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Lessons Learnt from Alarm Management in a Combined-Cycle Gas Turbine Power Plant
Sompura, J., Parag Shankar, Gamit, S., ,
Published in Elsevier B.V.
Volume: 40
Pages: 2461 - 2466
A combined cycle gas turbine (CCGT) is a complex interconnected system that uses gas turbine's hot exhaust to power the steam power plant for achieving higher thermal efficiency. Since performance of CCGT power plants is governed by huge number of parameter linked to various components (such as compressor, combustion unit and turbine), alarms are configured to inform system operators of the abnormal operating conditions (Wong et al., 2013). Alarm systems also play a vital role in ensuring safe operation of power plants. However poor management of alarm systems result in alarm flooding, nuisance alarms, chattering alarms and false alarms that can distract the operator from determining the true state of the process. Studies indicate poor alarm system to be one of the major causes for incidents (such as BP Texas refinery and Texaco's Oil Refinery, Milford Haven) in process industries (Shu et al., 2016). Therefore, alarm management has received much attention over the past with guidelines available for alarm rationalization, prioritization and elimination of nuisance alarms. In this work, we studied the alarm data collected from Dhuvaran CCGT power plant in Gujarat, India. Event log obtained for 6 days from the plant indicates that 12186 alarms are flagged per day (compared to 144 alarms as per EEMUA-191 guidelines) with approximately 8 alarms every minute (EEMUA-191,2013). We implemented univariate (such as chattering index) and multivariate data analytic tools (such as correspondence analysis) on this alarm data obtained from combined cycle gas turbine power plant to perform alarm rationalization. We removed chattering alarms (by varying threshold based on guidelines in the literature), reduced the replicated alarms and grouped multiple alarms based on correspondence analysis to introduce unit level alarms. After performing these tasks, the average alarm count reduced to 698 per day, a reduction of 94.3% alarms. We will discuss the details of the proposed alarm management system and demonstrate the results obtained from its applicability to CCGT power plant. © 2017 Elsevier B.V.
About the journal
JournalData powered by TypesetComputer Aided Chemical Engineering
PublisherData powered by TypesetElsevier B.V.
Open AccessNo