Steam Turbine Models for Monitoring Purposes. (May 2017)

• Record Type: Journal Article
• Authors: Dettori, S.; Colla, V.; Salerno, G.; Signorini, A.
• Is Part Of: Energy procedia. Volume 105(2017)
• Page Start: 524
• Page End: 529
• Publication Date: 2017-05
• Subjects: Steam turbine models -- Monitoring -- Steam Quality -- Neural Networks -- Thermodynamic Models; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2017.03.351
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: The paper proposes two different approaches for steam turbine modelling for on-line monitoring applications, a hybrid-thermodynamic method and a neural network approach. Both models can predict power and other features that cannot be easily measured such as outlet Steam Quality, Pressure and Temperature at drums outlet. Training and validation of both models was carried out by exploiting a dataset created by means the GE sizing design tool. The models were tested by means of real field data of a High Pressure Turbine.