SlideShare a Scribd company logo
International Journal of Electrical and Computer Engineering (IJECE)
Vol. 7, No. 1, February 2017, pp. 1~11
ISSN: 2088-8708, DOI: 10.11591/ijece.v7i1.pp1-11  1
Journal homepage: http://iaesjournal.com/online/index.php/IJECE
Study of Wind Turbine based Variable Reluctance Generator
using Hybrid FEMM-MATLAB Modeling
Tariq Benamimour, Amar Bentounsi, Hind Djeghloud
LGEC, Lab. of Electrotechnique Dept., University of Mentouri Constantine, Algeria
Article Info ABSTRACT
Article history:
Received Jan 3, 2016
Revised Mar 21, 2016
Accepted Jun 13, 2016
Based on exhaustive review of the state of the art of the electric generators
fitted to Wind Energy Conversion System (WECS), this study is focused on
an innovative machine that is a Variable Reluctance Generator (VRG).
Indeed, its simple and rugged structure (low cost), its high torque at low
speed (gearless), its fault-tolerance (lowest maintenance), allow it to be a
potential candidate for a small wind power application at variable wind
speed. For better accuracy, a finite element model of a studied doubly salient
VRG is developed using open source software FEMM to identify the
electromagnetic characteristics such as linkage flux, torque or inductance
versus rotor position and stator excitation. The obtained data are then
transferred into look-up tables of MATLAB/Simulink to perform various
simulations. Performance of the proposed wind power system is analyzed for
several parameters and results are discussed.
Keyword:
Finite element analysis
Matlab/simulink
Modeling and simulation
Variable reluctance generator
Wind turbine
Copyright © 2017 Institute of Advanced Engineering and Science.
All rights reserved.
Corresponding Author:
Tariq Benamimour,
LGEC, Lab. of Electrotechnique Dept.,
University of Mentouri Constantine,
Tel/Fax: +213 31819013, Algeria.
Email: tarekbenamimourelt@yahoo.fr
1. INTRODUCTION
Emerged recently in a context of energy crisis and rising pollution, the concept of sustainable
development has contributed to the development of renewable energies. Among the alternative resources,
wind power has seen the strongest growth. Various wind energy conversion systems (WECS) have been
proposed in association with different structures of electric generators where the major requirements are: high
power density, efficiency, high reliability, lowest maintenance, reduction of the system parts (gearless),
reasonable cost and other market criteria. The potential electrical generators candidates for WECS which
may satisfy the above criteria are standard self excited induction generator (SEIG), doubly-fed induction
generator (DFIG), permanent magnetic synchronous generator (PMSG) and, recently, a switched reluctance
machine (SRM) used either in high speed drive or low speed generator [1-4]. In a comparative study of
electrical generators fitted to wind turbine systems, the authors in [5] conclude that the PMSG seems to be
the most adapted candidate as illustrated in the Table 1 below taken from this reference, where the evaluation
is based in the main characteristics of the WECS, each them is graded from 1 to 5 points. Recently, due to
numerous advantages (simple structure, robustness, high performance, low cost), an innovative variable
reluctance generator (VRG) [6-14] has been recognized to have potential for wind power applications. This
explains our interest in the study of this type of generator.
The main contribution of this work is related to an original numerical-analytical approach carried
out under coupled FEMM-MATLAB user-friendly softwares used to model with better accuracy the studied
6/4 three-phase VRG fed with asymmetric half bridge converter [15].
 ISSN: 2088-8708
IJECE Vol. 7, No. 1, February 2017 : 1 – 11
2
The paper is organized as follows: Section 2 describes the main characteristics of wind turbine and
the finite element modeling of the studied VRG. In Section 3, the simulation process of WECS using
MATLAB/Simulink is presented and results are discussed. The paper concludes in Section 4.
Table 1. Wind Power Systems Evaluation [5]
2. MODELING OF WIND ENERGY CONVERSION SYSTEM
The wind energy conversion system (WECS) shown in Figure 1 is relatively standard. Usually, it
consists of four parts:
a. The wind turbine converts wind energy into kinetic energy.
b. The gearbox to adapt the speed of the turbine to that of the generator.
c. The generator that converts mechanical energy into electrical energy.
d. The static converter DC-AC which will not be examined in this study.
Figure 1. Wind Energy Conversion System
In order to perform simulations under MATLAB/SIMULINK environment, the mathematical model
of the WECS is represented by the synoptic diagram shown in Figure 2.
Generation
Systems
Characteristics
DFIG IG PMSG SRG
Power Density
Efficiency
Controllability
Reliability
Technological maturity
weight
Cost
4.5
4
5
4
5
3.5
4
3.5
3.5
4
3
5
3.5
4
5
5
5
4
4
5
3
3.5
3.5
4
5
4
2
5
 Total
30 26.5 31 26
IJECE ISSN: 2088-8708 
Study of Wind Turbine based Variable Reluctance Generator Using Hybrid .... (Tariq Benamimour)
3
Figure 2. Synoptic Diagram of the WECS
2.1. Main Characteristics of Wind Turbine
The wind power converted into mechanical power by the turbine is given by (1):
3
),(
2
1
AvCP pm  (1)
where  is the air density (kg/m3
), A=R2
is the turbine swept area (m2
), R is the radius of rotor blade (m),
Cp (,) is the power coeficient function of the blade pitch angle  (deg) and the tip-speed ratio (TSR) given
by:
v
R t
 (2)
where t is the rotational speed of the turbine (rad/s)
Hence, the TSR (  ) can be controlled by the rotational speed of generator. The coefficient Cp can
be represented by the following relationship [16]:


