Manoj Kumar Sharma | R.P. Pathak | Manoj Kumar Jha | M.F. Qureshi*
OPEN ACCESS
This paper presents a practical design of an intelligent type of controller using Interval Type-2 Fuzzy Logic Controller (IT2FLC) concepts for excitation control of a practical power generating system. This type of controller is suitable for real time operation and aims to improve the dynamic characteristics of the generating unit by acting properly on its original excitation system. The modeling of the power system under study consists of a synchronous generator connected via a transformer and a transmission line to an infinite bus. Next, digital simulations of the above system are performed using fuzzy control techniques that are based on previous work. The dynamic performances of the interval type-2 fuzzy logic controllers (IT2FLC) along with Interval type-1 Fuzzy logic controller in short FLC is presented by comparison using the integral square error criterion (ISE). Typical transient responses of the system are shown for comparison in order to demonstrate the effectiveness of the proposed controller. The computer simulation results obtained demonstrate clearly that the performance of the developed controller offers competitive damping effects on the generator oscillations, with respect to the associated ones of the FLC, over a wider range of operating conditions, while their hardware implementation is easier and the computational time needed for real-time applications is drastically reduced. In MATLAB/SIMULINK is simulated model of the synchronous generator connected to an AC system. A simple fuzzy logic control scheme is simulated for voltage control and generator stabilization.
synchronous machine, excitation control, dynamic stability, interval type 2 fuzzy logic controller, FLC
[1] Mao H, Malik OP, Hope GS, Fan J. (1990). An Adaptive Generator Excitation Controller Based on Linear Optimal Control. IEEE Trans. on Energy Conversion 5(4): 673-678. https://doi.org/10.1109/60.63138
[2] Papadopoulos DP. (1986). Excitation Control of Turbo-generators with Output Feedback. Int. J. Electr. Power & Energy Systems 8: 176-181. https://doi.org/10.1016/0142-0615(86)90032-3
[3] Ross T. (1995). Fuzzy Logic with Engineering Applications. Fuzzy-Logik. https://doi.org/10.1111/j.1468-1331.2005.01230.x
[4] Hassan MAM, Malik OP., Hope GS. (1991). A Fuzzy Logic Based Stabilizer for a Synchronous Machine. IEEE Trans. Energy Conv. 6(3): 407-413. https://doi.org/10.1109/60.84314
[5] Handschin E, Hoffmann W, et al. (1994). A new Method of Excitation Control Based on Fuzzy Set Theory. IEEE Trans. Power Syst. 9: 533-539. https://doi.org/10.1109/59.317569
[6] Djukanovic MB, Dobrijevic DM, Calovic MS, Novicevic M., Sobajic DJ. (1997). Coordinated Stabilizing Control for the Exciter and Governor Loops Using Fuzzy Set Theory and Neural Nets. International Journal of Electrical Power & Energy Systems 8: 489-499. https://doi.org/10.1016/s0142-0615(97)00020-3
[7] Karnavas YL, Papadopoulos DP. (2000). Excitation Control of a Power Generating System Based on Fuzzy Logic and Neural Networks. European Transactions on Electrical Power 10(4): 233-241. https://doi.org/10.1002/etep.4450100406
[8] Karnavas YL, Papadopoulos DP. (2002). A Genetic- Fuzzy System for the Excitation Control of a Synchronous Machine. ICEM '02, The 15th International Conference in Electrical Machines.
[9] Hornich K, Stinchcomebe M., White H. (1989). Multilayer Feed forward Networks are Universal Approximators. Neural Networks 2: 359-366. https://doi.org/10.1016/0893-6080(89)90020-8
[10] Karnavas YL, Papadopoulos DP. (2002). AGC for Autonomous Power Station Using Combined Intelligent Techniques. Electric Power Systems Research 62(3): 225-239. https://doi.org/10.1016/s0378-7796(02)00082-2
[11] Mcclelland J, Rumelhart D. (1987). Parallel Distributed Processing.
[12] Giles CL, Maxwell T. (1987). Learning, Invariance, and Generalization in High-Order Neural Network. Applied Optics 26(23). https://doi.org/10.1364/AO.26.004972
[13] Lippmann RP. (1989). Pattern Classification Using Neural Networks. IEEE Communications Magazine 27(11): 47-64. https://doi.org/10.1109/35.41401
[14] Shin Y, Ghosh J. (1992). Excient Higher-Order Neural Networks for Function Approximation and Classification. Int. J. Neural Syst. 3(4): 323-350.
[15] Robandi I. (2006). Modern Power System Design (Desain System Tenaga Modern, in Bahasa Indonesia), Andi Offset Publisher: 2006.
[16] Dobrescu M, Kamwa I. (2004). A New Fuzzy Logic Power System Stabilizer Performances. IEEE. https://doi.org/10.1109/PSCE.2004.1397498
[17] Kundur P. (1993). Power System Stability and Control. McGraw-Hill.
[18] Ross T, Logik F. (1997). Fuzzy Logic with engineering Applications. McGraw-Hill. https://doi.org/10.1111/j.1468-1331.2005.01230.x
[19] Liangand Q, Mendel JM. (2000). Interval Type-2 Fuzzy Logic System Theory and Design. IEEE. https://doi.org/10.1109/91.873577
[20] Mendel JM, Robert I, John B. (2002). Type-2 Fuzzy Sets Made Simple. IEEE. https://doi.org/10.1109/91.995115
[21] Castro JR, Castillo O. (2007). Interval Type-2 Fuzzy Logic for Intelligent Control Applications. IEEE. https://doi.org/10.1109/NAFIPS.2007.383907
[22] Mendel JM, Liu FL. (2007). Super-Exponential Convergence of the Karnik–Mendel Algorithms for Computing the Centroid of an Interval Type-2 Fuzzy Set. IEEE. https://doi.org/10.1109/tfuzz.2006.882463
[23] Jolevski D. (2009). Excitation System of Synchronous Generator. University of Split, Faculty of Electrical Engineering. Mechanical Engineering and Naval Arhitecture.
[24] Tesnjak S, Erceg G, Erceg R., Klarin D, Komericki Z. (2000). Excitation System of Synchronous Turbo Generator. Thermal Power Plant Features in the Meaning of Electric Power System Demands.
[25] Machowski J, Bialek JW, Robak S, Bumby JR. (1998). Excitation control system for use with synchronous generators. IEE Proc.- Gener. Transm. Distrib. 145(5). https://doi.org/10.1049/ip-gtd:19982182
[26] Sumina D, Erceg G, Idžotic T. (2005). Excitation control of a synchronous generator using fuzzy logic stabilizing controller. https://doi.org/10.1109/EPE.2005.219266
[27] Miskovic M, Mirosevic M, Erceg G. (2009). Load Angle Estimation of a Synchronous Generator Using Dynamical Neural Networks. Energija 58(2): 174-191. https://doi.org/10.1109/MELCON.2004.1348098
[28] Miskovic M, Mirosevic M, Milkovic M. (2009). Analysis of Synchronous Generator Angular Stability depending on the Choise of the Excitation System. Energija 58(4): 430-445.