Modelling and Simulations

ISSN 1974-9821 Vol. 4 N. 2 April 2011

International Review on

Modelling and Simulations (IREMOS)

PART

A

Contents: Optimization of Augmented Rails in Augmented-Parallel Railgun by Augmented-Lagrangian Genetic Algorithm by Mehrdad Jafarboland, Mehdi Peyvandi

458

Input-State Feedback Linearization Control of Three-Phase Dual-Bridge Matrix Converters Operating Under Unbalanced Source Voltages by Mahmoud Hamouda, Farhat Fnaiech, Kamal Al-Haddad

467

A New Switching Technique and Optimum Computation of DC Sources in Three-Phase Multilevel Inverter by J. Ebrahimi, G. Mokhtari, B. Vahidi

478

Optimal Design of Passive Filters for Voltage Source Inverters by H. Sarabadani, H. Feshki Farahani

485

Comparison Performances of Asymmetric Multilevel Inverters in the Maximum Voltage Rating of Power Electronic Devices by Bambang Sujanarko, Mochamad Ashari, Mauridhi Hery Purnomo

493

Computer Aided Design Tools in RF Power Amplifier Design by Abdullah Eroglu

501

Detailed Analysis of Cascaded Multilevel Converter Based STATCOM by M. Heidari, A. Kovsarian, S. GH. Seifossadat

507

Steady-State Electromagnetic and Thermal Modelling of an Induction Motor Under Healthy Operation and Under Broken-Bar Fault by Joya C. Kappatou, Dimitrios C. Stellas

517

Improved Simulation Strategy for DFIG in Wind Energy Applications by Ali M. Eltamaly, A. I. Alolah, M. H. Abdel-Rahman

525

Elimination Chaotic Ferroresonance in Autotransformers Including Linear and Nonlinear Core Losses Effect Considering Neutral Earth Resistance by Hamid Radmanesh, Roozbeh Kamali

533

Comparison of the Effect of Phase to Ground Faults and Three Phase Faults in a Micro-Turbine Generation System by Goodarz Cheraghi, Abdolreza Tavakoli, Seyed Hossein Alavi, Saeed Ahmadi, Seyed Morteza Alizadeh

541

(continued on inside back cover)

Copyright © 2011 Praise Worthy Prize S.r.l. - All rights reserved

International Review on Modelling and Simulations (IREMOS) Editor-in-Chief: Santolo Meo Department of Electrical Engineering FEDERICO II University 21 Claudio - I80125 Naples, Italy [email protected]

Editorial Board: Marios Angelides M. El Hachemi Benbouzid Debes Bhattacharyya Stjepan Bogdan Cecati Carlo Ibrahim Dincer Giuseppe Gentile Wilhelm Hasselbring Ivan Ivanov Jiin-Yuh Jang Heuy-Dong Kim Marta Kurutz Baoding Liu Pascal Lorenz Santolo Meo Josua P. Meyer Bijan Mohammadi Pradipta Kumar Panigrahi Adrian Traian Pleşca Ľubomír Šooš Lazarus Tenek Lixin Tian Yoshihiro Tomita George Tsatsaronis Ahmed F. Zobaa

(U.K.) (France) (New Zealand) (Croatia) (Italy) (Canada) (Italy) (Germany) (Bulgaria) (Taiwan) (Korea) (Hungary) (China) (France) (Italy) (South Africa) (France) (India) (Romania) (Slovak Republic) (Greece) (China) (Japan) (Germany) (U.K.)

Brunel University Univ. of Western Brittany- Electrical Engineering Department Univ. of Auckland – Department of Mechanical Engineering Univ. of Zagreb - Faculty of Electrical Engineering and Computing Univ. of L'Aquila - Department of Electrical and Information Engineering Univ. of Ontario Institute of Technology FEDERICO II Univ., Naples - Dept. of Electrical Engineering Univ. of Kiel Technical Univ. of Sofia - Electrical Power Department National Cheng-Kung Univ. - Department of Mechanical Engineering Andong National Univ. - School of Mechanical Engineering Technical Univ. of Budapest Tsinghua Univ. - Department of Mathematical Sciences Univ. de Haute Alsace IUT de Colmar FEDERICO II Univ., Naples - Dept. of Electrical Engineering Univ. of Pretoria - Dept.of Mechanical & Aeronautical Engineering Institut de Mathématiques et de Modélisation de Montpellier Indian Institute of Technology, Kanpur - Mechanical Engineering "Gh. Asachi" Technical University of Iasi Slovak Univ. of Technology - Faculty of Mechanical Engineering Aristotle Univ. of Thessaloniki Jiangsu Univ. - Department of Mathematics Kobe Univ. - Division of Mechanical Engineering Technische Univ. Berlin - Institute for Energy Engineering Brunel University - School of Engineering and Design