0068.0].54.0
116
.[5176.0),(
21


i
eC
i
p (3)
with:
1
035.0
08.0
11
3




i
(4)
The characteristic of the generated power vs. rotational speed according to the wind speed is
represented in Figure 3. The power coefficient vs. tip speed ratio for different values of pitch angle is
depicted in Figure 4. The ideal curve of power vs. wind speed shown in Figure 5 illustrates one of the major
factors affecting the performance of the wind power through three distinct zones:
a. Zone I: below cut-in wind speed, the turbine does not produce power.
b. Zone II: at cut-in wind speed, the system begins to produce power (Pv3
) until nominal wind speed.
c. Zone III: the turbine produces constant power (pitch control).
d. Zone IV: at cut-off wind speed, the system stops.
To extract the maximum power from the wind turbine, it is necessary to adjust the rotor speed (  )
at optimum value of TSR (opt) with wind speed variation (v); this is achieved in zone II. Table 2 is shows
parameters of wind turbine
 ISSN: 2088-8708
IJECE Vol. 7, No. 1, February 2017 : 1 – 11
4
Figure 3. Mechanic Power Characteristic vs. Rotating
Speed of the Rotor for different Values of Wind
Speed
Figure 4. Power Coefficient vs. Tip Speed Ratio for
different Values of β
Figure 5. Typical Power Curve of a Wind Turbine
Table 2. Parameters of Wind Turbine
Parameter Value
Cut-in speed 4 m/s
Cut-out speed 30 m/s
Rated wind speed
Rated power
8 m/s
3 kW
Blade radius
Optimal power coef.
Optimal TSR
2 m
0.4131
7.5
2.2. Mathematical Model of the Generator
2.2.1. Operating Principle
The studied three-phase 6/4 Variable Reluctance Generator has six salient poles on the stator and
four salient poles on the rotor as depicted in Figure 6. The rotor has no windings or magnets while the stator
windings are distributed as three pairs connected in series and fed with asymmetric half bridge converter
where each phase is represented in Figure 7. There are two operating sequences: (i) excitation sequence by
switching Q1 and Q2; (ii) generation sequence to supply the load via the diodes D1 and D2.
2.2.2. Basic Equations
The generated voltage per stator k-phase is expressed by:






),(
).,()( kk
k
k
kkkkk
iL
i
dt
di
iLirV (5)
where rk is the phase resistance, ik is the phase current, Lk is the incremental inductance and  is the angular
speed (rad/s) of generator. The third term of equation (5) represents the induced EMF which depends
essentially on the rotational speed  (we assume that the current and inductance slope are constant).
IJECE ISSN: 2088-8708 
Study of Wind Turbine based Variable Reluctance Generator Using Hybrid .... (Tariq Benamimour)
5
The electromagnetic torque per k-phase is expressed by:





