Ch 1

1. Overview of Performance Monitoring

1.1 Concept of Performance Monitoring

1.1.1 "Where You Are" Versus "Where You Should Be"Performance monitoring is the process of continuously evaluating the production capability and efficiency of a power plant and its equipment over time using measured plant data. Performance monitoring evaluations are repeated at regular intervals using data readily available from on-line instrumentation. This differs from a performance test, a one-time event that relies on precision instrumentation installed specifically for that test.

The objective of performance monitoring is to continuously evaluate the degradation (decrease in performance) of the plant and its equipment in order to provide plant operators additional information to help them identify problems, improve performance, and make economic decisions about scheduling maintenance and optimizing plant operation. A successful performance monitoring system can tell plant operators how much the plant performance has changed and how much each piece of equipment in the plant contributed to that change. This information enables operators to localize performance problems within the plant and to estimate the operational cost incurred because of the performance deficits.

While it is expected that performance monitoring will help operators diagnose and repair faults in plant equipment, the diagnostic procedures to accomplish this are beyond the scope of this book.

To answer the question "How good is my performance?" one must compare the current capability of the power plant and its equipment to its expected capability. Thus, performance monitoring is a comparison of the current capability, "Where You Are", to the expected capability, "Where You Should Be".

Production capability is a measure of the ability of equipment to produce the output that the equipment is designed to produce; it is not the current production. In other words, a plant that is designed to generate (produce) 600 MW, might only be able to generate 550 MW on a hot day, but still be capable of generating 600 MW when operating at its design conditions. The objective of performance monitoring is to continuously evaluate this capability and monitor its change over time.

Degradation is defined as the shortfall in equipment performance caused by mechanical problems in the equipment (such as wear, fouling, and

Page 13 1. Concept of Performance Monitoring

oxidation), but not by changes to set points under the control of the plant operators. For example, if plant operators increase the excess oxygen on a coal-fired boiler to reduce CO emissions when burning low quality fuel, the boiler efficiency will decrease. The boiler capability has not changed: if the fuel and excess oxygen level were returned to their original value, the boiler efficiency would also improve to its original value. Thus, the observed efficiency decrease in this example is not degradation, but is instead an opportunity for economic optimization.

A second example is a gas turbine whose water-to-fuel injection ratio must be increased to meet more restrictive NOX emissions requirements. The engine power would increase and the heat rate would get worse (increase). These changes in performance do not represent degradation, just a change in operating conditions.

Economic optimization is concerned with finding the plant operating mode and control set points that meet all constraints on plant operation (such as equipment protection and emissions limits) and maximize plant profits. The current degradation of plant equipment is an important input to optimization analysis and the current plant control set points are important inputs to degradation analysis, but the two are separate evaluations.

Performance monitoring involves two calculations: current production and expected production. The evaluation of performance degradation is a comparison between these two values. For example, a plant designed to produce 600 MW on a 59 F day may be expected to produce 550 MW on a 100 F day. If the plant meets its expected production of 550 MW on the 100 F day, then its performance is as expected (zero degradation) even though it did not perform at its design production level of 600 MW.

Table 1-1 lists the plant equipment types discussed in this book, the production objective(s) of each equipment type, and an output parameter that is a measure of each production objective. Any performance evaluation of the equipment listed in the table must relate the current production capability of the equipment to the expected production capability. Notice that the equipment types that consume fuel have two production objectives, and hence two measurements of performance. This is because output and efficiency are independent parameters for these equipment types. For fuel-consuming equipment, efficiency needs to be evaluated along with output production capability because it may be possible to achieve higher output by simply consuming more fuel.

For other equipment types (non-fuel-consuming types such as heat exchangers and steam turbines), the input source of energy is fixed (that is, not determined by the performance of the equipment type being monitored)


and therefore higher efficiency causes higher output. Thus, for these equipment types output and efficiency are not independent performance parameters.

