Generator Side Converter for Five-phase PMSG based Wind Turbine ...

International Journal on Power Engineering and Energy (IJPEE) ISSN Print (2314 – 7318) and Online (2314 – 730X)

Vol. (7) – No. (1) January 2016

Generator Side Converter for Five-phase PMSG based Wind Turbine Generators using Perturbation and Observation technique Abdel-Raheem youssef1, Mahmoud A.Sayed2,M.N.Abdelwhab3, Gaber Shabib4 Electrical Engineering Department, Faculty of Engineering, South Valley University. 3 Electrical Engineering Department, Faculty of Engineering, Suez Canal University. 4 Electrical Engineering Department, Faculty of Engineering, Aswan University. E-mail: [email protected]

1-2

Abstract: This paper presents a control method for maximum power point tracking (MPPT) of a wind energy conversion system (WECS). The WECS is based on five-phase permanent magnet synchronous generator (PMSG) and transmits its electrical power to an AC grid through an AC-DC-AC converter system with IGBT pulse-width modulation (PWM) converters. The generator-side converter use hill-climbing search HCS or Perturbation and Observation P&O method to extract maximum wind power. On the other hand, the grid-side inverter uses vector control to adjust the DC-link voltage and supply active power at unity power factor into grid. A model of directly driven five-phase PMSG- based variable speed WECS is developed and simulated in MATLAB/SIMULINK environment. The effectiveness of proposed control approach is validated through extensive simulation results. Keywords:

Perturbation and Observation, hillclimbing search, PMSG, MPPT 1. Introduction. Multi-phase drive systems have been widely investigated in the literature and their reviews are presented in [1]. Multiphase drive systems are shown to offer several advantages when compared with the three-phase drive system. This is possible due to the advanced development of the modern power electronic converters. The increased penetration of renewable energy generation especially wind energy generation system requires more robust, reliable and high power density generation system. The use of multi-phase generation system for renewable energy is reported recently [2]-[9]. Since the multi-phase machines offer the advantages of high reliability and high power density, they can be ideal choice of wind energy generation system. Permanent magnet generators (PMGs) are commonly used in small and medium-size wind turbine systems for electrical power generation [10,11]. Compared to the wind turbines equipped with induction generators, there are several advantages of using PMGs. First, the PMGs can provide high-efﬁciency and high-reliability power generation, since there is no need for external excitation and no copper losses in the rotor circuit. Second, the high-

power-density PMGs are small in size, which reduces the cost and weight of the wind turbine generator (WTG) system. Moreover, the wind turbine equipped with a directdrive PMG removes the need of using a gearbox. According to the statistical data reported in [12], about 19.4% downtime of WTGs is caused by failures of gearboxes. Without gearboxes, the WTG systems need less maintenance and have a reduced downtime and a higher reliability. The wind energy system extracts the wind energy and converts it to the electrical energy. The output power of wind energy system varies depend on the wind speed. Due the nonlinear characteristic of the wind turbine, it is a challenging task to maintain the maximum power output of the wind turbine for all wind speed conditions. There are extensive researches concerning with the approaches to track the maximum power point of the wind turbine called as MPPT (Maximum Power Point Tracking) control [13– 21]. There are three common MPPT methods , i.e. : a) perturbation and observation (P&O) or hill climbing searching (HCS) [13-17]; b) wind speed measurement (WSM) [18-20]; c) power signal feedback (PSF) [21].In the WSM method, the wind speed and rotor speed are measured and used to determine the optimum tip speed ratio (TSR). In [18], fuzzy logic control is employed to enhance the performance by dealing the parameter insensitivity. This method is simple, but has the drawback as follows: a) It is difficult and expensive to obtain accurate value of wind speed; b) The TSR is dependent on the wind energy system characteristics. In the PSF method tracks the maximum power by reading the current power output to determine the control mechanism to follow the maximum power curve stored in Lookup-table. In [21], fuzzy logic control is developed to overcome the uncertainties of the power curves. The main drawback of this method is that the maximum power curve should be obtained by simulations or experimental test. The P&O method, the rotor speed is perturbed by a small step, and then the power output is observed to adjust the next perturbation on the rotor speed. In [16,17], a constant step is introduced in the perturbation process. A variable step is employed in [13] by considering the slope of power changes. In [14], an adaptive memory algorithm is added to increase the search operation in [15], an advanced hill-climbing searching is proposed to work with different level of turbine inertia by detecting the inverter output power and inverter dc-link voltage. 610

