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SOP TRANSACTIONS ON POWER TRANSMISSION AND SMART GRIDVolume 1, Number 1, December 2014

SOP TRANSACTIONS ON POWER TRANSMISSION AND SMART GRID

Comparison of FLC-GA-PI Methods toSmooth the Output Power of Wind Turbinein the Grid Connected ModeMaziar Izadbakhsh*, Alireza Rezvani, Majid Gandomkar, Saeed VafaeiDepartment of Electrical Engineering, Saveh Branch, Islamic Azad University, Saveh, Iran

*Corresponding author: [email protected]

Abstract:Wind Turbines (WTs) have attracted considerable interest as a renewable energy source due todepleting fossil fuel reserves and environmental concerns as a consequence of using nuclearenergy. Dynamic performance of grid connected WT using Permanent Magnet SynchronousGenerator (PMSG) under variable wind speeds and load conditions are investigated in thispaper. Also, Fuzzy Logic Controller (FLC) method in comparison with Genetic Algorithm (GA)and PI controller in pitch angle of WT is evaluated. Besides, the FLC using wind speed andactive power as an inputs in pitch angle of wind turbine, can have faster responses, therebyleading to flatter power curves, improvement of dynamic responses of WT and prevention ofmechanical fatigues in PMSG. Inverter regulated the DC link voltage and active power is fed byd-axis and reactive power is fed by q-axis via using P/Q control mode. Simulation results depictthe effectiveness of FLC method in smoothing output power of WT in high wind speeds. Thecomplete modeling of Wind Power Generation System (WPGS) is simulated by Matlab/Simulink.

Keywords:Wind Turbine (WT); FLC; Genetic Algorithm (GA); Pitch Angle; P/Q Control

1. INTRODUCTION

Distributed Generation (DG) is defined as generating units in small-scale, installed and operate nextto the consumers. From different technologies of DG units, the renewable ones are widely utilized, asthey are considered green, sustainable and free energy sources. In the other words, implementing of DGsmay cause intense challenges to the grid in the case of secure and efficient operation of the power system.Many kind of power sources can be classified as DGs like diesel engines, battery units, Photo Voltaic(PV), Fuel Cell (FC), Wind Turbine (WT) and Micro Turbine (MT) [1, 2].

WT have gained great attention over the last decade as one of the most promising DGs due to theprobable depletion, high costs and negative environmental impacts of conventional energy sources.Among electric generators, Permanent Magnet Synchronous Generator (PMSG) is preferred due to itshigh efficiency, reliability, power density, gearless construction, high power factor, light weight, andself-excitation features.

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Comparison of FLC-GA-PI Methods to Smooth the Output Power of Wind Turbine in the Grid Connected Mode

WTs are controlled to operate only in a specified range of wind speeds limited by cut-in (Vcut−in) andcut-out (Vcut−out) speeds [3, 4]. When power production is below-rated power for the generator, theturbine operates to capture the maximum amount of energy available in the wind. In above-rated powersituation, the main purpose is maintaining the power output in constant value. In high wind speeds, theextra production of active power by wind turbine cause to increments consuming of reactive power inPMSG that, it should utilize the reactive power compensator for injecting reactive power that it has extracost too. Also, in above-rated wind speed operation, mechanical fatigues will make the producers to havemore maintenance cost which cause to utilize the suitable controller with fast and smoother responses[5, 6]. This paper is more concentrated on the above-rated wind speed and controlled the turbine outputpower in high speeds.

Maximum Power Point Tracking (MPPT) controller someway varies the rotor speed according tovariation of wind speed that the Tip Speed Ratio (TSR) is maintained in optimum value. One of themanners to obtain the MPPT is pitch angle control [7].

