WIND FARM INTEGRATED FUZZY LOGIC-BASED FACTS CONTROLLED POWER SYSTEM STABILITY ANALYSIS, 172-181.

Amit Kumar Yadav, Varun Kumar, Ajay Shekhar Pandey, Saurabh Mani Tripathi, and Abhishek Kumar

References

  1. [1] M. A. Mohamed, A. M. Eltamaly, and A. I. Alolah,“Sizing and techno-economic analysis of stand-alone hybridphotovoltaic/wind/diesel/battery power generation systems,”Journal of Renewable and Sustainable Energy, 7(6), 2015,63128, doi: 10.1063/1.4938154.
  2. [2] Ren21, Renewables, “Global status report,” REN21 secretariat,Paris, 2016.
  3. [3] S. Muller, M. Deicke, and R. W. De Doncker, “Doublyfed induction generator systems for wind turbines,” IEEEIndustry Applications Magazine, 8(3), May 2002, 26–33, doi:10.1109/2943.999610.
  4. [4] M. Tazil, V. Kumar, R. C. Bansal, S. Kong, Z. Y. Dong, W.Freitas, and H. D. Mathur, “Three-phase doubly fed inductiongenerators: An overview,” IET Electric Power Applications,4(2), 2010, 75–89.
  5. [5] H. T. Jadhav and R. Roy, “A comprehensive review on the gridintegration of doubly fed induction generator,” InternationalJournal of Electrical Power & Energy Systems, 49, 2013,8–18.
  6. [7]2 DIFG-based wind farmwith STATCOM-super-capacitor for lowvoltage rides(a) Low-voltage problem due tosymmetrical and asymmetricalfaults (b) Oscillations(a) Oscillations die out rapidly aftertransient using super-capacitor energystorage with STATCOM. (b) Injectionof the STATCOM in DFIG windturbine maintains the voltage to be inthe desired limit.
  7. [8]3 DFIG-based wind farmwith DVR(a) Voltage sag/swell (b) Lowvoltage ride through capability (c)Sub synchronous resonanceVoltage exerted by DVR is controlled toretain a constant voltage at thetransformer terminals, while thetransformer’s output voltage reducesthe voltage of the unit at a constantangle.
  8. [9]4 Improvement of thevoltage of DFIG-basedwind farm installed inbroad scale by the use ofsynchronised AVR andPSSUnder voltage dips Improvement ofvoltage regulation(a) The fuzzy logic technique is used toestablish communication between AVRand PSS increasing the reliability andregulation of the voltage by means of aunit signal.
  9. [10]5 Comparison ofSTATCOM and SVClinked to multi-machinenetwork in wind farms(a) Instability of wind farmintegrated system. (b) Problem dueto Three phases to ground fault atdifferent location.(a) Result of examination shows thatFLC has better execution with lessovershoot during transientshortcomings. (b) STATCOM givespreferred execution over SVC.
  10. [11]6 DFIG wind turbine withintegrating STATCOMand BESS (fuzzy controltechnique)(a) Problem related to reactivepower compensation (b)Fluctuations generated due tohybrid systemSTATCOM acquaints current with thenetwork and evacuate the symphoniouspiece of enlistment generator currentand burden current.
  11. [12]7 DFIG using STATCOM(static compensator)(a) Voltage swell/sag/harmonics(b) Switching functions (c) Issuedue step load change.(a) Static synchronous compensator isutilised to settle the lattice voltage afterframework side unsettling influences (b)It also provides mitigation of voltagefluctuations and flicker emission atfaster rate.