The International Review on Modelling and Simulations (IREMOS) is a publication of the Praise Worthy Prize S.r.l.. The Review is published bimonthly, appearing on the last day of February, April, June, August, October, December. Published and Printed in Italy by Praise Worthy Prize S.r.l., Naples, April 30, 2011. Copyright © 2011 Praise Worthy Prize S.r.l. - All rights reserved. This journal and the individual contributions contained in it are protected under copyright by Praise Worthy Prize S.r.l. and the following terms and conditions apply to their use: Single photocopies of single articles may be made for personal use as allowed by national copyright laws. Permission of the Publisher and payment of a fee is required for all other photocopying, including multiple or systematic copying, copying for advertising or promotional purposes, resale and all forms of document delivery. Permission may be sought directly from Praise Worthy Prize S.r.l. at the e-mail address: [email protected] Permission of the Publisher is required to store or use electronically any material contained in this journal, including any article or part of an article. Except as outlined above, no part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without prior written permission of the Publisher. E-mail address permission request: [email protected] Responsibility for the contents rests upon the authors and not upon the Praise Worthy Prize S.r.l.. Statement and opinions expressed in the articles and communications are those of the individual contributors and not the statements and opinions of Praise Worthy Prize S.r.l.. Praise Worthy Prize S.r.l. assumes no responsibility or liability for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained herein. Praise Worthy Prize S.r.l. expressly disclaims any implied warranties of merchantability or fitness for a particular purpose. If expert assistance is required, the service of a competent professional person should be sought.

International Review on Modelling and Simulations (I.RE.MO.S.), Vol. 4, N. 2 April 2011

Improved Simulation Strategy for DFIG in Wind Energy Applications Ali M. Eltamaly1, A. I. Alolah1, M. H. Abdel-Rahman2 Abstract – A detailed computer simulation for interconnecting wind energy system to electric utility is presented. The proposed system consists of four high rating wind turbines each one uses double fed induction generator (DFIG). Two back to back bidirectional PWM inverters are used in the rotor circuit of each DFIG to be interfaced with electrical utility. This computer simulation incorporates a flexible independent control for the active and reactive powers by using field oriented control technique. Also it introduces an effective technique to track the maximum power point of the wind energy system by controlling the pitch angle and rotational speed. Active power is controlled through the direct axis current of the rotor side converter in outer control layer. Reactive power is controlled by the quadrature axis of the rotor side converter. The dc-link voltage of the PWM converter is maintained constant by controlling the direct axis current of the grid side converter. The system shows a stable operation under different operating conditions. Copyright © 2011 Praise Worthy Prize S.r.l. - All rights reserved.

Keywords: DFIG, Induction Generator, Modeling, Wind Energy

Nomenclature

Ls ,Lr vqs ,iqs

Mechanical power from WT Air density (kg/m3) Radius of the swept area by the blades (m) Velocity of the wind (m/s) Power coefficient of performance The angular velocity of the shaft (rad/s) Tip speed ratio and blades pitch angle Value of λ at maximum coefficient of performance Stator resistance and leakage inductance Rotor resistance and leakage inductance Magnetizing inductance Total stator and rotor inductances q axis stator voltage and current

vqr ,iqr

q axis rotor voltage and current

vds ,ids

φqs ,φds

d axis stator voltage and current d axis rotor voltage and current Stator q and d axis fluxes

φqr ,φdr

Rotor q and d axis fluxes

θ m , ωr

Rotor angular position and angular velocity Number of pole pairs Electrical angular velocity ( P ⋅ Ω )

Pm

ρ

R u CP Ω λ,β

λnom Rs ,Lls Rr ,Llr Lm

vdr ,idr

P

ωe

θe Te , Tm

J

Pg , Qg

Active and reactive power from WT

Pg* , Q*g

Reference values of Pg , Qg

Ps , Qs Pgc , Qgc

Stator active and reactive power Active and reactive power from the GSC to utility d and q-axes of current from GSC

idgc , iqgc i*dgc , i*qgc i*dgc , i*qgc Rg , Lg * Vdc , Vdc

Reference value of d and q-axes of current from GSC Reference value of d and q-axes of the controlled voltage of GSC Series resistance and inductance of GSC transformer Actual and refererence dc-link voltages

ims

Stator magnetizing-current space phasor

idqr , vdqr

Space phasor components of rotor current and voltage Space phasor components of stator-current and voltage The modulus of the stator-voltage space phasor

idqs , vdqs vs

I.

Introduction

Electrical energy generated from wind increased in the last decade and it takes a considerable part of the energy of many countries. Before, wind was not reliable energy source as conventional generation stations as steam and gas power plants. With mature technology introduced to wind energy systems, (WES) it behaves like conventional stations. Now, the reactive power from

Electrical rotor angular position ( P ⋅ θ m ) Electromagnetic torque and shaft mechanical torque Combined rotor and load inertia coefficient

