A non-linear Control of Power Wind Turbine Based on Doubly Fed Induction Generator

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1 A non-linear Control of Power Wind Turbine Based on Doubly Fed Induction Generator Karima Boulaam and Akkila Boukhelifa Instrumentation Laboratory Faculty of Electronics and Computers University of Sciences and Technology Houari Boumediene Algiers Algeria Isam Janajreh Mechanical Engineering Masdar Institute of Science and Technology P. O. Box Abu Dhabi, United Arab Emirates Abstract- The efficiency of the wind power conversion systems can be significantly improved by the judicious choice of the control algorithm. To maximize the power extraction of a Doubly- Fed Induction Generator (DFIG) based wind turbine, we propose a non-linear control algorithm, based on a sliding mode theory. It has been used to control the wind turbine speed so that it reaches the desired value which corresponds to the maximum power point. For a great capacity to generate very good quality waveforms, the machine is connected to the grid via multilevel converter. To be able to easily control the wind turbine power generation, we will realize an independent control of generator stator active and reactive power. The control system adopts the oriented flux.simulation tests are established using MATLAB- Simulink. Analysis of simulation results confirms the validity of the proposed strategy. Keywords: Wind turbine, MPPT, sliding mode, DFIG, NPC Multilevel converter. I. INTRODUCTION The use of renewable energy resources is increasingly being pursued as a supplement and an alternative to large conventional central power stations. Wind energy is becoming one of among important renewable sources. So many studies [1-4, 7] are oriented toward this type of energy production in the aim to make it more efficient. Variable speed wind turbines are widely used in this field owing to their ability to maximize wind power extraction [1-5]. Most of these WECS are based on Doubly Fed Induction Generator (DFIG), Self-Excited Induction Generator (SEIG) and Permanent Magnet Synchronous Generator. The one analyzed in this paper is based on a doubly fed induction generator (DFIG). This machine presents different advantages [4] such as: operating in a large game of speed, generation of a constant frequency active power and the possibility of the generated active and reactive power to be controlled independently. Maximum power point tracking (MPPT) strategies play an important role in wind power conversion systems (WECS). Many of schemes focused on power maximization, produced significant increases in the maximum instantaneous power produced. Two strategies are used in literature [1-7], with or without speed control. In this paper we used the strategy with speed control. The main objective of a proposed work is to extract maximum power of wind turbine by optimal generator torque with speed control. Linear and non-linear control are used by authors [1, 4, 7], we adopted in this paper a non-linear control which is more suitable for non-linear systems, such as the wind turbine model. This control is based on sliding mode theory. The specification of a power-electronic interface is a very important point. Multilevel converters have been under research and development for more than three decades and have found successful industrial application. They are emerging as a new breed of power converter options for highpower applications such as wind energy conversion systems. The multilevel voltage source converters typically synthesize the staircase voltage wave from several levels of DC capacitor voltages These power converters have many advantages which are the capacity to generate a very good quality of waveforms, the reduced switching frequency, the low energy loss and the low effort on power devices [8]. Several Multilevel converter technologies have emerged recently.for our WECS, we have used one of the most important topologies like diode-clamped inverter (neutral-point clamped (NPC). The wind energy system conversion is presented in section II. In section III, we present the generator modeling and the command of active and reactive power using PI controllers. The wind turbine model and a turbine speed control model is given in section IV. In section V, we present a maximum power point tracking technique. The MPPT sliding mode algorithm is proposed to be applied to the speed control model is presented in section VI. Finally, analyzed results are presented in section VII. II. WIND ENERGY SYSTEM CONVERSION DFIG wind turbine includes a wound rotor induction generator connected to the wind turbine rotor through a gearbox. This generator presents the stator winding directly grid-coupled and a bidirectional power converter feeding the rotor winding. This converter is constituted by a NPC threelevel inverter structure associated with a NPC three level rectifier converter linked by a DC bus. This power converter decouples the electrical grid frequency and the mechanical rotor frequency, thus enabling variable speed wind turbine generation. The wind turbine rotor presents MPPT control based on a non-linear algorithm /13/$ IEEE 127

