Robust Active and Reactive Power Control Schemes for a Doubly Fed Induction Generator Based Wind Energy Conversion System

In view of resolving rising environmental concern arising out of fossil fuel based power generation, more electricity has to be generated from renewable energy sources. Out of the several renewable energy options available today, wind energy is considered to be the most promising one due to its high energy conversion efficiency compared to one of its competitors, i.e. the solar photovoltaic system. Now-a-days, large wind farms are generating thousands of megawatts of power feeding to the grid. In literature, number of controllers such as conventional proportional integral (PI) control, linear parameter varying (LPV) control, gain scheduling control, robust control, model predictive control have been proposed for both torque and pitch control. In these controllers, some of the important issues such as robustness for nonlinear dynamics of wind turbine and stability are not considered simultaneously. Hence, it is necessary to design appropriate controllers for extracting maximum power from the wind turbine whilst the robustness and stability of the Wind Energy Conversion System (WECS) are ensured. Hence, in this thesis, firstly the focus is made to design control system for the wind turbine coupled with the DFIG (torque and pitch control) using one of the very promising robust control paradigm called sliding mode controller for achieving robustness, reducing chattering phenomenon and stability of the WECS. Since the number of terms in control inputs (i.e. torque and pitch angle) and outputs (i.e. DFIG output power and speed) are more in wind control dynamics, selection of significant terms is important for reducing the complexity of controlling. Therefore, a Nonlinear Autoregressive Moving Average with exogenous input (NARMAX) model of the WECS has been developed. The parameters of this NARMAX model are estimated by suitably designing an on-line adaptive Recursive Least squares (RLS) algorithm. Subsequently for controlling speed and achieving efficient power regulation of the WECS a nonlinear model predictive controller (NAMPC) has been developed in which the control variables (torque and pitch) are optimised by formulating a cost function. Subsequently for the WECS, the power converters connecting the DFIG to the grid have been designed. For controlling stator active and reactive power of DFIG connected to the grid, a state feedback controller for the DFIG has been developed using a linear quadratic optimal theory with preview concept. This Linear Quadratic Regulator Optimal Preview Control (LQROPC) scheme is employed with a stator voltage oriented control (SVOC) technique. This Optimal preview control is used to solve the tracking and rejection problems with an assumption that the signals to be tracked or rejected are available a priori by a certain amount of time. Even though the OPC provides very good tracking and disturbance suppression performance, but it is sensitive to the DFIG circuit parameters which makes the WECS system unstable. Hence, to address the parameter uncertainty of the DFIG, a sliding mode controller has been proposed and the robustness of the WECS have been verified by using the Lyapunov criterion. Then, a 2 kW DFIG based WECS experimental setup has been developed in the laboratory to study the effectiveness of the controllers developed

Nonlinear Dual-Mode Control of Variable-Speed Wind Turbines with Doubly Fed Induction Generators

This paper presents a feedback/feedforward nonlinear controller for variable-speed wind turbines with doubly fed induction generators. By appropriately adjusting the rotor voltages and the blade pitch angle, the controller simultaneously enables: (a) control of the active power in both the maximum power tracking and power regulation modes, (b) seamless switching between the two modes, and (c) control of the reactive power so that a desirable power factor is maintained. Unlike many existing designs, the controller is developed based on original, nonlinear, electromechanically-coupled models of wind turbines, without attempting approximate linearization. Its development consists of three steps: (i) employ feedback linearization to exactly cancel some of the nonlinearities and perform arbitrary pole placement, (ii) design a speed controller that makes the rotor angular velocity track a desired reference whenever possible, and (iii) introduce a Lyapunov-like function and present a gradient-based approach for minimizing this function. The effectiveness of the controller is demonstrated through simulation of a wind turbine operating under several scenarios.Comment: 14 pages, 9 figures, accepted for publication in IEEE Transactions on Control Systems Technolog

A novel LMI-based robust model predictive control for DFIG-based wind energy conversion systems

summary:The optimal and reliable performance of doubly fed induction generator is essential for the efficient and optimal operation of wind energy conversion systems. This paper considers the nonlinear dynamic of a DFIG linked to a power grid and presents a new robust model predictive control technique of active and reactive power by the use of the linear matrix inequality in DFIG-based WECS. The control law is obtained through the LMI-based model predictive control that allows considering both economic and tracking factors by optimization of an objective function, constraints on control signal and states of system and effects of nonlinearities, generator parameter uncertainties and external disturbances. Robust stability in the face of bounded disturbances and generator uncertainty is shown using Lyapunov technique. Numerical simulations show that the proposed control method is able to meet the desired specification in active and reactive power control in the presence of varieties of wind speed and pitch angle