Reference Number: JO-P-0070


This paper studies the performance of grid connected direct-driven five-phase PMSG based wind turbines under continuous operation. The five-phase PMSG connected to the grid through ac-dc-ac back-to-back converter set. The control generator side converters to achieve maximum power point tracking by Perturbation and Observation algorithm. While, the control of the grid side converter is designed to operate at unity power factor and stabilize the dc-link voltage at its nominal value. The dynamics of the system and control action is simulated with detailed model using MATLAB/SIMULINK. In this paper, the results of obtained simulated model are investigated. 2.

Vol. (7) – No. (1) January 2016

Vw is the wind speed (m/sec) Cp is the coefficient of performance. The turbine power coefficients Cp, describes the power extraction efficiency of the wind turbine. It is a nonlinear function of both tip speed ratio λ and the blade pitch angle β. The tip speed ratio λ is a variable expressing the ratio of the linear speed of the tip of blades to rotational speed of wind turbine, as following.

Wind Energy Conversion System WECS.

(2)

Fig.1 shows the wind turbine configuration based five phase PMSG and the power interface back-to-back converter. A back-to-back VSC is used to connect five phase PMSG to the grid. It can be divided in to the machine side converter MSC and the grid side converter GSC. Both have different functions. The first one controls the speed of the rotor to realize MPPT. The second one controls the voltage on the DC-link capacitor voltage, addition to injected only active power to the grid. This paper will focus on the control of the generator side converter, to achieve maximum power point tracking by Perturbation and Observation algorithm.

Where ωm is the mechanical angular velocity of the rotor ( rad/s ).There are many different versions of the fitted equations for Cp made in the previous studies. This paper defines Cp as follows:

(3)

(4) In this paper, due to assumption of the fixed pitch rotor, the pitch angle β is set zero, the relation between and λ when β equal zero degree is shown in Fig.2. It can be noticed that the optimum value of is about 0.48 for λ equals 8.1. Maximum power extraction from wind turbine can be achieved when the turbine operates at the optimum 0.6 . Therefore, it is necessary to control the rotor speed of

Vdc

iabcde

m

iabc

vabc

m*

Pm

the wind turbine at optimum

and λ during wind speed

0.48

3.

Power Coeffient Cp

Fig.1 General control scheme.

Wind turbine model

0.36

Cp-opt

0.24 TSR-opt 0.12

The mechanical power generated by wind turbine can be expressed as.

(1)

Where: is the air density (kg/

)

R is radius of the turbine rotor (m)

0

0

0.9

1.8

2.7

3.6

4.5

5.4 6.3 7.2 Tip Speed Ratio TSR

8.1

9

9.9

10.8

11.7

12.6

Fig.(2). The relation between power coefficient (Cp) and tip speed ratio (λ). Fig.3 shows the relation between the mechanical powers generated by the turbine and the turbine rotor speed at different wind speeds. It is cleared that the maximum power point changes with the variation of wind speed and there is a unique maximum power point at each wind speed. The maximum power extraction can be achieved if the controller 611



can properly follow the optimum curve with variation of wind speed, as shown in Fig.3. 1.4

Vol. (7) – No. (1) January 2016

The mechanical equation of PMSG is given as follows:

(10) Vw1 , Vw2 , Vw3 , Vw4 , Vw5 = wind speed

1.2

Vw5

Where f is the friction coefficient, J the total moment of inertia and

Mechanical Power [pu]

1 Vw4

Pm-opt

0.8

turbine, 5.