2 The schematic diagram of the wind energy system conversion is shown in Fig. 1. The mathematic model of DFIG in the synchronous reference frame (dq frame) linked to the stator flux is as follows: (7) (8) III. Fig.1. Wind energy conversion system GENERATOR MODELING AND COMMAND The generator dynamic model written in a synchronously rotating frame d-q [2, 3, 7] given by the equation system below. (1) (2) (3) (4) (10) According to Eq. (10), we can see that the stator active and reactive power P s and Q s could be controlled by the rotor current d, q components I rq and I rd respectively. Fig. 2 shows the DFIG control structure containing two current control loops using PI controllers. The reference magnitude desired P sref, corresponds to the maximum power point given by the generator speed regulator. Q sref is imposed equal to zero, in order to operate at unitary power factor. (9) (5) s, (r) = Stator (rotor) index; d, q = Synchronous reference frame index; V (I) = Voltage (Current); = Flux; P s (Q s ) = Stator Active (Reactive) power; T em = Electromagnetic torque; R = Resistance; L (M) = Inductance (Mutual inductance); σ = Leakage coefficient, (σ = 1 M 2 /L s L r ); ω, (ω s ) = Angular speed (Synchronous speed); s = Slip; p = Pole pair number. To be able to easily control the wind turbine power generation, we will realize an independent control of generator stator active and reactive power. The control system adopts the oriented flux strategy, defined in the synchronous d-qframe fixed to the stator flux (6). (6) IV. Fig. 2. DFIG powers control scheme WIND TURBINE MODELING The aerodynamic power generated by a wind turbine is given by the equation [2][4][5][7]: (11) ρ:air density, : wind speed, C p:power coefficient, β: blade pitch angle, λ: tip-speed ratio, it given by (12). λ (12) Where R and Ω tutb are the radius and speed of the turbine rotor. The power coefficient C p determines the efficiency at which energy is extracted from the wind. This C p value typically varies with wind speed and is different for each turbine design. For our turbine, Itis expressed by Eq. (13) [1]: 128

3 ( ) (13) This control structure consists to adjust the torque appearing on the turbine shaft in order to fix the turbine speed at a reference which permits to track the maximum wind power. This reference is deducted from (12). The mechanical equation of the shaft is given by [5]: (14) J and fare the total moment of inertia and the viscous friction coefficient appearing at the generator side, T g is the gearbox torque, T em is the generator torque, and Ωis the mechanical generator speed. We write: G is the gear ratio, and T aer is the aerodynamic torque. V. MUXIMUM POWER POINT TRACKING TECHNIQUE (15) According to Eq. (12), we can see that if the rotor speed is kept constant, then any change in the wind speed will change the tip-speed ratio, leading to degrade the power coefficient C p, as well as the generated power output of the wind turbine. However, if the rotor speed is adjusted according to the wind speed variation, then the tip-speed ratio can be maintained at an optimal point opt, so C p at its maximum C pmax which could yield maximum power output from the system according to Eq. (11) [1, 5]. So the MPPT technique consists in varying turbine speed constantly according to wind speed variations, so that the tip-speed ratio is maintained in its optimum value, thus the power generation is optimum. This operation is obviously valid while the maximum allowable rotor speed and rated power are not reached. Arriving to these values; we are no more concerned by the MPPT, but rather by maintaining themconstant, a necessary proceeding for system protection. Fig. 3. Power Coefficient versus Tip- Speed Ratio for Different Values of the Pitch Angle. VI. MPPT USING SLIDING MODE CONTROL In order to extract the maximum power from the wind, we adopted the speed turbine control strategy. It permits to carry the speed wind turbine into the desired value which corresponds to the maximum power point. (16) The wind speed which is variable and unpredictable is considered as a perturbation for our system. Therefore, we need a robust control algorithm which permits the system to reach its reference without being affected by this perturbation. a. Sliding mode Sliding mode control is one of the non-linear techniques.it is a particular operation mode of variable structure control systems. Itsconcept consists in moving the state trajectory of the system toa predetermined surface called sliding surface and maintaining it around this latter with an appropriate logic commutation [10]. In general, for a system defined by the state Eq. (17), for a vector u of dimensionm, we must choose m surfaces. (17) and Concerning the surface form, [10] propose the following form: ( ) (18) e(x): the error between the variable and its reference. : positive constant indicating the desired control bandwidth. r: relative degree, equal to the number of times to derive the output to appear the command. When the control system operates in variable structure sliding mode, the switching (commutation low) always respects the condition S(x)=0. Therefore, the derivative versus time should also always be zero, i.e., Š(x)=0. So that this condition is respected at all times, the magnitude of command should take a well determined value, designated by the equivalent control u eq. So that the evolution trajectory of the system tends to S = 0, the system must be submitted to the attraction of this surface.this will be done by the attractive control a determined by the condition of attractiveness: S(x) Š(x)<0 This command defines the dynamic behavior of the system during the trajectory convergence mode to the sliding surface. It is equal to zero once the sliding mode is achieved. The simplest solution is to choose u a with the relay shape: ( ) With k>0 Thus the necessary low control to bring back the variable we want control to the selected surface, respecting both the existence and attractiveness conditions is given by: u=u eq +u a 129

