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VARIABLE SPEED WIND TURBINES USING CAGE ROTOR INDUCTION GENERATORS CONNECTED TO THE GRID L. Mihet-Popa, V. Groza, Member, IEEE, G. Prostean, I. Filip, and, I. Szeidert Abstract-- In this paper, the performance of variable speed wind turbine concept with cage rotor induction generator connected to the grid is investigated. Variable-speed wind turbine generator system has been modeled and simulated to study their steady state and dynamic behavior. A cage rotor induction machine of 11 kW rating with a vector controlled back-to-back PWM-VSI inverter on the stator side have been tested and the results compared with digital simulations. The cage rotor induction machine allows good speed range and it should be used in low-power variable-speed systems, replacing the classical direct grid connected fixed speed wind generator systems. Its capacity to deliver reactive power is remarkable. Index Terms— Aerodynamic model, back-to-back converter, induction generator, variable-speed wind turbine.
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• It reduces stresses in the drive train due to flywheel effect of the rotor; • It minimizes the audible noise when operating in light winds; • It simplifies the mechanical design and reduces mechanical stress. Due to the rapid development of power electronics, offering both higher power handling capability and lower price/kW, the application of power electronics in wind turbines will increase further [6]. Variable speed wind turbines are a spreading, dominating design principle of power converters applied in wind power turbines today: up to 75 % of all wind turbines installed in 2001 and up to 80 % of those built in 2002 [9]. The most commonly concepts using ac generators with speed variation applied in wind turbine configurations are displayed in Fig. 1 [5, 6, 13].
I. INTRODUCTION
ind turbines may be designed with either synchronous or asynchronous generators, and with various forms of direct and indirect grid connection of the generator. The vast majority of the installed power of wind turbine generators (WTG) in the world is grid connected [4, 10, 12]. Because the wind is highly variable, it is desirable to operate a wind turbine at variable speeds. Generally energy is generated using two operating modes of WTG [1, 5, 6]: • Constant Speed – Constant Frequency (CSCF); • Variable Speed – Constant Frequency (VSCF) control needs speed controller to obtain maximum power from the wind and a converter to change variable frequency of the generator to constant frequency of output voltage. With variable speed the turbine is able to operate at its maximum power for a given wind speed. Some of the advantages of VSCF-WTG against CSCF-WTG are [1]: • It generates more energy by operating on a larger wind speed range; L. Mihet-Popa, G. Prostean, I. Filip, I. Szeidert are with POLITEHNICA University of Timisoara, 300223, Timisoara, Romania, e-mail:
[email protected]. V. Groza is with University of Ottawa, Canada, e-mail:
[email protected].
a)
b)
c) Fig. 1. Standard variable-speed wind turbine configurations using doublyfed induction machine, a), cage rotor induction machine, b), and direct-drive synchronous machine, c).
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Various types of power control strategies have been suggested for application in variable speed wind turbines [1-8, 12]. One possible implementation scheme of adjustable speed generators consist of a synchronous generator and a power converter (Fig. 1c). The power converter, which has to be rated at 1 p.u. total system power, is expensive. The adjustable speed generators systems with cage rotor induction generator (Fig. 1b) are commonly used in low power variable-speed wind turbines replacing the classical direct grid connected fixed speed drives. The goals that can be achieved by using this topology are to increase the energy production especially in the low wind range, eliminate the capacitor bank for reactive power compensation and allow both grid-connection and stand-alone operation modes. With wind generator system depicted in Fig. 1a) variable speed operation is obtained by using a frequency converter in the rotor side of a doubly-fed induction generator (wound rotor). This converter has to handle about (20-40) % of the rated wind turbine power, depending on speed range. Nowadays this system is frequently applied because variable speed operation is obtained at relatively low converter costs [1, 13]. A comparative study regarding different power converter technologies that can be used in wind turbine applications [6] concluded that the backto-back converter is the least troublesome configuration as it uses standard commercial converters. The variable speed wind turbines represent a new technology within wind power for large-scale applications and their models have to be set up for making power stability investigations. Therefore, this concept will be analyzed as follows.
Fig. 2. Variable speed wind turbine using a cage rotor induction machine, a back-to-back PWM-VSI controlled by a dSPACE card and a LCL filter laboratory test system.
