NOVEL DEVELOPMENT OF A FUZZY CONTROL SCHEME WITH UPFC’s FOR DAMPING OF OSCILLATIONS IN MULTI-MACHINE POWER SYSTEMS

ABSTRACT:

This paper presents a novel development of a fuzzy logic controlled power system using UPFCs to damp the oscillations in a FACTS based integrated multi-machine power system consisting of 3 generators, 3 transformers, 9 buses, 4 loads & 2 UPFCs. Oscillations in power systems have to be taken a serious note of when the fault takes place in any part of the system, else this might lead to the instability mode & shutting down of the power system. UPFC based POD controllers can be used to suppress the oscillations upon the occurrence of a fault at the generator side or near the bus side. In order to improve the dynamic performance of the multi-machine power system, the behavior of the UPFC based POD controller should be coordinated, otherwise the power system performance might be deteriorated. In order to keep the advantages of the existing POD controller and to improve the UPFC-POD performance, a hybrid fuzzy coordination based controller can be used ahead of a UPFC based POD controller to increase the system dynamical performance & to coordinate the UPFC-POD combination. This paper depicts about this hybrid

combination of a fuzzy with a UPFC & POD control strategy to damp the electro-mechanical oscillations. The amplification part of the conventional controller is modified by the fuzzy coordination controller. Simulink models are developed with & without the hybrid controller. The 3 phase to ground symmetrical fault is made to occur near the first generator for 200 ms. Simulations are performed with & without the controller. The digital simulation results show the effectiveness of the method presented in this paper.

KEYWORDS:

1.     UPFC

2.     POD

3.     Fuzzy logic

4.     Coordination

5.     Controller

6.     Oscillations

7.     Damping

8.     Stability

9.     Simulink

10.   State space model.

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

SIMULINK BLOCK DIAGRAM:

 

EXPECTED SIMULATION RESULTS:

CONCLUSION:

A FACTS based multi-machine power system comprising of 3 generators, 9 buses, 3 loads with and without the 2 Fuzzy-POD-UPFC controllers was considered in this paper. Simulink models were developed in Matlab 7 with & without the Fuzzy- POD-UPFC controllers for the considered multimachine model in order to damp out the oscillations. The control strategy was also developed by writing a set of fuzzy rules. The fuzzy control strategy was designed based on the conventional POD-UPFC controller & put before the POD-UPFC in the modeling. The main advantage of putting the fuzzy coordination controller before the POD-UPFC in modeling is the amplification part of the conventional controller being modified by the fuzzy coordination unit, thus increasing the power system stability. Simulations were run in Matlab 7 & the results were observed on the scope. Graphs of power angle vs. time were observed with and without the controller. From the simulation results, it was observed that without the Fuzzy-POD-UPFC controller, the nine bus system will be having more disturbances, while we check the power angle on the first generator. There are lot of ringing oscillations (overshoots / undershoots) & the output takes a lot of time to stabilize, which can be observed from the simulation results. But, from the incorporation of the Fuzzy- POD-UPFC coordination system in loop with the plant gave better results there by reducing the disturbances in the power angle and also the post fault settling time also got reduced a lot. The system stabilizes quickly, thus damping the local mode oscillations and reducing the settling time immediately after the occurrence of the fault. The developed control strategy is not only simple, reliable, and may be easy to implement in real time applications. The performance of the developed method in this paper thus demonstrates the damping of the power system oscillations using the effectiveness of Fuzzy-POD-UPFC coordination concepts over the damping of power system oscillations without the Fuzzy-POD-UPFC coordination scheme.

REFERENCES:

[1]. L. Gyugi, “Unified Power flow concept for flexible AC transmission systems”, IEE Proc., Vol. 139, No. 4, pp. 323–332, 1992.

[2]. M. Noroozian, L. Angquist, M. Ghandari, and G. Anderson, “Use of UPFC for optimal power flow control”, IEEE Trans. on Power Systems, Vol. 12, No. 4, pp. 1629–1634, 1997.

[3]. Nabavi-Niaki and M.R. Iravani, “Steady-state and dynamic models of unified power flow

controller (UPFC) for power system studies”, IEEE’96 Winter Meeting, Paper 96, 1996.

[4]. C.D. Schauder, D.M. Hamai, and A. Edris. “Operation of the Unified Power Flow Controller (UPFC) under Practical constraints”, IEEE Trans. On Power Delivery, Vol. 13, No. 2. pp. 630~639, Apr. 1998.

[5]. Gyugyi, L., “Unified power flow controller concept for flexible AC transmission systems”, IEE Proc. Gener. Transm. Distrib., No.139, pp. 323-331, 1992.