)(
2
1 2 k
kk
L
iT (6)
From (6) we can conclude that the instantaneous torque is positive for increasing inductance (motor) and
negative for decreasing inductance (generator) as shown in Figure 8.
2.2.3. Analytical Model of Inductance
The rotation of the rotor poles (free from windings and magnets) with respect to the excited stator
poles varies the inductance of the generator periodically from maximum at the aligned position, Lmax, to
minimum at the unaligned position, Lmin. Usually, the fundamental component of the non-linear inductance is
approximated by series Fourier expressed by:
)cos(.)( 10  rk NLLL  (7)
where L0=(Lmax+Lmin)/2 and L1=(Lmax-Lmin)/2
Usually, Lmin is considered as constant while Lmax is analytically expressed using polynomial series as [17]:
432
max 00035.00022.00056.00045.0136.0)( iiiiiL  (8)
From equations (6) and (7), one can deduce the following analytical expression of the electromagnetic
torque:
)sin(..
2
1
1
2
rrkk NLNiT  (9)
Equation (9) shows the effect of parameter L1 in calculating the torque, i.e. of the gap between the
inductances Lmax and Lmin which we shall examine below.
Figure 6. Diagram of the Studied 6/4 VRG
Figure 7. A Phase Circuit of VRG Fed by the Inverter Figure 8. Motor and Generator Modes of the
Variable Reluctance Machine
 ISSN: 2088-8708
IJECE Vol. 7, No. 1, February 2017 : 1 – 11
6
2.2.4. Numerical Model of Inductance by FEA
Due to the high saturation of the magnetic circuit of the generator, it is very difficult to model
analytically the different characteristics. Thus, a 2-D non-linear finite element model using FEMM software
is performed. The schemes of magnetic flux density at the two extreme postions of rotor are depicted in
Figure 9. The finite element analysis (FEA) of the studied generator, with parameters given in Table 3,
allowed us to represent, as a function of the position and the current, the characteristics of linkage flux in
Figure 10 and inductance in Figure 11. In addition, the data given by the FEA are stored in a matrix in order
to build the look-up tables for 46 rotor positions, from 45° to 90°, correspondind to the decreasing inductance
(generator mode) and 6 different current values, from 0 to 10 A. Using MATLAB Look-up Table bloc, one
could plot the 3-D curves shown in Figure 12 and Figure 13.
Figure 9. Plot of Magneticflux at Aligned and Unaligned Postions of Rotor
Figure 10. Linkage Flux vs. Current at different Rotor
Positions
Figure 11. Inductance vs. Rotor Position at
different Currents
Figure 12. Flux/Position/Current Characteristic Figure 13. Current /Position/Torque Characteristic
IJECE ISSN: 2088-8708 
Study of Wind Turbine based Variable Reluctance Generator Using Hybrid .... (Tariq Benamimour)
7
Table 3. Parameters of VRG
Parameter Value
Number of stator poles 6
Number of rotor poles 4
Outer diameter
Rotor bore diameter
Air-gap length
228.4 mm
114.2 mm
0.25 mm
Shaft diameter
Stator pole angle
Rotor pole angle
40 mm
30 deg
30 deg
3. SIMULATION RESULTS OF WECS UNDER MATLAB/SIMULINK
3.1. Simulation of the Turbine and Gearbox
Based on equations (1) to (4) representing the mathematic model of the turbine, we conctructed the
Simulink diagram shown in Figure 14. The coupling turbine-gearbox with a gear ratio K is depicted in
Figure 15.
Figure 14. Model of the Turbine under Simulink
Figure 15. Bloc Diagram of the Wind Turbine and Gear Box
3.2. Simulation of the Generator
The simulink diagram model for the studied generator is shown in Figure 16. For simplifying the
simulation process, we took the same parameters in all phases, we neglect the mutual inductance, eddy effect
and hysteresis phenomena, and we assume that all switches of the inverter are ideal. As depicted in
Figure 17, the ultimate model of the generator contains several modules such as the three phases of the VRG,
the power inverter and its controllers. As mentioned previously, each phase contains the same parameters
while the stator windings are detailed in Figure 18 with an angular shift of 120° between them.
For starting the simulation process, we compute the position (the mechanical angle of the rotor)
from an integration of the speed, taking in account the original angle of the rotor when the simulation starts
as shown in Figure 19. The modeled torque equation using simulink is represented in Figure 20. The power
inverter contains three blocks, an exciting source and a load as depicted in Figure 21. Each block of the
inverter is represented in Figure 22.
 ISSN: 2088-8708
IJECE Vol. 7, No. 1, February 2017 : 1 – 11
8
Figure 16. Simulink Diagram of the Studied VRG
Figure 17. Blocs of One Phase of the Machine
Figure 18. Bloc Diagram of Calculating the Inductance of Phase Winding
IJECE ISSN: 2088-8708 
Study of Wind Turbine based Variable Reluctance Generator Using Hybrid .... (Tariq Benamimour)
9
Figure 19. Bloc Diagram of the Position Sensor
Figure 20. Bloc Diagram of Calculating the Electromagnetic Torque
Figure 21. Bloc Diagram of the Inverter
Figure 22. Bloc Diagram of an Inverter arm
 ISSN: 2088-8708
IJECE Vol. 7, No. 1, February 2017 : 1 – 11
10
3.3. Discussion of Results
For getting high performances of the machine, the control bloc must work respectively to a specified
turn-on angle (Θon=40°) and turn-off angle (Θoff =60°). To validate our model, we have used the same
conditions of simulation and same parameters as in [17]. The dynamic waveforms of currents and voltages in
the three phases of the generator are depicted in Figure 23 and Figure 24 respectively. The converted energy
by the proposed system can be estimated using the flux-current curve as represented in Figure 25. The
dynamic waveforms of the currents at different values of the turn-off angle Θoff are shown in Figure 26. All
these results confirm the validity of our model compared to the work of S. Song and W. Liu [17] and allow
us to consider other development prospects.
Figure 23. Dynamic Currents in the Three Phases Figure 24. Dynamic Voltages in the Three Phases
Figure 25. Flux vs. Current Diagram Figure 26. Dynamic Current for different θoff Values
4. CONCLUSION
This work allowed us to model and simulates a variable speed wind turbine associated conveniently
with gearless variable reluctance generator. This objective has been achieved using a user-friendly program
coupling the open source software FEMM with MATLAB/SIMULINK widely used by the academic
community. Another contribution of this work lies in the calculation by the finite element method of
inductances at aligned and unaligned position. This allowed us to carry out a detailed analysis of system
performances. It gave good results in dynamic non-linear generator operation. Currently, there are a little
research results in this field; a continuation to the work would be followed to optimize the system
performance by developing efficient control strategies.
REFERENCES
[1] K. Trinada, et al., “Study of Wind Turbine based SEIG under Balanced/Unbalanced Loads and Excitation,”
International Journal of Electrical and Computer Engineering, vol/issue: 2(3), pp. 353-370, 2012.
[2] A. M. Thin and N. S. Y. Kyaing, “Performance Analysis of Doubly Fed Induction Generator Using Vector Control
Technique,” International Journal of Electrical and Computer Engineering, vol/issue: 5(5), pp. 929-938, 2015.
IJECE ISSN: 2088-8708 
Study of Wind Turbine based Variable Reluctance Generator Using Hybrid .... (Tariq Benamimour)
11
[3] T. Z. Khaing and L. Z. Kyin, “Control Analysis of Stand-Alone Wind Power Supply System with Three Phase
PWM Voltage Source Inverter and Boost Converter,” International Journal of Electrical and Computer
Engineering, vol/issue: 5(4), pp. 798-809, 2015.
[4] S. M. Mohiuddin and M. R. I. Sheikh, “Stabilization of Solar-Wind Hybrid Power System by Using SMES,”
International Journal of Electrical and Computer Engineering, vol/issue: 4(3), pp. 351-358, 2014.
[5] A. Lebsir, et al., “Electric Generators Fitted to Wind Turbine Systems: An Up-to-Date Comparative Study,”
Journal of Electrical Systems, vol/issue: 11(3), pp. 281-295, 2015.
[6] H. Tiegna, et al., “Overview of High Power Wind Turbine Generators,” in IEEE ICRERA, Nagasaki, Japan, pp. 1-
6, 2012.
[7] A. Lebsir, et al., “Comparative Study of PMSM and SRM capabilities,” in IEEE POWERENG, Istanbul, Turkey,
pp. 760-763, 2013.
[8] H. Chen, “Implementation of a three-phase switched reluctance generator system for wind power applications,” in
IEEE SELT, Victoria, pp. 1-6, 2008.
[9] Y. Fan, et al., “A New Three-Phase Doubly Salient Permanent Magnet Machine for Wind Power Generation,” in
IEEE Trans. On Industry Applications, vol/issue: 42(1), pp. 53-60, 2006.
[10] R. Cardenas, et al., “Control of a Switched Reluctance Generator for Variable-Speed Wind Energy Applications,”
in IEEE Trans. On Energy Conversion, vol/issue: 20(4), pp. 781-791, 2005.
[11] V. B. Koreboina and L. Venkatesha, “Modelling and Simulation of Switched Reluctance Generator Control for
Variable Speed WECS,” in IEEE PEDES, Bengaluru, pp. 1-6, 2012.
[12] H. Chen, et al., “Research on the switched reluctance wind generator system,” in IEEE PESGM, pp. 1-6, 2001.
[13] K. Ogawa, et al., “Study for Small Size Wind Power Generating System Using Switched Reluctance Generator,” in
IEEE International Conference on Industrial Technology, Mumbai, pp. 1510-1515, 2006.
[14] D. A. Torrey, “Switched Reluctance Generators and their Control,” in IEEE Trans. On Industrial Electronics,
vol/issue: 49(1), pp. 3-14, 2002.
[15] T. Benamimour, et al., “CAD of Electrical Machines Using Coupled FEMM-MATLAB Softwares,” in IEEE
EPECS, Istanbul, pp. 1-6, 2013.
[16] A. Soetedjo, et al., “Modeling of Wind Energy System with MPPT Control,” in IEEE International conference on
Electrical Engeneering and Informatics, Indonesia 17-19 July 2011.
[17] S. Song and W. Liu, “A Novel Method for Nonlinear Modeling and Dynamic Simulation of a Four-phase Switched
Reluctance Generator System Based on MATLAB/SIMULINK,” in IEEE ICIEA, Harbin, pp. 1509-1514, 2007.

