Mitigation of Voltage Sag and Swell in Transmission Line using DPFC with PI and Fuzzy Logic Control

 

ABSTRACT:

The Power Quality problems during the last two decades has been the major concern of the power companies. The operation of power systems has become complex due to growing consumption and increased number of non-linear loads because of which compensation of multiple power quality issues has become an compulsion. A new component within the flexible AC-transmission system (FACTS) family, called Distributed Power-flow controller (DPFC) is presented in this paper. DPFC is derived from the unified power-flow controller (UPFC). DPFC can be considered as a UPFC with an eliminated common dc link. The active power exchange between the shunt and series converters, which is through the common dc link in the UPFC, is now through the transmission lines at the third-harmonic frequency. The DPFC employs the distributed FACTS (D-FACTS) concept, which is to use multiple small-size single-phase converters instead of the one large-size three-phase series converter in the UPFC. Power quality issues are studied and DPFC is used to mitigate the voltage deviation and improve power quality. In this paper, the capability of DPFC is observed for the transmission line based on PI and fuzzy logic controllers (FLC). On comparing the two controllers performance, we can say that Fuzzy Logic Controller based DPFC gives better compensation than PI Controller based DPFC. Simulink models are developed with and without the controllers. The three phase fault is created near the load. Simulation results show the effectiveness between the two controllers.

KEYWORDS:

  1. Power Quality
  2. D-FACTS
  3. DPFC
  4. Voltage Sag
  5. Swell
  6. PI Controller
  7. Fuzzy Logic Controller

SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

Fig 1: The DPFC Structure

EXPECTED SIMULATION RESULTS:

 

Fig 2: Voltage Sag without DPFC

Fig 3: Current Swell without DPFC

Fig 4: THD without DPFC

Fig 5: Voltage sag Compensation with DPFC using PI Controller

Fig 6: Current Swell Compensation with DPFC using PI Controller

Fig 7: THD with DPFC using PI Controller

Fig 8: Voltage Sag Compensation with DPFC using Fuzzy Logic Controller

Fig 9: Current Swell Compensation with DPFC using Fuzzy Logic Controller

Fig 10: THD with DPFC using Fuzzy Logic Controller

CONCLUSION:

In this study mitigation of power quality issues like voltage sag and swell are simulated in Matlab/Simulink environment employing a new FACTS device called Distributed Power Flow Controller(DPFC). The DPFC is emerged from the UPFC and inherits the control capability of the UPFC, which is the simultaneous adjustment of the line impedance, the transmission angle, and the bus voltage magnitude. The common dc link between the shunt and series converters, which is used for exchanging active power in the UPFC, is eliminated. This power is now transmitted through the transmission line at the third harmonic frequency. The series converter of the DPFC employs the D FACTS concept, which uses multiple small single phase converters instead of one large size converter. The reliability of the DPFC is greatly increased because of the redundancy of the series converters. The total cost of the DPFC is also much lower than the UPFC, because no high voltage isolation is required at the series converter part and the rating of the components of is low. It is proved that the shunt and series converters in the DPFC can exchange active power at the third harmonic frequency, and the series converters are able to inject controllable active and reactive power at the fundamental frequency .Also the performance of DPFC is simulated using two mechanisms i.e., with PI and Fuzzy Logic controllers.The results prove that the DPFC with Fuzzy controller gives better voltage compensation than DPFC with PI controller.

REFERENCES:

[1] Zhihui Yuan, Sjoerd W.H de Haan, Braham Frreira and Dalibor Cevoric “A FACTS Device: Distributed Power Flow Controller (DPFC)” IEEE Transaction on Power Electronics, vol.25, no.10,October 2010.

[2] Krishna Mohan Tatikonda,N.Swathi,K.Vijay Kumar”A Fuzzy Control scheme for damping of oscillations in multi machine system using UPFC” International trends for emerging trends in engineering and development on September 2012

[3] Y. H. Song and A. Johns. Flexible ac transmission systems (FACTS). Institution of Electrical Engineers, 1999.

