Abstract—Due to its advancements and enhanced usability Doubly fed Induction Generatorfind its application in most of the Wind Turbines and in all wind PowerGeneration. Grid connected wind turbine will generally experience faultycondition, it will leads to fault ride through of the turbine which in turnreduces the reliability of the system. To enhance the low voltage ride throughcapability of wind turbine a control strategy is to be framed. The existingcrowbar method for DFIG to protect Rotor Side Converter and Grid Side Converterbut makes the system more weak by absorbing more reactive power from thesystem.
In this paper Fuzzy Logic controller is used to limit the deviations ofsteady state values during and after faults in the grid and thereby reduces theneed of crowbar for the system. The designed fault detection and confrontationsystem manages attenuate the disturbance during fault which would supply thereactive power to the grid. The MATLAB/SIMULINK TOOL is used to model thecontroller and test the validity of the control over the Grid connected windturbine over weak ac signal. KeyWords: Fuzzy Control, DFIG, LVRT I.INTRODUCTION The grid connected DFIG contains woundrotor and stator windings.
The stator windings are directly connected to grid and rotor windingconnected to grid via two back-to-back converter. This converter provideoptimized control of active and reactive power and it is cost effective andsmaller in size. Although DFIG has a major drawback of absorbing more reactivepower from the grid when subjected to fault. Whenever fault occurs, at thestator windings results change in stator flux of the DFIG which provide an overcurrent to the rotor windings due to magnetic coupling. Dueto this over current the rotor side converter is affected and that leads tolarge fluctuations of DC-LINK voltage .
In order to protect the rotor windingscrowbar protection was applied. Crowbar circuit consists of bank of resistorsand with the help of power electronic devices it is connected to the rotorwindings. Whenever the fault occurs, Rotor Side Converters is disabledtemporarily and crowbar circuit is connected to the rotor windings. This typeof protection is not much effective there is considerable loss of output power.When the large transients and faults occurs in the grid crowbar protection isdeactivated and DFIG is disconnected from the grid.
Nowa days wind generator contributes substantial amount of power over the totalpower generation in India. As per grid code requirements the WT should haveLVRT capability during grid faults resulting in more than 85% voltage drop.This clearly shows that they should provide supply power to the grid during andafter grid faults, to improve the system stability 5.In8 is proposes a control by flux linkage tracking control method. The controlsystem is not depends on the system parameters for that decoupling of DC andnegative sequence components is not necessary. Even though the proposed methodis manages to enlarge the control action, but it has many drawbacks that couldnot be avoided. Properly designed fuzzy controller (FC) is better than atraditional proportional integral (PI) controller.
There are many researchworks are carried out to prove that the FC manages to limit the rotor currentduring the fault, with the elimination of external devices. However in these work grid code requirements is notdescribed properly. This control scheme can applied to the small voltage dip.Fuzzy logic controller acts as a protective device when the DFIG subjected toexternal fault when compare to traditional PI controller, result FC satisfiesthe grid code requirements. Based on the various analysis andresults studied from works so far, this paper interested to expand the conceptof the protection of the DFIG without the presence of added hardware. Thisendeavor is applied to DFIG during asymmetrical fault. The proposed methodcontribution to the most optimum co-ordination of the two converters. Theobjective is to improve system stability and reduce the disturbances to thesystem 9.
In order to come across from the difficulties met due to unresolvedof the system, the controller were proposed based on Fuzzy Logic Controller(FLC). By using the concept FC model the rotor over current and dc link overvoltages are effectively diminished. In addition the grid code requirementfulfilled such as FRT capability of the DFIG and reactive power supplied to themachine. II. MODELLING OF DFIG Figure2.1.
General Schematic Diagram of DFIGFigureshows the general schematic diagram of a grid connected DFIG system. Themodelling of DFIG have been suggested by grid code is that, the WT should beconnected through a mechanical shaft system, which is to be a low speed turbineshaft connected to high speed generator shaft via a gearbox. The DFIG is avariable speed wind generator , it consists of two windings rotor and statorside, where the stator windings is connected to a grid output without anyintermediary and rotor windings are connected via two back to back converternamely RSC& GSC as shown in Fig. 1. The ac/dc/ac converter is an IGBT basedPWM converter 3. A. Modellingof Wind Turbine It is accepted that the efficient designof Wind Turbine Rotor plays a major role to accomplish maximum wind powergeneration.
