Anamnesis for Improving Thermoeconomic Diagnosis: The Case of a 3×350 MW Coal-Fired Power Plant

The aim of thermoeconomic diagnosis is to identify malfunctioning components in energy systems and to quantify the increment of fuel consumption due to each anomaly. Anamnesis, or the repetition of diagnosis along the time, allows to overcome error induced by measurement uncertainty. In this paper, a diagnosis system based on the diagnosis algorithm proposed by Correas [1] and implemented at Teruel 3×350 MW coal-fired power plant is presented and applied to the anamnesis for a period of several years. First, the plant and the diagnosis system structure are briefly described. Then, the diagnosis model is presented, including the definition of the free diagnosis variables, (independent causes of additional fuel consumption) and the system efficiency indicators (dependent variables). In the free diagnosis variables not only indicators of component efficiency are included but also set-points, ambient conditions and fuel quality. The system has been used by the power plant O&M staff for more than a year, and this experience has yielded important conclusions on how to design and implement such diagnosis systems. Afterwards, some results of the anamnesis performed by using this system are presented. It can be seen how the measurement uncertainty induces dispersion, so that the direct comparison of only two situations could lead to inexact conclusions.