  12. [13]8 DFIG wind farm withSTATCOMStability analysis STATCOM is used for active andreactive compensation consideringtransient conditions.[19]9 DFIG wind farmSTATCOM with PIDfuzzy logic controllerStability control with fuzzySTATCOMSTATCOM with fuzzy logic controlleris used for active and reactivecompensation.[20]can result in protection malfunction, burdening apparatus,and insulation breakdown.This paper is ordered as follows: Section 1 givesintroduction and related work. DFIG-based wind farmand FLC for STATCOM is described in Sections 2 and3 followed by result and discussion in Section 4. Finally,conclusion and references are provided to conclude thepaper.173Figure 1. Offshore wind farm single line representation.2. DFIG-based Wind FarmAs nature of wind energy is unpredictable so nowadaysVSWT is widely used. Mathematical modelling of VSWTcan be found in [19]. Among various VSWT, DFIG hasnumerous advantages as compared to SCIG and PMSG-based wind turbine due to presence of gear box and it canplay a very important role in extracting wind energy andmaximise power at the output. DFIG also has advantage ofactive and reactive power control and reduced mechanicalstress. The essential part of DFIG is rotor side converter(RSC) which control active and reactive power and gridside converter (GSC) control the dc link voltage. The activeand reactive power can be controlled via RSC. GSC, on theother hand, is in charge of regulating the DC link voltage.The mechanical power generated by wind turbine (P)is:P =12adAcvwind2(1)where ad is the density of air, A is the swept area, c is theperformance coefficient, and vwind is the average value ofwind speed.In the present work, framework is made in MAT-LAB/Simulink and afterward it is examined for differentvarious conditions. The matrix model comprises of 132KV, 60 Hz framework flexibly point, which is taking careof a 25 KV appropriation framework through 132–25 KV,47 MVA venture down transformer. This progression downtransformer is taking care of 575 V conveyance frameworkthrough 25 KV–575 V, 12 MVA transformer and afterwardit is associated with DFIG generator of 45 MW rating asshown in Fig. 1.3. Fuzzy Logic Control TechniqueFuzzy logic control (FLC) technique is one of the robustcontrol techniques and has been widely used to enhanceTable 2Fuzzy Rule Base TableCE C B N M N S N Z S P M P B PB N B N B N B N B N M N S N ZM N B N B N B N M N S N Z S PS N B N B N M N S N Z S P M PZ B N M N S N Z S P M P B PS P M N S N Z S P M P B P B PM P S N Z S P M P B P B P B PB P Z S P M P B P B P B P B Pperformance of STATCOM by controlling the PI controllerparameter
  13. [14]. Researchers in power system domain haveextensively used fuzzy logic [28], [29]. Core of any FLCtechniques is fuzzy inference system (FIS). There are twotypes of FIS and they are Madmani FIS and Sugeno FIS
  14. [15]. In this paper, Mamdani FIS is used to design FLC thatcontrol quadrature axis reference current (Iq) of STAT-COM. We have used error voltage (E) and change of error(CE) as input and Iq as output to design FLC controller.The input and output membership function consists ofseven linguist of triangular type
  15. [16]. Table 2 details thefuzzy rule base used to design FLC where B N, M N, andS N represent Negative quantity (C, CE, and Iq) which isBIG, MEDIUM, and SMALL; Z represent Zero quantity;and S P, M P, and B P represent Positive quantity whichis BIG, MEDIUM, and SMALL linguistically.3.1 FLC STATCOMStatic synchronous compensator has been connected inshunt for reactive power control. It is a solid-state switching174Figure 2. MATLAB/Simulink model of FLC-based SATCOM.Figure 3. DFIG terminal voltage during fault.device that can store energy at input terminals
  16. [17]. Thereactive current which may be occurred at the output canbe independently controlled by system AC voltage. Havingvoltage source inverter driven by a DC storage capacitorwhich produce DC voltages
  17. [19]9 DFIG wind farmSTATCOM with PIDfuzzy logic controllerStability control with fuzzySTATCOMSTATCOM with fuzzy logic controlleris used for active and reactivecompensation.
