Gas turbines ingest large quantities of air during operation. As a result, large quantities of foreign particles ranging in size from smoke (0.01 to 1.0 micron) to pollen (10 micron) enter the unit and can contribute to both fouling and erosion depending on particle size. Fouling and erosion both lead to reductions in unit output and efficiency resulting in increased operational cost. Operators have historically combatted fouling through a combination of online water washes, more effective off-line water washes, and air filtration. As is the case with almost all engineering problems, the trade-off between the cost and effectiveness of these methods must be evaluated. Online washing is somewhat effective but has led to first stage blade erosion and unit trips in some cases. Off-line washing is more effective at cleaning the unit, but requires the unit to be shut down for extended periods of time. Air filtration can help prevent foreign particles from entering the unit, but higher efficiency filters are generally associated with a larger inlet pressure drop, leading to decreased unit output; this is balanced against reduced fouling rates. These tradeoffs between the costs associated with higher efficiency filters and the frequency of compressor washing need to be evaluated on a plant-by-plant basis to determine the best combination of air filtration and compressor washing programs. This paper presents a field study carried out to determine the effectiveness of high efficiency filters in preventing compressor fouling. Fourteen units at four sites were monitored over a 9 month to 3 year time period to determine the changes in unit performance and the impact of water washes on unit performance for both pre and final filters of lower and higher efficiency ratings. Results to date indicate that higher efficiency filters are effective at reducing the need for off-line water washes and potentially reduce life-cycle cost. Reduced output from the higher pressure drop, high efficiency filters is offset by the better performance retention offered from reduced fouling rates.

Unexpected outages and maintenance costs reduce plant availability and can consume significant resources to restore the unit to service. Although companies may have the means to estimate cash flow requirements for scheduled maintenance and on-going operations, estimates for unplanned maintenance and its impact on revenue are more difficult to quantify, and a large fleet is needed for accurate assessment of its variability. This paper describes a study that surveyed 388 combined-cycle plants based on 164 D/E-class and 224 F-class gas turbines, for the time period of 1995 to 2009. Strategic Power Systems, Inc. (SPS®), manager of the Operational Reliability Analysis Program (ORAP®), identified the causes and durations of forced outages and unscheduled maintenance and established overall reliability and availability profiles for each class of plant in 3 five-year time periods. This study of over 3,000 unit-years of data from 50 Hz and 60 Hz combined-cycle plants provides insight into the types of events having the largest impact on unplanned outage time and cost, as well as the risks of lost revenue and unplanned maintenance costs which affect plant profitability. Outage events were assigned to one of three subsystems: the gas turbine equipment, heat recovery steam generator (HRSG) equipment, or steam turbine equipment, according to the Electric Power Research Institute’s Equipment Breakdown Structure (EBS). Costs to restore the unit to service for each main outage cause were estimated, as were net revenues lost due to unplanned outages. A statistical approach to estimated costs and lost revenues provides a risk-based means to quantify the impact of unplanned events on plant cash flow as a function of class of gas turbine, plant subsystem, and historical timeframe. This statistical estimate of the costs of unplanned outage events provides the risk-based assessment needed to define the range of probable costs of unplanned events. Results presented in this paper demonstrate that non-fuel operation and maintenance costs are increased by roughly 8% in a typical combined-cycle power plant due to unplanned maintenance events, but that a wide range of costs can occur in any single year.

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This paper describes a methodology to quantify scheduled and unscheduled maintenance costs and a software framework for estimating operations and maintenance (O&M) costs of combined-cycle power plants over their operating life. Scheduled maintenance costs consist primarily of replacement and repair of hot section components of the combustion turbine that occur during planned inspections and overhaul events. Scheduled maintenance costs can be estimated based on anticipated parts life, operating conditions and parts costs. Some degree of uncertainty exists, but the range of costs is fairly well understood. Unscheduled maintenance costs are not as readily defined. Experiential data of unplanned events from a large sampling of plants over time can be used to estimate unscheduled costs. Because of the wide variation in experience from unit to unit, a range of costs are anticipated. This paper includes a description of a study of F-class combined-cycle plant data that provides the basis for defining a cost distribution of unscheduled maintenance costs. In addition, the reliability and availability statistics of these plants are used to estimate lost generation revenue due to unplanned outages, which can be significantly higher than the cost of performing the repairs to return the unit to service.

Project developers, insurers, financiers, and maintenance organizations have an interest in quantifying technical risks and evaluating risk mitigation alternatives for combustion turbine (CT) power plants. By identifying exposure to risk early in the project development process, optimal procurement decisions, and mitigation measures can be adopted for improved financial returns. This paper describes a methodology used to quantify all nonfuel O&M costs, including scheduled and unplanned maintenance, and business interruption costs due to unplanned outages. The paper offers examples that demonstrate the impact of technical risk on project profitability. An overview of activities required for addressing technical risk as part of the equipment selection and procurement process is provided, and areas of technical improvements for reducing life cycle costs are described.