Manuscript received and revised March 2011, accepted April 2011


525

Ali M. Eltamaly, A. I. Alolah, M. H. Abdel-Rahman

WES can be controlled independent of active power as in conventional power stations. Two modes of operations can be used in the electrical generation from the wind namely, constant speed constant frequency (CSCF) and variable speed constant frequency (VSCF). VSCF becomes more attractive especially with the modern technology of power electronics and digital control systems because of its higher energy capture, higher stability, decoupling control of active and reactive power, lower mechanical stresses and acoustic noise, and improved power quality. DFIG is the recommended generator in the large size wind turbine, (WT) to achieve all the benefits of the VSCF systems. The stator of DFIG is connected directly to the electric utility and the rotor is connected to electric utility via two back-to-back PWM converters and stepup transformer as shown in Fig. 1. Due to the presence of the converter in the rotor circuit, the rating of this converter is just a fraction of the main power transferred to electric system which is the main advantage of this configuration. The main objectives of the proposed controller are tracking of maximum power point, (MPP) and providing an independent control of active and reactive powers. Tracking MPP can be achieved by controlling the pitch angles of the WT's blades as an outer control loop to force WT to work around its maximum coefficient of performance (CP). The variation of pitch angle can be achieved by using the aerodynamic characteristics of the WT [1]-[4] or fuzzy controller [5]-[7]. Active power can be controlled in inner loop by controlling iqr while the reactive power is controlled by controlling idr [8], [9]. Modified response is introduced in this paper by using field oriented control (FOC). The proposed system contains four WTs each derives a DFIG.The system is connected to an electric utility via a step up and two-circuit transmission lines and step up transformers. The proposed FOC technique is aligning the d-axis of the reference frame along the rotor voltage position. In this case, active and reactive powers are controlled by using idr and iqr respectively [10]. The logic used in this strategy is explained in details below.

II. II.1.

P

Q

* I qr

I d _ ug

*

dq

I q _ ug

I abc _ ug abc

Q

Vds abc dq

dq

Vqs

Vds*

I d _ gc

dq

I q _ gc ω e ,θ e

Vqs*

abc

V abcs I abc _ gc

abc Vabcs

f Vdc

Tm

θr

Vdc*

Vdc

I d _ gc

θe −θr

I q _ gc I dr abc

dq

dq

I qr

Vdr*

Vdr

Vqr* * I qr

* I dr

Vqr

dq

abc

φs

Lm / Ls

I dr*

I abcr

abc

d / dt Ω

Vabcr

Vdqs I dqs

PLoss T*

P

*

P

Ω

Fig. 1. Schematic diagram of the proposed converter

The error signal is fed to PI-controller to generate i*qr. Rotational speed is fed to the aerodynamic model to determine the torque command depending on the aerodynamic characteristics of the WT. Torque command are fed to torque regulator model to determine the reference value of the direct axis current of the rotor side converter (RSC), i*dr. The reference values of direct and quadrature axis of rotor current are fed to the current regulator of RSC to determine the reference value of the direct and quadrature reference values of RSC, v*dr, and v*qr respectively. Space vector modulation (SVM) model uses v*dr, and v*qr to generate the suitable switching pattern for the RSC. The grid side controller controls the DC-link voltage, Vdc by comparing the actual value of Vdc with its reference value and the error signal is used to generate i*ds. Also i*qs can be generated from comparing the grid reactive power Qg with its corresponding reference value to improve the tracking of the reactive power control. The pitch angle controller compares the rotational speed with the rated speed and feeds the error signal to PI-controller to determine the value of β which is required to the WT model. A detailed representation of each part is shown in the following sections.

Wind Energy System Model

General Structure of Wind Energy System Model

The simulation model is built depending on speed variation is assumed to be varied faster than usual for the purpose of simulation time. Models of the proposed energy system are shown in Fig. 1. Aerodynamic characteristics of the WT are used to calculate the shaft power and torque of the WT. This torque is fed to DFIG model. The electric utility voltages and currents are fed to active and reactive power calculation model to calculate active and reactive power Pg and Qg output from DFIG.Reactive power Qg is compared with the reference value, Q*g that required by the system operator from the WES.

II.2.

Aerodynamic Model of Wind Turbine

Mechanical power generated by WT is given by [1]: Pm = 0.5 ⋅ CP ρ π R 2 u 3


(1)

International Review on Modelling and Simulations, Vol. 4, N. 2

526


When wind speed changes, the angular velocity of the shaft, Ω should be adjusted to achieve the best value of CP. This means that Ω and the wind speed must be combined into a single variable so that the curve showing the relation between CP and Ω can be drawn. Experiments show that this single variable is the ratio of the turbine tip speed RΩ to the wind speed u. This tip speed ratio, λ is defined as [1]:

λ = RΩ / u

model and the mechanical part by a second-order system [11], [12].

(

)

1 / λi = 1 / ( λ + c7 β ) − c8 / β 3 + 1

Cp

Pm Tm

Ω

Ω

Fig. 3. Aerodynamic model of WT

II.4.

Rotor-Side Converter (RSC) Control

The main task of RSC control system is to track the MPP of the WT and to control the reactive power required by the electric utility. RSC modeling contains four main parts which are presented in the following sections.

(3)

(4)

A- Maximum Power Point Tracking

The coefficients c1 to c8 are shown in [2].

Maximum power variation with rotation speed, ωr of DFIG is predefined for each WT. So, for MPP tracking (MPPT), the control system should follow the tracking characteristic curve (TCC) of the WT. Each WT has TCC similar to the one shown in Fig. 4. TCC is represented by the ABCD curve of Fig. 5. The actual WT speed, Ω is measured and the corresponding mechanical power of the TCC is used as the reference power for the power control loop [18]. TCC is divided into five regions summarized in Table I. The reference power in region-I is set to zero. In region-II, the TCC is a straight line. In region-III, the TCC is the locus of the maximum power of the turbine. The TCC of region-III can be approximated to second [14] or third [15] order polynomial. In the current simulation the TCC in region-III is characterized by third order polynomial. TCC in regionIV is a straight line from C to D.

