 Open Access
 Total Downloads : 1250
 Authors : Aarti Gupta, D.K. Jain, Surinder Dahiya
 Paper ID : IJERTV1IS7248
 Volume & Issue : Volume 01, Issue 07 (September 2012)
 Published (First Online): 25092012
 ISSN (Online) : 22780181
 Publisher Name : IJERT
 License: This work is licensed under a Creative Commons Attribution 4.0 International License
Fuzzy Logic Blade Pitch Angle Control of a Hybrid WindDieselBattery Energy Conversion System
Fuzzy Logic Blade Pitch Angle Control Of A Hybrid WindDieselBattery Energy Conversion System
Aarti Gupta D.K. Jain Surinder Dahiya
ABSTRACT
Wind energy conversion system integrated with diesel is used in autonomous operation worldwide. The paper investigates the operation of hybrid system employing Fuzzy Logic Controller for a wide range of wind speed capture. Power conditioning is achieved using a combination of fuzzy logic pitch controller and battery energy storage
Key words: WECS (wind energy conversion system), FLC (Fuzzy Logic Controller), BPA (Blade Pitch Angle Control

INTRODUCTION
Standalone systems are generally used to power remote houses or remote technical applications (e.g. for telecommunication systems). The wind turbines used for these purposes can vary from between a few watts and 50KW 1. For village or rural electrification systems of up to 300 kW, wind turbines are used in combination with a diesel generator and sometimes a battery system. The required power for the connected load can be effectively delivered using appropriate control and effective coordination among the various subsystems. the proposed winddiesel hybrid generator feeding isolated loads can be properly operated to achieve system powerfrequency balanced condition The WECS adopts an ACDCAC converter system with fully controlled PWM voltagesource converters (VSC). The DClink voltage command is determined according to output power fluctuations of the PMSG. The aerodynamic power captured by wind turbine is the cosine function of pitch angle. The pitch angle is kept zero for lower to medium wind velocities [2] but the effect of gust cannot be ignored due to the highly unpredictable nature of wind. The output power fluctuations in low and highfrequency domains are smoothed by the Fuzzy logic Blade Pitch angle control of the WECS and the DC link voltage control, respectively. By using the proposed method, the wind turbine blade stress is mitigated as the pitch action in
highfrequency domain is reduced. Variable speed wind turbines are preferable as they offer many advantages over fixed speed wind turbines such as increased energy capture, operation at maximum power point, better efficiency and power quality. However, the operation and control of variable speed wind turbines are more complicated than fixed speed wind turbines. Multipole design can be easily realized in the synchronous generator as increasing the number of poles type Felicitates gearless operation and hence, the features of lightweight and low maintenance can be obtained in this type of wind generation system [3].In addition, it is also easier to accomplish the fault ride through and grid support capabilities in a synchronous generator system than in other types of generators due to the fact that the fullrated power converter decouples the generator system from the micro grid [4],[5]. Taking the fore mentioned factors into consideration, a PMSGbased generation system is an important trend in the development of wind generation systems 6.7. There is enhanced awareness about power quality as Load equipments with microprocessorbased controls and power electronic devices used in the present are more sensitive to power quality variations. To increase the system efficiency, high efficiency devices based on power electronics equipments have been increasingly used in many applications. This causes increasing harmonic levels on power systems and concerns about the future impact on system capabilities. Active filter control coupled with robust FLC of BPA addresses this issue and helps to increase the life of the generator, in addition, fluctuations on the DC link are further smoothened. .The paper is arranged as follows, section

Explores the wind turbine dynamics and PI and fuzzy logic scheme employed in the paper is described in the next section. Section 4, discusses in brief the various methodologies adopted to design the control scheme of the hybrid WECS. The results obtained are discussed next section and the last section includes the list of references.
Schematic of the Proposed System
Fig.1