Table 1-1 List of equipment types and their production objectivesEquipment Production Objective Measured Output

Power Plant Electricity Net Power (MW)Efficiency Net Heat Rate

Gas Turbine Electricity PowerEfficiency Heat Rate

Boiler Steam Generation Steam Flow(s), Temperature(s) and Pressure(s)

Efficiency Boiler EfficiencyHeat Recovery Steam Generator Steam Generation Steam Flow(s), Temperature(s) and

Pressure(s)Steam Turbine Electricity Power

Condenser Vacuum Condenser Shell PressureCooling Tower Energy Rejection Cooling Water Temperature to

CondenserFeedwater Heater Feedwater Heating Feedwater Outlet

Temperature

The performance of a power plant has two measures: power and heat rate. They are independent measures of performance in that the highest power is not necessarily achieved at the best (lowest) heat rate. A plant operator generally has the option to control the plant for maximum power output or to control for maximum efficiency. A performance evaluation of a power plant must include evaluations of both the power generation capability and the heat rate capability.


A gas turbine is like a power plant; in fact, a simple-cycle gas turbine is a power plant. Thus, both power and heat rate are independent performance parameters that must be evaluated when monitoring a gas turbine.

A boiler consumes fuel to generate steam. Both the steam generation capability and the boiler efficiency are important parameters of boiler performance, and both must be evaluated.

The job of a heat recovery steam generator (HRSG) is to convert the available exhaust gas energy into as much steam as possible. When the plant is operating at full load, the temperature and pressure of the steam are controlled by the plant, and therefore are not independent parameters of HRSG performance. They represent requirements that the HRSG must meet. Improved HRSG effectiveness or efficiency results in increased steam generation. There is no opportunity to increase steam generation capability without increasing HRSG efficiency; thus, efficiency and steam generation are not independent parameters of performance. A performance monitoring system must compare the current value of HRSG steam generation or efficiency to its expected value.

A condenser's job is to condense all of the steam exhausted from the steam turbine at a pressure as low as possible. The need to condense all of the steam is a requirement that must be met. Condenser pressure is the measure of condenser performance: the lower the pressure the better the performance. A performance monitoring system must compare the current value of this pressure to its expected value. Other parameters of condenser performance, such as cleanliness, are only important because they are an indication of the ability of a condenser to reduce steam turbine exhaust (condenser) pressure to its expected value.

A cooling tower must reject all of the steam condensation energy (condenser duty) to the cooling media (air or water). The quantity of energy to reject is a requirement that the cooling tower must meet. The measure of performance of a cooling tower is the cooling water temperature at the exit of the cooling tower (or at the inlet to the condenser). A lower value of this temperature indicates better performance. A performance monitoring system must compare the current value of this temperature to its expected value.

1.1.2 Performance Calculation ProcedurePerformance monitoring involves a calculational procedure that is repeated at regular time intervals. The details of the calculation vary greatly from plant to plant, depending upon the measured data that is available, the plant type, and the degree of sophistication of the calculations. However, a


performance monitoring calculational procedure always involves some or all of the following steps:

1. Acquire measured data.

2. Review, check and/or validate the raw measured data to find errors and omissions.

3. If possible, fix errors or omissions identified in the measured data.

4. Improve precision of the measured data by averaging and/or other techniques.

5. Compute fluid thermal properties, such as enthalpy and entropy, from measurements.

6. Use mass, energy and/or chemical balances to calculate data that is not measured, but can be computed from the measurements that do exist.

7. Compute current values for equipment parameters of performance such as heat rates, efficiencies, effectiveness's, temperature differences, and cleanliness.

8. Predict expected values for equipment parameters of performance.

9. Compute the corrected performance of the plant equipment

10. Calculate the shortfall in performance (degradation), based upon the difference between the expected and current values of the performance parameters.

11. Estimate the effect (impact) that the equipment degradation has on plant performance and plant operating cost.

12. Perform plant optimization calculations to predict the most cost-effective way to run the degraded plant equipment.

A given performance monitoring system often will not perform all of these calculational steps, but the list is a fairly complete compilation of the calculations that can be and probably should be done in a comprehensive and successful performance monitoring system.

1.1.3 Expected Performance: "Where You Should Be"For performance monitoring to be meaningful, one must compare current performance to expected performance, and track that comparison over time. This process is equivalent to tracking degradation (the difference between expected and current performance) over time. Since performance monitoring is a continuous process, as opposed to a one-time event like a


performance test, the performance evaluation will be performed over a variety of plant operating conditions. This makes the evaluation of expected performance the most challenging aspect of performance monitoring.