A 3-D figure showing the relation between CP, λ, and β is shown in Fig. 2.

Cp

λ

Cp

β

From (2), it is important to note that the value of CP is a function of λ. The following equation is used to model the relation between CP, λ, and β [2]-[4], as:

where:

λ

R

(2)

CP ( λ , β ) = c1 ( c2 / λi − c3 β − c4 ) e− c5 / λi + c6 λ

Pw

1 ρAu 3 2

u

β

Fig. 2. Areodynamic power coefficient variation against λ, and β

The maximum value of CP is achieved for β=0o and for λ=8.1. This particular value of λ is defined as the nominal value, λnom. As shown in Fig. 1 the WT model has three inputs, Ω in pu, β in degrees and u in m/s.vTip speed ratio λ in pu of λnom is obtained from (2). Optimum value of CP is obtained from the characteristics of the WT by using (3) and (4), Pm is calculated from (1). The mechanical torque (Pm/Ω) will be used as an input to the model of DFIG. The block diagram used to implement the aerodynamic model of WT is shown in Fig. 3.

1.6 1.4 1.2 1 0.8 0.6 0.4 0.2

II.3.

Modeling of DFIG

0 0.4

The state space modeling of DFIG in a synchronously rotating reference frame (dq-frame) has been used here. The model is represented by a fifth-order state-space

0.6

0.8

1

1.2

1.4

Fig. 4. Tracking characteristics of the turbine



527


The power at point D is 1 pu and the speed at D must be greater than that at C. In Region-V (Beyond point D) the reference power is a constant (1 p.u). Modeling of TCC in Simulink has been implemented in look-Up Table (LUT). Other researches implement as logical blocks [16] which is the case in this research as shown in Fig. 5. The time variation of reference value of power and speed Ω is shown in Fig. 6.

phasors expressed in the stator-flux-oriented reference frame as [17]: ims = idqr + ( Ls / Lm ) idqs

The above equation can be written as:

Ω

idqs =

Lm ims − idqr Ls

ids =

Lm ( ims − idr ) Ls

(7)

iqs = −iqr ⋅ ( Lm / Ls )

(8)

and:

Ω>C

Wind speed

15

d d idqs + Lm idqr + dt dt + jωe Lm idqr

vdqs = Rs idqs + Ls

10

+ jωe Ls idqs 5

10

15

vdqs = 5

10

15

Rs Lm d ims − idqr + Lm ims + jωe Lm ims (10) Ls dt

(

)

The above equation can be rewritten as: Ls d ims + ims Rs dt

5 0 0

5

10

15

Fig. 6. Variation of reference value of power and speed Ω

Ls d L ims + ims = s vds + idr Rs dt Rs Lm

TABLE I PERFORMANCE CHARACTERISTICS OF TCC Limits Ω 0 to A

Power Limits

Pg = 0

TCC performance Constant

II

A to B

0 to Pg (B)

Linear equation

III

B to C

Pg (B) to Pg (C )

IV

C to D

Pg (c) to Pg (D)

Quadrature or Cubic polynomial Linear equation

V

Ω>D

Pg (D)

Constant

⎛ Ls ⎞ Ls vdqs + idqr (11) ⎜1 + jωe ⎟= R R s ⎠ s Lm ⎝

Above equation can be divided into real and imaginary parts as the following:

Time

Region I

(9)

Substitute from (6) into (9) yields:

1.2 1 0 10

(6)

Stator voltage equation is obtained in the special reference frame fixed to the stator-linkage space phasor, which rotates at a synchronous speed ωe:

Fig. 5. Block diagram of the logic of TCC

P, Pref

)

ΩB

Rotational speed

(

From (19):

Ω> A

5 0 1.4

(5)

ωe

Ls L ims = s vqs + iqr Rs Rs Lm

(12)

(13)

It is useful to express stator current, in terms of rotor currents in synchronously rotating reference frame. Thus it follows from (6) that by resolving it into its two-axis components, it follows that ids and iqs can be expressed in terms of the rotor current components established in the same reference frame as following:

B- Stator-Flux-Oriented Control of DFIG Stator magnetizing-current space phasor can be derived in terms of the stator and rotor current space



528


iqs = −iqr

Lm Ls

(14)

3 Qs = − vds iqs 2

(15)

Substitute from (14) and (15) into (21) and (22) yields: 3L (23) Ps = m vds ( ims − idr ) 2 Ls

and: ids =

Lm ( ims − idr ) Ls

It follows from (14) that iqr is proportional to the torque-producing (active) stator current component (iqs). However, in (15) stator magnetizing-current space phasor is also present, and this depends on the stator voltage. This dependency can now be obtained. For this purpose, it is assumed that the stator resistance Rs of the induction machine is neglected. Also, in the steady state the modulus of the stator magnetizing current (which is defined in (15)), is constant ( ims =constant). Thus, it

Qs =

C- Torque regulator

(16) Te =

or: ims =

vs

(17)

ωe Lm

1 Ls

⎛ vs ⎞ − Lm idr ⎟ ⎜ ⎝ ωe ⎠

(

)

(

)

i*dr = Te /

(19)

( ( Lm / Ls ) φqs )

φqs = ( vds − Rs ids ) / ( −ωe )

(26)

(27)

So by using the reference value of the generated torque, the reference value of direct axis rotor current can be obtained from equations (26) and Fig. 7.