[4] ” Power quality improvement and Mitigation case study using Distributed Power Flow Controller “Ahmad Jamshidi ,S.Masoud Barakati and Mohammad Moradi Ghahderijani,IEEE Transactions on,2012

[5] N.G.Hingorani and L.Gyugyi, Understanding FACTS, Concepts and Technology of Flexible AC Transmission Systems. Piscataway, NJ: IEEE Press 2000

Speed Control of Induction Motor Using New Sliding Mode Control Technique

ABSTRACT

Induction Motors have been used as the workhorse in the industry for a long time due to its easy build, high robustness, and generally satisfactory efficiency. However, they are significantly more difficult to control than DC motors. One of the problems which might cause unsuccessful attempts for designing a proper controller would be the time varying nature of parameters and variables which might be changed while working with the motion systems. One of the best suggested solutions to solve this problem would be the use of Sliding Mode Control (SMC). This paper presents the design of a new controller for a vector control induction motor drive that employs an outer loop speed controller using SMC. Several tests were performed to evaluate the performance of the new controller method, and two other sliding mode controller techniques. From the comparative simulation results, one can conclude that the new controller law provides high performance dynamic characteristics and is robust with regard to plant parameter variations.

 

KEYWORDS:

  1. Induction Motor
  2. Sliding Mode Control
  3. DC Motors
  4. PI Controller

 

SOFTWARE: MATLAB/SIMULINK

 

BLOCK DIAGRAM:

Induction motor drive system with sliding mode controller

Fig. 1 Induction motor drive system with sliding mode controller

EXPECTED SIMULATION RESULTS:

                           Rotor speed tracking performance (b)Rotor speed tracking error (c)Control effort Rotor speed tracking performance (b)Rotor speed tracking error (c)Control effort Rotor speed tracking performance (b)Rotor speed tracking error (c)Control effort

Fig.2 (a)Rotor speed tracking performance  (b)Rotor speed tracking error   (c)Control effort

image005 image006 image007

Fig.3 (a)Rotor speed tracking performance  (b)Rotor speed tracking error   (c)Control effort

image008 image009 image010

Fig.4 (a)Rotor speed tracking performance  (b)Rotor speed tracking error   (c)Control effort

 

CONCLUSION

In this paper, new technique to reduced chattering for sliding mode control is submitted to design the rotor speed control of induction motor. To validate the performances of the new proposed control law, we provided a series of simulations and a comparative study between the performances of the new proposed sliding mode controller strategy and those of the Pseudo and Saturation sliding mode controller techniques. The sliding mode controller algorithms are capable of high precision rotor speed tracking. From the comparative simulation results, one can conclude that the three sliding mode controller techniques demonstrate nearly the same dynamic behavior under nominal condition. Also, from the simulation results, it can be seen obviously that the control performance of the new sliding mode controller strategy in the rotor speed tracking, robustness to parameter variations is superior to that of the other sliding mode controller techniques.

 

REFERENCES

  1. Wade, M.W.Dunnigan, B.W.Williams, X.Yu, ‘Position control of a vector controlled induction machine using slotine’s sliding mode control’, IEE Proceeding Electronics Power Application, Vol. 145, No.3, pp.231-238, 1998.
  2. I.Utkin, ‘Sliding mode control design principles and applications to electric drives’, IEEE Transactions on Industrial Electronics, Vol.40, No.1, pp. 23-36, February 1993.
  3. K.Namdam, P.C.Sen, ‘Accessible states based sliding mode control of a variable speed drive system’, IEEE Transactions Industry Application, Vol.30, August 1995, pp.373-381.
  4. Krishnan, ‘Electric motor drives: modelling, analysis, and control’, Prentice-Hall, New-Jersey, 2001.
  5. J.Wai, K.H.Su, C.Y.Tu, ‘Implementation of adaptive enhanced fuzzy sliding mode control for indirect field oriented induction motor drive’, IEEE International Conference on Fuzzy Systems, pp.1440-1445, 2003.