  18. [20]can result in protection malfunction, burdening apparatus,and insulation breakdown.This paper is ordered as follows: Section 1 givesintroduction and related work. DFIG-based wind farmand FLC for STATCOM is described in Sections 2 and3 followed by result and discussion in Section 4. Finally,conclusion and references are provided to conclude thepaper.173Figure 1. Offshore wind farm single line representation.2. DFIG-based Wind FarmAs nature of wind energy is unpredictable so nowadaysVSWT is widely used. Mathematical modelling of VSWTcan be found in [19]. Among various VSWT, DFIG hasnumerous advantages as compared to SCIG and PMSG-based wind turbine due to presence of gear box and it canplay a very important role in extracting wind energy andmaximise power at the output. DFIG also has advantage ofactive and reactive power control and reduced mechanicalstress. The essential part of DFIG is rotor side converter(RSC) which control active and reactive power and gridside converter (GSC) control the dc link voltage. The activeand reactive power can be controlled via RSC. GSC, on theother hand, is in charge of regulating the DC link voltage.The mechanical power generated by wind turbine (P)is:P =12adAcvwind2(1)where ad is the density of air, A is the swept area, c is theperformance coefficient, and vwind is the average value ofwind speed.In the present work, framework is made in MAT-LAB/Simulink and afterward it is examined for differentvarious conditions. The matrix model comprises of 132KV, 60 Hz framework flexibly point, which is taking careof a 25 KV appropriation framework through 132–25 KV,47 MVA venture down transformer. This progression downtransformer is taking care of 575 V conveyance frameworkthrough 25 KV–575 V, 12 MVA transformer and afterwardit is associated with DFIG generator of 45 MW rating asshown in Fig. 1.3. Fuzzy Logic Control TechniqueFuzzy logic control (FLC) technique is one of the robustcontrol techniques and has been widely used to enhanceTable 2Fuzzy Rule Base TableCE C B N M N S N Z S P M P B PB N B N B N B N B N M N S N ZM N B N B N B N M N S N Z S PS N B N B N M N S N Z S P M PZ B N M N S N Z S P M P B PS P M N S N Z S P M P B P B PM P S N Z S P M P B P B P B PB P Z S P M P B P B P B P B Pperformance of STATCOM by controlling the PI controllerparameter [14]. Researchers in power system domain haveextensively used fuzzy logic [28], [29]. Core of any FLCtechniques is fuzzy inference system (FIS). There are twotypes of FIS and they are Madmani FIS and Sugeno FIS[15]. In this paper, Mamdani FIS is used to design FLC thatcontrol quadrature axis reference current (Iq) of STAT-COM. We have used error voltage (E) and change of error(CE) as input and Iq as output to design FLC controller.The input and output membership function consists ofseven linguist of triangular type [16]. Table 2 details thefuzzy rule base used to design FLC where B N, M N, andS N represent Negative quantity (C, CE, and Iq) which isBIG, MEDIUM, and SMALL; Z represent Zero quantity;and S P, M P, and B P represent Positive quantity whichis BIG, MEDIUM, and SMALL linguistically.3.1 FLC STATCOMStatic synchronous compensator has been connected inshunt for reactive power control. It is a solid-state switching174Figure 2. MATLAB/Simulink model of FLC-based SATCOM.Figure 3. DFIG terminal voltage during fault.device that can store energy at input terminals [17]. Thereactive current which may be occurred at the output canbe independently controlled by system AC voltage. Havingvoltage source inverter driven by a DC storage capacitorwhich produce DC voltages [18].Figure 2 shows Simulink model of FLC controllerbased on STATCOM. Here, system voltage