More Related Content

PDF
Generator and grid side converter control for wind energy conversion system
PDF
R36100108
PDF
MATHEMATICAL MODEL OF WIND TURBINE IN GRID-OFF SYSTEM
PDF
Maximum Power Point Tracking of Wind Turbine Conversion Chain Variable Speed ...
PDF
Power Control of DFIG-generators for Wind Turbines Variable-speed
PDF
Wind Energy Conversion Based On Matrix Converter
PDF
Starting torque and torque ripple reduction using SVPWM based vector control ...
PDF
IRJET- Decoupled Control Technique of DFIG with Dual PWM Converters for Wind ...
Generator and grid side converter control for wind energy conversion system
R36100108
MATHEMATICAL MODEL OF WIND TURBINE IN GRID-OFF SYSTEM
Maximum Power Point Tracking of Wind Turbine Conversion Chain Variable Speed ...
Power Control of DFIG-generators for Wind Turbines Variable-speed
Wind Energy Conversion Based On Matrix Converter
Starting torque and torque ripple reduction using SVPWM based vector control ...
IRJET- Decoupled Control Technique of DFIG with Dual PWM Converters for Wind ...

What's hot (17)

PDF
Control of PMSG based variable speed wind energy conversion system connected ...
PDF
Modeling and Control of a Doubly-Fed Induction Generator for Wind Turbine-Gen...
PDF
M347781
PDF
Economic Selection of Generators for a Wind Farm
PDF
Modeling of Wind Energy on Isolated Area
PDF
Improved Performance of DFIG-generators for Wind Turbines Variable-speed
PDF
Indirect Control of a Doubly-Fed Induction Machine for Wind Energy Conversion
PDF
Wind and solar integrated to smart grid using islanding operation
PDF
DESIGN AND DEVELOPMENT OF WIND TURBINE EMULATOR TO OPERATE WITH 1.5KW INDUCTI...
PDF
A new control methods for offshore grid connected wind energy conversion syst...
PDF
F046013443
PDF
Modeling and performance analysis of a small scale direct driven pmsg based w...
PDF
Analysis of wind turbine driven permanent magnet synchronous generator under ...
PDF
Modeling, simulation and control of a doubly-fed induction generator for wind...
PDF
Comparative study of two control strategies proportional integral and fuzzy l...
PDF
Dynamic Modeling, Control and Simulation of a Wind and PV Hybrid System for G...
PDF
Power fuzzy adaptive control for wind turbine
Control of PMSG based variable speed wind energy conversion system connected ...
Modeling and Control of a Doubly-Fed Induction Generator for Wind Turbine-Gen...
M347781
Economic Selection of Generators for a Wind Farm
Modeling of Wind Energy on Isolated Area
Improved Performance of DFIG-generators for Wind Turbines Variable-speed
Indirect Control of a Doubly-Fed Induction Machine for Wind Energy Conversion
Wind and solar integrated to smart grid using islanding operation
DESIGN AND DEVELOPMENT OF WIND TURBINE EMULATOR TO OPERATE WITH 1.5KW INDUCTI...
A new control methods for offshore grid connected wind energy conversion syst...
F046013443
Modeling and performance analysis of a small scale direct driven pmsg based w...
Analysis of wind turbine driven permanent magnet synchronous generator under ...
Modeling, simulation and control of a doubly-fed induction generator for wind...
Comparative study of two control strategies proportional integral and fuzzy l...
Dynamic Modeling, Control and Simulation of a Wind and PV Hybrid System for G...
Power fuzzy adaptive control for wind turbine
Ad

Similar to Study of Wind Turbine based Variable Reluctance Generator using Hybrid FEMM-MATLAB Modeling (20)

PDF
11.modeling and performance analysis of a small scale direct driven pmsg base...
PDF
Modeling and Analysis of Wind Energy Conversion Systems Using Matlab
PDF
Advanced Control of Wind Electric Pumping System for Isolated Areas Application
PDF
Fl3610001006
PDF
Fuzzy optimization strategy of the maximum power point tracking for a variab...
PDF
Dynamic Modeling of Autonomous Wind–diesel system with Fixed-speed Wind Turbine
PDF
Intelligent Control for Doubly Fed Induction Generator Connected to the Elect...
PDF
Wind Turbine Generator Tied To Grid Using Inverter Techniques and Its Designs
PDF
4.power quality improvement in dg system using shunt active filter
PDF
Control Strategy Used in DFIG and PMSG Based Wind Turbines an Overview
PDF
Load Frequency Control of DFIG-isolated and Grid Connected Mode
PDF
PERMANENT MAGNET SYNCHRONOUS GENERATOR BASED WIND ENERGY CONVERSION SYSTEM
PDF
Transient analysis and modeling of wind generator during power and grid volta...
PDF
Micro-Turbine Generation Control System Optimization Using Evolutionary algor...
PDF
Performance analysis of various parameters by comparison of conventional pitc...
PDF
Performance analysis of various parameters by comparison of conventional pitc...
PDF
Nonlinear control of WECS based on PMSG for optimal power extraction
PDF
STATCOM Based Wind Energy System by using Hybrid Fuzzy Logic Controller
PDF
A Fuzzy Logic Control Strategy for Doubly Fed Induction Generator for Improve...
PDF
Dynamic_Analysis_of_Grid_Connected_Wind_Farms_Using_ATP.pdf
11.modeling and performance analysis of a small scale direct driven pmsg base...
Modeling and Analysis of Wind Energy Conversion Systems Using Matlab
Advanced Control of Wind Electric Pumping System for Isolated Areas Application
Fl3610001006
Fuzzy optimization strategy of the maximum power point tracking for a variab...
Dynamic Modeling of Autonomous Wind–diesel system with Fixed-speed Wind Turbine
Intelligent Control for Doubly Fed Induction Generator Connected to the Elect...
Wind Turbine Generator Tied To Grid Using Inverter Techniques and Its Designs
4.power quality improvement in dg system using shunt active filter
Control Strategy Used in DFIG and PMSG Based Wind Turbines an Overview
Load Frequency Control of DFIG-isolated and Grid Connected Mode
PERMANENT MAGNET SYNCHRONOUS GENERATOR BASED WIND ENERGY CONVERSION SYSTEM
Transient analysis and modeling of wind generator during power and grid volta...
Micro-Turbine Generation Control System Optimization Using Evolutionary algor...
Performance analysis of various parameters by comparison of conventional pitc...
Performance analysis of various parameters by comparison of conventional pitc...
Nonlinear control of WECS based on PMSG for optimal power extraction
STATCOM Based Wind Energy System by using Hybrid Fuzzy Logic Controller
A Fuzzy Logic Control Strategy for Doubly Fed Induction Generator for Improve...
Dynamic_Analysis_of_Grid_Connected_Wind_Farms_Using_ATP.pdf
Ad