Figure 1-1 illustrates the concept of expected versus actual (degraded) power for a gas turbine engine. The baseload power of a gas turbine engine varies with inlet air temperature, as illustrated by the expected power line in this figure. It is assumed for the purposes of this discussion that ambient temperature is the only environmental parameter that is changing. Gas turbine vendors typically provide performance curves which show how performance will change with environmental conditions. A vendor performance curve can be used to compute the expected power line. Notice that one point on the expected power line is the rated power, which occurs at only one air inlet temperature (shown as TRererence in Figure 1-1).

When a degraded gas turbine is operated over a range of inlet air temperatures, the measured gas turbine power levels will likely be along a line below the expected power line, as illustrated in Figure 1-1.

The corrected power is the power that the actual (degraded) engine would produce if operated at the reference temperature. The difference between the rated and corrected power is the degradation of the engine from rated.

The procedure to calculate expected performance is to start with the expected performance at the reference operating conditions (the rated performance), and then use a model or models of equipment performance to predict the change in equipment performance when the equipment is operated at conditions different from the reference operating conditions. The model(s) of equipment performance can be very simple, such as table look-ups, or very complex, such as a physically based computer code.


Performance Evaluation Terms

The expected performance line in Figure 1-1 is actually a simple example of a performance model of a gas turbine. This line shows how gas turbine power will change as the gas turbine inlet temperature changes. This line could be converted into a table look-up as part of a computerized performance model.

Of course, any gas turbine performance monitoring system must also account for changes in other reference operating conditions such as inlet pressure loss, exhaust pressure loss, fuel properties, inlet pressure, inlet relative humidity, steam/water injection, inlet guide vane angle and firing temperature. Since these are independent parameters of gas turbine performance, separate models can be used for each condition, and the total power change is the product of the power changes predicted from the changes in each reference operating condition. Using curves to evaluate equipment performance is discussed later in this chapter under "Curve-Based Methods".


Figure 1-1 Comparison of rated, expected, measured and corrected power for a

gas turbine

Table 1-20 Typical rating specifications for a gas turbine engine

An alternative model of gas turbine performance is a computer code that includes physically based mathematical models of the compressor, combustor and expander. Such a code would take the operating conditions as inputs and predict the gas turbine power and heat rate at those operating conditions. It would be necessary to adjust (tune) such a computer code so that it accurately predicts the gas turbine rated performance at the reference operating conditions. Then the performance monitoring system could input measured data into the computer code to predict the expected performance at the current measured operating conditions. Using physically based computer models to evaluate equipment performance is described later in this chapter under "Model-Based Performance Analysis".

1.1.4 Equipment RatingsThe rated performance of plant equipment must include a specification of all the external conditions and control settings that change equipment performance but are not part of the equipment itself. Table 1-1 lists all of the specifications that are required to state the rating of a gas turbine.

There are several ways to obtain the rating data for a plant and its equipment. For performance monitoring purposes, the choice is somewhat arbitrary since a monitoring system tracks changes in performance or degradation over time. If the monitoring system defines degradation as the fall-off in performance over time, the absolute value of the rating cancels out. Several ways to define equipment ratings are:

• Use vendor guarantees

• Use acceptance test (as-built) data for the plant and equipment

• Use plant measured data at the time the monitoring system is installed

• Baseline (tune) the ratings on a regular basis using plant measured data

A gas turbine will produce its rated power and heat rate only at the reference operating conditions listed. The values of the reference operating conditions are called the reference data. All of the data in Table 1-2 are related. Change any of the operating conditions (from their reference values), and the power and heat rate of the engine will change (from rated).

Table 1-2 Typical rating specifications for a steam turbine/generator

Gas Turbine Rating Specifications Example DataRATING:

Gross Power 170 MWGross Heat Rate 9400 Btu/KW-hr

REFERENCE OPERATING CONDITIONS:Ambient Temperature 59 deg-FAmbient Pressure 14.65 psiaAmbient Specific Humidity 0.0065 lbm H20/lbm airInlet Pressure Loss 4 in H20Exhaust Pressure Loss 12 in H20Steam Water Injection noneFuel Type Natural GasFuel Lower Heating Value 20200 Btu/lbmInlet Guide Vane Angle 86 degFiring Temperature 2300 deg-FInlet Cooling or Heating none

The expected performance prediction for a gas turbine, or for any equipment type, requires both a set of rating specifications (which includes both the rated performance and the reference operating conditions), plus a model of performance that predicts how performance changes as the operating conditions change.