is comparedwith reference voltage to generate error signal. This errorand time rate of CE are used as input for FLC and resultsin reactive reference current Iqr. This Iqr is then comparedwith reactive current of STATCOM and the output is usedto control PWM inverter.4. Result and Discussion4.1 Case 1: Simulation Results under NormalConditionWhen our test structure is exposed to 3-phase fault wesee the various condition we see DFIG terminal voltageis 1.002 p.u. which is decrease to 0.757 p.u. duringfault and after fault, i.e., 3.2 s which is settled to1.002 with FLC STATCOM as we compare that duringfault without STATCOM voltage across DFIG terminal isdecreases to 0.558 which can be improved to 0.760 withSTATCOM which can be further improved to 0.775 withFLC STATCOM. Similarly, change in active power whichis 43.8 MW without any STATCOM and trip during fault,can be improved by STATCOM (improvement from −8.2MW) which can be further improved to −7.0 MW withthe help of FLC STATCOM. The aforementioned cases areshown in Figs. 3–5. Bus voltages B1, B2, and B3 in p.u.(a) without STATCOM, (b) with STATCOM, and (c) withFLC STACOM are listed in Table 3.From Table 3, it is evident that fuzzy logic controlled-based STATCOM gives best result (among the threetechniques used) for bus voltages. In all the simulation,maximum pitch angle was 32.6◦.4.2 Case 2: Simulation Results under VoltageSagging ConditionA heavy inductive load for 0.2 s results in voltage sag in thesystem. During voltage sag, the DFIG terminal voltage isshown in Fig. 6. Figures 7 and 8 show active and reactivepower profile during voltage sag, respectively. From Figs. 7and 8, it can be observed that FLC STATCOM gives bestresult in terms of handling active and reactive power undervoltage sag.175Figure 4. DFIG active power during fault.Figure 5. DFIG reactive power during fault.Table 3Value of Different Parameter of Test System during LLLG FaultParameters Without STATCOM With STATCOM With FLC STATCOMBeforeFaultDuringFaultAfterFaultBeforeFaultDuringFaultAfterFaultBeforeFaultDuringFaultAfterFaultVDF IG(p.u.) 0.995 0.558 0.893 0.995 0.760 0.994 1.000 0.775 1.000VB1(p.u.) 0.972 0.570 0.911 0.972 0.598 0.971 0.997 0.620 0.997VB2(p.u.) 0.960 0.440 0.900 0.960 0.480 0.960 0.990 0.510 0.990VB3(p.u.) 0.969 0.558 0.893 0.969 0.631 0.968 1.000 0.689 1.000PDF IG(MW ) 43.8 Trip Trip 43.8 –8.2 43.8 43.9 –7 43.9QDF IG(MV AR) 13.1 Trip Trip –4.2 26.4 –4.2 13.1 25.1 13.1Table 4 details the finding of handling voltage sag andits effects on active and reactive power. From the table, itis evident that FLC STATCOM outperforms STATCOMand DFIG in controlling voltage sag.4.3 Case 3: Simulation Results under VoltageSwelling ConditionA large capacitive load for 0.2 s (i.e., during 3 s to 3.2s) is exposed to the system to get voltage swell. If theterminal bus voltage exceeds 1.2 p.u., the DFIG protectionmechanism will trip. Figures 9–11 show terminal voltage,active power, and reactive power variation, respectively,for DFIG, DFIG with STATCOM, and DFIG with FLCSTACOM. From these figures, we can conclude that FLCSTATCOM outperforms other two methods. Quantitativeanalysis of parameters obtained for voltage swell caseis reported in Table 5. The improvement in values ofparameters of the system for the above discussed casestudies is reported in Table 6.176Figure 6. DFIG terminal voltage during voltage sag.Figure 7. DFIG active power during voltage sag.Figure 8. DFIG reactive power during voltage sag.5. ConclusionThis work shows improvement of transient stability of aDFIG-based wind farm connected power system networkthrough reactive power compensation via STATCOM.Wind DFIG could not maintain its stability withoutreactive