WIND TURBINE DYNAMICS
Power in the wind turbine varies as the cubic function of the wind speed.
W
P=0.5AV 3 (1)
wind turbine can only extract part of the power from the wind, which is limited by the Betz limit (maximum 59%). This fraction is described by the power coefficient of the turbine, Cp, which is a function of the blade pitch angle and the tip speed ratio.6.,7.Therefore the mechanical power of the wind turbine extracted from the wind is where Cp is the power coefficient of the wind turbine, is the blade pitch angle and is the tip speed ratio.
Pw=0.5Cp(,)AVW3 (2)
The tip speed ratio is defined as the ratio between the blade tip speed and the wind speed VW where is the turbine rotor speed and R is the radius of the wind turbine blade
Fig.2
The pitch angle is controlled in order to limit the
=
(3)
generator output power to its nominal value for high
Thus, any change in the rotor speed or the wind speed induces change in the tip speed ratio leading to power coefficient variation. In this way, the generated power is affected. Fig. 2 shows a group of typical Cp curves where optimum values of tip speed ratio, opt, correspond to the maximum power coefficient, Cp.max. Fig. 3 shows that the mechanical power converted from the turbine blade is a function of the rotational speed, and the converted power is maximized at the particular rotational speed for various wind speeds
wind speeds.
W=(_ (1 ^2 ) + ^2 ^2 (1 + ^2 ) ) (4) The resultant relative velocity gives rise to Aerodynamic forces on the blade, therefore a lift force
is produced given by
FL=1 2CW2CL (5)
and drag force is given by
FD=1 2CW2CD (6)
where CL is lift coefficient, CD is drag coefficient and c is the chord length of the blade. In the pitchadjusting variablespeed wind turbines, the angle of attack, , decreases when the pitch angle, , increases,. The lift force, FL, decreases as well and this causes reduction of the mechanical power of the wind turbine. According to the pitch angle control, the initial angle the power of the wind turbines will increase at the increasing wind. The wind turbine must be protected against mechanical overloads and possible risk of damages at strong wind.
This is achieved by pitching the blades into the position where a part of incoming wind will pass by the wind turbine.6. The power will be kept at its rated value at this region. By pitching, the thrust is reduced. Fig. 6 shows the curve of the pitch angle versus incoming wind speed which is computed with use of the BEM method for the given 1.5 MW wind turbine.
Fig.3

PI AND FUZZY LOGIC CONTROLLERS
opt, the optimized pitch angle can be defined using the BEM method(fig.3) from the incoming wind and it is in very few degrees around zero. A ProportionalIntegral (PI) controller fig.4 is used to control the blade pitch angle in order to limit the electric output power to the nominal mechanical power. The pitch angle is kept constant at zero degree when the measured electric output power is under its nominal value. When it increases above its nominal value the PI controller increases the pitch angle to bring back the measured power to its nominal value. The control system is illustrated in the figure:
(PI Controller) Fig.4
A FLC controller was designedto make the system more effective and increase the speed of the response. The fuzzy logic control strategy may have the potential when the system contains strong non linearity, such as wind turbulence is strong, or the control objectives include fatigue loads. The design of the fuzzy logic controller and the comparisons with conventional pitch angle control strategies with various controlling variables are carried out. The simulation shows that the fuzzy logic controller can achieve better control performances than conventional pitch angle control strategies, namely lower fatigue loads, lower power peak and lower torque peak.
Fig.5
Rule based fuzzy logic controllers (fig.5) are useful when the system dynamics are not well known or when they contain significant nonlinearity. The intermittency of wind introduces large turbulence. Fuzzy logic controllers apply intuitive reasoning, similar to how human beings make decisions, and thus the controller rules contain expert knowledge of the system. The big advantages of fuzzy logic control when applied to a wind turbine are that the turbine system neither needs to be accurately described nor does it need to be linear.6. Power smoothening is achieved which in turn enhances the power quality and increases the longevity of the generators protecting them against gust.
fig.6
Surface view of the rules of the FLC block