4 Power coefficient Sliding surface Real and reference generator speed (rd/s) Wind speed (m/s) st International Conference & Exhibition on the Applications of Information Technology to Renewable Energy Processes and Systems b. Design of sliding mode control algorithm To design a variable structure speed controller [10], we consider Eq. (19): Ω Ω (19) We choose the error as being the sliding surface: This surface derivative is: (20) (21) To ensure the attractiveness condition as follow:, is chosen (22) k 1 and k 2 are positive constants, sign(s) is the signum function. So, the torque command T em ref can be obtained from Eqs. (19), (21) and (22): ( ) Ω (23) VII. SIMULATION RESULTS The wind turbine speed control is tested on a variable wind power conversion system based on a doubly-fed induction generator (DFIG) of 1.5MW.The wind turbine parameters are given in table I. In order to evaluate the MPPT control strategy proposed in this paper, the simulation is carried out using the MATLAB/Simulink software. Fig. 6 shows the wind speed used. Simulation results are shown in Fig. 7 to Fig. 11, for a chosen controller. Simulation results show that our objective is attained. The sliding mode controller has permitted to extract the maximum of power from the wind. Fig. 7 shows that the generator speed follows its reference with rapid response. The sliding mode surface (Fig. 8) equals to zero, which shows that the controller parameters are properly chosen. Concerning the power coefficient (Fig. 9), it reaches the optimal value (C pmax =0.5) and it s not affected by a sudden wind speed variation. Figs. 10 and 11 present the output active and reactive powers of DFIG. They show that the decoupling is successfully effected. The two powers reached their references with the presence of fluctuations due to the three level converters. Finally, all results verified the effectiveness of the proposed control law Fig. 6. Wind Speed Profile 50 0 Fig. 7. Generator speed Fig. 8. Sliding surface Fig. 9. Power coefficient. 130

5 orientation theory. The simulation results clearly show the effectiveness of a sliding mode approach in terms of maximization of extracted power. In addition, the non-linear control successfully controls the variable speed wind turbine, satisfying static and dynamic performances. Vector control permitted to obtain a separate control of the active and reactive powers. REFERENCES Fig. 10. Active power. Fig. 11. Reactive Power TABLE I WIND TURBINE PARAMETERS Rated power 1.5 MW Density of air = kg/m 3 Number of blades 3 Radius of rotor R= 30.5m Gear ratio G= 90 Turbine total inertia J =1000 kg.m 2 Total viscous friction coefficient f = N.m/s VIII. CONCLUSION In this paper, we have proposed a non-linear MPPT control strategy of a variable wind turbine based on a sliding mode algorithm. The machine is controlled by the stator flux [1] Oscar Barambones, PatxiAlkorta and Manuel De La Sen+ EUI de Vitoria, Wind Turbine Output Power Maximization Based on Sliding Mode Control Strategy, IEE2010, pp [2] B. Beltran, M.E.H. Benbouzidand T. Ahmed-Ali, High-Order Sliding Mode Control of a DFIG-Based Wind Turbine for Power Maximization and Grid Fault Tolerance, 2009IEEE, pp [3] XuemeiZheng, Lin Li, DianguoXu, Jim Platts, Sliding Mode MPPT Control of Variable Speed Wind Power System, 2009 IEEE. [4] G.Tapia and A.Tapia, Wind Generation Optimization Algorithm for a Doubly Fed Induction Generator, IEE Proc.-Gener.Transm. Distrib.,vol. 152, No.2, pp , March [5] S. El Aimani, Modélisation de Différentes Technologies d Eoliennes Intégrées dans un Réseau de Moyenne Tension, Thèse de Doctorat, Lille [6] V.Rogez, Modélisation Simplifiée de Sources de Production Décentralisées pour des Etudes de Dynamique des Réseaux. Application à l Intégration d une Production Eolienne dans un Réseau de Distribution Insulaire, Thèse de Doctorat, Lille [7] Tinglong Pan, ZhichengJi, Zhenhua Jiang, Maximum Power Point Tracking of Wind Energy Conversion Systems Based on Sliding Mode Extremum Seeking Control, IEEE Energy 2030, Atlanta, GA USA, November, [8] Ying Cheng, Chang Qian, Mariesa L. Crow, Steve Pekarek, AComparison of Diode-Clamped and Cascaded Multilevel Converters for a STATCOM With Energy Storage Industrial Electronics, IEEE Transactions on Volume 53, Issue 5, Oct.2006 Page(s): [9] Slotine.J.J.E. and W. Li., Applied Non-Linear Control [M], Prentice- Hall, Englewood Cliffs, NJ. 1991, No [10] V.I Utkin, Sliding Mode Control Design. Principles and Applications to Electric Drives, IEEE Trans, on Industrial Electronics, Vol. 40, No. 1 pp , February