To achieve an optimum wind power generation design of wind turbineblades, diameter of rotor, blade pitch angle, the transmission system and gearbox, blade chord, tower length should be determined. The maximum power obtainedfrom the wind is directly depends on the speed of the rotor and maximum powercan be expressed as, Pmax = (1) At the optimum operating point themaximum value of power can be written as, Pmax= (2) Pmax– Maximum powerR– Radius of the rotor?– Tip Speed Ratio?– Rotor Speed Vw- Wind Speed The maximum power extraction is thefunction of tip speed ratio and pitch angle so that the specific value of TSR(?) should be maintained. Figure 2 showstypical characteristics of the wind turbine using the Cp versus ? curve. Figure2.2. Cp versus ? curveThepitch angle ? is kept constant at zero degree until the speed reaches point Das shown in Figure 2.
2. Figure2.3. ABCD curve B. MathematicalModeling of DFIG Thestudied system represented by the following equations, the mechanical power andthe stator electric power output are computed as follows, Protor = Tm*?r (1) Pstator=Tm*?s (2) For a loss lessgenerator the mechanical equation is, J d?m (3) In steady-stateat fixed speed for a loss less generator, Tm = Tsm and Pm= Ps + Pr (4) Pr = Pm-Ps = Tm ?r + Tem ?s =-sPs (5) Wheres=( ?s- ?r) ? ?sBased on thedynamic operating characteristics of DFIG the voltage and flux linkageequations are given by, (6) (7) (8) ?ds = – Ls ids+ Lmidr (9)?qs = – Ls iqs+ Lmiqr (10)?dr = Lr idr + Lmids (11)?qr = Lr iqr + Lmiqs (12) Where,Vqs,Vds – direct and quadratureaxis stator voltagesiqs,ids – direct andquadrature axis stator current?qs,?ds – direct and quadratureaxis stator flux linkageVqr,Vdr – direct and quadrature axis rotor voltageiqr,idr – rotor current in d-q reference frame.
?qr,?dr – direct and quadrature axis rotor flux linkages Rs,Rr are the stator and rotorresistances of machine per phaseLs,Lr are the leakage inductances of stator and rotor windings. Figure 2. Rotor Side Converter Figure3. Grid Side Converter TheOptimized control system for the DFIG has been separated into two convertersRSC and GSC as shown in figure 2, figure 3. These two converters are generallyused to obtain regulated voltage by controlling real and reactive power. Inorder to reach enhanced control of active and reactive power, the parktransformation of current components is accomplished using a reference frameoriented technique where q-axis current component controls the active power in statorside. Theefficiency of the system is depends on the load characteristics of the entiresystem, thus the Maximum Power Point Tracking (MPPT) Technique is employed todetermine the feasible operating point of the system, that can be given to thereference value of the active power.
The input of the power controller is thedifference between Pr and Pr-ref, the error is given to the power controller.The observed value of the q-axis rotor current is compared with the actualvalue of iqr and the error isdriven to the current controller. This output value has been considered as reference voltage forq axis component vqr. Wheneverthe DFIG is subjected to fault and connected with weak power system the RSC canbe activated to provide reactive power compensation. In case the DFIG is connected with strong power system thecontrol action is not involved. In this work, the DFIG is connected to weak acgrid and unconventional performance of the system is studied and appropriatecontrol action has been taken instead of reactive power control.
The computedvoltage from the generator terminals is compared with its reference value anderror signal for the d-axis current. The current controller providesreference voltage for the d-axis rotor terminals in which input of thecontroller is obtained by comparing the error signal from voltage regulator andthe d-axis current. The desired output signal vdr and vqr aretransformed into abc components. These components are driven by the PWM moduleto generate the IGBT gate control signals. Thedc link voltage is maintained as constant with the help of GSC.
In this paper,the reactive power is considered to be neutral by setting Qgc_ref=0.The control system of GSC is shown in Figure. 3. The reference frame orientedvector control is applied for threephase quantities into dq transformation. The dc voltage and the reactive powercan be controlled by d-axis reference frame current and q-axis referencecurrent respectively. III. OPTIMIZED CONTROL SYSTEM Theoptimized control system intends to have enhanced LVRT capability of the DFIGindependently. RSC is modified with fine-tune fuzzy controller.
In other wordsmodified RSC to make it an optimized control system. Figure 4 shows optimizedcontrol system where fault detection and confrontation system (FDCS) isintroduced. Depending on the deviation of percentage of voltage control blockis activated (or) else set to be ideal. Only 10% of voltage sag is allowed fromthe reference value. The abstraction of the control strategy is achieved byconsidering two major deviations in RSC. By the means of the drastic decrementin rotor over current and dc link over voltage will lead to successfulprotection of DFIG. Due to sudden changes in the system , dc voltage and rotorcurrent will be exceed their limits.