Modelling of PMSG, back to back PWM converter control and Battery energy storage
The PMSG is modelled in the dq frame of reference. The voltage and torque equations of the PMSG are given with the following equations.
Vd=Raid+L eLqiq (7)
Vq=eLqid+Raiq+L
where the rotational speed error is used as the input to a speed controller, which produces qaxis stator
Te=P{Kiq+(LdLq)idiq} (9)
Vd and Vq are the d and q axis voltages respectively and id and iq are the dq axis currents. Ra is the stator resistance, Ld and Lq are the direct and quadrature axis inductances. e is the generator rotational speed, K is the permanent magnetic flux and P is the number of pole pairs. The motion equation of the PMSG is given by
Te=Jeq +Dm+Tw (10)
The WECS adopts an ACDCAC converter system. The PMSG is connected to the grid through two PWMVSCs: a generatorside converter and a gridside inverter. Each of the four quadrant power converters is a standard 3phase twolevel unit, composed of six insulated gate bipolar transistors (IGBTs) and controlled by triangularwave PWM law. The generatorside converter achieves variable speed operation by controlling the rotational speed of the PMSG. On the other hand, the loadside inverter supplies the electrical power, which is synchronized with the grid frequency (diesel).The generatorside converter controls the rotational speed of the PMSG to achieve variablespeed operation with the MPPT control 8., 9. Vector control scheme is used in the control methodology 10.,11., The speed control of the PMSG is realized on a rotating reference frame,
current command iq . A salientpole synchronous machine is used in this paper. To achieve efficient operation of the PMSG, daxis stator current command id* is set to zero the actual dqaxis currents are used as inputs to the current controllers. The current controllers produce dqaxis voltage commands vd and vq after the decoupling. The dq axis voltages are transformed to phasor vabc and fed to the pulse generator.
The load side converter control is realized by using a synchronous reference frame , the DClink voltage (VDC) is controlled by the gridside inverter. The VDC*(ref) is set to 1000V for UPF operation, iq*= 0, [10]. The active power exchange is directly proportional to the id and this directaxis current id is also responsible for regulating the dclink voltage.9.
The interfacing of the battery is done with the help of a buck boost converter. During high wind conditions, the buck converter utilizes the extra generated power to feed the battery whereas during low wind speeds it acts as a boost converter to compensate the fluctuations on the DC link. The PI controller compares the dc link voltage to a reference and generates the reference current signal

SIMULATION RESULTS AND DISCUSSION
The proposed system was simulated using MATLAB Simulink software and the results obtained for a direct drive PMSG rated for 20KW.
RESULTS FOR PI CONTROLLER
FUZZY LOGIC CONTROLLER
Analysis of results fig.7obtained during the simulation shows that the behaviour of the system as regards the variation in the generated wind power is much less using an FLC, than while using a PID controller. The DC link fluctuations are much less which translates to fewer fluctuations on the diesel group. Moreover, the generator is protected from gust as the pitch angle control facilitates the adjustment of generated power reducing the pressure on the PMSG and hence prolonging its life and efficiency. Without control, mechanical power can exceed nominal power in a wind turbine, Owing to wind speed increase above the nominal wind speed(12m/s) for the turbine. Hence,
Fig.7
the WECS operation is unsustainable. For a horizontal axis wind turbine, pitch angle control is one method to control the peak of the mechanical power, returning to normal power condition without stopping the WECS. Simulation results indicate that the control of the pitch angle is able to limit the mechanical power excursion, but the response takes time to capture normal operation condition, depending on the inertia of the rotor. FLC is smoother and faster besides being more effective. For gust wind speeds between 20m/s and 22m/s, the response of the two controllers can be compared. At t=5sec, the wind speed changes to 20m/s and the power generated by the wind also increases. The response of
the PI controller is sluggish, as the generated power settles down to the optimum value after a period 1 sec and again, when the wind speed further increases to 22m/s, the response takes time to stabilize. In contrast, the fuzzy logic controller stabilises the system response almost instantly and the power remains at the optimum till the gust remains. The DC link voltage is also smooth for a wide range of wind speed (10m/s to 22m/s). Hence power conditioning is realized using a combination of battery energy storage and FLC pitch controller, the results are validated using MATLAB simulink model .

REFERENCES

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