(20)

D- Reactive Power Regulator

Equation (24) shows a direct relationship between Qs and iqr. So, i*qr can be used to produce the reactive power required by the system operator. The value of i*qr can be obtained from comparing the actual and reference values of reactive power and feeding the error signal to PIcontroller. The reference values of the RSC voltages is obtained from i*dr and i*qr in the current regulator of RSC as shown in Fig. 8.

vβ vα

By aligning the d-axis of the reference frame along with the grid voltage position vqs=0 and vqs= constant because the grid voltage is assumed to be constant. Thin the active and reactive power can be obtained from the following equations: 3 Ps = vds ids 2

(25)

The value of φqs can be obtained from [11], [12] as:

and, the angle is:

θe = ∫ ωe dt = tan −1

)

Te = ( Lm / Ls ) ⋅ φqs idr or

(18)

The stator reactive power as: 3 vqs ids − vds iqs 2

(

Substituting φds = 0 in the torque equation, yields:

The stator active power can be defined as [17]: 3 vds ids + vqs iqs 2

Lm φqs idr − φds iqr Ls

By aligning the d-axis of the reference frame along with the grid voltage position vqs = 0 , then φds = 0 .

From (15) and (17), ids is as following:

Qs =

(24)

The relation between torque, stator flux and rotor current is obtained from the following equation:

vs = ωe Lm ims

Ps =

3Lm vds iqr 2 Ls

From (23) and (24) and since the machine parameters (Lm, Ls) and also |vs| and |ims| are constant, it follows that, the active stator power Ps can be controlled by idr and the reactive stator power Qs can be controlled by iqr.

follows from (10) that:

ids =

(22)

II.5.

Grid-Side Converter Control

The main function of the GSC is to control Vdc and to control active and reactive power from Vdc to the gird side.

(21)



529


The value of Vdc is controlled by vector control scheme with the reference frame oriented along the grid voltage vector position [12]. This scheme permits independent control of Vdc and reactive power. The active and reactive power from GSC to electric utility is obtained from the following equations: Pgc = ( 3 / 2 ) ⋅ vds idgc + vqs iqgc

(

)

(28)

(

)

(29)

Qgc = ( 3 / 2 ) ⋅ vqs idgc − vds iqgc

I dr I qs Lm

ωe − ω r

(

and:

ωe − ω r Rr

(

iqr

Llr + Lm

ωe − ω r

)

Lm I ds

(31)

I qr * I qr

Fig. 8. Current Regulator at rotor converter side

III. Simulation Results

⎡iagc ⎤ ⎡iagc ⎤ ⎢ ⎥ d ⎢ ⎥ ⎢ibgc ⎥ − Lg ⎢ibgc ⎥ dt ⎢ ⎥ ⎢ ⎥ ⎢⎣ icgc ⎦⎥ ⎣⎢ icgc ⎦⎥

Simulation has been carried out by using Simulink with Matlab. The system consists of four WT with rating of 2 MW which are connected to the electric utility via step-up tansformer, 20km transmission line, and stepdown transformer. The system contains 500kW local load. The speed variation and the required reactive power are changed in stiff way to see the response of the control system during these conditions. Fig. 9 shows the time variation of wind speed (m/s), rotational speed (pu), bitch angle, tip speed ratio, and output power. It is clear from this Fig. that the pitch angle is set to zero when the rotational speed less than the rated value (The value at point D of Fig. 4). It is also notable that when the output power exceeds the rated value the aerodynamic system increases the pitch angle to reduce the output power to the rated value. Fig. 10 shows the time variation of Qg and Q*g , iqr, i*qr, idr, i*dr, Vdc, and idgc, i*dgc. It is clear from the first curve (top one) that the system follows the reactive power required from the system even with highly change in the reactive power. Also it is clear from the second curve of Fig. 10 that i*qr increase in negative direction with increasing the reactive power required and vice versa. Also it is clear from this Fig. that iqr follows exactly its reference value i*qr. It is also clear from the third curve of Fig. 10 that the power going to electric utility follows the reference or calculated value. Also it is clear from fourth curve of Fig. 10 that idr follows exactly its reference value i*dr. It is also clear from the fifth curve of Fig. 10 that Vdc is almost constant even in sever conditions. The last curve shows that idgc follows exactly its reference value, i*dgc.

(32)

Using Park's transformations, yields: ⎡ vdgc ⎤ ⎡ vds ⎤ ⎡ −iqgc ⎤ ⎢ ⎥ = ⎢ ⎥ + ωe Lg ⎢ ⎥+ ⎢⎣ vqgc ⎥⎦ ⎣ vqs ⎦ ⎢⎣ idgc ⎥⎦ ⎡ −idgc ⎤ d ⎡ −idgc ⎤ − Rg ⎢ ⎥ − Lg ⎢ ⎥ dt ⎢⎣ iqgc ⎥⎦ ⎢⎣ iqgc ⎥⎦

(33)

The cross coupling effect is represented by ωe Lg idgc and ωe Lg iqgc . The voltages v*dgc and v*qgc that obtained from (33) are fed to space vector modulation (SVM) module.

