An Expert System Based Approach for Diagnosis of Occurrences in Power Generating Units

Abstract

Nowadays power generation utilities use complex information management system, as new monitoring and protection equipment are being installed or upgraded in power plants. Usually these devices can be configured and accessed remotely, thus, companies that own several stations can monitor their operation from a central office. This monitoring information is crucial in order to evaluate the power plant operation under normal and abnormal situations. Specially in abnormal cases, like fault disturbances and generator forced shutdown, the monitoring system data are used to evaluate the cause and origin of such disturbance. As the data can be accessed remotely, in general the analysis is performed at a specific department of the utility. The engineers at this department spend, on a daily basis, a substantial amount of time collecting and analyzing the data recorded during the occurrences, some of them severe and others resulting from normal operation procedures. Example of a severe occurrence is the forced shutdown of a loaded generator due to a fault (short-circuit). Concerning normal occurrences, examples are the energization and de-enegization procedures and maintenance tests. The main data used to analyze occurrences are disturbance records generated by Digital Fault Recorders (DFRs) and the sequence of events (SOE) generated by the supervisory control and data acquisition (SCADA) system. Usually this information is accessible through distinct systems, which complicates the analyst’s work due to data spreading. The analyst’s task is to verify the information generated at the power stations and to evaluate whether an important occurrence has occurred. In this case, it is also needed to identify the cause of the disturbance and to evaluate whether the generators protection systems operated as expected. Although this investigation is usually performed off line, it has become common in case of severe contingencies to contact the DFR specialist to ask for his advice before returning the generator to operation. Thus the importance to perform the analysis as quickly as possible (Moreto et al., 2009). The excess of data that needs to be analyzed every day is a problem faced in most analysis centers. It is of fundamental importance to reduce the time spent in disturbance analysis as more and more data become available to the analyst as the power system grows and technology improves (Allen et al., 2005). In practice, engineers can’t verify all the occurrences 17