AN IMPROVED CONTROL STRATEGY FOR THE THREE-PHASE GRID-CONNECTED INVERTER

ABSTRACT:

An improved control strategy for the three-phase grid-connected inverter with space vector pulse  width modulation (SVPWM) is proposed. When the grid current contains harmonics, the d- and q-axis grid currents will be interacted, and then the waveform quality of the grid current will be poorer. As the reference output voltage cannot directly reflect the change of the reference grid current, the dynamic response of the grid-connected inverter is slow. In order to solve the aforementioned problems, the d- and q-axis grid currents in the decoupled components of the grid current controller can be substituted by the d- and q-axis reference grid currents, respectively. The operating principles of the traditional and proposed control methods are illustrated. Experimental results for a 15-kVA three-phase grid-connected inverter with SVPWM verify the theoretical analysis. Compared with the traditional control strategy, the grid-connected inverter with the improved control strategy has high waveform quality of the grid current, small ripple power, and fast dynamic response.

KEYWORDS:

1.     Inverters

2.     LCL filter

3.     Grid-connected

4.     SVPWM

5.     Total harmonic distortion.

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

EXPERIMENTAL  RESULTS:

CONCLUSION:

This paper has proposed an improved SVPWM control strategy for the three-phase grid connected inverter. The reference grid current is used in the decoupled components of the grid current controller in the proposed control method to replace the grid current. Experimental results of a 15-kVA three-phase SVPWM grid-connected inverter show that the grid-connected inverter with the proposed control strategy has high waveform quality of the grid current, small ripple power, and fast dynamic response compared with the traditional control strategy.

  

REFERENCES:

[1] Li, R., Ma, Z., Xu, D.: ‘A ZVS grid-connected three-phase inverter’, IEEE Trans. Power Electron., 2012, 27, (8), pp. 3595–3604

[2] Kirubakaran, K., Jain, S., Nema, R. K.: ‘DSP-controlled power electronic interface for fuel cell-based distributed generation’, IEEE Trans. Power Electron., 2011, 26, (12), pp. 3853–3864

[3] Blaabjerg, F., Liserre, M., Ma, K.: ‘Power electronics converters for wind turbine systems’, IEEE Trans. Ind. Appl., 2012, 48, (2), pp. 708–719

[4] Yao, Z., Xiao, L., Yan, Y.: ‘Seamless transfer of single-phase grid-interactive inverters between grid-connected and stand-alone modes’, IEEE Trans. Power Electron., 2010, 25, (6), pp. 1597–1603

[5] Espi, J. M., Castello, J., García-Gil, R., Garcera, G., Figueres, E.: ‘An adaptive robust predictive current control for three-phase grid-connected inverters’, IEEE Trans. Ind. Electron., 2011, 58, (8), pp. 3537–3546

Mitigation of Power Quality Problems using Unified Power Quality Conditioner (UPQC)

ABSTRACT:

Power quality has become a crucial factor today due to wide application of power electronics based equipment. Conventional equipment for enhancement of power quality is becoming inadequate. Unified power quality conditioner (UPQC) is one modern device which deals with voltage and current imperfections simultaneously. In this paper, an attempt has been made to model the UPQC for voltage and current compensation with the help of two different control schemes. The current and voltage harmonics as well as voltage sag and swells compensation are shown.

KEYWORDS:

1.     Power Quality

2.     Active power Filter

3.     Modeling of UPQC

4.     Simulation.

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

EXPECTED SIMULATION RESULTS:

CONCLUSION:

This work proposes a control scheme for UPQC based on hysteresis voltage and current  controller. In this scheme the series APF and the shunt APF of the UPQC are controlled by the combination of UVT and instantaneous p-q theory. The UPQC model was developed and simulated in MATLAB/SIMULINK environment. It can be observed from the results obtained through simulation that the supply side voltage sag/swell, harmonic as well as the load side current harmonics are easily taken care of by the use of the proposed control scheme. It can also be noticed from the results that the supply side current and load voltage harmonics levels are well below the IEEE 519 standards [10].

REFERENCES:

 [1] H. Awad, M. H.J Bollen, “Power Electronics for Power Quality Improvements,” IEEE Symp. on Industrial Electronics, 2003, vol.2 , pp.1129-1136.

[2] Aredes M., Heumann K., Watanabe E.H., “An universal active power line conditioner”, IEEE Transactions on Power Delivery, 1998, vol. 13, pp. 545-551.

[3] Metin Kesler and Engin Ozdemir, “A Novel Control Method for Unified Power Quality Conditioner(UPQC ) Under Non-Ideal Mains Voltage and Unbalanced Load Conditions,” IEEE Conference on Applied Power Electronics, Feb. 2010, pp. 374-379.

[4] V. Khadkikar, P. Agarwal, A. Chandra, A.O. Bany and T.D.Nguyen , “A Simple New Control Technique For Unified Power Quality Conditioner (UPQC),” IEEE International Conference on Harmonics and Quality of Power, Sept. 2004, pp. 289 – 293.

[5] F. A. Jowder, “Modeling and Simulation of Dynamic Voltage Restorer (DVR) Based on Hysteresis Voltage Control,” The 33rd Annual Conference of the IEEE Industrial Electronics Society (IECON) Nov. 2007, pp. 1726-1731.