Generalized Predictive Control Scheme for a Wind Turbine System

In this paper, a generalized predictive control scheme for wind energy conversion systems that consists of a wind turbine and a doubly-fed induction generator is proposed. The design is created by using the maximum power point tracking theory to maximize the extracted wind power, even when the turbine is uncertain or the wind speed varies abruptly. The suggested controller guarantees compliance with current constraints by applying them in the regulator’s conceptual design process to assure that the rotor windings are not damaged due to the over-current. This GPC speed control solves the optimization problem based on the truncated Newton minimization method. Finally, simulation results, which are obtained through the Matlab/Simulink software, show the effectiveness of the proposed speed regulator compared to the widely used Proportional-integral controller for DFIG.The University of the Basque Country (UPV/EHU) (grant number PIF 18/127) has funded the research in this paper

Offset-Free Direct Power Control of DFIG Under Continuous-Time Model Predictive Control

This paper presents a robust continuous-time model predictive direct power control for doubly fed induction generator (DFIG). The proposed approach uses Taylor series expansion to predict the stator current in the synchronous reference frame over a finite time horizon. The predicted stator current is directly used to compute the required rotor voltage in order to minimize the difference between the actual stator currents and their references over the predictive time. However, as the proposed strategy is sensitive to parameter variations and external disturbances, a disturbance observer is embedded into the control loop to remove the steady-state error of the stator current. It turns out that the steady-state and the transient performances can be identified by simple design parameters. In this paper, the reference of the stator current is directly calculated from the desired stator active and reactive powers without encompassing the parameters of the machine itself. Hence, no extra power control loop is required in the control structure to ensure smooth operation of the DFIG. The feasibility of the proposed strategy is verified by the experimental results of the grid-connected DFIG and satisfactory performances are obtained

Direct power control for grid-connected doubly fed induction generator using disturbance observer based control

A disturbance observer based control method for a grid-connected doubly fed induction generator is presented in this study. The proposed control method consists of a state-feedback controller and a disturbance observer (DO). The DO is used to compensate for model uncertainties with the aim of removing the steady-state error. The control objective consists of regulating the stator currents instead of the rotor currents in order to achieve direct control of the stator active and reactive powers. Such a control scheme removes the need for an exact knowledge of the machine parameters to achieve accurate control of the stator active and reactive powers. The main advantage of this control method is ensuring a good transient performance as per the controller design specifications, while guaranteeing zero steady-state error. Moreover, the proposed control method was experimentally validated on a small scale DFIG setup

Integral Backstepping Based Nonlinear Control for Maximum Power Point Tracking and Unity Power Factor of a Grid Connected Hybrid Wind-Photovoltaic System

This paper proposes a novel integral backstepping-based nonlinear control strategy for a grid-connected wind-photovoltaic hybrid system. Firstly, detailed three-phase models of the hybrid system elements are presented, and then an overall state-space model is derived. Secondly, nonlinear control laws for the hybrid system’s converters are developed with the aim of ensuring maximum extraction of the available renewable energy, stabilizing the DC bus voltage and guaranteeing the operation of the hybrid system at unity power factor. The overall stability of the closed-loop system is demonstrated on the basis of Lyapunov’s stability theory. Comprehensive simulations, using the MATLAB/Simulink software environment, are carried out to assess the effectiveness of the proposed control methodology. The simulation results obtained confirm that the proposed control strategy offers high efficiency in various operating modes of the hybrid generation system

Modeling and Lyapunov-designed based on adaptive gain sliding mode control for wind turbines

In this paper, modeling and the Lyapunov-designed control approach are studied for the Wind Energy Conversion Systems (WECS). The objective of this study is to ensure the maximum energy production of a WECS while reducing the mechanical stress on the shafts (turbine and generator). Furthermore, the proposed control strategy aims to optimize the wind energy captured by the wind turbine operating under rating wind speed, using an Adaptive Gain Sliding Mode Control (AG-SMC). The adaptation for the sliding gain and the torque estimation are carried out using the sliding surface as an improved solution that handles the conventional sliding mode control. Furthermore, the resultant WECS control policy is relatively simple, meaning the online computational cost and time are considerably reduced. Time-domain simulation studies are performed to discuss the effectiveness of the proposed control strateg