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Fuzzy logic control of wind energy conversion system Hassan M. Farh and Ali M. Eltamaly Citation: J. Renewable Sustainable Energy 5, 023125 (2013); doi: 10.1063/1.4798739 View online: http://dx.doi.org/10.1063/1.4798739 View Table of Contents: http://jrse.aip.org/resource/1/JRSEBH/v5/i2 Published by the American Institute of Physics.

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JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY 5, 023125 (2013)

Fuzzy logic control of wind energy conversion system Hassan M. Farh1,a) and Ali M. Eltamaly2,a) 1

Department of Electrical Engineering, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia 2 Sustainable Energy Technologies Center, Department of Electrical Engineering, College of Engineering, King Saud university, Riyadh 11421, Saudi Arabia (Received 4 November 2012; accepted 11 March 2013; published online 3 April 2013)

This paper proposes a variable speed control scheme of grid-connected wind energy conversion system, WECS, using permanent magnet synchronous generator. The control algorithm tracking the maximum power for wind speeds below rated speed of wind turbines (WTs) and ensure the power will not exceed the rated power for wind speeds higher than the rated speed of wind turbine. The control algorithm employed fuzzy logic controller (FLC) to effectively do this job. The WT is connected to the grid via back-to-back pulse width modulationvoltage source converter (PWM-VSC). Two effective computer simulation software packages (PSIM and SIMULINK) have been used to carry out the simulation effectively where PSIM contains the power circuit of the WECS and MATLAB/SIMULINK contains the control circuit of the system. The control system has two controllers for generator side and grid side converters. The main function of the generator side controller is to track the maximum power from wind through controlling the rotational speed of the turbine using FLC. In the grid side converter, active and reactive power control has been achieved by C 2013 American controlling d-axis and q-axis current components, respectively. V Institute of Physics. [http://dx.doi.org/10.1063/1.4798739]

I. INTRODUCTION

Wind is one of the most promising renewable energy resources for producing electricity due to its cost competitiveness compared to other conventional types of energy resources. It takes a particular place to be the most suitable renewable energy resources for electricity production. It isn’t harmful to the environment and it is an abundant resource available in nature. Hence, wind power could be utilized by mechanically converting it to electrical power using wind turbines (WTs). Various WT concepts have a quick development of wind power technologies and significant growth of wind power capacity during last two decades. Variable speed operation and direct drive (DD) WTs have been the modern developments in the technology of wind energy conversion system (WECS). Variable-speed operation has many advantages over fixed-speed generation such as increased energy capture, operation at MPPT over a wide range of wind speeds, high power quality, reduced mechanical stresses, and aerodynamic noise improved system reliability, and it can provide (10%–15% higher output power and has less mechanical stresses when compared with the operation at a fixed speed.1,2 WTs can be classified, according to the type of drive train, into DD and gear drive (GD). The GD type uses a gear box, squirrel cage induction generator, SCIG, and classified as stall, active stall, and pitch control WT, and work in constant speed applications. The variable speed WT uses doubly fed induction generator, DFIG, especially in high power WTs. The gearless DD and WTs have been used with small and medium size WTs employing permanent magnet synchronous generator (PMSG) with higher numbers of poles to eliminate the need for gearbox a)

Authors to whom correspondence should be addressed. Electronic addresses: [email protected] (Tel.: þ966553334130) and [email protected] (Tel.: þ966500507630). Fax: þ96614676757.