V

ds

Te*

I ds Rs

φqs

ωe

ωe − ωr

(30)

It is clear from (30), (31), that the active and reactive powers can be controlled independently by idgc and iqgc respectively. The control of Vdc is obtained by double closed loop technique [12], [18]-[20]. The voltage at the leg of the GSC is obtained from the following equation: ⎡ vagc ⎤ ⎡ v ⎤ ⎢ ⎥ ⎢ as ⎥ ⎢ vbgc ⎥ = ⎢ vbs ⎥ − Rg ⎢ ⎥ ⎢v ⎥ ⎣⎢ vcgc ⎦⎥ ⎣ cs ⎦

idr

Vqr*

)

Qgc = − ( 3 / 2 ) ⋅ vds iqgc

Llr + Lm

Vdr*

Substituting for Vqs in (28) and (29) yields: Pgc = ( 3 / 2 ) ⋅ vds idgc

* I dr

I dr*

Lm / Ls

Fig. 7. Torque regulator



530


u(m/s)

15

point tracking for the available energy from the wind independent of the control of the required reactive power from the wind energy system. The maximum power point tracker uses inner loop to control the blades pitch angle and outer loop uses vector control technique by controlling the d-axis of the rotor current. The reactive power has been controlled effectively using the q-axis of the rotor current. The grid-side converter is controlled with a vector control strategy with the grid voltage orientation. The d-axis voltage component is fixed with the orientation of grid voltage space vector, and the qaxis voltage component is zero. So the active power and reactive power of the grid-side converter can be controlled independently using d and q-axes of grid side converter current respectively. Simulation results show the effective behavior and the superiority of the control system even with sudden change in the wind speed or sudden change in the required reactive power.

10 5

0

5

10

15

0

5

10

15

0

5

10

15

0

5

10

15

wr(pu)

1.2 1.15 1.1

Beta

5

0

Lamda

15 10 5 Pg,P*g

10

References

5 0

[1]

0

5

10

15

Fig. 9. Time variation of wind speed (m/s), rotational speed (pu), bitch angle, tip speed ratio, and output power

[2]

0 0 0 -0.5 -1 0 10 5

5

10

15

5

10

15

5

10

15

5

10

15

[4]

[5]

Pg,P*g

iqr ,i*qr

Qg,Q*g

[3]

5

[6]

0.5 [7]

0 0 1220 1200 1180 0 0.1 0 -0.1 -0.2 0

[8]

5

10

15 [9]

idgc ,i*dgc

Vdc

idr ,i*dr

0 0

5

10

[10]

15

Time * Fig. 10. Time variation of Q g , Qg* (MVAR), iqr , iqr , Pg , Pg* ,

[11]

* * idr , idr , Vdc , and idgc , idgc

[12]

IV.

Conclusion

This paper presents in details a complete simulation for interconnecting WT having DFIG with electric utility. The control technique permits a maximum power

[13]


Ali M. Eltamaly, Modeling of Wind Turbine Driving Permanent Magnet Generator with Maximum Power Point Tracking System, Journal of King Saud University, Vol. 19 (issue 2), pp.223-228, , 200. S. Heier, Grid Integration of Wind Energy Conversion Systems, John Wiley & Sons Ltd, 2nd Edition, ISBN 0470868996, 2006. A.A. El-Sattar, N.H. Saad, M.Z. Shams El-Dein, Dynamic response of doubly fed induction generator variable speed wind turbine under fault, Electric Power Systems Research, Vol. 78, pp.1240–1246, 2008. L. Krichen, B. François and A. Ouali, A fuzzy logic supervisor for active and reactive power control of a fixed speed wind energy conversion system, Electric Power Systems Research, Vol.78, pp.418–424, 2008. Qichang Duan, Fengxia Hao, Shicheng Feng, Adaptive Fuzzy Control Used in DFIG VSCF Wind Power Generator System, in Proc. Conf.,2008, Proc. of the 7th World Congress on Intelligent Control and Automation, China, 2008, pp. 29-32. Le-Ren Chang-Chien, Chih-Min Hung, Yao-Ching Yin, Dynamic Reserve Allocation for System Contingency by DFIG Wind Farms", IEEE Trans. on Power Systems, Vol. 23, No. 2, 729-736, May 2008. V. Calderaro, V. Galdi, A. Piccolo, P. Sian, A fuzzy controller for maximum energy extraction from variable speed wind power generation systems, Electric Power Systems Research, Vol. 78, pp.1109–1118, , 2008. D. Aouzellag, K. Ghedamsi and E.M. Berkouk,"Network power flux control of a wind generator, Renewable Energy, Vol. 34, pp. 615–622, March 2009. X. Yu, Z. Jiang, and Y. Zhan, A Synergetic Control Approach to Grid-Connected, Wind-Turbine Doubly-Fed Induction Generators, in Conf. Proc., PESC, 2008, pp.2070 – 2076. K. Gogas, G. Joos, B. T. Ooi, Y. Z. Zhang, B. Mwinyiwiwa, Design of a Robust Speed and Position Sensorless Decoupled P-Q Controlled Doubly-Fed Induction Generator for Variable-Speed Wind Energy Applications, in conf. proc.,2007, EPC 2007, Canada, pp. 62 – 67. P. C. Krause, O. Wasynczuk, and S.D. Sudhoff, Analysis of Electric Machinery, book, IEEE Press, 2002. R. Pena, J. C. Clare, and G. M. Asher, A doubly fed induction generator using back-to-back PWM converters and its application to variable- speed wind-energy generation, Proc. IEE Trans., Vol. 143, No. 5, pp. 231–241, 1996. P.V. Kumar, S. K. Kottayil, K.S. Meera, Transient Fault Response of Grid Connected Wind Electric Generators, in Conf. Proc., 2006, PEDES 2006, pp. 1 – 6.