 

Speed Controller of Switched Reluctance Motor

ABSTRACT

Fuzzy logic control has become an important methodology in control engineering. The paper proposes a Fuzzy Logic Controller (FLC) for controlling a speed of SRM drive. The objective of this work is to compare the operation of P& PI based conventional controller and Artificial Intelligence (AI) based fuzzy logic controller to highlight the performances of the effective controller. The present work concentrates on the design of a fuzzy logic controller for SRM speed control. The result of applying fuzzy logic controller to a SRM drive gives the best performance and high robustness than a conventional P & PI controller. Simulation is carried out using Matlab/Simulink.

 

KEYWORDS: P Controller, PI Controller, Fuzzy Logic Controller, Switched Reluctance Motor

 

SOFTWARE: MATLAB/SIMULINK

 

BLOCK DIAGRAM

Block diagram of SRM speed control

Figure 1. Block diagram of SRM speed control

 

 SIMULATION MODELS

Simulation model using P controller

Figure 2. Simulation model using P controller

Simulation model using PI controller.

Figure 3. Simulation model using PI controller.

Simulink model using FLC.

Figure 4. Simulink model using FLC.

 

SIMULATION RESULTS

Output flux.

Figure 5. Output flux.

Output current

Figure 6. Output current

Output torque

Figure 7. Output torque.

Speed

Figure 8. Speed.

 

CONCLUSION

Thus the SRM dynamic performance is forecasted and by using MATLAB/simulink the model is simulated. SRM has been designed and implemented for its speed control by using P, PI controller and AI based fuzzy logic controller. We can conclude from the simulation results that when compared with P & PI controller, the fuzzy Logic Controller meet the required output. This paper presents a fuzzy logic controller to ensure excellent reference tracking of switched reluctance motor drives. The fuzzy logic controller gives a perfect speed tracking without overshoot and enchances the speed regulation. The SRM response when controlled by FLC is more advantaged than the conventional P& PI controller.

 

REFERENCES

  1. Susitra D, Jebaseeli EAE, Paramasivam S. Switched reluctance generator – modeling, design, simulation, analysis and control -a comprehensive review. Int J Comput Appl. 2010; 1(210):975–8887.
  2. Susitra D., Paramasivam S. Non-linear flux linkage modeling of switched reluctance machine using MVNLR and ANFIS. Journal of Intelligent and Fuzzy Systems. 2014; 26(2):759–768.
  3. Susitra D, Paramasivam S. Rotor position estimation for a switched reluctance machine from phase flux linkage. IOSR–JEEE. 2012 Nov–Dec; 3(2):7.
  4. Susitra D, Paramasivam S. Non-linear inductance modeling of switched reluctance machine using multivariate non- linear regression technique and adaptive neuro fuzzy inference system. CiiT International Journal of Artificial Intelligent Systems and Machine Learning. 2011 Jun; 3(6).
  5. Ramya A, Dhivya G, Bharathi PD, Dhyaneshwaran R, Ramakrishnan P. Comparative study of speed control of 8/6 switched reluctance motor using pi and fuzzy logic controller. IJRTE; 2012

 

 

 

Indirect Vector Control of Induction Motor Using Sliding-Mode Controller

 

ABSTRACT:

The paper presents a sliding-mode speed control system for an indirect vector controlled induction motor drive for high performance. The analysis, design and simulation of the sliding-mode controller for indirect vector control induction motor are carried out. The proposed sliding-mode controller is compared with PI controller with no load and various load condition. The result demonstrates the robustness and effectiveness of the proposed sliding-mode control for high performance of induction motor drive system.