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which can be translated to higher efficiency. PMSG appears more and more attractive, because of the advantages of permanent magnet, PM machines over electrically excited machines such as its higher efficiency, higher energy yield, no additional power supply for the magnet field excitation, and higher reliability due to the absence of mechanical components such as slip rings. In addition, the performance of PM materials is improving, and the cost is decreasing in recent years. Therefore, these advantages make direct-drive PM wind turbine generator systems more attractive in application of small and medium-scale wind turbines.1,3,4 Robust controller has been developed in many literatures5–15 to track the maximum power available in the wind. They include tip speed ratio, TSR,5,13 power signal feedback, PSF,8,14 and the hill-climb searching, HCS11,12 methods. The TSR control method regulates the rotational speed of the generator to maintain an optimal TSR at which power extracted is maximum.13 For TSR calculation, both the wind speed and turbine speed need to be measured, and the optimal TSR must be given to the controller. The first barrier to implement TSR control is the wind speed measurement, which adds to system cost and presents difficulties in practical implementations. The second barrier is the need to obtain the optimal value of TSR; this value is different from one system to another. This depends on the turbine-generator characteristics that result in custom-designed control software tailored for individual wind turbines.14 In PSF control,8,14 it is required to have the knowledge of the wind turbine’s maximum power curve, and track this curve through its control mechanisms. The power curves need to be obtained via simulations or off-line experiment on individual wind turbines or from the datasheet of WT which makes it difficult to implement with accuracy in practical applications.7,8,15 The HCS technique does not require the data of wind, generator speeds and the turbine characteristics. But, this method works well only for very small wind turbine inertia. For large inertia wind turbines, the system output power is interlaced with the turbine mechanical power and rate of change in the mechanically stored energy, which often renders the HCS method ineffective.11,12 On the other hand, different algorithms have been used for maximum power extraction from WT in addition to the three methods mentioned above. For example, Oghafy and Nikkhajoei1 presents an algorithm for maximum power extraction and reactive power control of an inverter through the power angle, d of the inverter terminal voltage and the modulation index, ma based variable-speed WT without wind speed sensor. Chinchilla et al.16 present an algorithm for MPPT via controlling the generator torque through q-axis current and, hence, controlling the generator speed with variation of the wind speed. These techniques are used for a decoupled control of the active and reactive power from the WT through q-axis and d-axis current, respectively. Also, Song et al.17 present a decoupled control of the active and reactive power from the WT, independently through q-axis and d-axis current but maximum power point operation of the WECS has been produced through regulating the input dc current of the dc/dc boost converter to follow the optimized current reference. Eltamaly18 presents an algorithm for MPPT through directly adjusting duty ratio of the dc/dc boost converter and modulation index of the PWM-VSC. Hussein et al.19 present MPPT control algorithm based on measuring the dc-link voltage and current of the uncontrolled rectifier to attain the maximum available power from wind. Finally, MPPT control based on fuzzy logic controller (FLC) has been presented in (Pati and Sahu; Yao and Liu; Abo-Khalil and Seok).20–22 The function of FLC is to track the generator speed with the reference speed for maximum power extraction at variable speeds. In this study, the WECS is designed as PMSG connected to the grid via a back-to-back PWM-VSC as shown in Fig. 1. MPPT control algorithm has been introduced using FLC to regulate the rotational speed to force the PMSG to work around its maximum power point in speeds below rated speeds and to produce the rated power in wind speed higher than the rated wind speed of the WT. Indirect vector-controlled PMSG system has been used for this purpose. The input to FLC is two real time measurements which are the change of output power and rotational speed between two consequent iterations (DPm and Dxm). The output from FLC is the required change in the rotational speed Dxm*. The detailed logic behind the new proposed technique is explained in detail in the following sections. Two effective computer simulation software packages (PSIM and SIMULINK) have been integrated to carry out the simulation effectively. PSIM contains the power circuit of the WECS and MATLAB/SIMULINK contains

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FIG. 1. Schematic diagram of the overall system.

the control circuit of the system. The idea behind integrating these two different software packages is the effective tools provided with PSIM for power circuit and the effective tools in SIMULINK for control circuit and FLC. This integration between PSIM and SIMULINK has never been used in MPPT of wind energy systems in the literature and this approach will help researchers to develop many other control techniques in this area. The interconnection between PSIM and SIMULINK makes the simulation process easier, efficient, fast response, and powerful. In the grid side converter, active and reactive power control has been achieved by controlling d-axis and q-axis grid current components, respectively. The q-axis grid current is controlled to be zero for unity power factor and the d-axis grid current is controlled to deliver the power flowing from the dc-link to the grid. II. WIND ENERGY CONVERSION SYSTEM DESCRIPTION

Fig. 2 shows a co-simulation (PSIM/SIMULINK) program for interconnecting WECS to electric utility. The PSIM program contains the power circuit of the WECS and MATLAB/ SIMULINK program contains the control of this system. The interconnection between PSIM and MATLAB/SIMULINK has been done via the SimCoupler block. The basic topology of the power circuit, which has PMSG driven wind turbine connected to the utility grid through the ac-dc-ac conversion system, is shown in Fig. 1. The PMSG is connected to the grid through back-toback bidirectional PWM voltage source converters VSC. The generator side converter is connected to the grid side converter through dc-link capacitor. The control of the overall system has been done through the generator side converter and the grid side converter. MPPT algorithm has been achieved through controlling the generator side converter using FLC. The

FIG. 2. Co-simulation block of wind energy system interfaced to electric utility.