power support during transients; however, itbecame stable when coupled with STATCOM. The STAT-COM also aids in the improvement of the test system’sbus voltage profile. It also boosts DFIG’s operatingpower factor. Use of fuzzy logic with STATCOM devicecan improve the aforesaid STATCOM performance. Theproposed researcher investigated dynamic performanceof a DFIG-based wind turbine connected to nine bus177Table 4Value of Several Parameter of Studied System during Voltage SagParameter Without STATCOM With STATCOM With FLC STATCOMBeforeSagDuringSagAfterSagBeforeSagDuringSagAfterSagBeforeSagDuringSagAfterSagVDF IG(p.u.) 0.995 0.510 0.892 0.995 0.710 0.990 1.001 0.750 1.001VB1(p.u.) 0.966 0.523 0.911 0.981 0.568 0.968 0.997 0.587 0.997VB2(p.u.) 0.959 0.196 0.897 0.897 0.210 0.970 0.994 0.220 0.990VB3(p.u.) 0.962 0.538 0.892 0.892 0.645 0.892 1.001 0.679 1.001PDF IG(MW ) 43.8 TRIP TRIP 43.8 −0.6 43.8 43.9 −0.5 43.9QDF IG(MV AR) −2.8 TRIP TRIP 12.6 26.3 −2.8 12.3 25.3 12.3Figure 9. DFIG terminal voltage during voltage swell condition.Figure 10. DFIG active power during voltage swell condition.Figure 11. DFIG reactive power during voltage swell condition.178Table 5Value of Several Parameter of Studied System during Voltage SwellParameter Without STATCOM With STATCOM With FLC STATCOMBeforeSwellDuringSwellAfterSwellBeforeSwellDuringSwellAfterSwellBeforeSwellDuringSwellAfterSwellVDF IG(pu.) 0.994 1.48 0.892 0.994 1.08 0.990 1.001 1.03 1.001VB1(p.u.) 0.970 1.80 0.911 0.970 1.61 0.970 1.001 1.55 1.001VB2(p.u.) 0.967 2.86 0.900 0.960 2.50 0.999 0.994 2.456 0.960VB3(p.u.) 0.962 1.65 0.892 1.01 1.56 1.01 0.962 1.53 0.962PDF IG(MW ) 43.8 103.6 TRIP 43.8 92.8 43.8 43.9 85 43.8QDF IG(MV AR) −2.8 −76.6 −2.8 12.6 −70.6 0 12.6 −65.6 12.6Table 6Case Study of Percentage Improvement between Case 1, Case 2, and Case 3Parameter Percentage Improvement withFLC-SATCOM as Compared toSTATCOM during FaultPercentage Improvement withFLC-SATCOM as Compared toSTATCOM during SagPercentage Improvement withFLC-SATCOM as Compared toSTATCOM during SwellVDF IG(P U) 1.97% 5.63% 4.62%VB1(P U) 3.68% 3.34% 3.61%VB2(P U) 6.25% 4.76% 1.76%VB3(P U) 9.19% 5.27% 1.92%PDF IG(MW ) 14.63% 16.66% 8.42%QDF IG(MV ARs) 4.92% 3.802% 7.08%systems using three methods: (a) without STATCOM, (b)with STATCOM, and (c) with fuzzy driven STATCOM.STATCOM was used at the point of common coupling(PCC) in this study to maintain voltage and enhancepower quality by preventing a DFIG-based wind farmlinked to a weak grid from collapsing during faults andafter disturbances. A STATCOM with FLC was used inconjunction with a PI controller and an FLC to improvethe power stability of a two-area four generator linkedpower system. Study shows FLC STATCOM outperformsSTATCOM and DFIG in terms of handling faults andhence stable operation of wind farm. In the future, advanceAI techniques like reinforcement learning and its variant
  19. [21],
  20. [22] that learns its control action by trial and errorcan be used along with STATCOM.References[1] M. A. Mohamed, A. M. Eltamaly, and A. I. Alolah,“Sizing and techno-economic analysis of stand-alone hybridphotovoltaic/wind/diesel/battery power generation systems,”Journal of Renewable and Sustainable Energy, 7(6), 2015,63128, doi: 10.1063/1.4938154.[2] Ren21, Renewables, “Global status report,” REN21 secretariat,Paris, 2016.[3] S. Muller, M. Deicke, and R. W. De Doncker, “Doublyfed induction generator systems for wind turbines,” IEEEIndustry Applications Magazine, 8(3), May 2002, 26–33, doi:10.1109/2943.999610.[4] M. Tazil, V. Kumar, R. C. Bansal, S. Kong, Z. Y. Dong, W.Freitas, and H. D. Mathur, “Three-phase doubly fed inductiongenerators: An overview,” IET Electric Power Applications,4(2), 2010, 75–89.