Mathematical Modeling and Fuzzy Based Speed Control of Permanent Magnet Synchronous Motor Drive

ABSTRACT:

To design a control system it is desirable to represent the actual system in mathematical form. So a mathematical representation of a permanent magnet synchronous motor is presented here. The inductances of a PMSM vary as a function of rotor position, the d-q model is commonly used to represent PMSM. The d-q model is obtained to implement the current control in rotor reference frame. A fuzzy logic based speed controller for permanent magnet synchronous motor is proposed and investigated. In the paper the dynamic response of PMSM drive with proposed controller is analyzed for different loading conditions and with various speed.

KEYWORDS:

1.     FLC

2.     Mathematical model

3.     PI controller

4.      PMSM

5.     SVM

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

EXPECTED SIMULATION RESULTS:

CONCLUSION:

A mathematical modeling of PMSM is presented here and d-q model is obtained to implement the current control in rotor reference frame. In this paper performance of a FLC is investigated to speed control of PMSM. FLC is designed with three scaling factors (two inputs & one output) for setting the controller parameter according to actual system. Tuning of these scaling factors is done based on the parameter of motor and intervals for which membership functions are defined. Performance of proposed FLC with gain tuning is found good in all operating conditions.

REFERENCES:

 [1] M. Kadjoudj, M. E. H. Benbouzid, C. Ghennai, and D. Diallo, "A robust hybrid current control for permanent-magnet synchronous motor drive," IEEE Transactions on Energy Conversion, vol. 19, pp. 109- 115, 2004.

[2] Y. Baudon, D. Jouve, and J. P. Ferrieux, "Current control of permanent magnet synchronous machines. Experimental and simulation study," IEEE Transactions on Power Electronics, vol. 7, pp. 560- 567, 1992.

[3] B. K. Bose, Modern power electronics and AC drives: Prentice Hall PTR USA, 2002.

[4] R. H. Park, "Two-reaction theory of synchronous machines-II," Transactions of theAmerican Institute of Electrical Engineers, vol. 52, pp. 352-354, 1933.

[5] P. Vas, Sensorless vector and direct torque control vol. 729: Oxford university press Oxford, UK, 1998.

Indirect Vector Control of Induction Motor Using Fuzzy Sliding Mode Controller

ABSTRACT:

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

KEYWORDS:

1.     Indirect vector control

2.     Fuzzy logic control

3.     PI controller

4.     Induction motor

5.     Speed control

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

EXPECTED SIMULATION RESULTS:

CONCLUSION:

This paper has successfully demonstrated the application of the proposed fuzzy sliding mode control system to an indirect field-oriented induction motor drive for tracking periodic commands. First, the description of the classical sliding mode controller (SMC) is presented in detail. Then, the fuzzy logic control is used to mimic the hitting control law to remove the chattering. Compared with the conventional sliding mode control system, the fuzzy sliding mode control system results in robust control performance without chattering. The chattering free improved performance of the FSMC makes it superior to conventional SMC, and establishes its suitability for the induction motor drive.

REFERENCES:

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

[2]R.J.Wai, “Fuzzy sliding-mode control using adaptive tuningtechnique,”IEEETrans.Ind.Elelctron.Vol.54,no.1,pp .586-594,feb2007.

[3] K.B.Mohanty, “Sensorless sliding mode control of induction motor drives,” IEEE Region10 conference, TENCON, Hyderabad, Nov 2008, pp.1-6.

[4] E.Cerruto,A.Consoli,A.Testa,“Fuzzy adaptive vector control of induction motor drives,” IEEE Transaction on Power Electronic, vol.12, no.6, pp.1028-1040, Nov.1997.

[5] K..B.Mohanty, “A fuzzy sliding mode controller for a field-oriented induction motor drive,” Journal of Institution of Engineers (India), vol.86, pp.160-165, Dec.2005.

Indirect Vector Control of Induction Motor

Using Fuzzy Logic Controller

ABSTRACT:

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

KEYWORDS:

1.     Indirect vector control

2.     Fuzzy logic control

3.     PI controller

4.     Induction motor

5.     Speed control

  

SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

EXPECTED SIMULATION RESULTS:

CONCLUSION:

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

REFERENCES:

 [1] B.K Bose “modern power electronics and ac drives “Prentice-Hall Publication,Englewood Cliffs,New Jersey,1986

[2] F.BLASCHKE, “The principle of field orientation as applied to the new transvector closed loop control system for rotating-field machine,” Siemens Rev., Vol.34,no.3,pp.217-220,May1972.

[3] M Nasir Udin,Tawfik S.Radwan,and M.Azizur Rahman,“ Performance of Fuzzy-Logic-Based Indirect vector control for induction motor drive,”IEEE Transaction on Industry Applications,vol.38,no.5,September/October 2002.

[4] Z Ibrahim and E.Levi, “A comparative analysis of Fuzzy Logic and PI controller in High-Performance AC machine drives using Experimental Approach,”IEEE Trans.Industry Application,vol.38,no.5,pp1210-1218,Sep/Oct 2002.

[5] Gilberto C.D.Sousa,Bimal K.Bose and John G.Cleland “Fuzzy Logic Based On-Line Efficiency Optimisation Vector-Controlled Induction Motor Drives,”IEEE Trans.Industrial Electronics,Vol.42,pp.192-198,April 1995.