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grid-side converter controller maintains the dc-link voltage at the desired value by exporting active power to the grid and it controls the reactive power exchange with the grid. A. Wind turbine model

Wind turbine converts the wind power to a mechanical power. This mechanical power generated by wind turbine at the shaft of the generator can be expressed as 1 Pm ¼ CP ðk; bÞ q A u3 ; 2

(1)

where q is the air density (typically 1.225 kg/m3), b is the pitch angle (in degree), A is the area swept by the rotor blades (in m2); u is the wind speed (in m/s), and Cp(k, b) is the windturbine power coefficient (dimensionless). The turbine power coefficient, Cp(k, b), describes the power extraction efficiency of the wind turbine and is defined as the ratio between the mechanical power available at the turbine shaft and the power available in wind. A generic equation is used to model Cp(k, b). This equation, based on the modeling turbine characteristics, is shown as follows:23 

 1 21 CP ðk; bÞ ¼ 0:5176 116   0:4b  5 e ki þ 0:0068k; ki with

(2)

1 1 0:035  ¼ ; ki k þ 0:08b 1 þ b3

where CP is a nonlinear function of both tip speed ratio, k and the blade pitch angle, b. k is the ratio of the turbine tip speed, xm*R to the wind speed, u. k is defined as24 k¼

xm  R ; u

(3)

where xm is the rotational speed and R is the turbine blade radius, respectively.For a fixed pitch angle, b, CP becomes a nonlinear function of k only. According to Eq. (3), there is a relation between k and xm. Hence, at a certain u, the power is maximized at a certain xm called optimum rotational speed, xopt. This speed corresponds to optimum tip speed ratio, kopt.15 The value of the tip speed ratio is constant for all maximum power points. So, to extract maximum power at variable wind speed, the WT should always operate at kopt in speeds below the rated speed. This occurs by controlling the rotational speed of the WT to be equal to the optimum rotational speed. Fig. 3 shows that the mechanical power generated by WT at the shaft of the generator as a function of xm. These curves have been extracted from PSIM support team for the wind turbine used in this paper. It is clear from this figure that for each wind speed the mechanical output power is maximized at particular rotational speed, xopt, as shown in Fig. 3. B. PMSG model

The generator is modeled by the following voltage equations in the rotor reference frame (dq-axes):25 dksd  xr ksq dt dksq þ xr ksd ; vsq ¼ Rs isq þ dt vsd ¼ Rs isd þ

(4)

where ksq and ksd are the stator flux linkages in the direct and quadrature axis of rotor which in the absence of damper circuits can be expressed in terms of the stator currents and the magnetic flux as follows:25

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FIG. 3. Typical output power characteristics.

ksd ¼ Ls isd þ wF ksq ¼ Ls isq ;

(5)

where wF is the flux of the permanent magnets. The electrical torque, Te, of the three-phase generator can be calculated as follows:25,26 3 Te ¼ P ½ksd isq  ksq isd ; 2

(6)

where P is the number of pole pairs. For a non-salient-pole machine, the stator inductances Lsd and Lsq are approximately equal.25 This means that the direct-axis current isd does not contribute to the electrical torque. Our concept is to keep isd to zero in order to obtain maximal torque with minimum current. Then, the electromagnetic torque results, 3 Te ¼ P wF isq ¼ Kc isq ; 2

(7)

where isq is the quadrature-axis component of the stator-current space vector expressed in the rotor reference frame and Kc is called the torque constant and represents the proportional coefficient between Te and isq. III. CONTROL OF THE GENERATOR SIDE CONVERTER

The generator side controller controls the rotational speed to produce the maximum output power via controlling the electromagnetic torque according to Eq. (7), where the indirect vector control is used. The proposed control logic of the generator side converter is shown in Fig. 4. The speed loop will generate the q-axis current component to control the generator torque and speed at different wind speed via estimating the references value of ia and ib as shown in Fig. 4. The torque control can be achieved through the control of the isq current as shown in Eq. (7). Fig. 5 shows the stator and rotor current space phasors and the excitation flux of the PMSG.25 The quadrature stator current, isq, can be controlled through the rotor reference frame (a, b axes) as shown in Fig. 5. So, the references value of ia and ib can be estimated easily * and the rotor angle, ⍜r. Initially, to find the rotor angle, ⍜r, the relafrom the amplitude of isq tionship between the electrical angular speed, xr, and the rotor mechanical speed (rad/s), xm may be expressed as

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FIG. 4. Control block diagram of the generator side converter.

xr ¼

P xm : 2

(8)

So, the rotor angle, ⍜r, can be estimated by integrating of the electrical angular speed, xr. The input to the speed control is the actual and reference rotor mechanical speed (rad/s) and the output is the (a, b) reference current components. The actual values of the (a, b) current components are estimated using Clark’s transformation to the three phase current of PMSG. The FLC can be used to find the reference speed along which tracks the maximum power point. IV. FUZZY LOGIC CONTROLLER FOR MPPT

At certain wind speed, the power is maximized at a certain x called optimum rotational speed, xopt. This speed corresponds to optimum tip speed ratio, kopt.15 So, to extract maximum

FIG. 5. The stator and rotor current space phasors and the excitation flux of the PMSG.