More from Yayah Zakaria (20)

PDF
Improving the Proactive Routing Protocol using Depth First Iterative Deepenin...
PDF
Improvement at Network Planning using Heuristic Algorithm to Minimize Cost of...
PDF
A Vertical Handover Algorithm in Integrated Macrocell Femtocell Networks
PDF
Symmetric Key based Encryption and Decryption using Lissajous Curve Equations
PDF
Gain Flatness and Noise Figure Optimization of C-Band EDFA in 16-channels WDM...
PDF
Novel Resonant Structure to Compact Partial H-Plane Band-Pass Waveguide Filter
PDF
Vehicular Ad Hoc Networks: Growth and Survey for Three Layers
PDF
Barriers and Challenges to Telecardiology Adoption in Malaysia Context
PDF
Novel High-Gain Narrowband Waveguide-Fed Filtenna using Genetic Algorithm
PDF
Improved Algorithm for Pathological and Normal Voices Identification
PDF
Uncertain Systems Order Reduction by Aggregation Method
PDF
A Three-Point Directional Search Block Matching Algorithm
PDF
Human Data Acquisition through Biometrics using LabVIEW
PDF
A Survey on Block Matching Algorithms for Video Coding
PDF
An Accurate Scheme for Distance Measurement using an Ordinary Webcam
PDF
Identity Analysis of Egg Based on Digital and Thermal Imaging: Image Processi...
PDF
Recognition of Tomato Late Blight by using DWT and Component Analysis
PDF
Fuel Cell Impedance Model Parameters Optimization using a Genetic Algorithm
PDF
Noise Characterization in InAlAs/InGaAs/InP pHEMTs for Low Noise Applications
PDF
Effect of Mobility on (I-V) Characteristics of Gaas MESFET
Improving the Proactive Routing Protocol using Depth First Iterative Deepenin...
Improvement at Network Planning using Heuristic Algorithm to Minimize Cost of...
A Vertical Handover Algorithm in Integrated Macrocell Femtocell Networks
Symmetric Key based Encryption and Decryption using Lissajous Curve Equations
Gain Flatness and Noise Figure Optimization of C-Band EDFA in 16-channels WDM...
Novel Resonant Structure to Compact Partial H-Plane Band-Pass Waveguide Filter
Vehicular Ad Hoc Networks: Growth and Survey for Three Layers
Barriers and Challenges to Telecardiology Adoption in Malaysia Context
Novel High-Gain Narrowband Waveguide-Fed Filtenna using Genetic Algorithm
Improved Algorithm for Pathological and Normal Voices Identification
Uncertain Systems Order Reduction by Aggregation Method
A Three-Point Directional Search Block Matching Algorithm
Human Data Acquisition through Biometrics using LabVIEW
A Survey on Block Matching Algorithms for Video Coding
An Accurate Scheme for Distance Measurement using an Ordinary Webcam
Identity Analysis of Egg Based on Digital and Thermal Imaging: Image Processi...
Recognition of Tomato Late Blight by using DWT and Component Analysis
Fuel Cell Impedance Model Parameters Optimization using a Genetic Algorithm
Noise Characterization in InAlAs/InGaAs/InP pHEMTs for Low Noise Applications
Effect of Mobility on (I-V) Characteristics of Gaas MESFET

Recently uploaded (20)

PPTX
Geodesy 1.pptx...............................................
PPT
Project quality management in manufacturing
PPTX
FINAL REVIEW FOR COPD DIANOSIS FOR PULMONARY DISEASE.pptx
PPTX
Engineering Ethics, Safety and Environment [Autosaved] (1).pptx
PPTX
MET 305 2019 SCHEME MODULE 2 COMPLETE.pptx
PDF
Well-logging-methods_new................
PDF
Digital Logic Computer Design lecture notes
PDF
Embodied AI: Ushering in the Next Era of Intelligent Systems
PDF
Evaluating the Democratization of the Turkish Armed Forces from a Normative P...
PDF
Model Code of Practice - Construction Work - 21102022 .pdf
PDF
PPT on Performance Review to get promotions
PDF
BMEC211 - INTRODUCTION TO MECHATRONICS-1.pdf
PDF
Operating System & Kernel Study Guide-1 - converted.pdf
PDF
R24 SURVEYING LAB MANUAL for civil enggi
PDF
The CXO Playbook 2025 – Future-Ready Strategies for C-Suite Leaders Cerebrai...
PPTX
Lecture Notes Electrical Wiring System Components
PDF
Mitigating Risks through Effective Management for Enhancing Organizational Pe...
PPTX
Construction Project Organization Group 2.pptx
PPTX
bas. eng. economics group 4 presentation 1.pptx
DOCX
573137875-Attendance-Management-System-original
Geodesy 1.pptx...............................................
Project quality management in manufacturing
FINAL REVIEW FOR COPD DIANOSIS FOR PULMONARY DISEASE.pptx
Engineering Ethics, Safety and Environment [Autosaved] (1).pptx
MET 305 2019 SCHEME MODULE 2 COMPLETE.pptx
Well-logging-methods_new................
Digital Logic Computer Design lecture notes
Embodied AI: Ushering in the Next Era of Intelligent Systems
Evaluating the Democratization of the Turkish Armed Forces from a Normative P...
Model Code of Practice - Construction Work - 21102022 .pdf
PPT on Performance Review to get promotions
BMEC211 - INTRODUCTION TO MECHATRONICS-1.pdf
Operating System & Kernel Study Guide-1 - converted.pdf
R24 SURVEYING LAB MANUAL for civil enggi
The CXO Playbook 2025 – Future-Ready Strategies for C-Suite Leaders Cerebrai...
Lecture Notes Electrical Wiring System Components
Mitigating Risks through Effective Management for Enhancing Organizational Pe...
Construction Project Organization Group 2.pptx
bas. eng. economics group 4 presentation 1.pptx
573137875-Attendance-Management-System-original