531


[14] G. Ramtharan, J. B. Ekanayake, and N. Jenkins, Support for Spinning Reserve from DFIG based wind turbines, in Conf. proc., ICIIS 2007, Sri Lanka, pp.111-115. [15] A. Yazdani, Islanded Operation of A Doubly-Fed Induction Generator (DFIG) Wind-Power System with Integrated Energy Storage, in Conf. Proc. EPC 2007. Canada, 2007 pp. 153 – 159. [16] N. Strachan and D. Jovcic, Dynamic Modelling, Simulation and Analysis of an Offshore Variable-Speed Directly-Driven Permanent-Magnet Wind Energy Conversion and Storage System (WECSS), in Conf. Proc. OCEANS 2007 – Europe, 2007, pp.1-6. [17] P. Vas, Sensorless Vector and Direct Torque Control, Oxford science publications, ISBN: 13- 9780198564652, 1998. [18] M. Fazli R. Jahani, Ali Fazli, J. Olamaei, H. A. Shayanfar, New Method to Connect Wind Turbines Equipped With DFIGs to the Power Grid Using FCL and STATCOM, International Review on Modeling and simulation Journal, IREMOS, vol. 3, (issue 4), pp. 598-603, Aug. 2010. [19] B. Vahidi, H. Yazdanpanahi, The Effect of Wind Farm to AC Grid Connection Type on Overvoltages Due to Lightning, International Review on Modeling and simulation Journal, IREMOS, vol. 2, (issue 5), pp. 598-603, Oct.. 2009. [20] S. V. Heidari, M. Sedighizadeh, A. Rezazadeh, M. Ahmadzadeh, Lyapunov Based Self-tuning Control of Wind Energy Conversion System, International Review on Modeling and simulation Journal, IREMOS, vol. 3, (issue 5), (part A), pp. 864-869, Oct. 2010.

A. I. Alolah (S'85,AM'86,M'87,SM'96) was born in 1957. He received a B.Sc. in EE dept., King Saud University, Riyadh, Saudi Arabia in 1979 and Ph.D. in EE dept., University of Bradford, England in 1986. In May 86 Dr. Alolah joined King Saud University as an Assistant professor. He was promoted to an Associate professor and then to a Professor in May 90 and Nov. 94, respectively. He is the chairman of EE dept., King Saud University. His current research interest includes electrical machines and power electronics. Mansour Hassan Abdel-Rahman was born in Egypt in 1947. He received the B.Sc. and M.Sc. degrees in electrical engineering from Cairo University in 1970 and 1975, respectively, and the Ph.D. degree in electrical engineering from the University of Manchester Institute of Science and Technology (UMIST), U.K., in 1979. He has been a Full Professor at the University of ElMansoura, Egypt, since 1987. He spent visiting assignments, teaching and researching, at the University of Toronto, and, University of Windsor, Canada, the University of Cambridge, U.K., where he was a Fellow of Churchill College, University of Western Australia, Australia, University of Canterbury, New Zealand, Doshisha University, Japan, University of Iceland, Iceland, , The School of Renewable Energy Science (RES), Iceland, Helsinki University of Technology, Finland, University of Aalborg, Denmark, Jordan University, Jordan, and Kuwait University, Kuwait. Dr. Abdel-Rahman received the John Madsen Medal for the best paper submitted to the Institute of Engineers, Australia, in 1989, and three awards from the IEEE for the best paper in 1987 and 1988, respectively.

Authors’ information 1 2

Electrical Engineering Department, King Saud University. Electrical Engineering Dept., Mansoura University, Egypt.

Dr. Ali M. Eltamaly was born on June, 1969, Egypt. He received the B. S. (with distinction and honor degree), M.Sc., and PhD from Texas A&M University-USA, in 1992, 1996, and 2000, respectively. He joined Elmina University, Egypt, from 1992-1997. He joined electrical engineering dept., Texas A&M university, USA from 1997-2000. He was a member of the faculty of the college of engineering, Elminia and Elmansoura universities, Egypt from 2000 to 2005. He is currently an associate Professor of the college of engineering of King Saud University, Saudi Arabia since Oct. 2005 till now. Currently Dr. Eltamaly is a Wind Energy Section Supervisor of Sustainable Energy Technology program of King Saud University. Dr. Eltamaly research interests are in the area of renewable energy, power electronics, and power quality where he supervised a number of MS.c and PhD thesis and published about 50 papers in international journals and conferences, number of books and book chapters for famous publishers, and number of national and international technical projects. Dr. Eltamaly conducts several courses and workshops in the area of renewable energy and power quality.



