFIG controller for wind turbine system to improve its transient performance with, rise time, settling time and peak overshoot by using optimization and soft computational evolutionary techniques. The techniques namely: Static output feedback (SOF), Particle swarm optimization (PSO), Bacterial forging optimization (BFO), Firefly algorithm (FFA), Differential evolution algorithm (DE) and Genetic Algorithm (GA) in conjunction with their fitness functions have been described for DFIG controller design for WECs in detail. These evolutionary techniques have several advantages over the conventional methods like use of objective function, no other auxiliary functions, irrespective to the type of parameters, avoid local optimization solutions, probabilistic nature and provide solution for any number of dimensions. During design process, a sixth order transfer function of DFIG model as a plant transfer function is used for performance improvement of the DFIG based wind energy conversion system. On the other hand, an on-off Control method is used for MPPT and anticipated to control the rotor side converter of DFIG based wind turbine connected to the grid. This approach is trying to keep the torque within the optimal value at which the maximum power is obtained. A concept of MPPT has been proposed to achieve the goal of tracking maximum power at a given wind velocity. To perform the MPPT from the wind system, the MPPT block in coordination with the rotor control block acts to maintain the torque to the value that is optimum for extracting the maximum power output from it. The energy conversion device which is used in wind turbine systems is DFIG therefore; a doubly fed induction generator is modelled as an energy conversion device. The Grid Side Converter is controlled in such a way to assure a smooth DC voltage as well as ensure the sinusoidal current on the network. Finally the Reliability of DFIG based wind turbine with performance analysis is described in details, for calculating the reliability of the DFIG based wind turbine unit which builds on the reliability of its components by using the Markov process. This thesis is organized in following seven chapters to describe the reliable controller design of DFIG for performance enhancement of the WECs.techniques have improved the control parameters however; this thesis proposes to design a DFIG controller for wind turbine system to improve its transient performance with, rise time, settling time and peak overshoot by using optimization and soft computational evolutionary techniques. The techniques namely: Static output feedback (SOF), Particle swarm optimization (PSO), Bacterial forging optimization (BFO), Firefly algorithm (FFA), Differential evolution algorithm (DE) and Genetic Algorithm (GA) in conjunction with their fitness functions have been described for DFIG controller design for WECs in detail. These evolutionary techniques have several advantages over the conventional methods like use of objective function, no other auxiliary functions, irrespective to the type of parameters, avoid local optimization solutions, probabilistic nature and provide solution for any number of dimensions. During design process, a sixth order transfer function of DFIG model as a plant transfer function is used for performance improvement of the DFIG based wind energy conversion system. On the other hand, an on-off Control method is used for MPPT and anticipated to control the rotor side converter of DFIG based wind turbine connected to the grid. This approach is trying to keep the torque within the optimal value at which the maximum power is obtained. A concept of MPPT has been proposed to achieve the goal of tracking maximum power at a given wind velocity. To perform the MPPT from the wind system, the MPPT block in coordination with the rotor control block acts to maintain the torque to the value that is optimum for extracting the maximum power output from it. The energy conversion device which is used in wind turbine systems is DFIG therefore; a doubly fed induction generator is modelled as an energy conversion device. The Grid Side Converter is controlled in such a way to assure a smooth DC voltage as well as ensure the sinusoidal current on the network. Finally the Reliability of DFIG based wind turbine with performance analysis is described in details, for calculating the reliability of the DFIG based wind turbine unit which builds on the reliability of its components by using the Markov process. This thesis is organized in following seven chapters to describe the reliable controller design of DFIG for performance enhancement of the WECs.