To achieve full control of the output, the DC-link voltage must be boosted to a level higher than the amplitude of the grid voltage. The power flow of the grid side converter is controlled in order to keep the DC-link voltage constant. A technical advantage of this topology is the capacitor decoupling between the grid converter and the generator converter. This decoupling offers separate control of the two converters, as can be seen in Fig. 3. The complete grid-side controller including DC-link, full bridge grid inverter, space vector modulator (SVM), LCL filter and grid is shown in Fig. 3. The current controller is designed in d-q synchronous reference frame using two PI regulators for each component. Grid voltages are measured and feed-forward to compensate grid voltages. Cross couplings are compensated with (ωL) terms, assuming that (dω / dt) = constant. PI regulators with anti-windup are used to determine appropriate voltages for the reference currents.
II. EXPERIMENTAL ARANGEMENTS There is an increase demand on the market for low-power variable speed wind turbines that can be used in remote places. To achieve this goal a relatively complex control strategy need to be developed using power converters to process the power flow. In this section a flexible development platform using dSPACE - DS1103 card is used in order to control the power converters for an 11 kW wind generator system. The back-toback voltage source converter is a bi-directional power converter consisting of two conventional voltage source inverters rated at 18.5 kW / 400 V. One frequency inverter is connected to the induction generator and uses the standard vector control (VC) to regulate the speed and provide magnetizing flux. The second one is connected to the grid through an LCL filter and is working as an active rectifier. The LCL filter is used because it achieves better current ripple attenuation than L or RL-filters. Both inverters are controlled via dSPACE 1103 system connected to a PC, as shown in Fig. 2. The dSPACE - DS1103 PPC [11] is a mixed RISC / DSP digital controller providing a powerful 64-bit floating-point processor for calculations as well as comprehensive I/O capability making it very attractive for high-performance machine control applications.
Fig. 3. Schematic block diagram of the grid converter side controller.
The reference current (iq*) in the q-branch of the current loop is set to zero in order to achieve 0 phase angle between voltage and current and therefore unity power factor. Grid synchronization is achieved using the calculated grid voltage phase angle (using PLL) from measurements of the grid voltage.
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The wind emulator is composed of a cage rotor induction machine (15 kW) supplied by a speed-regulated standard commercial frequency converter (VLT 5022-scalar control) used to control the mechanical power (PM=TM*Ωr) on the generator shaft. The cage – rotor induction motor is mechanically coupled with the induction generator. The desired torque from the maximum power tracking algorithm is setting the torque reference for the generator converter which has internal torque regulator. The wind speed is calculated as an average value of the fixedpoint wind speed over the whole rotor, and it takes the tower shadow and the rotational turbulences into account [4, 10, 13]. The aerodynamic model of the wind turbine rotor is based on the power coefficient (Cp), which represents the rotor efficiency of the turbine (aerodynamic efficiency of the blades), taken from a look-up table. The aerodynamic torque is given by:
Trot =
Paero
ω rot
=
1 2 ⋅ ρ ⋅ π ⋅ R 3 ⋅ u eq ⋅ C p ……(1) 2⋅λ
Fig. 4. Simulation model of the variable-speed wind generator system implemented in MATLAB & Simulink software package.
where (Paero) is the aerodynamic power developed on the main shaft of wind turbine with the blade radius (R), at a wind speed (ueq) and the air density (ρ). The blade tip speed ratio (λ) depends on the rotor speed (ωrot), blade radius and wind speed, according to:
λ=
ω rot ⋅ R u eq
……….…………..(2)
The power coefficient (Cp) decreases when the wind speed (ueq) increases (λ small). This fact is used in the passive stall control wind turbines (our case). The equation of motion at the induction generator shaft is given by:
Telm − Td = J ⋅
III. SIMULATION RESULTS Simulation results are used for implementation and to verify the wind generator system model. There are two modes of operation of grid converter, rectifying mode (Fig. 5 b) and generating mode (Fig. 5 a). Fig. 5 shows the phase current (ia) and phase voltage (ua) at nominal load in steady-state in both operation modes. In grid – connection mode, basically all the available power, which can be extracted from the wind turbine, is injected into the grid.
dΩ r ……….….(3) dt
In which (Telm) represents the electromagnetic torque of induction machine, (Td) is the driving torque (positive in motoring mode and negative in generating mode), (J) represent the equivalent moment of inertia for induction machine and the driving mechanism and (Ωr) is the mechanical rotor angular speed. III. SIMULATION MODEL A simulation model is built in order to verify the validity of the designed controllers and the LCL-filter. The simulation model is implemented using MATLAB & Simulink software, using standard and SimPowerSystems blocks. The complete simulation model consists of Grid and Grid mode control, LCL-filter, 2 back-to-back PWM-VSI inverters, modulator, measurements block and DC-link voltage controller, as shown in Fig. 4.