One of the most implemented controllers in MPPT algorithms is PID controller. However, PIDcontroller is not the most efficient one over a wide range of operating conditions (below and aboverated wind speed), because the WT system is a complicated dynamic system with a highly nonlinearcharacteristic. Although by the reported Genetic Algorithm (GA) in [8–11], instead of PID created abetter performance for MPPT and as well as, limit the extra active power in above rated speed and reachto nominal value. It is noted that, by the introduction of fuzzy logic, the best suppressive way to omit thedifficult mathematical understanding of system. In comparing PIDs, GA and fuzzy logic systems, FuzzyLogic Controller (FLC) has more stability, smaller overshoot, faster and flatter response. The FLC basedMPPT scheme is appropriate and practical, but somehow complex to implement [12, 13]. However, theFLC for MPPT control can implement sensorless maximum power tracking and overcome some problemsof conventional algorithms. The maximum power can be obtained via the Mamdani fuzzy controller bymeasuring the wind speed and deviation of active power without measuring rotor speed, reactive powerand etc.

In [14–16] pitch angle based on FLC is reported. In these references, active or reactive powers withrotor speed are applied as input signals while wind speed is ignored. The implemented FLC in thesereferences has not fast and smoother response, which leads to remain the power in above rated value andincrease the mechanical fatigues in PMSG. As well as, another drawback in mentioned papers that theyare not considered in grid connected mode in order to evaluate the system performance [15–17].

In recent years, many topologies based on power electronic devices with different level of complexityand cost is developed investigated in order to connect a PMSG to network. There are two modes forinverter operating: 1) Active and reactive control mode (P/Q control), 2) Voltage and frequency controlmode (V/F control) [18, 19].

Dynamic performance analysis of grid connected wind turbine based PMSG using P/Q control modeunder load circumstances and variable wind speeds and also, improvement of dynamic responses in WindPower Generation System (WPGS) using pitch angle based on FLC is investigated in this paper. The pitchangle is designed based on FLC by adding wind speed as an input signals to regulate the turbine outputpower in extra high speed.

The paper is organized as follows: In part II details of WT based PMSG system and pitch angle usingGA and FLC methods are discussed. In Part III, P/Q controller is described. The simulation result isreported in part IV. Conclusions are presented in part V.

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2. STRUCTURE OF WIND TURBINE BASED PMSG

The block diagram of WT based on PMSG integrated to grid is illustrated in Figure 1. Turbine outputis rectified by using uncontrolled rectifier. Then DC link voltage is regulated by PI controller until itreaches a constant value and then, the constant voltage is inverted to AC voltage using inverter. Inverterregulated the DC link voltage and injected active power by d-axis and injected reactive power by q-axisusing P/Q control method. Therefore, turbine output is adjusted via pitch angle based on FLC in extrahigh wind speeds. By increasing pitch angle via fuzzy controller, the exceeding power of wind turbine ismore limited, reaching to the nominal value. Besides, by the reduction of injected output power of windturbine, the injection of extra total active power to grid is decreased.

Figure 1. The block diagram of WT based on PMSG.

2.1 Wind Turbine Modelling

The amount of electricity production in WT is depends on rotor speed and wind speed which propelsthe rotor [20, 21]. The WT mechanical power can be expressed by following equations:

P = 0.5ρACp(λ ,β )V 3w (1)

λ =WmR

Vw(2)

Where P, ρ , A , Vw, Wm and R are power, air density, rotor swept area of the wind turbine , wind speedin m/sec, rotor speed in rad/sec and radius of turbine respectively. Also, Cp is the aerodynamic efficiencyof rotor.

Cp(λ ,β ) = 0.5176(

116λi

−0.4β −5)

e−21λi (3)

λi =

[1

λ +0.08β− 0.035

β 3 +1

]−1 (4)

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Furthermore, the Cp depends on TSR and blade pitch angle. Figure 2 shows the typical variation of Cp

respect to the TSR or various values of the pitch angle (β ) [22].

Figure 2. Cp Vs λ for various pitch angles (β ).