 KEYWORDS:

  1. Indirect vector control
  2. Sliding mode control
  3. PI controller
  4. Induction motor
  5. Speed control

 SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

image001

Figure 1: Indirect vector controlled induction motor drive

EXPECTED SIMULATION RESULTS:

 image002

Figure 2: Speed response of PI controller at no load

image003

Figure 3:Speed response of Sliding-mode controller at no load

image004

Figure 4: Speed response of PI controller at load

image005

Figure 5: Speed response of Sliding- mode controller at load

image006

Figure 6:X-Y plot of Rotor flux of PI controller

image007

Figure 7: x-v plot of Rotor flux of Sliding-mode controller

CONCLUSION:

In this paper sliding-mode controller for the control of an indirect vector-controlled induction motor was described. The drive system was simulated with sliding-mode controller and PI controller and their performance was compared. Here simulation results shows that the designed sliding-mode controller realises a good dynamic behaviour of the motor with a rapid settling time, no overshoot and has better performance than PI controller. Sliding-mode control has more robust during change in load condition.

.REFERENCES:

[1] B.K Bose “Modern power electronics and ac drives “Prentice-Hall OJ India, New Delhi, 2008.

[2] M.Masiala;B.Vafakhah,;A.Knght,;J.Salmon,;”Performa nce of PI and fuzzy logic speed control of field-oriented induction motor drive,” CCECE , jul. 2007, pp. 397-400.

[3] F.Barrero;A.Gonzalez;A.Torralba,E.Galvan,;L.G.Franqu elo; “Speed control of induction motors using a novel Fuzzy-sliding mode structure,”IEEE Transaction on Fuzzy system, vol. 10, no.3, pp. 375-383, Jun 2002.

[4] H.F.Ho,K.W.E.Cheng, “position control of induction motor using indirect adaptive fuzzy sliding mode control,” P ESA, , Sep. 2009, pp. 1-5.

[5] RKumar,R.A.Gupta,S.V.Bhangale, “indirect vector controlled induction motor drive with fuzzy logic based intelligent controller,” IETECH Journals of Electrical Analysis, vol. 2, no. 4, pp. 211-216, 2008.

 

 

 

Performance Improvement of Single-Phase Grid–Connected PWM Inverter Using PI with Hysteresis Current Controller

 

ABSTRACT:

Now a day’s distributed generation (DG) system uses current regulated PWM voltage-source inverters (VSI) for synchronizing the utility grid with DG source in order to meet the following objectives: 1) To ensure grid stability 2) active and reactive power control through voltage and frequency control 3) power quality improvement (i.e. harmonic elimination) etc. In this paper the comparative study between hysteresis and proportional integral (PI) with hysteresis current controller is presented for 1-Φ grid connected inverter system. The main advantage of hysteresis+PI current controller is low total harmonic distortion (THD) at the point of common coupling (PCC) at a higher band width of the hysteresis band. The studied system is modeled and simulated in the MATLAB Simulink environment.

KEYWORDS:

  1. Hysteresis current controller
  2. PI controller
  3. Point of common coupling (PCC)
  4. DG
  5. Utility grid
  6. THD

 SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

 image001

Fig.1. Block diagram for hysteresis current control of single-phase grid connected VSI

EXPECTED SIMULATION RESULTS:

 image002

 Fig.2. Simulation result of the hysteresis current controller for fixed band (a) grid voltage (Vg) and grid current (Io) (b) reference current, actual current and current error(c) switching frequency

image003

Fig.3. Simulation result of the hysteresis+PI current controller for fixed band (a) grid voltage (Vg) and grid current (Io) (b) reference current, actual current and current error(c) switching frequency

image004

Fig.4. Simulation result of hysteresis current controller for change in band (a) grid current (b) switching frequency(c) current error

image005

Fig.5. Simulation result of hysteresis+PI current controller for change in band (a) grid current (b) switching frequency(c) current error

image006

Fig.6. THD of grid current for hysteresis current controller (a) HB=1(b)HB=3(c)HB=5

image007

Fig.7. THD of grid current for hysteresis+PI current controller (a) HB=1(b) HB=3(c) HB=5

CONCLUSION:

From the study we observed that, hysteresis+PI current controller can enable to reduce switching frequency even if the band width increased without any significant increase in the current error. Hence it provides considerably less THD at higher band width as compared to conventional hysteresis current controller.