0.6

Control of Machine Side Converter MSC

Vw3

The machine side converter is mainly used to control the wind turbine speed in order to extract maximum power from

0.4 Vw2 0.2

wind turbine

Vw1 0

is the mechanical torque produced by wind is electromagnetic torque of PMSG.

0

0.2

0.4

0.6

0.8 1 Rotor Speed [pu]

1.2

1.4

1.6

1.8

operate at maximum power coefficient

. Therefore, it

is necessary to keep the generator rotor speed

Fig 3. The relation among generated mechanical powers and rotor speeds for different wind speeds. 4.

. In this case, the turbine should

Five-phase PMSG model.

The voltage equations of five-phase permanent magnet synchronous generator expressed in the rotor reference frame using an extended park transformation (d1,q1 and d2,q2) axis can be described as follows:

(5)

at an

optimum value of tip speed ratio . The PMSG rotor speed should be adjusted to follow the change of speed and consequently adjust the turbine speed with wind variations .The PMSG speed control can be implemented through generator side converter. This allows the generator to rotate freely depending on wind variation. Fig.(4) shows the schematic diagram of the generator side converter control scheme. In order to understand the speed control concept, PMSG dynamic equation of motion should be studied . The generator motion equation is given based on equation (11) as follows:

(6) (11) (7)

The mechanical rotational speed of PMSG rotor is given by: (12)

(8) Where the (d,q) axis, the (d,q) axis,

and

represent the stator voltages in and

represent the currents in

represent stator resistance , L represent

armature inductance ,

represents the (d,q) axis

inductance, (p is number of pole pairs, represent the turbine rotor angular speed and ψ is the permanent flux linkage). The electrical torque of the five-phase PMSG can be formulated as:

Where,

turbine rotational speed and

gear ratio (if

existed). For gearless PMSG based wind turbine

.

From (11), the speed control of generator can be achieved by the control of electromagnetic torque Te. From(9) the electromagnetic torque can be controlled directly by q-axis current component

, therefore the speed can be

controlled by controlling the

axis current. The reference

axis current component can be formulated, based on eq. (10), as follows. (13)

(9) 612 Reference Number: JO-P-0070


The

(

)-axis

currents

Vol. (7) – No. (1) January 2016

component , or decrementing shaft speed results

is set to zero to minimize the current and resistive cupper losses for a given torque.

, the direction of the shaft speed change must be reversed. The advantages of the P&O method is that it neither requires prior knowledge of maximum wind turbine power at different wind velocities, nor electrical machine parameters [22]. However, the P&O method is suitable for system with small inertia [23], such as solar energy conversion systems with no inertia, or low-power, low-inertia wind turbine systems [24]. For medium- and large-inertia wind turbine systems, the turbine speed cannot follow changes in wind velocity quickly, so the P&O method (without any other controller) will not be able to can't the wind turbine system properly. The flow chart of the P&O or HCS method is illustrated in Fig.6. Fig.4 Machine Side Controller MSC

6.

Maximum power point tracking Technique.

To obtain optimal and , the rotational speed needs to be adjusted as the wind speed changes. Many MPPT algorithms have already been proposed. Among them, the Perturbation and Observation P&O or hill-climb searching HCS method is popularly applied since it is simple, fast and can operate independently from predefined wind turbine characteristic. 7.

Perturbation and Observation P&O Method.

The P&O or HCS method is based on perturbing the turbine shaft speed in small steps and observing the resulting changes in turbine mechanical power [22],[23].