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4 Using the control desk panel interface the parameters of the wind generator system can be shown in both representations, numerically and graphically, as can be seen in Fig. 6. Reference values and parameters of the experimental system can be changed online during the operation mode. Fig. 7 illustrates an acquisition of data in steady-state using an Oscilloscope (TDS 540) at nominal load (11 kW) in generating mode (Fig. 7 a) and in motoring mode (Fig. 7 b). In rectifying mode phase voltage (ua) is in phase with phase current (ia), while the difference in generating mode has 90 degrees. The DC-link voltage controller (regulator) maintains the DC-link voltage almost constant when applying disturbance of nominal load (DC-link voltage drop is under 4 %).
b) Fig. 5. Simulated grid phase current and voltage at nominal power (11 kW) in rectifying mode, (b), and generating mode, (a).
IV. EXPERIMENTAL RESULTS In order to verify the performance of the wind generator system the whole control strategy, including the generator control and the grid converter control, is implemented using DS1103 prototype. A virtual control panel interface has been developed in Control Desk [11] in order to monitor the parameters of the wind generator system, as shown Fig. 6. a)
b)
Fig. 6. The control desk panel interface to monitor online the parameters of the 11 kW wind generator system.
Fig. 7. Phase current (ia), phase voltage (ua) and DC voltage (UDC) at nominal load in generating mode, (a), and in rectifying mode (b), acquired by an Oscilloscope.
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The correspondence between simulations (Fig. 5) and experiments (Fig. 7) in steady-state is good and confirm successful design of the control system. The performances of the wind generator system using cage – rotor induction machine are shown in Fig. 8, during a startup at nominal load (11 kW), monitoring the rotor speed (n), torque (T) and mechanic power (Pm). It is shown that the machine is connected to the power supply at t=3 s and then the induction generator is connected to the grid at 12 seconds when the speed reaches 1050 rpm (reference speed) and the mechanical power becomes 11.5 kW.
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c) Fig. 8. Speed (n) and reference speed (n*), a) and torque (T), b) and mechanical power (Pm) of the induction machine during a start-up at nominal load. The data were acquired by MATLAB via dSPACE card.
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Implementation of the system has been done in order to verify the simulation results, controller design and LCL - filter design. Also, the experimental results show good dynamic performance during the start-up of the machine at nominal load.
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V. CONCLUSIONS
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In this paper a variable speed wind turbine concept using cage rotor induction generator connected to the grid is presented. The simulation results were compared with experimental results and good agreement was obtained. The experimental results also show good dynamic performance during the startup of the machine at nominal load. Simulation results and experimental results confirm successful design of the wind generator system. A flexible development platform with DS1103 dSPACE is used to implement and test a control strategy for 11 kW variable-speed wind turbines with a cage rotor induction generator connected to the grid through a vector controlled back-to-back PWM-VSI inverter and a LCL-filter. Using this configuration is possible to increase the energy production especially in the low wind range, up to 1 MW per unit, eliminate the capacitor bank for reactive power compensation and allow both grid-connection and stand-alone operation modes. By using this flexible development platform, that allows a short development time and high degree of flexibility, is also possible to implement and test different control strategies for variable – speed wind generator systems. Using control desk panel interface, controller parameters and references can be changed online. Acquisition of the measured
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values of the real – time system is also possible to be stored and analyzed offline in the post – processing. Both simulation and experimental models can be used for further development in the field of low – harmonics elimination, especially in the case of distorted grid.
REFERENCES Periodicals: [1] S. Muller, M. Deicke and Rik W. De Doncker, “Doubly Fed Induction Generator Systems for Wind Turbines”, IEEE Industry Applications Magazine, May-June 2002, pp. 26-33. [2] D.S. Zinger, E. Muljadi, “Annualized wind energy improvement using variable speeds”, Industrial & Commercial Power Systems technical Conference, 1997. Conference Records, Papers presented at the 1997 Annual Meeting, IEEE 1997, 11-16 May 1997, pp. 80-83.
Dissertations: [13] L. Mihet-Popa, “Wind Turbines using Induction Generators connected to the grid”, Ph. D Thesis, Timisoara, October 2003.
