Due to compressor fouling, gas turbine efficiency decreases over time, resulting in decreased power output of the plant. To counteract the effects of compressor fouling, compressor on-line and off-line washing procedures are used. The effectiveness of compressor off-line washing is enhanced if combined with the cleaning of the VIGVs and the first compressor blade row by hand. This paper presents a thorough analysis of the effects of compressor on-line washing on the gas turbine performance. The analysis is based on the measured data of six gas turbines operated at two different plants. Different washing schedules and washing fluids are analyzed and compared. Furthermore, the effects of compressor on-line washing on the load distribution within the compressor are analyzed. The performance benefit of daily compressor on-line washing compared with weekly compressor on-line washing is quantified. As expected, daily compressor on-line washing yields the lowest power degradation caused by compressor fouling. Also, the effect of washing additives is analyzed. It is shown with long term data that compressor on-line washing cleans up to the first 11 compressor stages, as can be detected well in the compressor. With a view to gas turbine performance optimization, the recommendation is to perform compressor off-line washing at regular intervals and to take advantage of occasions such as inspections, when the gas turbine is cooled down anyhow. Especially for gas turbines with a high fouling rate, a daily compressor on-line washing schedule should be considered to reduce the power loss. For gas turbines operating with high fogging, compressor on-line washing has no added benefit. To determine the optimal compressor washing schedule, compressor blade erosion also has to be considered. A reasonable balance between compressor on-line washing and off-line washing improves the gas turbine performance and optimizes the gas turbine availability.

Recoverable and non-recoverable performance degradation has a significant impact on power plant revenues. A more in depth understanding and quantification of recoverable degradation enables operators to optimize plant operation. OEM degradation curves represent usually non-recoverable degradation, but actual power output and heat rate is affected by both, recoverable and non-recoverable degradation. This paper presents an empirical method to correct longterm performance data of gas turbine and combined cycle power plants for recoverable degradation. Performance degradation can be assessed with standard plant instrumentation data, which has to be systematically stored, reduced, corrected and analyzed. Recoverable degradation includes mainly compressor and air inlet filter fouling, but also instrumentation degradation such as condensate in pressure sensing lines, condenser or bypass valve leakages. The presented correction method includes corrections of these effects for gas turbine and water steam cycle components. Applying the corrections on longterm operating data enables staff to assess the non-recoverable performance degradation any time. It can also be used to predict recovery potential of maintenance activities like compressor washings, instrumentation calibration or leakage repair. The presented correction methods are validated with long-term performance data of several power plants. It is shown that the degradation rate is site-specific and influenced by boundary conditions, which have to be considered for degradation assessments.

Due to compressor fouling, gas turbine efficiency decreases over time, resulting in decreased power output of the plant. To counteract the effects of compressor fouling, compressor on-line and off-line washing procedures are used. The effectiveness of compressor off-line washing is enhanced if combined with the cleaning of the VIGVs and the first compressor blade row by hand. This paper presents a thorough analysis of the effects of compressor on-line washing on the gas turbine performance. The analysis is based on the measured data of six gas turbines operated at two different plants. Different washing schedules and washing fluids are analyzed and compared. Furthermore, the effects of compressor on-line washing on the load distribution within the compressor are analyzed. The performance benefit of daily compressor on-line washing compared to weekly compressor on-line washing is quantified. As expected, daily compressor on-line washing yields the lowest power degradation caused by compressor fouling. Also, the effect of washing additives is analyzed. It is shown with long term data that compressor on-line washing cleans up to the first 11 compressor stages, as can be detected well in the compressor. With a view to gas turbine performance optimization, the recommendation is to perform compressor off-line washing at regular intervals and to take advantage of occasions such as inspections, when the gas turbine is cooled down anyhow. Especially for gas turbines with a high fouling rate, a daily compressor on-line washing schedule should be considered to reduce the power loss. For gas turbines operating with high fogging, compressor on-line washing has no added benefit. To determine the optimal compressor washing schedule, compressor blade erosion also has to be considered. A reasonable balance between compressor on-line washing and off-line washing improves the gas turbine performance and optimizes the gas turbine availability.

In this paper, a prognostic methodology is applied to gas turbine field data to assess its capability as a predictive tool for degradation effects. On the basis of the recordings of past behavior, the methodology provides a prediction of future performance, i.e., the probability that degradation effects are at an acceptable level in future operations. The analyses carried out in this paper consider two different parameters (power output and compressor efficiency) of three different Alstom gas turbine power plants (gas turbine type GT13E2, GT24, and GT26). To apply the prognostic methodology, site specific degradation threshold values were defined, to identify the time periods with acceptable degradation (i.e., higher-than-threshold operation) and the time periods where maintenance activities are recommended (i.e., lower-than-threshold operation). This paper compares the actual distribution of the time points until the degradation limit is reached (discrete by nature) to the continuously varying distribution of the time points simulated by the probability density functions obtained through the prognostic methodology. Moreover, the reliability of the methodology prediction is assessed for all the available field data of the three gas turbines and for two values of the threshold. For this analysis, the prognostic methodology is applied by considering different numbers of degradation periods for methodology calibration and the accuracy of the next forecasted trends is compared to the real data. Finally, this paper compares the prognostic methodology prediction to a “purely deterministic” prediction chosen to be the average of the past time points of higher-than-threshold operations. The results show that, in almost all cases, the prognostic methodology allows a better prediction than the “purely deterministic” approach for both power and compressor efficiency degradation. Therefore, the prognostic methodology seems to be a robust and reliable tool to predict gas turbine power plant “probabilistic” degradation

Highly competitive and volatile energy markets are currently observed, as resulting from the increased use of intermittent renewable sources. Gas turbine combined cycle power plants (CCPP) owners therefore require reliable, flexible capacity with fast response time to the grid, while being compliant with environmental limitations. In response to these requirements, a new operation concept was developed to extend the operational flexibility by reducing the achievable Minimum Environmental Load (MEL), usually limited by increasing pollutant emissions. The developed concept exploits the unique feature of the GT24/26 sequential combustion architecture, where low part load operation is only limited by CO emissions produced by the reheat (SEV) burners. A significant reduction of CO below the legal limits in the Low Part Load (LPL) range is thereby achieved by individually switching the SEV burners with a new operation concept that allows to reduce load without needing to significantly reduce both local hot gas temperatures and CCPP efficiency. Comprehensive assessments of the impact on operation, emissions and lifetime were performed and accompanied by extensive testing with additional validation instrumentation. This has confirmed moderate temperature spreads in the downstream components, which is a benefit of sequential combustion technology due to the high inlet temperature into the SEV combustor. The following commercial implementation in the field has proven a reduction of MEL down to 26% plant load, corresponding to 18% gas turbine load. The extended operation range is emission compliant and provides frequency response capability at high plant efficiency. The experience accumulated over more than one year of successful commercial operation confirms the potential and reliability of the concept, which the customers are exploiting by regularly operating in the LPL range.