Fig. 5. Turbine power versus shaft speed and principle of the P&O method

The concept and schematic diagram of the P&O method are shown in Fig.5. The details of the P&O method are presented in [22]. To implement the P&O method, one can check the signs of

and

increased in small steps

. The shaft speed is either as long as

,

or decrease in small steps as long as . This is continued until the maximum power point is reached, i.e,

. If incremented the shaft speed results in Fig.6. Flow chart of P&O algorithm [25] 613



8. Grid-side converter control The objective of grid side converter control is to adjusts the DC link capacitor voltage at its reference value, and adjusts the active power and reactive power delivered to grid while wind changing. In grid side converter, a PI controller is used to stabilize the DC voltage reference value. The dynamic model of the grid connection, in reference frame rotating synchronously with the grid voltage, is given as follows [26]

Vol. (7) – No. (1) January 2016

system by controlling the active and reactive power delivered to the electrical grid. Further, unity power factor flow (zero reactive power exchange) could be easily obtained, unless the grid operators require different reactive power settings. Vdc

Vdc*

vd

id

V DC

id*

Vdc

iq

− L

(20) id

Q* 2 3vd

 LL 

i q*

id iq

vq

iq

(21)



Where L and R are the grid inductance and resistance, vd

respectively. are the d-q axis inverter voltage components. If the reference frame is oriented along the supply voltage, the grid vector voltage is:

vq  

Fig.5 Grid side converter control (22) 9.

Simulation results and discussion

Active and reactive power can be expressed as follows [26].

(23)

(24) It could be seen from above equations that we can control the active and reactive powers by respectively changing the d and q-current components. Also in order to transfer all the active power generated by the wind turbine the dc-link voltage must remain constant [27].

(25) Where subscript ‘g‘ refers to the grid and ‘t‘ refers to the wind turbine. Based on (25), if the two powers (the wind turbine power and the grid power) are equal there will be no change in the dc-link voltage. The grid side converter control scheme contains two cascaded loops. The inner loop controls the network currents and the outer loop controls the DC-link voltage. The inner loop regulates the power flow of the

To examine the performance of the implemented control scheme, two case studies considering different wind speed variations have been conducted; the parameter of the system is defined in the appendix. The proposed control scheme for the five-phase PMSG based variable speed WECS has been carried out using MATLAB/Simulink at different values of wind speed in order to track the maximum power point of the wind turbine called as MPPT (Maximum Power Point Tracking) control at the generator side in addition to the unity power factor at the grid side. Step Change

9.1

wind Speed : Fig.8 shows the actual wind speed, the reference and actual rotor speed. According to wind turbine characteristic; when wind speed varies the controller adjust PMSG rotor speed to follow the same value of . It is clear that the actual and reference rotor speed agree well and the error between them is very small. Fig.9 shows power coefficient, tip speed ratio, the mechanical and electromagnetic torque of the PMSG and mechanical power from wind turbine. The power coefficient and tip speed ratio are almost constant following their optimal values for the whole simulating period. This in-turn proves that the MPPT has been achieved. The mechanical and electromagnetic torques of five-phase PMSG are varying as steps with different values -40, -60 614



wind speed [m/sec]

12 11 10 9

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

rotor speed [rpm]

600 500 400 300 200

Ref. speed Act. speed 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Time [sec]

power coefficient Cp

Fig.8 wind speed and rotor speed response

0.96

0.48

0

0

0.1

0.2

0.3

0.4

0 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.5

0.6

0.7

0.8

0.9

1

Tip speed ratio TSR

12.15 8.1 4.05

Time [sec]

Fig.9 power coefficient and tip speed ratio response

Power Factor

1 0.5 0 -0.5 -1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

6000 Grid power

and -80 N.m according to the step change in wind speed with values 8,10 and 12m/sec, respectively. And the actual and maximum power agrees well and the error between them is very small. Fig.10 shows five-phase current of PMSG at each value of wind speed. It is clear that generator terminal currents change according to the change in wind speed. Fig.11 shows grid voltage and current, the dc-link capacitor voltage, d-axis grid current, q-axis current, power factor, and injected active and reactive power. It is clear that sinusoidal grid voltage and current are in-phase for the whole simulating period to achieve unity power factor. The reference and actual dc-link voltage coincide well, the difference between actual and reference d-axis current is very small, in order to achieve injected active power into grid, the actual and reference q-axis current at grid side is always controlled to be zero to achieve unity power factor. The injected reactive power is zero during the whole simulation time, whereas the injected active power has a step change according to the change in the wind speed.