2.2 Modelling of PMSG

A synchronous generator with reference to Park’s transformation is illustrated which d-axis is rotatingalong magnetic field direction. The PMSG voltage equations are reported by [23]:

dids

dt=

1Ld

[−Vds −Rsids +ωLqiqs

](5)

diqs

dt=

1Lq

[−Vqs −Rsiqs −ωLdids +ωφm

](6)

Where Vds and Vqs are d and q axis machine voltages and Ids and Iqs are d and q axis machine currents,Rs: Stator Resistance, ω: electrical angular frequency, Ld : d axis inductance, Lq: q axis inductance,φm: amplitude of the flux linkage caused by permanent magnet. If rotor is cylindrical (Ld Lq = Ls), theelectromagnetic torque equation written as following:

Te =32

pφmiqs (7)

Where, p is the number of pole pairs of the PMSG [23, 24].

2.3 Pitch Angle Based on Genetic Algorithm (GA)

In wind velocities below rated, pitch angle value should be considered as zero for obtaining the maximalpossible energy from wind. If wind speed exceeds its nominal value, generation power of WT is still keptin nominal level by desirable adjusting of pitch angle degree. GA is a robust optimization method based

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on natural selection. The principle target of GA is to optimize functions called fitness functions. GAbased approaches differ from conventional problem-solving methods in several ways. The proposed GAcontroller method in WT can be illustrated in Figure 3. In this paper, GA is utilized to obtain the optimalpitch angle of WT in order to control the output power in high wind speeds and extract the maximumpower in below rated speed. The details of GA controller are presented in [25–28].

Figure 3. The block diagram of WT using GA controller.

2.4 Pitch Angle Based on Fuzzy Logic Controller (FLC)

The FLC includes four main interactive mechanisms. The fuzzification unit determining inputsmembership values to the fuzzy sets of the discourse universe. The Fuzzy Inference System (FIS)evaluates at each time which control rules are appropriate using the base knowledge. The deffuzificationunit computes the crisp output of the rules leading to the optimal plant control [29, 30]. The block diagramof FLC is depicted in Figure 4.

Figure 4. The Structure of FLC System.

The presented FLC is consisting of two input signal and one output signal. The first input signal isbased on deviation between active power and rated value in P.U, which, positive value indicate turbine’snormal operation and negative value shows the extra power generation during above rated wind speed.The pitch angle degree is adjusted on zero in a normal operation. The wind energy can be converted tomechanical energy and when, the pitch angle starts to increase from the zero value, the wind attach angleto the blades is increased, which leading to aerodynamic power reduction and consequently, reducing theoutput power. Also, the second signal is wind speed that is taken from anemometer [14–16].

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Controller’s response is so faster, flatter and more stable when wind speed is implemented as an inputsignal compared to rotor speed and reactive power However, mechanical fatigues in high wind speed arediminished by adjusting the FLC. Designing the pitch angle controller based on fuzzy logic for regulatingthe turbine output power in high wind speeds is being proposed in this paper. Three Gaussian membershipfunctions are proposed in this paper. Moreover, Min-Max method is used as a defuzzification referencemechanism for Bisector. The membership functions are depicted in Figure 5.

(a)

(b)

(c)

Figure 5. The membership function of FLC: (a) Membership functions of active power (error signal), (b) Member-ship functions of wind speed, (c) Membership functions of output (β ).

Also, the rules are applied to obtain require pitch angle are presented in Table 1. While the linguisticvariables are shown by VG (very great), SG (small great), OP (optimum), SL (small low) and VL (verylow) for error signal and VL (very low), SL (small low), OP (optimum), SH (small high) and VH (veryhigh) for wind speed signal and for output signal NL (negative large), NS (negative small), Z (zero),PS(positive small) and PL (positive large), respectively. Figure 6 Shows the three dimensional curve ofinputs and output.

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Table 1. Fuzzy rules.