REFERENCES:

[1] Blaabjerg, F.; Teodorescu, R.; Liserre, M.; Timbus, A.V., “Overview of Control and Grid Synchronization for Distributed Power Generation Systems” IEEE Transactions on Industrial Electronics,Vol.:53 , Issue:5, Page(s): 1398 – 1409, 2006

[2] F.Blaabjerg, Zhe Chen, and S.B. Kjaer. “Power Electronics as Efficient Interface in Dispersed Power Generation Systems”, IEEE Transactions on Power Electronics, 19(5):1184–1194, Sept. 2004.

[3] Ho, C.N.-M.,Cheung, V.S.P.,Chung, H.S.-H.” Constant-Frequency Hysteresis Current Control of Grid-Connected VSI without Bandwidth Control”,IEEE Trans. on Power Electronics, TPEL 2009,Volume: 24, no. 11 ,, Pp:2484 – 2495, 2009

[4] Rahman, M.A.; Radwan, T.S.; Osheiba, A.M.; Lashine, A.E.; “Analysis of Current Controllers for Voltage-Source Inverter” IEEE Trans. On Industrial Electronics, Volume: 44 , no. 4 , Pp. 477 – 485, ,1997

[5] Tekwani, P.N, Kanchan, R.S., Gopakumar, K.; “Current-error spacevector- based hysteresis PWM controller for three-level voltage source inverter fed drives” Proceedings of Electric Power Applications, IEE Volume: 152 , Issue: 5, Pp: 1283 – 1295,2005

Active Power Factor Correction for Rectifier using Micro-controller

 

ABSTRACT:

Industrialization increases the use of inductive load and hence power system loses its efficiency. Rigid occurrence of mains rectification circuits and the day by day increase in electronics consumers inside the electronic devices enhances the cause of mains harmonic distortion. Power is very precious in the present technological revolution and thus it requires to improve the power factor with a suitable method.This paper presents the simulation and the experimental results for active power factor correction system. Closed loop circuit is simulated in MATLAB using PI controller. The system has been implemented in MATLAB/SIMULINK environment.

 

KEYWORDS:

 

  1. Micro-controller
  2. Power factor correction system
  3. DC-DC boost converter
  4. Total harmonic distortion (THD)
  5. PI controller

 SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

image001

Fig. 1. Circuit diagram of active power factor correction system

EXPECTED SIMULATION RESULTS:

 image002

Fig. 2. Input voltage of conventional converter in PSIM software

image003

Fig. 3. Output voltage of conventional converter in PSIM software

image004

Fig. 4. Output and input current waveform of conventional converter in PSIM software.

image005

Fig. 5. Input current waveform at 15kHz in PSIM software

image006

Fig. 6  Input voltage waveform at 15 kHz in PSIM software.

image007

Fig. 7 . Output voltage waveform at 15kHz in PSIM software.

image008

Fig. 8. Input current waveform in PSIM software.

image009

Fig. 9. Input voltage waveform in PSIM software

image010

Fig. 10. Output voltage waveform in PSIM software.

image011

Fig. 11. Firing pulse for MOSFET IRF640 captured in DSO.

image012

Fig. 12. Input current and voltage waveform captured in DSO.

CONCLUSION:

Analog firing circuit designing makes circuit complex and also it requires the maintenance. Employing microcontroller instead reduces all its disadvantages thus being economical. It is easier to design with precision output. It was very interesting and absorbing to design AC-DC converter in the power electronics laboratory using power MOSFET IRF640.The design is adequate for many purposes. These improvements have been tested in principle, but some detailed work remains to be done in this area. This research work can be extended for the speed control of the motor using PI controller or fuzzy logic controller, Maximum Power Point Tracking (MPPT) using this circuit can be studied later on.

 REFERENCES:

[1] B.K.Bose, “Modern power electronics and AC Drives”, PHI,2001 .

[2] P.C.Sen, “Power Electronics”, Tata McGraw Hill Publishers, 4th edition, 1987.

[3] N.Mohan, T.M.Undeland, W.P.Robbins, “Power Electronics: Converters application and Design”, New York: Wiley, 3rd edition, 2006.