Vol. (7) – No. (1) January 2016

4000 P [w] Q [var]

2000 0

-2000

0

0.1

9.2

0.2

0.3

0.4

0.5 0.6 Time [sec]

0.7

0.8

0.9

1

Fig.12 power factor and grid power Random Change Wind Speed

The effectiveness of the proposed control techniques has been investigated with Random wind speed variation. Fig.12 shows the actual wind speed, the reference and actual rotor speed. It is clear that the turbine shaft speed is controlled to track its reference value. Achievement of MPPT is known, Fig.13 shows power coefficient and tip speed ratio, the mechanical and electromagnetic torque of the PMSG, mechanical power from wind turbine. The power coefficient which is almost constant value at (0.48) and the change of the tip speed ratio that varies in a relatively small range around the optimum value of (8.1), and the mechanical and electromagnetic torques of PMSG coincide well and error between maximum and actual mechanical power very small. Fig.14 shows five-phase current of PMSG at each value of wind speed. It is clear that generator terminal currents change according to the change in wind speed. Fig.15 shows grid voltage and current, the dc-link capacitor voltage, daxis grid current,q-axis current, power factor and injected active and reactive power. It is clear that sinusoidal grid voltage and current are in-phase for the whole simulating period to achieve unity power factor. The reference and actual dc-link voltage coincide well, the difference between actual and reference d-axis current is very small, in order to achieve injected active power into grid, the actual and reference q-axis current at grid side is always controlled to be zero to achieve unity power factor. The injected reactive power is zero during the whole simulation time, whereas the injected active power has a step change according to the change in the wind speed. According to the simulation results of the system at step change and random change wind speed it is cleared that, the MSC has the ability to control the PMSG to extract the maximum power based on Perturb and Observe algorithm speed control technique, and the GSC has the ability to achieve unity power factor at the grid side. 615



Vol. (7) – No. (1) January 2016

wind speed [m/sec]

12 11.5

1

10.5

0.5

10

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

power factor

11

1

0 -0.5

rotor speed [rpm]

600 Ref. value Act. value

-1

500

Grid power

400

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

4000 P[watt]

2000

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Time [sec]

Q[var] 0

Fig.13 wind speed and rotor speed response -2000 power coefficient Cp

0.96

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Time [sec]

Fig.17 power factor and grid power 0.48

0

0

0.1

0.2

0.3

0.4

0 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.5 0.6 Time [sec]

0.7

0.8

0.9

1

10. CONCLUSION Control strategy for a variable speed wind energy conversion system has been presented in this paper along with a compressive analysis and simulation using MATLAB/SIMULINK. From the simulation results, the maximum power extraction control algorithm at the generator side converter has been implemented based on estimating optimum rotor speed, using the Perturbation and Observation algorithm to adjust the generator rotational speed at optimum value through hysteresis current controller for extraction maximum power from the available wind power. Additionally, a simple vector current controller has been employed on the grid side converter to get unity power factor and to keep dc-link voltage at its nominal value. Simulation results proved that the proposed control scheme has a great capability to obtain unity power factor and to keep dc-link voltage at constant value at the grid side converter and to achieve maximum power point tracking from the available wind power.

12.15 tip speed ratio TSR

0

8.1 4.05

mechanical power [watt]

Fig.14 power coefficient and tip speed ratio response 4000

3500 max. power 3000

act. power 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.31

0.32

0.33

0.5 Time [sec]

0.6

0.7

0.8

0.9

1

0.9

1

current [A]

20 20 0

0 -20 0.3

0.34

-20 0

0.1

0.2

0.3

0.4

0.8

11.