Study of Wind Turbine based Variable Reluctance Generator using Hybrid FEMM-MATLAB Modeling

  • 1. International Journal of Electrical and Computer Engineering (IJECE) Vol. 7, No. 1, February 2017, pp. 1~11 ISSN: 2088-8708, DOI: 10.11591/ijece.v7i1.pp1-11  1 Journal homepage: http://iaesjournal.com/online/index.php/IJECE Study of Wind Turbine based Variable Reluctance Generator using Hybrid FEMM-MATLAB Modeling Tariq Benamimour, Amar Bentounsi, Hind Djeghloud LGEC, Lab. of Electrotechnique Dept., University of Mentouri Constantine, Algeria Article Info ABSTRACT Article history: Received Jan 3, 2016 Revised Mar 21, 2016 Accepted Jun 13, 2016 Based on exhaustive review of the state of the art of the electric generators fitted to Wind Energy Conversion System (WECS), this study is focused on an innovative machine that is a Variable Reluctance Generator (VRG). Indeed, its simple and rugged structure (low cost), its high torque at low speed (gearless), its fault-tolerance (lowest maintenance), allow it to be a potential candidate for a small wind power application at variable wind speed. For better accuracy, a finite element model of a studied doubly salient VRG is developed using open source software FEMM to identify the electromagnetic characteristics such as linkage flux, torque or inductance versus rotor position and stator excitation. The obtained data are then transferred into look-up tables of MATLAB/Simulink to perform various simulations. Performance of the proposed wind power system is analyzed for several parameters and results are discussed. Keyword: Finite element analysis Matlab/simulink Modeling and simulation Variable reluctance generator Wind turbine Copyright © 2017 Institute of Advanced Engineering and Science. All rights reserved. Corresponding Author: Tariq Benamimour, LGEC, Lab. of Electrotechnique Dept., University of Mentouri Constantine, Tel/Fax: +213 31819013, Algeria. Email: tarekbenamimourelt@yahoo.fr 1. INTRODUCTION Emerged recently in a context of energy crisis and rising pollution, the concept of sustainable development has contributed to the development of renewable energies. Among the alternative resources, wind power has seen the strongest growth. Various wind energy conversion systems (WECS) have been proposed in association with different structures of electric generators where the major requirements are: high power density, efficiency, high reliability, lowest maintenance, reduction of the system parts (gearless), reasonable cost and other market criteria. The potential electrical generators candidates for WECS which may satisfy the above criteria are standard self excited induction generator (SEIG), doubly-fed induction generator (DFIG), permanent magnetic synchronous generator (PMSG) and, recently, a switched reluctance machine (SRM) used either in high speed drive or low speed generator [1-4]. In a comparative study of electrical generators fitted to wind turbine systems, the authors in [5] conclude that the PMSG seems to be the most adapted candidate as illustrated in the Table 1 below taken from this reference, where the evaluation is based in the main characteristics of the WECS, each them is graded from 1 to 5 points. Recently, due to numerous advantages (simple structure, robustness, high performance, low cost), an innovative variable reluctance generator (VRG) [6-14] has been recognized to have potential for wind power applications. This explains our interest in the study of this type of generator. The main contribution of this work is related to an original numerical-analytical approach carried out under coupled FEMM-MATLAB user-friendly softwares used to model with better accuracy the studied 6/4 three-phase VRG fed with asymmetric half bridge converter [15].
  • 2.  ISSN: 2088-8708 IJECE Vol. 7, No. 1, February 2017 : 1 – 11 2 The paper is organized as follows: Section 2 describes the main characteristics of wind turbine and the finite element modeling of the studied VRG. In Section 3, the simulation process of WECS using MATLAB/Simulink is presented and results are discussed. The paper concludes in Section 4. Table 1. Wind Power Systems Evaluation [5] 2. MODELING OF WIND ENERGY CONVERSION SYSTEM The wind energy conversion system (WECS) shown in Figure 1 is relatively standard. Usually, it consists of four parts: a. The wind turbine converts wind energy into kinetic energy. b. The gearbox to adapt the speed of the turbine to that of the generator. c. The generator that converts mechanical energy into electrical energy. d. The static converter DC-AC which will not be examined in this study. Figure 1. Wind Energy Conversion System In order to perform simulations under MATLAB/SIMULINK environment, the mathematical model of the WECS is represented by the synoptic diagram shown in Figure 2. Generation Systems Characteristics DFIG IG PMSG SRG Power Density Efficiency Controllability Reliability Technological maturity weight Cost 4.5 4 5 4 5 3.5 4 3.5 3.5 4 3 5 3.5 4 5 5 5 4 4 5 3 3.5 3.5 4 5 4 2 5  Total 30 26.5 31 26
  • 3. IJECE ISSN: 2088-8708  Study of Wind Turbine based Variable Reluctance Generator Using Hybrid .... (Tariq Benamimour) 3 Figure 2. Synoptic Diagram of the WECS 2.1. Main Characteristics of Wind Turbine The wind power converted into mechanical power by the turbine is given by (1): 3 ),( 2 1 AvCP pm  (1) where  is the air density (kg/m3 ), A=R2 is the turbine swept area (m2 ), R is the radius of rotor blade (m), Cp (,) is the power coeficient function of the blade pitch angle  (deg) and the tip-speed ratio (TSR) given by: v R t  (2) where t is the rotational speed of the turbine (rad/s) Hence, the TSR (  ) can be controlled by the rotational speed of generator. The coefficient Cp can be represented by the following relationship [16]:   0068.0].54.0 116 .[5176.0),( 21   i eC i p (3) with: 1 035.0 08.0 11 3     i (4) The characteristic of the generated power vs. rotational speed according to the wind speed is represented in Figure 3. The power coefficient vs. tip speed ratio for different values of pitch angle is depicted in Figure 4. The ideal curve of power vs. wind speed shown in Figure 5 illustrates one of the major factors affecting the performance of the wind power through three distinct zones: a. Zone I: below cut-in wind speed, the turbine does not produce power. b. Zone II: at cut-in wind speed, the system begins to produce power (Pv3 ) until nominal wind speed. c. Zone III: the turbine produces constant power (pitch control). d. Zone IV: at cut-off wind speed, the system stops. To extract the maximum power from the wind turbine, it is necessary to adjust the rotor speed (  ) at optimum value of TSR (opt) with wind speed variation (v); this is achieved in zone II. Table 2 is shows parameters of wind turbine