532

International Review on Modelling and Simulations (IREMOS) (continued from outside front cover) A Comparative Study on Optimal Design of LLC Resonant Converter by Intelligent Optimization Techniques by K. S. Rama Rao, Nur Syahirah Mohd Azhar, Nor Hisham Hamid

547

Losses Minimization in DTC-DPWM Induction Motor Drives by H. Kraiem, M. Dhaoui, L. Sbita

555

Doubly Fed Induction Generator Based a Novel Nine-Switch AC/AC Converter by Mohamad Reza Banaei, Ali Reza Dehghanzadeh

562

Suppression Chaotic Overvoltages in Potential Transformer Including Nonlinear Core Losses Considering Neutral Earth Resistance by Hamid Radmanesh, Roozbeh Kamali, Negar Farmani

568

Direct Torque Controlled Induction Motor Drives Using Space Vector Based PWM Techniques for Reduced Common Mode Voltage by V. Anantha Lakshmi, T. Bramhananda Reddy, M. Surya Kalavathi, V. C. Veera Reddy

575

Electromagnetic Analysis of the Effects of Static Eccentricity Fault on the Radial Force Variations in Switched Reluctance Motors by H. Torkaman, M. S. Toulabi, E. Afjei

585

Reduced Common Mode Voltage PWM Algorithms for Vector Controlled Induction Motor Drives by K. Satyanarayana, T. Brahmananda Reddy, J. Amarnath, A. Kailasa Rao

591

Sympathetic Inrush Phenomenon Analysis and Solution for a Power Transformer by Abdullah Asuhaimi Mohd Zin, Hana Abdull Halim, Sazali P. Abdul Karim

601

Low-Impedance Restricted Earth Fault Numerical Algorithms Operation in Power-Transformer Protection by B. Nim Taj, A. Mahmoudi, S. Kahourzade

608

A Series DC Motor Time-Varying Observer Based on Flatness and Genetic Algorithm by A. Mansour, H. Jerbi, N. Benhadj Braiek

616

TORUS and AFIR Axial-Flux Permanent-Magnet Machines: a Comparison via Finite Element Analysis by A. Mahmoudi, N. A. Rahim, W. P. Hew

624

Analysis and Robust Controller Design for a Hybrid Electrical Vehicle with PMSM by Ghazanfar Shahgholian, Pegah Shafaghi, Navid Lotfi Zadeh

632

Modelling of an Electro-Hydraulic Forklift in Matlab Simulink by Tatiana A. Minav, Denis M. Filatov, Lasse I. E. Laurila, Juha J. Pyrhönen, Victor B. Vtorov

640

The Use of SOM and MLP Neural Networks in the Classification of Pulse-Echo Ultra-Sonic Signals by A. Karimi, S. Seyedtabaii

648

Effects of Oil Palm Shell Filler on Inception and Propagation of Electrical Treeing in Silicone Rubber Composite Material Under AC Voltage by M. H. Ahmad, H. Ahmad, Y. Z. Arief, R. Kurnianto

653

(continued on outside back cover) Abstracting and Indexing Information: Academic Search Complete - EBSCO Information Services Cambridge Scientific Abstracts - CSA/CIG Elsevier Bibliographic Database SCOPUS Index Copernicus (Journal Master List): Impact Factor 6.55 Autorizzazione del Tribunale di Napoli n. 78 del 1/10/2008

(continued from inside back cover) Noise Smoothing for GPS Receivers Positioning Data Using Wavelet Transform by M. R. Mosavi, A. Ayatollahi, I. Emamgholipour

661

Theoretical Aspects Related to Active Force Evaluation in the Case of Electromagnetic Devices by Adrian Pleşca

668

Modeling of Distribution of PD Pulses within Micro-Cavities by Alireza A. Ganjovi, Ghasem Rastpour

674

Analysis Natural Frequencies a Functionally Graded Cylindrical Shell with Effects Symmetrical Boundary Conditions by M. R. Isvandzibaei, M. Setareh

683

A New Module Design for 3D Graphic Transformations Using Generated Floating-Point Core Units by İ. Şahin, İ. Koyuncu

691

Study on Post Arc Current and Transient Recovery Voltage in Vacuum Circuit Breaker by Amir Hayati Soloot, Ahmad Gholami, Kaveh Niayesh

699

Static and Dynamic Behaviors of an Electrostatically Actuated Micro Beam by M. M. S. Fakhrabadi, B. Dadashzadeh, V. Norouzifard, M. Dadashzadeh

710

Modified Spectrum Sensing and Awareness in Wireless Radio Networks by Pouya Derakhshan Barjoei

718

Simulation of High Operating Temperature InSb/In1-xAlxSb Infrared Photodetector by Mohammad Nadimi, Ali Sadr

723

Optimization of Organic Solar Cells Using the New Unified Model of Electric Field at the Active Layer by M. R. Merad Boudia, A. M. Ferouani, A. Cheknane, B. Benyoucef

727

Modeling and Simulation of Discharges Propagating Over Discontinuously Polluted Insulator Surfaces Under Impulse Voltages by A. Beroual, S. Diampeni, N. H. Malik, A. A. Al-Arainy, E. A. Al-Ammar

732

(continued on Part B)

This volume cannot be sold separately by Part B

1974-9821(201104)4:2;1-V Copyright © 2011 Praise Worthy Prize S.r.l. - All rights reserved

Modelling and Simulations

Modelling and Simulations

Suggest Documents