Real-Time On-Line Performance Diagnostics of Heavy-Duty Industrial Gas Turbines

2000 ◽  
Author(s):  
S. Can Gülen ◽  
Patrick R. Griffin ◽  
Sal Paolucci
Keyword(s):  
Real Time ◽  
Gas Turbines ◽  
Performance Monitoring ◽  
Engine Performance ◽  
Combined Cycle ◽  
Ex Post ◽  
Ex Post Facto ◽  
Industrial Gas Turbines ◽  
On Line ◽  
And Performance

This paper describes the results of real-time, on-line performance monitoring of two gas turbines over a period of five months in 1997. A commercially available software system is installed to monitor, analyze and store measurements obtained from the plant’s distributed control system. The software is installed in a combined-cycle, cogeneration power plant, located in Mass., USA, with two Frame 7EA gas turbines in April 1997. Vendor’s information such as correction and part load performance curves are utilized to calculate expected engine performance and compare it with measurements. In addition to monitoring the general condition and performance of the gas turbines, user-specified financial data is used to determine schedules for compressor washing and inlet filter replacement by balancing the associated costs with lost revenue. All measurements and calculated information are stored in databases for real-time and historical trending and tabulating. The data is analyzed ex post facto to identify salient performance and maintenance issues.

Real-Time On-Line Performance Diagnostics of Heavy-Duty Industrial Gas Turbines

2002 ◽  
Vol 124 (4) ◽  
pp. 910-921 ◽  
Author(s):  
S. C. Gu¨len ◽  
P. R. Griffin ◽  
S. Paolucci
Keyword(s):  
Real Time ◽  
Gas Turbines ◽  
Performance Monitoring ◽  
Engine Performance ◽  
Combined Cycle ◽  
Ex Post ◽  
Ex Post Facto ◽  
Industrial Gas Turbines ◽  
On Line ◽  
And Performance

This paper describes the results of real-time, on-line performance monitoring of two gas turbines over a period of five months in 1997. A commercially available software system is installed to monitor, analyze and store measurements obtained from the plant’s distributed control system. The software is installed in a combined-cycle, cogeneration power plant, located in Massachusetts, USA, with two Frame 7EA gas turbines in Apr. 1997. Vendor’s information such as correction and part load performance curves are utilized to calculate expected engine performance and compare it with measurements. In addition to monitoring the general condition and performance of the gas turbines, user-specified financial data is used to determine schedules for compressor washing and inlet filter replacement by balancing the associated costs with lost revenue. All measurements and calculated information are stored in databases for real-time and historical trending and tabulating. The data is analyzed ex post facto to identify salient performance and maintenance issues.

Plant Performance Monitoring and Diagnostics: Remote, Real-Time and Automation

2014 ◽  
Author(s):  
Xiaomo Jiang ◽  
Craig Foster
Keyword(s):  
Power Plant ◽  
Anomaly Detection ◽  
Real Time ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Performance Monitoring ◽  
Performance Modeling ◽  
Combined Cycle ◽  
Remote Monitoring System ◽  
And Performance

Combined cycle gas turbine plants are built and operated with higher availability, reliability, and performance than simple cycle in order to help provide the customer with capabilities to generate operating revenues and reduce fuel costs while enhancing dispatch competitiveness. The availability of a power plant can be improved by increasing the reliability of individual assets through maintenance enhancement and performance degradation recovery through remote efficiency monitoring to provide timely corrective recommendations. This paper presents a comprehensive system and methodology to pursue this purpose by using instrumented data to automate performance modeling for real-time monitoring and anomaly detection of combined cycle gas turbine power plants. Through thermodynamic performance modeling of main assets in a power plant such as gas turbines, steam turbines, heat recovery steam generators, condensers and other auxiliaries, the system provides an intelligent platform and methodology to drive customer-specific, asset-driven performance improvements, mitigate outage risks, rationalize operational patterns, and enhance maintenance schedules and service offerings at total plant level via taking appropriate proactive actions. In addition, the paper presents the components in the automated remote monitoring system, including data instrumentation, performance modeling methodology, operational anomaly detection, and component-based degradation assessment. As demonstrated in two examples, this remote performance monitoring of a combined cycle power plant aims to improve equipment efficiency by converting data into knowledge and solutions in order to drive values for customers including shortening outage downtime, lowering operating fuel cost and increasing customer power sales and life cycle value of the power plant.

Remote Thermal Performance Monitoring and Diagnostics: Turning Data Into Knowledge

2013 ◽  
Author(s):  
Xiaomo Jiang ◽  
Craig Foster
Keyword(s):  
Anomaly Detection ◽  
Gas Turbines ◽  
Performance Monitoring ◽  
Combined Cycle ◽  
Integrated System ◽  
Site Specific ◽  
Performance Improvements ◽  
Maintenance Schedule ◽  
Effectiveness Monitoring ◽  
And Performance

