Hybrid neuro-fuzzy static var compensator stabilizer for power system damping improvement in the presence of load parameters uncertainty

Electric Power Systems Research

Volumn 56, Issue 3, 2000, Pages 211-223

  Ellithy, K ^a   Al Naamany, A ^a  

^a SULTAN QABOOS UNIVERSITY   (Oman)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; DAMPING; ELECTRIC LOADS; ELECTRIC POTENTIAL; FEEDFORWARD NEURAL NETWORKS; FUZZY SETS; INFERENCE ENGINES; MATHEMATICAL MODELS; TUNING;

ADAPTIVE NETWORK BASED FUZZY INFERENCE SYSTEM (ANFIS); STATIC VAR COMPENSATOR;

ELECTRIC POWER SYSTEMS;

EID: 0034547902     PISSN: 03787796     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0378-7796(00)00125-5     Document Type: Article

References (22)

1. Milanovic J.V., Hiskens I.A. Damping enhancement by robust tuning of SVC controllers in the presence of load parameters uncertainty. IEEE Trans. Power Syst. 13:(4):1998;1298-13103.
2. El-Saady G., El-Sadek M., Abo-Elsaoud M. Fuzzy adaptive model reference approach-based power system static VAR stabilizer. Electric Power Syst. Res. 45:1998;1-11.
3. Ellithy K.A., Al-Alawi S.M. Tuning a static var compensator controller over a wide range of load models using an artificial neural network. Electric Power Syst. Res. 38:1996;97-104.
4. Cheng C.H., Hsu Y.Y. Damping of generator oscillations using an adaptive static VAR compensator. IEEE Trans. Power Syst. 7:(2):1992;718-725.
5. Hsu Y., Wu C.J. Adaptive control of a synchronous machine using the auto-searching method. IEEE Trans. Power Syst. 3:(4):1988;1434-1439.
6. Lee S., Liu C.C. An adaptive output feedback static VAR controller for the damping of generator oscillations. Electric Power Syst. Res. 29:1994;9-16.
7. R.M. Hamoud, M.R. Irvani, R. Hackam, Coordinated static var compensators and power system stabilizers for damping power system oscillations, Presented at Power Winter Meeting, Paper'87 WM 045-8, 1987.
8. M. Nayebzadeh, H.-J. Haubrich, D. Povh, G. Guth, W. Dietel, Applications of static var compensators in extended power systems, Cigre, Paris, September 1994.
9. Static var compensator models for power flow and dynamic performance simulation. IEEE Trans. Power Syst. 9:(1):1994;229-239.
10. Milianovic J.V., Hiskens I.A. Effect of load dynamic on power system damping. IEEE Trans. Power Syst. 10:(2):1995;1022-1028.
11. Langevin M., Auriol P. Load response to voltage variations and dynamic stability. IEEE Trans. Power Syst. PWRS-1:(4):1986;112-118.
12. Ellithy K.A., Choudhry M.A. Effect of load models on ac/dc system stability and modulation control design. IEEE Trans. Power Syst. 4:1989;411-418.
13. Choudhry M.A., Reza M.A., Ellithy K.A. Design of a robust modulation controller over a wide range of load characteristics for ac/dc systems. IEEE Trans. Power Syst. 5:(1):1990;212-218.
14. K.A. Ellithy, Effect of voltage dependent load models on power system stabilizers design, Fifth International Middle East Power System Conference (MEPCON'97), vol. 1, January 1997, pp. 370-376.
15. Craven R.H., Micheal M.R. Load representation in the dynamic simulation of the Queensland power system. J. Electrical Electron. Eng. 3:(1):1983;1-7.
16. W. Xu, E. Vaahedi, Y. Mansour, J. Tamby, Voltage stability load parameter determination from field tests on B.C. hydro's system, IEEE Trans. Power Syst. 12(3) (1997) 1290-1296.
17. IEEE Task Force on Load Representation for Dynamic Performance, Bibliography on load models for power flow and dynamic performance simulation, IEEE Trans. Power Sys. 10(1) 1995, 524-38.
18. Jang J. ANFIS: adaptive-network-based fuzzy inference system. IEEE Trans. Syst. Man Cybern. 23:(3):1993;665-685.
19. T. Takagi, M. Sugeno, Derivation of fuzzy control rules from human operator's control actions, Proceeding of IFAC Symposium Fuzzy Information, Knowledge Representation and Decision Analysis, Marseilles, France, July 1983, pp. 55-60.
20. Wang L.X., Mendel J.M. Fuzzy basis functions universal approximation and orthogonal least squares learning. IEEE Trans. Neural Netw. 3:(5):1992;807-814.
21. Jang J. Neuro-Fuzzy and Soft Computing. 1997;Prentice Hall, Englewood Cliffs, NJ.
22. T. Takagi, M. Sugeno, Fuzzy identification of systems and its applications to modeling and control, IEEE Trans. Systems Man Cybern. 15 (1985) 116-132.