Fig.15 Mechanical power and generators currents

1.1 Specification of wind turbine

500

phase voltage

20*phase current

The

Va & Ia

500 0

0 -500 0.3

-500

0

0.1

0.2

0.3

0.4

0.32 0.5

coefficients

0.34 0.6

0.7

0.8

0.9

1

C1 to C6 blade radius

1000 Vdc [V]

Appendix

Air density 500

0

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Ref. value Act. value 0.8 0.9 1

Optimal tip speed ratio Maximum power Coefficient

Time [sec]

d-axis current [A]

10

1.2 Five-phase PMSG parameters

5 0 -5

Ref. value Act. value 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

q-axis current [A]

Reference10Number: JO-P-0070 0 -10 -20

Ref. value

1

616


Pole pairs number Stator resistance Direct-axis inductance quadrature-axis inductance Moment of inertia Flux linkage 1.3 DC bus and gird parameters

dc-link voltage Capacitor of the dc-link Grid frequency Grid resistance Grid inductance 1.4 Machine side control

Vol. (7) – No. (1) January 2016

pp1604-1611,2000. [4] Basic D, Zhu JZ, Boardman G. "Transient performance

study of a brushless doubly fed twin stator induction generator". IEEE Transactions on Energy Conversion. vol.18,no.3, pp 400-408,2000. [5] Levy D., ""Analysis of a double-stator induction

machine used for a variable speed/constant-frequency small-scale hydro/wind electric power generator"," Electric Power Systems Research, pp. 205-223, 1986. [6] Singh GK, Yadav KB, Saini RP. "Modeling and

analysis of multi-phase (six phase) self-excited induction generator". In: Proceedings on IEEE conference of the eighth international conference on electrical machines and systems, ICEMS’05, 2005 vol. 3, pp1922-1927. [7] Singh GK, Yadav KB, Saini RP. "Analysis of a saturated multi-phase (six-phase) self-excited induction generator". International Journal of Emerging Electric Power Systems , vol.7, no.2,pp1-23,2006. [8] Singh GK. ,"Modeling and experimental analysis of a self-excited six-phase induction generator for standalone renewable energy generation". Renewable Energy, vol. 33, pp1605-1621,2008. [9] Singh GK, Yadav KB, Saini RP. "Capacitive self-

1.5 Grid side control

1.1 1.2 1.3 1.4

excitation in six-phase induction generator for small hydro power- an experimental investigation". Proceedings of IEEE conference on power electronics, drives and energy systems for industrial growth. New Delhi. pp1-6,2006. [10] W.Qiao,L.Qu,

and R.G.Harely" Control of IPM synchronous generator for maximum wind power generation considering magnetic saturation,"," IEEE Trans. Ind. Appl.,, vol. 45, no. 3, pp. 1095-1105, May/june 2009.

[11] Y.chen,P.Pillay, and A.khan, " PM wind generator

12. References [1] E. Levi, “Multiphase electric machine for variable speed applications,”. IEEE Trans. Ind. Electron., vol. 55, no. 5, pp. 1893–1909, May 2008. [2] G.K. Singh, A. S. Kumar, and R.P. Saini, "Selection of

capacitance for six-phase self-excited induction generator for stand-alone renewable energy generation " Energy, vol. 35, pp. 3273-3283, 2010. [3] Ojo O, Davidson IE. "PWM-VSI inverter-assisted

stand-alone dual stator winding induction generator". IEEE Transactions on Energy Conversion. vol.36, no.6,

topologies,"," IEEE Trans. Energy Convers., vol. 45, no. 6, pp. 1619-1105, Nov./Dec.2005. [12] J.Ribrant and L.M.Bertling, "" Surevy of failure in

wind power systems with focous on swedish wind power plants during 1997-2005,"," IEEE Trans.Energy Covers.,, vol. 22, no. 1, pp. 167-173, Mar2007. [13] E. Koutroulis and K. Kalaitzakis, “Design of a

Maximum Power Tracking System for Wind-EnergyConversion Applications”, IEEE Transactions on Industrial Electronics, Vol. 53, No. 2, pp. 486-494, April 2006.

