Small hydro power plant identification using NNARX structure

Neural Computing and Applications

Volumn 14, Issue 3, 2005, Pages 212-222

  Kishor, Nand ^a   Saini, R P ^a   Singh, S P ^b  

^a INDIAN INSTITUTE OF TECHNOLOGY ROORKEE   (India)

^b INDIAN INSTITUTE OF TECHNOLOGY ROORKEE   (India)

Author keywords

Exogenous input signal; Hydro turbine; Identification; Neural network; Single machine infinite bus

Indexed keywords

EID: 28844452213     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-004-0456-6     Document Type: Article

References (27)

1. ∞, governor/exciter controller design for a power system. In: Proceedings of the 1st IEEE conference on control applications, 13-16th Sep. 1993 vol 2; pp 770-775
2. Qiang LU, Chunxiao SUN, Yuangzhang SUN (1993) Non-linear governor control for hydroturbine generator sets. In: Proceedings of IEEE Region 10 conference on computer, communication, control and power engineering. TENCON' 93, 19-21 Oct 1993, Beijing, vol 2, pp 38-42
3. Garcez JN, Garcez AR (1996) A connectioninst approach to hydroturbine speed control parameters tuning using artificial neural network. In: Proceedings of 38 Midway symposium on circuits and systems, 13-16 Aug 1995, vol 2, pp 641-644
4. Djukanovic MB, Dobrijevic DM, Calovic MS, Novicevic M, Sobajic DJ (1997) Coordinated stabilizing control for the exciter and governor loop using fuzzy set theory and neural nets. Elect Power Energy Sys 19(8):489-499
5. Yusong SUN, Yuanzhang SUN, Qiang LU, Yixiang SHAO (2000) Nonlinear decentralized robust governor control for hydroturbo-generator sets of multi-machine system. In: Proceedings of the 3rd world congress on intelligent control and automation, Hefei, 28 June-2 July 2000, pp 45-52
6. Chen Guang-Da, Cai WY, Xu HK, Yuang MH (2002) The application of intelligent integral realized by fuzzy logic for hydroturbine governing system. In: Proceedings of the 1 international conference on machine learning and cybernetics, Beijing, 4-5 Nov 2002, pp 674-678
7. Qijuan C, Zhihuai X (2000) Dynamic modeling of hydroturbine generating set. In: Proceedings of IEEE international conference on systems, man and cybernetics. 8-11 Oct 2000, vol 5, pp 3427-3430
8. Kamwa I, Lefebvre D, Loud L (2002) Small signal analysis of hydro-turbine governors in large interconnected power plants. In: Proceedings of IEEE power engineering society winter meeting, 27-31 Jan 2002, pp 1178-1183
9. Irwin GW, Warwick K, Hunt KJ (1995) Neural networks application in control. The Institution of electrical Engineers, London
10. Narendra K.S, Parthasarathy K (1990) Identification and control of dynamical systems using neural networks. IEEE Trans Neural Net 1(1):4-27
11. Rivera DE, Jun K S (2001) An integrated identification and control design methodology for multivariable process system application. IEEE control systems magazine 20:25-37
12. Herron J, Wozniak L (1991) A state-space pressure and speed sensing governor for hydrogenerators. IEEE Transact Energy Conv 6(3):414-418
13. Arnautovic DB, Skataric DM (1991) Sub-optimal design of hydro-turbine governors. IEEE Transact Energy Conv 6(3):438-444
14. Abdel-Magid YL, Bettayeb M, Selim SZ (1997) Power system output feedback stabilizer design via genetic algorithms. In: Proceedings of IEEE conference on genetic algorithms in engineering systems, innovations and applications, 2-4 Sept 1997, pp 56-62
15. Venayagamoorthy GK, Harley RG (1999) A continually online trained artificial neural network identifier for a turbogenerator. In: Proceedings of the international electric machines, drives conference IEMDC'99, Seattle, 9-12 May 1999, pp 404-406
16. Cybenko G (1989) Approximations by superpositions of a sigmoidal function. Math Control Signals Syst 4(2):303-314
17. Funahashi K (1989) On the approximate realization of continuous mappings by neural networks. Neural Net 2:183-192
18. Pienaar JD, Bodenstein CP (1998) The identification of nonlinear dynamic systems around operating points using neural networks. In: Proceedings of IEEE international symposium on industrial electronics ISTE'93, 7-10 July 1998, pp 105-109
19. Nørgaard M (2000) Neural network based system identification toolbox, Tech. Report. 00-E-891, 2000. Department of Automation, Technical University of Denmark
20. Chong AZS, Wilcox SJ, Ward J (2001) Prediction of gaseous emissions from a chain grate stroker boiler using neural networks of ARX structure. IEEE Proc Sci Meas Technol 148(3):95-102
21. Hecht-Nielsen R (1990) Neurocomputing Addison-Wesley, Reading
22. Mechaqrane A, Zouak M (2004) A comparison of linar and neural network ARX models applied to a prediction of the indoor temperature of a building. Neural Comput Applic 13:32-37
23. Chiras N, Evans C, Rees D (2002) Nonlinear gas turbine modeling using feedforward neural networks. In: Proceedings of ASME TORBO EXPO 2002, 3-6 June 2002, Amsterdam, The Netherlands, pp 1-8
24. Billings SA, Voon WSF (1986) Correlation based model validity tests for non-linear models. Int J Control 44:235-244
25. Gorodkin J, Hansen LK, Lautrup B, Solla SA (1987) Universal distributed of saliences for pruning in layered neural networks. Int J Neural Syst 8(5, 6):489-498
26. Kundur P (1994) Power system stability and control, EPRI power system engineering series. McGraw-Hill, New York
27. Anderson PM, Fouad AA (1977) Power system control and stability, vol 1. The Iowa State University Press, Ames