[5] H. T. Jadhav and R. Roy, “A comprehensive review on the gridintegration of doubly fed induction generator,” InternationalJournal of Electrical Power & Energy Systems, 49, 2013,8–18.[6] V. V. G. Krishnan, S. C. Srivastava, and S. Chakrabarti, “Arobust decentralized wide area damping controller for windgenerators and FACTS controllers considering load modeluncertainties,” IEEE Transactions on Smart Grid, 9(1), 2018,360–372.[7] C. D. Le and M. H. J. Bollen, “Ride-through of inductiongenerator based wind park with switched capacitor, SVC, orSTATCOM,” Proc. IEEE PES General Meeting, Minneapolis,MN, 2010, 1–7.[8] M. Stiebler, “PM synchronous generator with diode rectifier forwind systems using FACTS compensators,” Proc. Int. Symp.on Power Electronics Power Electronics, Electrical Drives,Automation and Motion, Sorrento, 2012, 1295–1300.[9] L. Qi, J. Langston, and M. Steurer, “Applying a STATCOMfor stability improvement to an existing wind farm with fixed-speed induction generators,” Proc. IEEE Power and EnergySociety General Meeting-Conversion and Delivery of ElectricalEnergy in the 21st Century, Pittsburgh, PA, 2008, 1–6.[10] M. Laouer, A. Mekkaoui, and M. Younes, “STATCOM andcapacitor banks in a fixed speed wind farm,” Energy Procedia,50, 2014, 882–892.179[11] S. M. Abd-Elazim and E. S. Ali, “Imperialist competitivealgorithm for optimal STATCOM design in a multimachinepower system,” International Journal of Electrical Power &Energy Systems, 76, 2016, 136–146.[12] K. B. Mohanty and S. Pati, “Fuzzy logic controller basedSTATCOM for voltage profile improvement in a micro-grid,”Proc. Annual IEEE Systems Conf. (SysCon), Orlando, FL,2016, 1–6.[13] L. Wang and D.-N. Truong, “Stability enhancement of DFIG-based offshore wind farm fed to a multi-machine system usinga STATCOM,” IEEE Transactions on Power Systems, 28(3),2013, 2882–2889.[14] M. Narimani and R. K. Varma, “Application of static varcompensator (SVC) with fuzzy controller for grid integration ofwind farm,” Proc. Canadian Conf. on Electrical and ComputerEngineering, Calgary, AB, 2010, 1–6.[15] Y. Bai and D. Wang, “Fundamentals of fuzzy logic control—Fuzzy sets, fuzzy rules and defuzzifications,” in Advanced fuzzylogic technologies in industrial applications, (London: Springer,2006), 17–36.[16] M. G. Hemeida, H. Rezk, and M. M. Hamada, “A comprehensivecomparison of STATCOM versus SVC-based fuzzy controllerfor stability improvement of wind farm connected to multi-machine power system,” Electrical Engineering, 100(2), 2018,935–951.[17] N. Sreekanth and N. P. K. Reddy, “PI Fuzzy logic basedcontrollers STATCOM for grid connected wind generator,”International Journal of Engineering Research and Applica-tions, 2(5), 2012, 617–623.[18] M. Laouer, A. Mekkaoui, and M. Younes, “STATCOM andcapacitor banks in a fixed-speed wind farm,” Energy Procedia,50, 2014, 882–892.[19] V. Kumar, V. Patel, A. S. Pandey, S. K. Sinha, and D. Kuma,,“Transient stability enhancement of DFIG based offshore windfarm connected to a power system network using STATCOM,”International Journal of Engineering & Technology, 7, 2018,1303–1311.[20] C. Pal, V. Kumar, and A.K. Yadav, “Comparative analysis ofDFIG based wind farm connected power system using fuzzycontroller based FACTS,” International Journal for Researchin Applied Science & Engineering Technology, 8, 2020, 813–818.[21] A. Kumar, “Reinforcement learning: Theory and applicationin control engineering,” Positif Journal, 22, 2022, 60–68.[22] A. Kumar, R. Sharma, and P. Varshney, “Lyapunov fuzzyMarkov game controller for two link robotic manipulator,”Journal of Intelligent & Fuzzy Systems, 34(3), 2018, 1479–1490,doi: 10.3233/JIFS-169443.