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power at variable wind speed, the turbine should always operate at kopt. This occurs by controlling the rotational speed of the turbine. Controlling of the turbine to operate at optimum rotational speed can be done using the FLC. Each wind turbine has one value of kopt at variable speed but xopt changes from a certain wind speed to another. From Eq. (3), the relation between xopt and wind speed, u, for constants R and kopt can be obtained as follows: xopt ¼

kopt u: R

(9)

From Eq. (9), the relation between the optimum rotational speed and wind speed is linear. FLC is used to search the rotational speed reference which tracks the maximum power point at variable wind speeds. The block diagram of FLC is shown in Fig. 6. Two variables are used as input to FLC (DPm and Dxm) and the output is (Dxm*). Membership functions are shown in Fig. 7. Triangular symmetrical membership functions are suitable for the input and output, which give more sensitivity especially as variables approach to zero value. FLC does not require any detailed mathematical model of the system and its operation is governed simply by a set of rules. The principle of the FLC is to perturb the reference speed, xm* and to observe the corresponding change of power, DPm. If the output power increases with the last speed increment, the searching process continues in the same direction. On the other hand, if the speed increment reduces the output power, the direction of the searching is reversed. The FLC is efficient to track the maximum power point, especially in case of frequently changing wind conditions.22 The input and output membership functions have been shown in Fig. 7. The control rule for input and output variables are listed in Table I. Dxm is varied from 0.15 rad/s to 0.15 rad/s and DPm is varied from 30 W to 30 W. The membership definitions are used as follows: N (negative), NB (negative big), NS (negative small), ZE (zero), P (positive), PS (positive small), and PB (positive big).

V. CONTROL OF THE GRID SIDE CONVERTER

The power flow of the grid-side converter is controlled in order to maintain the dc-link voltage at reference value, 600 V. Since increasing the output power than the input power to dc-link capacitor causes a decrease of the dc-link voltage and vise versa, the output power will be regulated to keep dc-link voltage approximately constant. The dc-link voltage has been maintained and the reactive power flowing into the grid has been controlled at zero value. This has been done via controlling the grid side converter currents using the d-q vector control approach. By aligning the d-axis of the reference frame along with the grid voltage position vq ¼ 0 and then the active and reactive power can be obtained from the following equations:

FIG. 6. Input and output of fuzzy controller.

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FIG. 7. Membership functions of FLC.

3 Ps ¼ vd id ; 2

(10)

3 Qs ¼ vd iq : 2

(11)

Active and reactive power control has been achieved by controlling d-axis and q-axis current components, respectively, using two control loops. An outer dc-link voltage control loop is used to set the d-axis current reference for active power control. The inner control loop controls the reactive power by setting the q-axis current reference to zero value for unity power factor as shown in Eq. (11). The control block diagram of the grid side converter is shown in Fig. 8. VI. SIMULATION RESULTS

Two effective computer simulation software packages (PSIM and SIMULINK) have been integrated together to carry out the simulation of the modified system effectively. The model of WECS (power circuit) in PSIM contains the WT connected to the utility grid through backto-back bidirectional PWM converter. The control of whole system in SIMULINK contains the generator side controller and the grid side controller. The idea behind integrating these two different software packages is that PSIM is a very effective and a simple tool for modeling the power electronics circuits whereas SIMULINK is a very effective and a simple tool for modeling the control system especially for FLC and mathematical manipulation. The wind turbine

