Abstract:This paper proposes a second-order active disturbance rejection control (ADRC)-based control strategy with an integrated design of the flux damping method, for the fault ride-through (FRT) improvement in wind power generation systems with a doubly-fed induction generator (DFIG). First, a first principles model of the rotor and grid side converter of DFIG is developed, which is then used to theoretically analyze the system characteristics and show the damage caused to the DFIG system by a grid voltage fault. Then, the flux damping method is used to suppress the rotor current during a fault ride-through. In order to enhance the robustness and effectiveness of the flux damping method under complex working conditions, an ADRC approach is proposed for disturbance attenuation of the DFIG systems. Finally, a comparison of the proposed method with three other control approaches on a 1.5-MV DFIG system benchmark is performed. It is shown that the proposed method can adaptively and effectively improve the system performance during an FRT.Keywords: wind energy conversion system (WECS); doubly fed induction generation (DFIG); voltage fault ride through (FRT); flux damping method; active disturbance rejection control (ADRC)
Doubly Fed Induction Machine: Modeling and Control for Wind Energy Generation books pdf file
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This book will be focused on the modeling and control of the DFIM based wind turbines. In the first part of the book, the mathematical description of different basic dynamic models of the DFIM will be carried out. It will be accompanied by a detailed steady-state analysis of the machine. After that, a more sophisticated model of the machine that considers grid disturbances, such as voltage dips and unbalances will be also studied. The second part of the book surveys the most relevant control strategies used for the DFIM when it operates at the wind energy generation application. The control techniques studied, range from standard solutions used by wind turbine manufacturers, to the last developments oriented to improve the behavior of high power wind turbines, as well as control and hardware based solutions to address different faulty scenarios of the grid. In addition, the standalone DFIM generation system will be also analyzed.
In this paper the issue of control strategies for the doubly fed induction generator (DFIG) is addressed in a wind energy production. The active and reactive power between the stator of DFIG and the grid are controlled independently by using a novel linear control scheme called the Active Disturbance Rejection Control (ADRC) based on the extended state observer (ESO) in order to ensure the decoupling of the system from the actual disturbance acting on the plant. In order to maximize the power of wind energy conversion, the use of MPPT control is indispensable. Finally, a numerical simulation with MATLAB/Simulink confirms the performance of the proposed controller.
Over the last decade, wind energy has taken an increasingly important place in the field of electric energy generation. This kind of energy source is developed due to the global growing of electricity demand and the trend towards renewable and non-polluting energy sources in the world [1]. Indeed, in wind energy conversion system (WECS), the maximum wind power could be extracted when the tip-speed-ratio of the turbine is maintained at its optimum value for different wind speed patterns [2]. Thus, it is necessary to develop more advanced control strategies for WECS. To this end, several control methods have been designed and implemented for wind energy generation such as, vector control which is based on voltage and flux oriented vector using the d-q rotating frame to decouple the active and reactive power, [3, 4]. In fact, this strategy is sensible to parameters variations of the system such as resistance and inductance variations. To overcome this problem, direct torque control (DTC) has been introduced by [5, 6] to directly control generator torque and stator flux using a predefined lookup table based on the estimation of the stator flux and electromagnetic torque. Direct power control (DPC) proposed in [7], has used the same concept of the DTC method. DPC control strategy is based on decoupling and direct control of reactive and active power [8]. In fact, the non-linear behaviors of mechanical and electrical parts of WECS as well as variations of electromechanical parameters represent crucial problems [9]. In addition, wind turbine (WT) works under high wind speed variations, which makes its control a serious challenge [10]. As result, several nonlinear control techniques have been developed in the literature for WT, such as fuzzy logic [11], neural networks [12], and high-order sliding mode control [13].