Table 1 -3 lists the rating specifications for a typical heat recovery steamvenerator.


Table 1-3 Typical rating specifications for a heat recovery steam generator (HRSGjHeat Recovery Steam Generator Rating Specification

Example Data

RATING:HP Steam Flow 415,000 lb/hrIP Steam Flow 70,000 lb/hr

REFERENCE OPERATING CONDITIONS:Exhaust Gas Flow 3,250,000 lb/hrExhaust Gas Temperature 1138 FExhaust Gas Composition 3% H20HP Drum Pressure 1900 psiaIP Drum Pressure 400 psiaLP Drum Pressure 100 psiaInlet Feedwater Temperature 140 FHP Steam Temperature H O O FDuct Burner Fuel Flow noneSteam Extraction to Process 20.000 lb/hrWater Extraction to Process 30,000 lb/hr

Once again, the rating specifications for an HRSG indicate that the HRSG will produce the rated steam flows only if it is operating at the reference operating conditions. To predict HRSG expected performance, a monitoring system must be able to predict the change in HRSG performance as operating conditions change from their reference values.


Table 1-4 gives typical rating specifications for a steam turbine.Steam Turbine Rating Specification Example DataRATING:

Gross Power 190 MWREFERENCE OPERATING CONDITIONS:

Throttle Steam Flow 930,000 lb/hrThrottle Steam Temperature 1137 FThrottle Steam Pressure 1800 psiaCondenser Back Pressure 0.8 psiaReheat Steam Temperature 1000 FHP Extraction Flow noneLP Admission Flow 160.000 lb/hr

A steam turbine will generate its rated power only at the rated steam flow conditions and condenser pressure. Any change in these flow conditions or pressures will cause the steam turbine power to change.


Table 1-5 Typical rating specifications for a condenser

A condenser is required to condense all of the incoming steam and transfer the energy released from condensation to the cooling water. The condenser duty, the cooling water flow and the cooling water inlet temperature are imposed upon the condenser by the performance of other equipment in the plant (external to the condenser). The condenser is designed to achieve its rated pressure at a given (reference) set of inlet flow conditions. Any change in the inlet steam or water flows will be expected to change the condenser pressure.


Condenser Rating Specification Example DataRATING:Shell (Steam) Pressure 0.8 psiaREFERENCE OPERATING CONDITIONS:Inlet Steam Flow 930.000 lb/hrInlet Steam Enthalpy 1000 Btu/lbCooling Water Flow 6,000,000 lb/hrCooling Water Inlet Temperature 80 F

Table 1-25 Typical rating specifications for a feedwater heater

Table 1-6 Typical rating specifications for a COAL-FIRED BOILER

1. Concept of Performance Monitoring page 26

Boiler Rating Specification Example DataRATING:

Main Steam Generation 2,560,000 lb/hrBoiler Efficiency 89.59%

REFERENCE OPERATING CONDITIONS:

Fuel Input Energy 3374 mmBtu hrSteam Drum Pressure 2800 psigSteam Temperature 1005 FReheat Steam Temperature 1005 FReheat Steam Flow 2.275,000 lb/hrReheat Steam Inlet Pressure 592 psigFuel Higher Heating Value 11,495 Btu/lbFuel Composition (C, H, N, S, H:0, Ash) (64.2.4.1,2.5.4.4,0.8,4.1,19.9)Inlet Feedwater Temperature 475 FInlet Air Temperature 80 FInlet Air Relative Humidity 60 %


Feedwater Heater Rating Specification Example DataRATING:

Outlet Feedwater Temperature 420 FOutlet Drain Water Temperature 380 F

REFERENCE OPERATING CONDITIONS:Inlet Steam Flow 120.000 lb/hrInlet Steam Temperature 890 FInlet Steam Pressure 320 psia



Inlet Feedwater Flow 2.600,000 lb/hrFeedwater Inlet Temperature 370 FInlet Drain Water Flow 150,000 lb/hrInlet Drain Water Temperature 460 F

1.1.5 Corrected Performance: The Indicator of DegradationFor combined-cycle power plants, the expected performance varies greatly over time. This makes it difficult to track changes in performance, as the measured values of most performance parameters vary due to changes in plant operating conditions. One methodology to make the identification of performance changes over time easier is to "correct" the current performance to a standard operating condition, usually the reference operating conditions. To correct the performance means to account for the performance variations that would be expected due to the changes in environmental conditions and control set points. The corrected performance is the performance that would be expected if the current (degraded) engine were operating at the reference operating conditions. The virtue of corrected performance is that its expected value remains constant and equal to the rated value. Thus, any change in a corrected value represents a change in equipment performance capability.