TABLE I. Rules of FLC. DPm/Dxm

NB

NS

ZE

PS

PB

N

PB

PS

ZE

NS

NB

ZE P

NM NB

NS NS

ZE ZE

PS PM

PM PB

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characteristics and the parameters of the PMSG are listed in the Appendix. The generator can be directly controlled by the generator side controller to track the maximum power available from the WT. To extract maximum power at variable wind speed, the turbine should always operate at kopt. This occurs by controlling the rotational speed of the WT. So, it always operates at the optimum rotational speed, xopt, for different wind speed. The fuzzy logic controller is used to search the optimum rotational speed which tracks the maximum power point at variable wind speeds. The proposed system has been compared with the system shown in Ref. 22 to validate the results. The whole simulation results of the proposed system and results from Ref. 22 are shown in Fig. 9 in left hand side (LHS) and right hand side (RHS), respectively. The input wind speeds have been assumed to be saw-tooth as the wind speed in Ref. 22 for easy comparison. Figs. 9(a1) and 9(a2) show the input wind speed variation for the proposed system and the system shown in Ref. 22, respectively. Reference rotational speed for the proposed system and the system shown in Ref. 22 are shown in Figs. 9(b1) and 9(b2), respectively. At a certain wind speed, the actual and reference rotational speed have been estimated and this agrees with the power characteristic of the wind turbine shown later in Fig. 3 (i.e., the WT always operates at the optimum rotational speed which can be obtained from the output of FLC). Figs. 9(c1) and 9(c2) show the variation of the actual rotational speed for the proposed system and the system shown in Ref. 22, respectively. It is clear from Figs. 9(c1) and 9(c2) that the rotational speed variation of the proposed system follows the reference rotational speed strictly without noise in the waveform. Figs. 9(d1) and 9(d2) show the active power extraction from the proposed system and the system shown in Ref. 22, respectively. It is clear from this figure that the output power generated from the proposed system is higher and follows strictly the maximum power of

FIG. 8. Control block diagram of grid-side converter.

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Fig. 3 than the output power from the system shown in Ref. 22. The reference value of the reactive power has been set at zero value. Figs. 9(e1) and 9(e2) show the waveform of the actual reactive power for the proposed system and the system shown in Ref. 22, respectively. It is clear from this figure that the reactive power obtained from the proposed system is strictly following the reference value without spikes more than the one obtained from the system shown in Ref. 22. Also, the dc-link voltage has been set at 600 V in both systems. The actual dc-link voltage waveforms are shown in Figs. 9(f1) and 9(f2) for the proposed system and the system shown in Ref. 22, respectively. It is clear that the dc-link voltage obtained from the proposed system is following the reference value strictly more than the one obtained from the system shown in Ref. 22. It is clear from the above discussion that the proposed system in this paper is superior and showed a stable operation and followed strictly the reference values of rotational speed, reactive power, and the dc-link voltage. Also, it is clear from the simulation results of the proposed system that the maximum power has been extracted strictly as the maximum power obtained from Fig. 3.

FIG. 9. Different simulation waveforms of prposed system in LHS compared to the same waveforms obtained from Ref. 22 in RHS: (a) Wind speed variation, (b) reference rotational speed (rad/s), (c) actual rotational speed (rad/s), (d) active power (W), (e) reactive power (Var), and (f) dc-link volltage (V).

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FIG. 9. (Continued).

VII. CONCLUSION

A co-simulation (PSIM/SIMULINK) program has been proposed for WECS where PSIM contains the power circuit of the WECS and MATLAB/SIMULINK contains the control circuit of the WECS. The integration between PSIM and SIMULINK is the first time to be used in modeling WECS which help researchers in modifying the modeling of WECS in the future. The interconnection between PSIM and SIMULINK makes the simulation process easier, efficient, fast response and powerful. The WT is connected to the grid via back-to-back PWM-VSC. The generator side controller and the grid side controller have been done in SIMULINK. The main function of the generator side controller is to track the maximum power from wind through controlling the rotational speed of the turbine using fuzzy logic controller. The fuzzy logic algorithm for the maximum output power of the grid-connected wind power generation system using a PMSG has been proposed and implemented above. The PMSG was controlled in indirect-vector field oriented control method and its speed reference was determined using fuzzy logic controller. In the grid side converter, active and reactive power control has been achieved by controlling d-axis and q-axis grid current components, respectively. The q-axis grid current is controlled to be zero for unity power factor and the d-axis grid current is controlled to deliver the

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power flowing from the dc-link to the grid. The simulation results prove the superiority of FLC and the whole control system. ACKNOWLEDGMENTS

The authors acknowledge the College of Engineering Research Center and Deanship of Scientific Research at King Saud University in Riyadh for the financial support to carry out the research work reported in this paper. APPENDIX: PARAMETERS OF WT MODEL AND PMSG TABLE II. Parameters of wind turbine model and PMSG. Wind turbine Nominal output power Wind speed input Base wind speed

PMSG 19 kW

Rs (stator resistance)

1m

8:12 m/s (saw tooth) 10 m/s

Ld (d-axis inductance) Lq (q-axis inductance)

1m 1m

Base rotational speeds

190 rpm

No. of poles P

30

Moment of inertia Blade pitch angle input

1m 0

Moment of inertia Mech. time constant

100 m 1

1

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