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  25. [28],
  26. [29]. Core of any FLCtechniques is fuzzy inference system (FIS). There are twotypes of FIS and they are Madmani FIS and Sugeno FIS[15]. In this paper, Mamdani FIS is used to design FLC thatcontrol quadrature axis reference current (Iq) of STAT-COM. We have used error voltage (E) and change of error(CE) as input and Iq as output to design FLC controller.The input and output membership function consists ofseven linguist of triangular type [16]. Table 2 details thefuzzy rule base used to design FLC where B N, M N, andS N represent Negative quantity (C, CE, and Iq) which isBIG, MEDIUM, and SMALL; Z represent Zero quantity;and S P, M P, and B P represent Positive quantity whichis BIG, MEDIUM, and SMALL linguistically.3.1 FLC STATCOMStatic synchronous compensator has been connected inshunt for reactive power control. It is a solid-state switching174Figure 2. MATLAB/Simulink model of FLC-based SATCOM.Figure 3. DFIG terminal voltage during fault.device that can store energy at input terminals [17]. Thereactive current which may be occurred at the output canbe independently controlled by system AC voltage. Havingvoltage source inverter driven by a DC storage capacitorwhich produce DC voltages [18].Figure 2 shows Simulink model of FLC controllerbased on STATCOM. Here, system voltage is comparedwith reference voltage to generate error signal. This errorand time rate of CE are used as input for FLC and resultsin reactive reference current Iqr. This Iqr is then comparedwith reactive current of STATCOM and the output is usedto control PWM inverter.4. Result and Discussion4.1 Case 1: Simulation Results under NormalConditionWhen our test structure is exposed to 3-phase fault wesee the various condition we see DFIG terminal voltageis 1.002 p.u. which is decrease to 0.757 p.u. duringfault and after fault, i.e., 3.2 s which is settled to1.002 with FLC STATCOM as we compare that duringfault without STATCOM voltage across DFIG terminal isdecreases to 0.558 which can be improved to 0.760 withSTATCOM which can be further improved to 0.775 withFLC STATCOM. Similarly, change in active power whichis 43.8 MW without any STATCOM and trip during fault,can be improved by STATCOM (improvement from −8.2MW) which can be further improved to −7.0 MW withthe help of FLC STATCOM. The aforementioned cases areshown in Figs. 3–5. Bus voltages B1, B2, and B3 in p.u.(a) without STATCOM, (b) with STATCOM, and (c) withFLC STACOM are listed in Table 3.From Table 3, it is evident that fuzzy logic controlled-based STATCOM gives best result (among the threetechniques used) for bus voltages. In all the simulation,maximum pitch angle was 32.6◦.4.2 Case 2: Simulation Results under VoltageSagging ConditionA heavy inductive load for 0.2 s results in voltage sag in thesystem. During voltage sag, the DFIG terminal voltage isshown in Fig. 6. Figures 7 and 8 show active and reactivepower profile during voltage sag, respectively. From Figs. 7and 8, it can be observed that FLC STATCOM gives bestresult in terms of handling active and reactive power undervoltage sag.175Figure 4. DFIG active power during fault.Figure 5. DFIG reactive power during fault.Table 3Value of Different Parameter of Test System during LLLG FaultParameters Without STATCOM With STATCOM With FLC STATCOMBeforeFaultDuringFaultAfterFaultBeforeFaultDuringFaultAfterFaultBeforeFaultDuringFaultAfterFaultVDF IG(p.u.) 0.995 0.558 0.893 0.995 0.760 0.994 1.000 0.775 1.000VB1(p.u.) 0.972 0.570 0.911 0.972 0.598 0.971 0.997 0.620 0.997VB2(p.u.) 0.960 0.440 0.900 0.960 0.480 0.960 0.990 0.510 0.990VB3(p.u.) 0.969 0.558 0.893 0.969 0.631 0.968 1.000 0.689 1.000PDF IG(MW ) 43.8 Trip Trip 43.8 –8.2 43.8 43.9 –7 43.9QDF IG(MV AR) 13.1 Trip Trip –4.2 26.4 –4.2 13.1 25.1 13.1Table 4 details the