06/00744 Implementation of on-line performance monitoring system at Seoincheon and Sinincheon combined cycle power plant

2006 ◽  
Vol 47 (2) ◽  
pp. 111
Author(s):  
B. Chudnovsky ◽  
L. Levin ◽  
A. Talanker ◽  
V. Mankovsky ◽  
A. Kunin

Diagnostics of large size combined-cycle power plant components (such as: Gas Turbine, HRSG, Steam Turbine and Condenser) plays a significant role in improving power plant performance, availability, reliability and maintenance scheduling. In order to prevent various faults in cycle operation and as a result a reliability reduction, special monitoring and diagnostic techniques is required, for engineering analysis and utility production management. In this sense an on-line supervision system has developed and implemented for 370 MW combined-cycle. The advanced diagnostic methodology is based on a comparison between actual and target conditions. The actual conditions are calculated using data set acquired continuously from the power plant acquisition system. The target conditions are calculated either as a defined actual best operation (Manufacturer heat balances) or by means of a physical model that reproduces boiler and plant performance at off-design. Both sets of data are then compared to find the reason of performance deviation and then used to monitor plant degradation, to support plant maintenance and to assist on-line troubleshooting. The performance calculation module provides a complete Gas Turbine, HRSG and Steam Turbine island heat balance and operating parameters. This paper describes a study where an on-line performance monitoring tool was employed for continuously evaluating power plant performance. The methodology developed and summarized herein has been successfully applied to large size 360–370 MW combined cycles based on GE and Siemens Gas Turbines, showing good capabilities in estimating the degradation of the main equipment during plant lifetime. Consequently, it is a useful tool for power plant operation and maintenance.


Author(s):  
Fernando Ramos Fernandez De Bobadilla ◽  
Joe Nasal ◽  
Sid Sutherland ◽  
Greg Noe

Union Fenosa began commercial operation of the 300 MW Naco Nogales combined cycle plant in October, 2003 under a power purchase agreement with Mexico’s Comision Federal de Electricidad, and is therefore in a financial risk-reward situation depending on the operational efficiency of the facility. As part of their effort to maximize the profitability of the plant, an on-line performance monitoring system was installed to alert and advise the operating and management staff of performance improvement opportunities. The Naco Nogales Plant consists of one 501G Siemens Westinghouse combustion turbine, a Mitsui Babcock HRSG, and a Siemens steam turbine. To readily identify equipment performance deficiencies, cycle isolation problems, or instrumentation problems in a timely manner, the plant installed an on-line performance monitoring system. The system monitors, archives process data and calculated results, and automatically reports on key performance indicators. A rigorous, first principles thermodynamic model validates the accuracy of measured data and provides off-line “What-If” optimization analyses to assist in operating and business decisions. Key to achieving improved operation was a unique combination of state-of-the-art software and technology transfer through training and mentoring for the plant operations team. This combination provided the information needed for improved information as well as a knowledgeable workforce that understood how to use the “new” information and tools to improve operations and business processes. This paper, written from the Plant’s perspective, describes some key features of the performance monitoring and optimization system, the technology transfer process and several examples of savings recognized by placing an emphasis on profit through a combination of workforce training and the latest software technologies.


2014 ◽  
Vol 63 ◽  
pp. 2394-2401
Author(s):  
Satoshi Saito ◽  
Norihide Egami ◽  
Toshihisa Kiyokuni ◽  
Mitsuru Udatsu ◽  
Hideo Kitamura ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document