[4] Mohammed E. El-Hawary, “Principles of Electric Machines with Power Electronic Applications”, Wiley India, 2nd edition, 2011.

[5] Gayakwad, “Operational Amplifier”, Prentice Hall of India, 2009.

 

 

 

Sensor Less Speed Control of permanent magnet synchronous motor (PMSM) using SVPWM Technique Based on MRAS Method for Various Speed and Load Variations

ABSTRACT:

The permanent magnet synchronous motor (PMSM) has emerged as an alternative to the induction motor because of the reduced size, high torque to current ratio, higher efficiency and power factor in many applications. Space Vector Pulse Width Modulation (SVPWM) technique is applied to the PMSM to obtain speed and current responses with the variation in load. This paper analysis the structure and equations of PMSM, SVPWM and voltage space vector process. The Model Reference Adaptive System (MRAS) is also studied. The PI controller uses from estimated speed feedback for the speed senseless control of PMSM based on SVPWM with MRAS. The control scheme is simulated in the MATLAB/Simulink software environment. The simulation result shows that the speed of rotor is estimated with high precision and response is considerable fast. The whole control system is effective, feasible and simple.

KEYWORDS:

  1. PMSM
  2. Space vector pulse width modulation
  3. Model reference adaptive system

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Schematic Block of MRAS scheme                      

Fig. 1. Schematic Block of MRAS scheme

Sensor less control block diagram with MRAS system

Fig. 2. Sensor less control block diagram with MRAS system

EXPECTED SIMULATION RESULTS:

Reference and real speed of PMSM

Fig. 3. Reference and real speed of PMSM

Electromagnetic torque of PMSM

Fig. 4. Electromagnetic torque of PMSM

Reference and real speed of PMS

Fig. 5. Reference and real speed of PMS

Electromagnetic torque of PMSM

Fig. 6. Electromagnetic torque of PMSM

 Reference and real speed of PMSM

Fig. 7. Reference and real speed of PMSM

Electromagnetic torque of PMSM

Fig. 8. Electromagnetic torque of PMSM

Reference and real speed of PMSM

Fig. 9. Reference and real speed of PMSM

Electromagnetic torque of PMSM

Fig. 10. Electromagnetic torque of PMSM

CONCLUSION:

A detailed Simulink model for a PMSM drive system with SVPWM based on model reference adaptive system has being developed. Mathematical model can be easily incorporated in the simulation and the presence of numerous toll boxes and support guides simplifies the simulation. The space vector pulse width modulation technique (SVPWM) control technique is used in PMSM drive which has its potential advantages, such as lower current waveform distortion, high utilization of DC voltage, low switching and noise losses, constant switching frequency and reduced torque pulsations provides a fast response and superior dynamic performance. Matlab/Simulink based computer simulation results shows that the adaptive algorithm improve dynamic response, reduces torque ripple, and extended speed range. Although this control algorithm does not require any integration of sensed variables.

REFERENCES:

[1] Young Sam Kim, Sang Kyoon Kim, Young Ahn Kwon, “MRAS Based Sensorless vontrol of permanent magnet synchronous motor”, SICE Annual conference in Fukui, August 4-6,2003.

[2] Xiao Xi, LI Yongdong, Zhang Meng, Liang Yan, “A Sensorless Control Based on MRAS Method in Interior Pernanent-Magnet Machine Drive”, pp734-738, PEDS 2005.

[3] Zhang Bingy, Cen Xiangjun et al. “A pposition sensor less vector control system based on MRAS for low speeds and high torque PMSM drive”, Railway technology avalanche, vol.1, no.1, pp.6, 2003.

[4] P. Vas, “Sensorless Vector and Direct Torque Control”, Oxford University Press, 1988.

[5] A. K. Gupta and A. M. Khambadkone, “A Space Vector PWM Scheme for Multilevel Inverters Based on Two-Level Space Vector PWM,” IEEE Transactions on Industrial Electronics, vol. 53, no 5, pp. 1631-1639, Oct. 2006.