finding of handling voltage sag andits effects on active and reactive power. From the table, itis evident that FLC STATCOM outperforms STATCOMand DFIG in controlling voltage sag.4.3 Case 3: Simulation Results under VoltageSwelling ConditionA large capacitive load for 0.2 s (i.e., during 3 s to 3.2s) is exposed to the system to get voltage swell. If theterminal bus voltage exceeds 1.2 p.u., the DFIG protectionmechanism will trip. Figures 9–11 show terminal voltage,active power, and reactive power variation, respectively,for DFIG, DFIG with STATCOM, and DFIG with FLCSTACOM. From these figures, we can conclude that FLCSTATCOM outperforms other two methods. Quantitativeanalysis of parameters obtained for voltage swell caseis reported in Table 5. The improvement in values ofparameters of the system for the above discussed casestudies is reported in Table 6.176Figure 6. DFIG terminal voltage during voltage sag.Figure 7. DFIG active power during voltage sag.Figure 8. DFIG reactive power during voltage sag.5. ConclusionThis work shows improvement of transient stability of aDFIG-based wind farm connected power system networkthrough reactive power compensation via STATCOM.Wind DFIG could not maintain its stability withoutreactive power support during transients; however, itbecame stable when coupled with STATCOM. The STAT-COM also aids in the improvement of the test system’sbus voltage profile. It also boosts DFIG’s operatingpower factor. Use of fuzzy logic with STATCOM devicecan improve the aforesaid STATCOM performance. Theproposed researcher investigated dynamic performanceof a DFIG-based wind turbine connected to nine bus177Table 4Value of Several Parameter of Studied System during Voltage SagParameter Without STATCOM With STATCOM With FLC STATCOMBeforeSagDuringSagAfterSagBeforeSagDuringSagAfterSagBeforeSagDuringSagAfterSagVDF IG(p.u.) 0.995 0.510 0.892 0.995 0.710 0.990 1.001 0.750 1.001VB1(p.u.) 0.966 0.523 0.911 0.981 0.568 0.968 0.997 0.587 0.997VB2(p.u.) 0.959 0.196 0.897 0.897 0.210 0.970 0.994 0.220 0.990VB3(p.u.) 0.962 0.538 0.892 0.892 0.645 0.892 1.001 0.679 1.001PDF IG(MW ) 43.8 TRIP TRIP 43.8 −0.6 43.8 43.9 −0.5 43.9QDF IG(MV AR) −2.8 TRIP TRIP 12.6 26.3 −2.8 12.3 25.3 12.3Figure 9. DFIG terminal voltage during voltage swell condition.Figure 10. DFIG active power during voltage swell condition.Figure 11. DFIG reactive power during voltage swell condition.178Table 5Value of Several Parameter of Studied System during Voltage SwellParameter Without STATCOM With STATCOM With FLC STATCOMBeforeSwellDuringSwellAfterSwellBeforeSwellDuringSwellAfterSwellBeforeSwellDuringSwellAfterSwellVDF IG(pu.) 0.994 1.48 0.892 0.994 1.08 0.990 1.001 1.03 1.001VB1(p.u.) 0.970 1.80 0.911 0.970 1.61 0.970 1.001 1.55 1.001VB2(p.u.) 0.967 2.86 0.900 0.960 2.50 0.999 0.994 2.456 0.960VB3(p.u.) 0.962 1.65 0.892 1.01 1.56 1.01 0.962 1.53 0.962PDF IG(MW ) 43.8 103.6 TRIP 43.8 92.8 43.8 43.9 85 43.8QDF IG(MV AR) −2.8 −76.6 −2.8 12.6 −70.6 0 12.6 −65.6 12.6Table 6Case Study of Percentage Improvement between Case 1, Case 2, and Case 3Parameter Percentage Improvement withFLC-SATCOM as Compared toSTATCOM during FaultPercentage Improvement withFLC-SATCOM as Compared toSTATCOM during SagPercentage Improvement withFLC-SATCOM as Compared toSTATCOM during SwellVDF IG(P U) 1.97% 5.63% 4.62%VB1(P U) 3.68% 3.34% 3.61%VB2(P U) 6.25% 4.76% 1.76%VB3(P U) 9.19% 5.27% 1.92%PDF IG(MW ) 14.63% 16.66% 8.42%QDF IG(MV ARs) 4.92% 3.802% 7.08%systems using three methods: (a) without STATCOM, (b)with STATCOM, and (c) with fuzzy driven STATCOM.STATCOM was used at the point of common coupling(PCC) in this study to maintain voltage and enhancepower quality by preventing a DFIG-based wind farmlinked to a weak grid from collapsing during faults andafter disturbances. 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