During the period of transient theexisting amount of energy, that is to be properly pumped through converter andconnected to the grid, in order to fetch the value of the rotor current and dcvoltage back to their desired value. DCvoltage can be attenuated or eliminated by reducing the rotor current but therotor current cannot be minimized after certain value. Fault ride throughcapability of the DFIG can be achieved only by taking rectifying signals intoaccount and also the value of dc voltage should be consider. A. Fuzzy Controller Fuzzylogic controller is used to control the speed and power of DFIG. It is known for its precision and itcan be implemented in simple manner. Mamdhani type fuzzy controller is used dueto its robustness of control.
Rotor current and dc voltage are input signals offuzzy controller and output signal is command signal generator which will becompared with the quadrature axis rotor voltage and this signal from the faultdetection. The current controller is corrected by a quantity derived by a FuzzyController, FCFRT. The inputs of FCFRT, Vdc?, ir? aregiven by equation.
13, 14. Where ss denotes for the steady state value justbefore fault, mv stands for manufacturer value. Figure 4. Optimized Control System TABLEIFCFRT INPUTS Vdc’ Ir’ S M B S OK SP BP M SN OK SP B BN SN OK Vdc?= (13) (14) The actual values of Vdc’, ir’are processed through fuzzy control system. They are made as fuzzy values whenit is processed through fuzzy interference system. Triangular membershipfunction will be apt for both voltage and current as their values will increaseand reach peak value at a time. The modulation index (Ucrf)calculated from the fuzzy expert system finds the deviation from the settledvalue. The deviations include both positive and negative deviations.
Positivedeviations shall be taken into account leaving out negative deviations. Thefuzzification process is done in Mamdanisystem. The rules framed in fuzzy set between two inputs and the index areclassified into five subsets for the three different values classification ofinputs. Neglecting of negative values of Ucrf will lead to easydefuzzification process when we can obtain the actual value to be applied tothe controller system.
IV.SIMULATION RESULT MATLAB STIMUATION TOOL is usedfor stimulation work. The twice fed induction generator (1.5 MW) is modelledwhich supplies electrical power to a weak power system. A three phase fault isintroduced to an electrical system at t=1.2 s resulting in voltage sag of 85%dip in normal voltage. The simulation output is compared for the aboveelectrical system, the proposed control system moderates the fault periods andthe response during and after fault periods seems to be good which shows that this control system can makethe DFIG to successfully overcome the fault. The parameters of the electricalsystem are given in the Table II, III.
Apartfrom good ride through capability of DFIG, Rotor Side Converter is continuouslybeing active throughout the fault period and after the fault period therebysupplies reactive power to the grid, which is useful for balancing the voltagecaused by three phase fault. By the rapid recovery system of proposed controlsystem the need for large amount of reactive power from the DFIG during faultyconditions can be reduced. DFIG along with proposed control system supplies therequired amount of reactive power to the grid which maintains the ac voltage ofthe grid.
TABLEII SYSTEMPARAMETERS OF DFIG (1.5 MW) Parameters Symbol Range Rated Power P 1.5 MW Rated Stator Voltage Vs 575 V Rated Frequency F 60 Hz Nominal Wind Speed Vw 12m/s Stator Resistance Rs 0.023 pu Rotor Resistance Rr 0.016 pu Stator leakage inductance Ls 0.18 pu Rotor leakage inductance Lr 0.16 pu Magnetizing inductance Lm 2.9 pu Nominal dc-link voltage Vdc 1150 V Dc bus capacitor Cf 10 m? TABLEIII PARAMETERSOF THE AC GRID Rated Voltage 25 KV Rated frequency 60 Hz Short circuit ratio at the PPC 2.
23 Time (sec) Figure5.Rotor Current with controller Time (sec) Figure 6. DC Voltage withcontroller Time (sec) Figure7. Rotor Current without controller Time(sec) Figure8. DC Voltage without controller 1 1.1 1.2 1.
3 1.4 1.5 1.6 1.
7 1.8 1.9 2 Figure9. Response of the system with controller V.CONCLUSION Improved LVRT capability grid connectedDFIG has been implemented with the absence of external hardware. This paperexplains, the DFIG could feed the electrical system during the fault and afterthe fault period.
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