Corrected power is a barometer of engine performance. It goes down when degradation increases and it goes up when degradation decreases. In fact, the degradation in performance from one point in time to another is equal to the change in corrected performance over that time range.

Figure 1-2 Measured and corrected gas turbine power over a nine-month time period. An overhaul was performed on the gas turbine during October 2002; this time period is evident on the plot as the time during which there is no measured

data.

Corrected gas turbine power accounts for changes in engine operating conditions and predicts the equipment performance if the equipment were to operate at the reference operating conditions (including inlet filter delta-P, ambient conditions, load level, water/steam injection, fuel heating value, and exhaust delta-P). If changes in the engine operating conditions were to cause changes in gas turbine power, the corrected power would not change.

Figure 1-2 is an actual trend of gas turbine measured and corrected power. The measured power is shown on the plot only when the engine was operating at or above 99% percent of baseload power. Notice that measured


baseload power vanes during each day, and is higher in the winter months than in the summer months. The trend display of measured power is a history of operation, but gives the viewer little information about degradation.

Each corrected power point shown in Figure 1 -2 is an average of calculated corrected power over a time period of approximately two hours. Corrected power is a prediction of the power that the engine would generate if operating at reference operating conditions. It is essentially the current rating of the engine, or it is a prediction of the power the engine would achieve in a performance test at reference operating conditions.

The corrected power is a convenient plotting parameter because it shows degradation in the engine. Notice that the engine corrected power started at over 161 MW in July and degraded to approximately 158 MW by October, a loss of approximately 3 MW over a three-month period. The engine overhaul in October improved the corrected power back up to approximately 162 MW. In other words, this plot shows that the overhaul improved the engine's power capability by 3 MW to 4 MW.


Figure 1-3 shows corrected condenser pressure at a combined-cycle power plant in the United Kingdom. Notice the slow increase in corrected pressure over 150 days, indicating fouling of the condenser tubes and/or blockage in the waterboxes. Cooling water flow through the tubes also decreased about 4° o during this time period (not shown on the figure). When the tubes and

waterboxes were cleaned during a plant outage, the corrected condenser pressure improved back to approximately the same level as the beginning of the trend, and the cooling water flow rate also recovered (not shown on the figure).

1.1.6 What is My Degradation?Degradation is the reduction in equipment performance capability that has occurred over time. It is a relative parameter; it compares equipment capability at one point in time to that at another time. Since the corrected gas turbine power is a prediction of the current rating of the engine, the difference in corrected power from one point in time to another is the degradation that has occurred over the time period. Thus, degradation may be defined as the change in corrected performance over time.

For the value of degradation to be meaningful, the start time and end time of the degradation must be stated. If no time range is stated, it is usually assumed that the degradation is over the operational lifetime of the equipment, which is from the time the equipment was put into service to the present.

Often when historical data is not available, degradation may be stated as the difference between the current equipment capability and its rated capability. This is equal to the difference between the rated performance and the corrected performance. Since degradation is defined as a change in performance over time, this definition of degradation is only true if the equipment actually achieved its rated performance at some point in time. Rated performance is often set equal to the vendor guarantee as opposed to a performance test at the beginning of equipment life. Thus, the equipment may not have ever operated at its rated performance.

Degradation will be defined throughout this book as the difference between corrected and rated performance. Ideally, the rated performance should be defined as the actual performance at some given point in time, but if sufficient plant data is not available it may be set equal to the vendorguarantee.

The definition of degradation as a change over time instead of the change from vendor guarantee is significant to the concept of performance monitoring because a change over time is an aid in identifying changes in equipment performance, while a change from guarantee may be misleading. If the degradation is defined as the change from guarantee (a level of performance that the equipment may never have actually operated at), some plant equipment may show may show negative degradation, indicating that the

equipment is performing better than the guarantee level.


1.1.7 How Much is Degradation Costing Me?Knowing the amount of degradation is important, but it's not the full story. In order to make decisions about which maintenance to perform, plant operators need to know how much the degradation is costing plant operation.