617 Reference Number: JO-P-0070


[14] J.Hui and A.Bakhshi, "A Fast and Effective Control

Algorithm for Maximum Power Point Tracking in Wind Energy Systems," in Proceedings of the World Wind Energy , 2008. [15] Q. Wang, L. Chang, “An Intelligent Maximum Power

Extraction Algorithm for Inverter-Based Variable Speed Wind Turbine Systems”, IEEE Transactions on Power Electronics, Vol. 19, No. 5, pp. 1242- 1249, Sept. 2004. [16] G. Moor, J. Beukes, “Maximum Power Point Tracking

methods for small scale Wind Turbines”, in Proceedings of Southern African Telecommunication Networks and Applications Conference (SATNAC) 2003. [17] H. Gitano, S. Taib, M. Khdeir, “Design and Testing of a Low Cost Peak-Power Tracking Controller for a Fixed Blade 1.2 kVA Wind Turbine”, Electrical Power Quality and Utilisation Journal, Vol. XIV, No. 1, pp. 95-101, 2008. [18] E. Adzic, Z. Ivanovic, M. Adzic, V. Katic, “Maximum Power Search in Wind Turbine Based on Fuzzy Logic Control”, Acta Polytechnica Hungaria, Vol. 6, No. 1, pp 131-148, 2009.

Vol. (7) – No. (1) January 2016

Electron., vol. 19, no. 5, pp. 1242–1249, Sep. 2004. [24] E. Koutroulis, K. Kalaitzakis, and N. C. Voulgaris,

“Development of a microcontroller-based, photovoltaic maximum power point tracking control system,” IEEE Trans. Power Electron., vol. 16, no. 1, pp. 46–54, Jan. 2001. [25] Xing-Peng Li, Wen-Lu Fu, " A Fuzzy Logical MPPT

Control Strategy for PMSG Wind Generation Systems" Journal of Electrical Science and Technology, Vol,11,No.1, March 2013 [26] Chinchilia.M, Arnaltes S, Burgos J. Control of

permanent-magnet generator applied to variable-speed wind-energy systems connected to the grid. IEEE Trans. Energy Convers,Vol.21, No.1, 2006. [27] Muyeen SM, Takahashi R, Murata T, Tamura J. A

variable speed wind turbine control strategy to meet wind farm grid code requirements. IEEE Trans. Power Syst. Vol.25, No.1, 2010.

[19] A.M. Eltamaly, "Modeling of Wind Turbine Driving

Permanent Magnet Generator with Maximum Power Point Tracking System" Journal of King Saud University, Engineering Science (2), Vol. 19, pp.223237, 2007. [20] A.youssef,

M.A.Sayed, M.N.Abdelwhab and F.A.khalifa " Control Scheme of Five-Phase PMSG Based Wind Turbinefor Utility Network Connection" in Proceedings of the 16th International Middle East Power Systems Conference , Cairo,Dec 2014

[21] M. Azouz, A. Shaltout, M.A.L. Elshafei, “Fuzzy Logic

Control of Wind Energy Systems”, in Proceedings of the 14th International Middle East Power Systems Conference, pp. 935-940, Dec. 2010. [22] S.M. Barakati,M.Kazerani, andX. Chen, “Anewwind

turbine generation system based on matrix converter,” in Proc. IEEE PES Gen. Meet., 2005, pp. 2083–2089 [23] Q. Wang and L. Chang, “An intelligent maximum

power extraction algorithm for inverter-based variable speed wind turbine systems,” IEEE Trans. Power

618 Reference Number: JO-P-0070