In this paper, the combined application of two different approaches to the diagnosis of energy systems is proposed. The first approach is based on thermoeconomic analysis. It consists on the filtration of effects due the dependence of the efficiencies of components on their operating condition. This is obtained through productive models which relate resources and products. With respect to physical models, these are generally less accurate but more compact and thus more suitable to deal with the available measurements in real plants. The second approach is an artificial intelligence (AI) technique. This is based on the calculation of appropriate indicators that experience shows to be affected by possible anomalies. Malfunctions are detected and recognized through the analysis of deviations registered by the indicators during plant operation. The diagnosis methods are applied to a gas turbine plant with real anomalies. These are investigated in order to highlight possible advantages and disadvantages of the two methods and the benefits that can be reached through their combined application.

This content is only available via PDF.
You do not currently have access to this content.