  • 4.  ISSN: 2088-8708 IJECE Vol. 7, No. 1, February 2017 : 1 – 11 4 Figure 3. Mechanic Power Characteristic vs. Rotating Speed of the Rotor for different Values of Wind Speed Figure 4. Power Coefficient vs. Tip Speed Ratio for different Values of β Figure 5. Typical Power Curve of a Wind Turbine Table 2. Parameters of Wind Turbine Parameter Value Cut-in speed 4 m/s Cut-out speed 30 m/s Rated wind speed Rated power 8 m/s 3 kW Blade radius Optimal power coef. Optimal TSR 2 m 0.4131 7.5 2.2. Mathematical Model of the Generator 2.2.1. Operating Principle The studied three-phase 6/4 Variable Reluctance Generator has six salient poles on the stator and four salient poles on the rotor as depicted in Figure 6. The rotor has no windings or magnets while the stator windings are distributed as three pairs connected in series and fed with asymmetric half bridge converter where each phase is represented in Figure 7. There are two operating sequences: (i) excitation sequence by switching Q1 and Q2; (ii) generation sequence to supply the load via the diodes D1 and D2. 2.2.2. Basic Equations The generated voltage per stator k-phase is expressed by:       ),( ).,()( kk k k kkkkk iL i dt di iLirV (5) where rk is the phase resistance, ik is the phase current, Lk is the incremental inductance and  is the angular speed (rad/s) of generator. The third term of equation (5) represents the induced EMF which depends essentially on the rotational speed  (we assume that the current and inductance slope are constant).
  • 5. IJECE ISSN: 2088-8708  Study of Wind Turbine based Variable Reluctance Generator Using Hybrid .... (Tariq Benamimour) 5 The electromagnetic torque per k-phase is expressed by:      )( 2 1 2 k kk L iT (6) From (6) we can conclude that the instantaneous torque is positive for increasing inductance (motor) and negative for decreasing inductance (generator) as shown in Figure 8. 2.2.3. Analytical Model of Inductance The rotation of the rotor poles (free from windings and magnets) with respect to the excited stator poles varies the inductance of the generator periodically from maximum at the aligned position, Lmax, to minimum at the unaligned position, Lmin. Usually, the fundamental component of the non-linear inductance is approximated by series Fourier expressed by: )cos(.)( 10  rk NLLL  (7) where L0=(Lmax+Lmin)/2 and L1=(Lmax-Lmin)/2 Usually, Lmin is considered as constant while Lmax is analytically expressed using polynomial series as [17]: 432 max 00035.00022.00056.00045.0136.0)( iiiiiL  (8) From equations (6) and (7), one can deduce the following analytical expression of the electromagnetic torque: )sin(.. 2 1 1 2 rrkk NLNiT  (9) Equation (9) shows the effect of parameter L1 in calculating the torque, i.e. of the gap between the inductances Lmax and Lmin which we shall examine below. Figure 6. Diagram of the Studied 6/4 VRG Figure 7. A Phase Circuit of VRG Fed by the Inverter Figure 8. Motor and Generator Modes of the Variable Reluctance Machine
  • 6.  ISSN: 2088-8708 IJECE Vol. 7, No. 1, February 2017 : 1 – 11 6 2.2.4. Numerical Model of Inductance by FEA Due to the high saturation of the magnetic circuit of the generator, it is very difficult to model analytically the different characteristics. Thus, a 2-D non-linear finite element model using FEMM software is performed. The schemes of magnetic flux density at the two extreme postions of rotor are depicted in Figure 9. The finite element analysis (FEA) of the studied generator, with parameters given in Table 3, allowed us to represent, as a function of the position and the current, the characteristics of linkage flux in Figure 10 and inductance in Figure 11. In addition, the data given by the FEA are stored in a matrix in order to build the look-up tables for 46 rotor positions, from 45° to 90°, correspondind to the decreasing inductance (generator mode) and 6 different current values, from 0 to 10 A. Using MATLAB Look-up Table bloc, one could plot the 3-D curves shown in Figure 12 and Figure 13. Figure 9. Plot of Magneticflux at Aligned and Unaligned Postions of Rotor Figure 10. Linkage Flux vs. Current at different Rotor Positions Figure 11. Inductance vs. Rotor Position at different Currents Figure 12. Flux/Position/Current Characteristic Figure 13. Current /Position/Torque Characteristic
  • 7. IJECE ISSN: 2088-8708  Study of Wind Turbine based Variable Reluctance Generator Using Hybrid .... (Tariq Benamimour) 7 Table 3. Parameters of VRG Parameter Value Number of stator poles 6 Number of rotor poles 4 Outer diameter Rotor bore diameter Air-gap length 228.4 mm 114.2 mm 0.25 mm Shaft diameter Stator pole angle Rotor pole angle 40 mm 30 deg 30 deg 3. SIMULATION RESULTS OF WECS UNDER MATLAB/SIMULINK 3.1. Simulation of the Turbine and Gearbox Based on equations (1) to (4) representing the mathematic model of the turbine, we conctructed the Simulink diagram shown in Figure 14. The coupling turbine-gearbox with a gear ratio K is depicted in Figure 15. Figure 14. Model of the Turbine under Simulink Figure 15. Bloc Diagram of the Wind Turbine and Gear Box 3.2. Simulation of the Generator The simulink diagram model for the studied generator is shown in Figure 16. For simplifying the simulation process, we took the same parameters in all phases, we neglect the mutual inductance, eddy effect and hysteresis phenomena, and we assume that all switches of the inverter are ideal. As depicted in Figure 17, the ultimate model of the generator contains several modules such as the three phases of the VRG, the power inverter and its controllers. As mentioned previously, each phase contains the same parameters while the stator windings are detailed in Figure 18 with an angular shift of 120° between them. For starting the simulation process, we compute the position (the mechanical angle of the rotor) from an integration of the speed, taking in account the original angle of the rotor when the simulation starts as shown in Figure 19. The modeled torque equation using simulink is represented in Figure 20. The power inverter contains three blocks, an exciting source and a load as depicted in Figure 21. Each block of the inverter is represented in Figure 22.
