A data-based method for monitoring air in-leakages into the oxyfuel process

Abstract

In conventional power plants, the attention paid to air in-leakage is minor. This is due to the low impact of air in-leakages on the cost effectiveness of the plant. However, in oxyfuel power plants the minimization of air in-leakages into the process becomes a crucial issue to improve the efficiency of the process. For this reason, it is an aim of the operator of an oxyfuel plant to identify and localize such leakages as early as possible to initiate appropriate maintenance steps. In the present, paper a data-based method is described that can serve as a monitoring tool for the plant. In case of increasing air in-leakages an early identification and localization of the disturbance is possible. The investigations are based on an experiment conducted in Vattenfall’s Oxyfuel Pilot Plant in Schwarze Pumpe, Germany. During the test leakage air was dosed into the process at several locations that are characteristic for leakages. The process data gathered in this experiment were later-on analyzed in a principal component analysis (PCA). It was found that the monitoring of appropriate process variables in a PCA model provides a possibility for both to identify increasing leakages and to localize the region where the leakage occurs.