Pitch command Active power (Error)

Wind speed

VG SG OP SL VLVL PL PS Z Z ZSL PL PS Z Z ZOP PL PS Z Z ZSH PL PS PS PS PSVH PL PL PL PL PL

Figure 6. The three dimensional curve in FLC.

3. P/Q CONTROL STATEGY

A three phase DC-AC Voltage Source Inverter (VSI) is utilized for grid connection by Pulse WidthModulation (PWM) technic. Applying inverter by PWM technic produces high frequency harmonicswhich cause to filter and diminish the harmonics. The VSI can play role as an ideal sinusoidal voltagesource. Wind power fluctuates due to wind velocity which output voltage and frequency change, con-tinuously. A bridge rectifier provides AC to DC and then, DC link voltage using PI controller to obtainconstant value, then DC voltage will be inverted to obtain desired AC voltage [31]. The active and reactivepowers feeding into the grid can be expressed as:

P =32(VgdId +VgqIq) (8)

Q =32(VgqId −VgdIq) (9)

Active and reactive power control can be implemented by controlling the direct current (Id) andquadrature current (Iq), respectively. Also, Vgdand Vgq are voltages of d-axis and q-axis, respectively.If synchronous frame is synchronized with grid voltage, voltage vector is V=Vgd+j0 which active andreactive power may be as following:

P =32

VgdId (10)

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Q =32

VgdIq (11)

Synchronous reference frame calculates quantities of d-axis, q-axis and zero sequence in two axisrotational reference vector for three phase sinusoidal signal which is illustrated in Figure 7. The equationsare presented by (12) and (13).

Figure 7. The synchronous reference machine.

Vd

Vq

V0

= C

Va

Vb

Vc

,

idiqi0

= C

iaibic

(12)

Cdq0 =23

cosθ cos(θ −2π/3) cos(θ +2π

/3)

−sinθ −sin(θ −2π/3) −sin(θ +2π

/3)

12

12

12

(13)

Inverter control model is depicted in Figure 8. The aim of grid side controller is to remain the DClink voltage in constant value, regardless of power amplitude. Inverter control strategy is consisting oftwo control loops. Internal control loop is control the grid current and external control loop is controlthe voltage. Internal control loop which is responsible for power quality such as low Total HarmonicDistortion (THD) and enhancement of power quality and external control loop is responsible for balancingthe power. One of the most important characteristics of P-Q control loop is the capability of independentperformance of grid. Another advantage of this mode is increasing operational reliability and powerquality. The external loop capacitor voltage control is utilized to set reference current for d-axis in orderto control active power .The q-axis reference current is determined to inverter output reactive power. Ifpower factor is unit, therefore this current will be zero. The Phase Locked Loop (PLL) blocks whichmeasure the voltage phase angle θ g is based on Park transformation and also synchronize the inverter togrid [32].

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Figure 8. The inverter control model.

4. SIMULATION RESULTS

In this section, simulation results under different terms of operation use with Matlab /Simulink ispresented. System block diagram is shown in Figure 9. Detailed model descriptions are reported inAppendix A.

Figure 9. The block diagram of grid connected WT in Matlab/Simulink.

4.1 Case Study (Variations of Wind Speed and Load)

In this paper, the dynamic performance of WPGS under variations of wind speed and load circumstancesis proposed. The evaluation of FLC with comparing to GA and PI controller in pitch angle of WPGS iscarried out. There is no power exchange between WPGS and grid in normal condition. During 0 < t < 1sec, the load power is 77 kW and at t= 1 sec, it has %35 step increment in load that is constant until t=12sec. As well as, wind speed during 0< t <1.5 sec is 12 m/s which at t= 1.5 sec, it is declined to 9.5 m/s.Then, during 1.5< t < 4.8 sec, wind speed is 9.5 m/s which, at t= 4.8 sec, it is extremely incremented to18 m/s. By applying PI and GA controller, when wind speed is more than rated value (12 m/s), turbine

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output power is incremented by acutely increasing wind speed and the power is maintained in high level;as regards, by using FLC, the power is declined to rated value (approximately) and made it smoother thanother methods, which lead to enhance the dynamic responses and also, prevent the mechanical erosion toPMSG.

