In this work the efficiency of the artificial neural network technology for evaluating the turbine speed and drain synchronous valve during the turn-off transient phase of an actual hydraulic power plant has been evaluated. These results have been achieved avoiding a detailed time consuming analysis of the power plant. Several net architectures have been set up and verified with regard to their response to this strongly non-linear problem.
PuttréM.Neural networks provide solutions to nonlinear problems. Mech. Engng, October 1993, 69–72.
2.
KraftT.OkagakiK.IshiiR.SurkoP.Hybrid neural net and rule based system for boiler monitoring and diagnosis. Proceedings of the American Power Conference, Vol. 53–11, Chicago, Illinois, 1991.
3.
KhademM.AlexandroF. J.ColleyR. W.Application of neural networks to validation of feedwater flow rate in nuclear power plants. Proceedings of the American Power Conference, Vol. 55–11, Chicago, Illinois, 1993, pp. 842–847.
4.
IpakchiA.KhademM.AlexandroF. J.ColleyR. W.Neural network applications to measurement calibration verification in power plants. Proceedings of the American Power Conference, Vol. 53–11, Chicago, Illinois, 1991, pp. 958–963.
5.
BidiniG.GrimaldiC. N.MarianiF.Applicazione delle reti neurali artificiali ai problemi energetici. Proceedings of the Forty-ninth National Congress of ATI (Italian Thermo-technical Association) Perugia, Italy, 26–30 September 1994.
6.
GrimaldiC. N.MarianiF.Artificial neural networks for the evaluation of the energy requirements in manufacturing plants. Proceedings of the Winter Annual Meeting of ASME, Chicago, Illinois, 1994.
7.
BidiniG.GrimaldiC. N.MarianiF.Innovative control and diagnostic techniques for cogeneration plant steam generators. Proceedings of the Cogen-Turbo Power 1995, Vienna, Austria, 1995.
8.
GrimaldiC. N.MarianiF.Prediction of the energy requirements in a refrigeration plant using advanced simulation techniques. ASME Proceedings of the Engineering Systems Design and Analysis Conference, PD-Vol. 73, Montpellier, France, 1996, pp. 237–243.
9.
BidiniG.DesideriU.ScarpaM.Previsione dei fab-bisogni di energia elettrica con tecniche di intelligenza arti-ficiale. VII Italian National Congress on Complex Technologies and Energy Systems, Bologna, Italy, 15–16 June 1995.
10.
ScarpaM.Applicazioni di tecniche di intelligenza artificiale in campo energetico. MS thesis, University of Florence, Italy, 1994.
11.
SamadT.Hybrid neural net and rule based system for boiler monitoring and diagnosis. Proceedings of the American Power Conference, Vol. 53–11, Chicago, Illinois, 1991, pp. 952–957.
12.
TsoukalasL.IkonomopoulosA.UhrigR. E.Hybrid expert system-neural network methodology for transient identification. Proceedings of the American Power Conference, Vol. 53–II, Chicago, Illinois, 1991, pp. 1206–1211.
13.
GrimaldiC. N.MarianiF.SaettaS.Possible applications of artificial intelligence techniques to the maintenance of reciprocating internal combustion engines for cogenerationManutenzione, Tecnica e Management, January 1997, 4(1), 65–67.
14.
NguyenD.WidrowB.Improving the learning speed of 2-layer neural networks by choosing initial values of the adaptive weights. International Joint Conference on Neural Networks, Vol. 3, 1990, pp. 21–26.
15.
DayhoffY.Neural Network Architectures, 1990 (Van Nostrand Reinhold, New York).