Gas turbine simple or combined cycle plants are built and operated with higher availability, reliability, and performance in order to provide the customer with sufficient operating revenues and reduced fuel costs meanwhile enhancing customer dispatch competitiveness. A tremendous amount of operational data is usually collected from the everyday operation of a power plant. It has become an increasingly important but challenging issue about how to turn this data into knowledge and further solutions via developing advanced state-of-the-art analytics. This paper presents an integrated system and methodology to pursue this purpose by automating multi-level, multi-paradigm, multi-facet performance monitoring and anomaly detection for heavy duty gas turbines. The system provides an intelligent platform to drive site-specific performance improvements, mitigate outage risk, rationalize operational pattern, and enhance maintenance schedule and service offerings via taking appropriate proactive actions. In addition, the paper also presents the components in the system, including data sensing, hardware, and operational anomaly detection, expertise proactive act of company, site specific degradation assessment, and water wash effectiveness monitoring and analytics. As demonstrated in two examples, this remote performance monitoring aims to improve equipment efficiency by converting data into knowledge and solutions in order to drive value for customers including lowering operating fuel cost and increasing customer power sales and life cycle value.

scholarly journals Industrial Gas Turbine Performance: Compressor Fouling and On-Line Washing

2014 ◽  
Vol 136 (10) ◽  
Author(s):  
Uyioghosa Igie ◽  
Pericles Pilidis ◽  
Dimitrios Fouflias ◽  
Kenneth Ramsden ◽  
Panagiotis Laskaridis
Keyword(s):  
Gas Turbine ◽  
Gas Turbines ◽  
Engine Performance ◽  
Operating Conditions ◽  
Compressor Cascade ◽  
Compressor Blades ◽  
Turbine Performance ◽  
Industrial Gas Turbines ◽  
On Line ◽  
The Impact

Industrial gas turbines are susceptible to compressor fouling, which is the deposition and accretion of airborne particles or contaminants on the compressor blades. This paper demonstrates the blade aerodynamic effects of fouling through experimental compressor cascade tests and the accompanied engine performance degradation using turbomatch, an in-house gas turbine performance software. Similarly, on-line compressor washing is implemented taking into account typical operating conditions comparable with industry high pressure washing. The fouling study shows the changes in the individual stage maps of the compressor in this condition, the impact of degradation during part-load, influence of control variables, and the identification of key parameters to ascertain fouling levels. Applying demineralized water for 10 min, with a liquid-to-air ratio of 0.2%, the aerodynamic performance of the blade is shown to improve, however most of the cleaning effect occurred in the first 5 min. The most effectively washed part of the blade was the pressure side, in which most of the particles deposited during the accelerated fouling. The simulation of fouled and washed engine conditions indicates 30% recovery of the lost power due to washing.

GSP, a Generic Object-Oriented Gas Turbine Simulation Environment

2000 ◽  
Author(s):  
Wilfried P. J. Visser ◽  
Michael J. Broomhead
Keyword(s):  
Performance Analysis ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Engine Performance ◽  
Object Oriented ◽  
Control Logic ◽  
Turbine Engine ◽  
Industrial Gas Turbines ◽  
On Line ◽  
Turboshaft Engine

NLR’s primary tool for gas turbine engine performance analysis is the ‘Gas turbine Simulation Program’ (GSP), a component based modeling environment. GSP’s flexible object-oriented architecture allows steady-state and transient simulation of any gas turbine configuration using a user-friendly drag&drop interface with on-line help running under Windows95/98/NT. GSP has been used for a variety of applications such as various types of off-design performance analysis, emission calculations, control system design and diagnostics of both aircraft and industrial gas turbines. More advanced applications include analysis of recuperated turboshaft engine performance, lift-fan STOVL propulsion systems, control logic validation and analysis of thermal load calculation for hot section life consumption modeling. In this paper the GSP modeling system and object-oriented architecture are described. Examples of applications for both aircraft and industrial gas turbine performance analysis are presented.

Active On-Line Protective Tuning Adjustment Technique to Achieve Better Availability and Performance in Pre-Mix DLN Combustion

2003 ◽  
Author(s):  
C. Koeneke ◽  
M. Nomura ◽  
H. Iba ◽  
T. Kawakami ◽  
T. Koga
Keyword(s):  
Gas Turbines ◽  
Pressure Fluctuations ◽  
Calorific Value ◽  
Combined Cycle ◽  
Operating Conditions ◽  
Protection System ◽  
Fuel Quality ◽  
Flame Instability ◽  
On Line ◽  
And Performance

Stable combustion of gas turbines is essential to ensure reliability, availability and achieve maximum component life capability. Combustor instabilities can trigger high-pressure fluctuations that are generally due to sudden changes in fuel calorific value or fuel quality, large ambient temperature swings, or sudden changes in operating load conditions. In order to protect against combustor instabilities, Mitsubishi developed an advanced monitoring and protection system known as the Advanced Combustor Pressure Fluctuation Monitoring (advanced CPFM) system. This on-line monitoring and protection system automatically tunes the air bypass valve, main and pilot fuel flows to maintain appropriate fuel/air ratio depending on the combustion chamber flame instability condition. The response to such actions successfully prevents flame out occurrence, combustion oscillation, and flame flash back under various modes while trying to maintain emissions within specified levels. This paper describes the operation and functionalities of the advanced CPFM system that has been tested at Mitsubishi’s in-house combined cycle power plant under real operating conditions.

On-Line Performance Monitoring and Diagnostics for Large Combined Cycle Power Plant

2016 ◽  
Author(s):  
B. Chudnovsky ◽  
L. Levin ◽  
A. Talanker ◽  
V. Mankovsky ◽  
A. Kunin
Keyword(s):  
Power Plant ◽  
Steam Turbine ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Performance Monitoring ◽  
Combined Cycle ◽  
Plant Performance ◽  
Combined Cycle Power Plant ◽  
Large Size ◽  
On Line

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.

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