Figure 10 demonstrates the variation of wind speed in presented system. Inverter output voltage isconstant, which is shown in Figure 11. The variation of pitch angle using FLC is depicted in Figure12. As can be seen, in normal conditions, the pitch angle is set as zero. At wind speeds above the ratedspeed, the extracted wind power has to be limited by increasing the pitch angle (β ). The exceeding powerof wind turbine is limited and also, the inverter output current is more reduced by FLC in comparisonto PI and GA controllers. It is clear that, by using FLC method the power curve is more smoothenedand reaches to the rated value. In Figure 13, Figure 14 and Figure 15 the performance of PI, GA andFLC methods in output current of WT is investigated, respectively. DC link voltage remains at a constantvalue (960V), thereby proving the effectiveness of the established P/Q controller as illustrated in Figure16. The reactive power generated by the WT is adjusted at zero, in order to the power factor maintainsunity as shown in Figure 17. The grid current with PI, GA and FLC methods are evaluated in Figure 18,Figure 19 and Figure 20, respectively.

It can be observed from the Figure 21, Figure 22 and Figure 23 that, by decreasing of injected outputpower of WT using FLC in high wind speeds, the injection of extra active power of WT to grid is moredecreased in comparison to PI and GA methods. One of the most important aspects of using DG sourcesis remaining the THD at the minimum value. According to IEEE Std.1547.2003, it should be around 5%.In THD curve, it is around 3% to 6%, which is illustrated Figure 24.

Figure 10. Variation of wind speed.

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Figure 11. Inverter output voltage.

Figure 12. Variation of pitch angle using FLC.

Figure 13. Inverter output current using PI controller.

Figure 14. Inverter output current using GA controller.

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Figure 15. Inverter output current by FLC.

Figure 16. DC link voltage.

Figure 17. Reactive power.

Figure 18. Grid current by PI controller.

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Figure 19. Grid current by GA controller.

Figure 20. Grid current by FLC.

Figure 21. Active powers by PI controller.

Figure 22. Active powers by GA.

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Figure 23. Active powers by FLC.

Figure 24. THD (%).

5. CONCLUSIONS

The dynamic responses of grid connected wind turbine based PMSG under load circumstances andvariations of wind speed was investigated in this paper. Control strategy and precise modeling of DC/ACgrid connected inverter was reported. Inverter regulated the DC link voltage and active power was fed byd-axis and reactive power was fed by q-axis (using P/Q control mode). The simulation results show thatusing FLC could dramatically reduce the disadvantages of PI and GA methods. Besides, the proposed FLCin the WT, by adding wind speed as an input signal, could have faster and smoother responses, preventmore mechanical fatigues and also, the dynamic performance of WT could be improved. Moreover, byincrementing pitch angle by FLC, the exceeding power of wind turbine was more limited, reaching to thenominal value and reduced inverter output current. Therefore, by the reduction of injected output powerof WT, the injection of extra total active power to grid was more decreased. It was clear that, the WPGSby implementing FLC in pitch angle with the cooperation of grid could easily meet the load demand.

APPENDIX A: DESCRIPTION OF THE DETAILED MODEL

PMSG parameters: Stator resistance per phase: 2.6 Ω, Inertia: 0.84e−3 kg.m2, Torque constant: 12N-M/A, Pole pairs: 8, Output power: 77 kW, Nominal speed: 12 m/s, Ld =La= 7.4 mH. Grid parameters:X/R: 7, F: 60 Hz, Vgrid : 220 V and other parameters, DC link capacitor: 5250 µF, DC link voltage: 960V, Load power: 77 kW.

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