Currently, most WECS use Double feed induction generator (DFIG). This is due to many advantages such as variable speed operation of the generator ( 30% around the synchronous speed), decoupling between active and reactive powers, maximization of energy generation and competitive price [1]. But, DFIG is subjected to many constraints, such as the effects of parametric variations and the disturbance of the wind speed, which could deviate the system from its optimal operation point. Many control techniques of the DFIG have been presented with different control schemes. The conventional Proportional-Integral (PI) controller, although widely used in many control applications [14], requires adjustment for every change in reference patterns. Another main disadvantage of this controller is its sensibility to external disturbances and parameters variations. Because of the frequent uncertainty in wind speed variations, this type of conventional controller fails to give quality power generation and tracking references given by an MPPT. Predictive control based on rotor voltage and stator power equations for direct power control, is proposed in [15, 16]. Nevertheless, the calculated output reactive and active power which depend on the generator parameters as well as the time calculation, are the main drawbacks of this method [17]. In addition, internal uncertainties and external disturbances produce serious oscillations of the WECS. To ensure the robustness of the system against parametric variations and external disturbances, the authors in [18, 19] have introduced sliding mode control (SMC). In fact, SMC could achieve active and reactive power tracking and improve the dynamic.
This paper is organized as follow: Section 2 recalls a short overview of first order sliding mode control and second order sliding mode control. In the Section 3, we present the structure of wind energy conversion system then the modelling of turbine and the double feed induction generator. In the first part of Section 4, we present the estimation of the aerodynamic torque. In the second part of Section 4, we describe the control of the aerodynamic torque. In Section 5, we interest to the control of DFIG. In this context, we compare three types of controllers such as PI, sliding mode control and second order sliding mode control. Finally, Section 6 shows the simulation results of the proposed system.
The major problem of standard law is mainly the determination with accuracy the value of kopt since λopt change significantly over time. To achieve WT power efficiency maximization, rotor speed should track the reference given by the optimum speed ratio, under variable wind speed and unknown aerodynamic torque. The wind speed variation would lead to aerodynamic power fluctuation and high mechanical effort, which results in less energy capture and poor performance in terms of active power generation. In the following, a second order sliding mode control (SOSMC) with aerodynamic torque observer is proposed.
The need for energy in the world is increasing day by day and renewable energy resources prove to be an excellent choice to meet the energy demand. Wind energy resource is one such renewable energy resources, but the speed variation of wind can cause undesirable fluctuations in output voltage frequency. But doubly fed induction generator can work with variable speed input while maintaining the grid frequency constant. This paper presents the state of art of doubly fed induction generator in a wind energy conversion system.
Model Predictive Control of Wind Energy Conversion Systems addresses the predicative control strategy that has emerged as a promising digital control tool within the field of power electronics, variable-speed motor drives, and energy conversion systems.The authors provide a comprehensive analysis on the model predictive control of power converters employed in a wide variety of variable-speed wind energy conversion systems (WECS). The contents of this book includes an overview of wind energy system configurations, power converters for variable-speed WECS, digital control techniques, MPC, modeling of power converters and wind generators for MPC design. Other topics include the mapping of continuous-time models to discrete-time models by various exact, approximate, and quasi-exact discretization methods, modeling and control of wind turbine grid-side two-level and multilevel voltage source converters. The authors also focus on the MPC of several power converter configurations for full variable-speed permanent magnet synchronous generator based WECS, squirrel-cage induction generator based WECS, and semi-variable-speed doubly fed induction generator based WECS. Furthermore, this book:* Analyzes a wide variety of practical WECS, illustrating important concepts with case studies, simulations, and experimental results* Provides a step-by-step design procedure for the development of predictive control schemes for various WECS configurations* Describes continuous- and discrete-time modeling of wind generators and power converters, weighting factor selection, discretization methods, and extrapolation techniques* Presents useful material for other power electronic applications such as variable-speed motor drives, power quality conditioners, electric vehicles, photovoltaic energy systems, distributed generation, and high-voltage direct current transmission.* Explores S-Function Builder programming in MATLAB environment to implement various MPC strategies through the companion websiteReflecting the latest technologies in the field, Model Predictive Control of Wind Energy Conversion Systems is a valuable reference for academic researchers, practicing engineers, and other professionals. It can also be used as a textbook for graduate-level and advanced undergraduate courses. 2ff7e9595c
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