  • 8.  ISSN: 2088-8708 IJECE Vol. 7, No. 1, February 2017 : 1 – 11 8 Figure 16. Simulink Diagram of the Studied VRG Figure 17. Blocs of One Phase of the Machine Figure 18. Bloc Diagram of Calculating the Inductance of Phase Winding
  • 9. IJECE ISSN: 2088-8708  Study of Wind Turbine based Variable Reluctance Generator Using Hybrid .... (Tariq Benamimour) 9 Figure 19. Bloc Diagram of the Position Sensor Figure 20. Bloc Diagram of Calculating the Electromagnetic Torque Figure 21. Bloc Diagram of the Inverter Figure 22. Bloc Diagram of an Inverter arm
  • 10.  ISSN: 2088-8708 IJECE Vol. 7, No. 1, February 2017 : 1 – 11 10 3.3. Discussion of Results For getting high performances of the machine, the control bloc must work respectively to a specified turn-on angle (Θon=40°) and turn-off angle (Θoff =60°). To validate our model, we have used the same conditions of simulation and same parameters as in [17]. The dynamic waveforms of currents and voltages in the three phases of the generator are depicted in Figure 23 and Figure 24 respectively. The converted energy by the proposed system can be estimated using the flux-current curve as represented in Figure 25. The dynamic waveforms of the currents at different values of the turn-off angle Θoff are shown in Figure 26. All these results confirm the validity of our model compared to the work of S. Song and W. Liu [17] and allow us to consider other development prospects. Figure 23. Dynamic Currents in the Three Phases Figure 24. Dynamic Voltages in the Three Phases Figure 25. Flux vs. Current Diagram Figure 26. Dynamic Current for different θoff Values 4. CONCLUSION This work allowed us to model and simulates a variable speed wind turbine associated conveniently with gearless variable reluctance generator. This objective has been achieved using a user-friendly program coupling the open source software FEMM with MATLAB/SIMULINK widely used by the academic community. Another contribution of this work lies in the calculation by the finite element method of inductances at aligned and unaligned position. This allowed us to carry out a detailed analysis of system performances. It gave good results in dynamic non-linear generator operation. Currently, there are a little research results in this field; a continuation to the work would be followed to optimize the system performance by developing efficient control strategies. REFERENCES [1] K. Trinada, et al., “Study of Wind Turbine based SEIG under Balanced/Unbalanced Loads and Excitation,” International Journal of Electrical and Computer Engineering, vol/issue: 2(3), pp. 353-370, 2012. [2] A. M. Thin and N. S. Y. Kyaing, “Performance Analysis of Doubly Fed Induction Generator Using Vector Control Technique,” International Journal of Electrical and Computer Engineering, vol/issue: 5(5), pp. 929-938, 2015.
  • 11. IJECE ISSN: 2088-8708  Study of Wind Turbine based Variable Reluctance Generator Using Hybrid .... (Tariq Benamimour) 11 [3] T. Z. Khaing and L. Z. Kyin, “Control Analysis of Stand-Alone Wind Power Supply System with Three Phase PWM Voltage Source Inverter and Boost Converter,” International Journal of Electrical and Computer Engineering, vol/issue: 5(4), pp. 798-809, 2015. [4] S. M. Mohiuddin and M. R. I. Sheikh, “Stabilization of Solar-Wind Hybrid Power System by Using SMES,” International Journal of Electrical and Computer Engineering, vol/issue: 4(3), pp. 351-358, 2014. [5] A. Lebsir, et al., “Electric Generators Fitted to Wind Turbine Systems: An Up-to-Date Comparative Study,” Journal of Electrical Systems, vol/issue: 11(3), pp. 281-295, 2015. [6] H. Tiegna, et al., “Overview of High Power Wind Turbine Generators,” in IEEE ICRERA, Nagasaki, Japan, pp. 1- 6, 2012. [7] A. Lebsir, et al., “Comparative Study of PMSM and SRM capabilities,” in IEEE POWERENG, Istanbul, Turkey, pp. 760-763, 2013. [8] H. Chen, “Implementation of a three-phase switched reluctance generator system for wind power applications,” in IEEE SELT, Victoria, pp. 1-6, 2008. [9] Y. Fan, et al., “A New Three-Phase Doubly Salient Permanent Magnet Machine for Wind Power Generation,” in IEEE Trans. On Industry Applications, vol/issue: 42(1), pp. 53-60, 2006. [10] R. Cardenas, et al., “Control of a Switched Reluctance Generator for Variable-Speed Wind Energy Applications,” in IEEE Trans. On Energy Conversion, vol/issue: 20(4), pp. 781-791, 2005. [11] V. B. Koreboina and L. Venkatesha, “Modelling and Simulation of Switched Reluctance Generator Control for Variable Speed WECS,” in IEEE PEDES, Bengaluru, pp. 1-6, 2012. [12] H. Chen, et al., “Research on the switched reluctance wind generator system,” in IEEE PESGM, pp. 1-6, 2001. [13] K. Ogawa, et al., “Study for Small Size Wind Power Generating System Using Switched Reluctance Generator,” in IEEE International Conference on Industrial Technology, Mumbai, pp. 1510-1515, 2006. [14] D. A. Torrey, “Switched Reluctance Generators and their Control,” in IEEE Trans. On Industrial Electronics, vol/issue: 49(1), pp. 3-14, 2002. [15] T. Benamimour, et al., “CAD of Electrical Machines Using Coupled FEMM-MATLAB Softwares,” in IEEE EPECS, Istanbul, pp. 1-6, 2013. [16] A. Soetedjo, et al., “Modeling of Wind Energy System with MPPT Control,” in IEEE International conference on Electrical Engeneering and Informatics, Indonesia 17-19 July 2011. [17] S. Song and W. Liu, “A Novel Method for Nonlinear Modeling and Dynamic Simulation of a Four-phase Switched Reluctance Generator System Based on MATLAB/SIMULINK,” in IEEE ICIEA, Harbin, pp. 1509-1514, 2007.