Lucian Mihet-Popa received the B.S. degree, M.S. degree and Ph.D. degree from the POLITEHNICA University of Timisoara, Timisoara, Romania, in 1999, 2000 and 2003, respectively, all in electrical engineering. He is currently working as Lecturer Professor in the Department of Electrical Machines and Drives, Timisoara, Romania. He has visited Aalborg University, Denmark, in 2000, 2001 and 2002 and Siegen University, Germany in 2004 as a guest researcher. He received in 2005 the second prize paper award of the IEEE Industry Applications Society. His research interest includes control and modeling of induction machines, detection and diagnosis of faults, especially for wind turbine applications. Voicu Groza received the B.S. degree and Ph.D. degree from the POLITEHNICA University of Timisoara, Romania, in 1972 and 1985, respectively. He is currently working as Associate Professor in School of Information Technology and Engineering, University of Ottawa. His research interest includes real-time embedded systems, distributed intelligent instrumentation and smart sensors networks.
[3] A. Miller, E. Muljadi, D.S. Zinger, “A Variable Speed Wind Turbine Control”, IEEE Transactions on Energy Conversion, vol.12, no. 2, June 1997, pp. 181-186. [4] L. Mihet-Popa, F. Blaabjerg and I. Boldea, ”Wind Turbine Generator Modeling and Simulation where Rotational Speed is the Controlled Variable”, IEEE-IAS Transactions on Energy Conversion, January / February 2004, Vol. 40, No. 1.
Books: [5] Siegfried Heier, Wind energy conversion systems, book, John Wiley & Sons Inc., New York, 1998.
Technical Reports: [6] L.H. Hansen, L. Helle, F. Blaabjerg, E. Ritchie, S. Munk-Nielsen, H. Bidner, P. Sorensen and B. Bak-Jensen, ”Conceptual Survey of Generators and Power Electronics for Wind Turbines”, Riso-R1205 (EN), December 2001.
Papers from Conference Proceedings (Published): [7] L.H. Hansen, P. Sorensen, U.S. Paulsen, “Variable Speed Wind Turbine using Full Conversion”, Proceedings of NORpie; 2000, Aalborg, Denmark, pp. 115-119, 2000. [8] R. Cardenas, R. Pena, G.M. Asher and J.C. Clare, “Experimental emulation of wind turbines and flywheels for wind energy applications”, Proceedings of EPE Conference, Graz, 2001. [9] D. Schreiber, “Applied Designs of Variable Speed Wind Turbines and New Approaches”, PCIM 2002. [10] L. Mihet-Popa, F. Blaabjerg and I. Boldea, “Simulation of Wind Generator Systems for the Power Grid”, Record of OPTIM 2002, Poiana Brasov – Romania, 16 – 18 May, 2002, Vol. 2, pp. 423-428.
G. Prostean received the B.S. degree and Ph.D. degree from the POLITEHNICA University of Timisoara, Romania, in 1989 and 2003, respectively. She is currently working as Associate Professor at the POLITEHNICA University of Timisoara, Romania. Her research interest includes real-time embedded systems, artificial intelligence and expert systems. I. Filip received his BSc degree (1992) and PhD (1999) in Automatic Systems from Politehnica University of Timisoara (Romania). He joined the “Politehnica” University of Timisoara (1992-2004), where he is currently an associate professor at the Applied Informatics and Automatics Department. Besides countless scientific publications, he is an author and co-author of several books and numerous essays and articles. His research interests include: adaptive control, fuzzy control, modeling and simulation, neural networks. I. Szeidert received the B.S. degree and M.S. degree from the POLITEHNICA University of Timisoara, Romania, in 1999, 2000, all in automatic control engineering. He is currently working toward the Ph. D degrees in control systems applied in unconventional energetic. He is currently working as Assistant Professor in the Department of Automation and Applied Informatics from POLITEHNICA University of Timisoara (Romania). His research interests include: adaptive control, fuzzy control, modeling and simulations of electrical machines and neural networks.
[11] R. Otterbach, T. Pohlmann, A. Rukgauer and J. Vater, “DS1103 PPC controller board – rapid prototyping with combined RISC and DSP power for motion control”, Proceedings of PCIM’98, Nurnberg. [12] R. Teodorescu, F. Iov, F. Blaabjerg and E. Urlep, “Control implementation and test of an adjustable speed wind turbine using flexible development platform”, Proceedings of EPE 2003, Toulouse, France.
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