For example, a reduction in gas turbine performance (power and heat rate) has an effect on overall combined-cycle plant performance, which can be calculated using an overall plant model. The power reduction in the gas turbine reduces plant power because both the gas turbine and the steam turbine power levels will change. The steam turbine power changes because the gas turbine exhaust flow and temperature normally change as a result of the gas turbine degradation. The heat rate increase of the gas turbine will cause the plant to consume more fuel per MW-hr of power produced. These effects on plant power and heat rate can then be converted to operating costs by applying a fuel cost to the extra fuel being burned, and/or a MW-hr cost to the power which is not being sold because of the degradation.

Here is a situation where the definition of degradation as a change in performance over time, as opposed to a change from vendor guarantee, is particularly important. Once the plant is accepted and goes into commercial operation it is too late to worry about equipment guarantees. The best that the operators can be expected to do is to maintain plant performance at a level that the plant actually operated in the past. Therefore, degradation is an estimate of the performance improvement that is possible, and any existing degradation can be looked upon as the source of an operational cost that is potentially avoidable.

Degradation normally is evaluated in different engineering units for each equipment type: gas turbine degradation is in MW while condenser degradation is in either psia or percent cleanliness. This makes it difficult to compare degradations calculated for different parts of the plant or for different equipment types. One way to make a meaningful comparison is to calculate the impacts of the degradation on overall plant power, heat rate and operating cost. The definition of a plant impact is the change in plant performance that would be realized if the degradation were to be returned to zero by some maintenance action.

For example, a condenser may have a degradation of 0.1 psia (6.9 mbar). This means that the condenser is operating at a pressure 0.1 psi (0.69 mbar) higher than it would operate if the degradation were zero. This degradation causes a reduction in steam turbine power, which is also a reduction in plant power. The impact of the condenser degradation on plant power is equal to the change in plant power caused by the degradation of the condenser.


The reduction in plant power due to the condenser degradation increasesplant heat rate since fuel flow is not changed. Actually, fuel flow in aRankine cycle plant with condenser degradation may decrease slightlybecause the increased condenser pressure will lead to higher feedwatertemperature entering the boiler, which will reduce boiler fuel consumption.even so. the plant power always decreases and heat rate always increaseswhen condenser pressure increases. The change in plant heat rate caused bythe degradation in the condenser is called the impact of condenserdegradation on plant heat rate.

These changes in plant performance reduce electric sales revenues andincrease fuel costs, resulting in a net operating cost to the plant. The changein plant revenues minus fuel costs is called the impact of condenserdegradation on plant costs.

The idea behind the overall plant impacts is to convert all of thedegradations in the plant to their respective costs on plant performance.Then these degradations can be compared and evaluated on a consistent

(apples to apples) basis. Table 1-7 below illustrates the concept for acombined-cycle plant.

Table 1-8 Example of plant equipment degradations and their impacts on plantperformance

Equipment Degradation Impact on Plant PerformancePower(MW)

Heat Rate(Btu/kw-hr)

Operating Cost($/hr)

Inlet Air Filter 1.1 in-H20 0.3 16 46GAS Turbine 1.9 MW 2.2 75 294HRSG 12.000 lb/hr 1.2 41 169Steam Turbine 0.8 MW 0.8 31 84Condenser 0.1 psi 0.4 25 56Cooling Tower 2.1 F 0.2 13 22Total Plant 5.1 191 671


The inlet air filter in Table 1-8 has a pressure-loss degradation equal to 1.1 in-H;0. If this degradation were eliminated by replacing the air filters, the gas turbine inlet pressure would increase, resulting in a gas turbine power increase. The steam turbine power would also increase because of the increase in gas turbine exhaust energy. The total plant power would increase by 0.3 MW, which is defined as the impact of the air filter on plant power. This plant power increase would cause a plant heat rate decrease equal to 16 Btu/kW-hr. Overall these changes in plant power and heat rate would yield a net increase of 46 $/hr in plant operating profits (electric sales revenues minus fuel costs). Methods to calculate these impacts are reviewed in the chapter 6, "Impacts of Degradation on Overall Plant Performance".

The total plant power degradation is equal to the sum of the equipment impacts on plant power. In other words, the total of the equipment impacts on plant power is equal to the degradation in plant power, which is equal to the rated plant power minus the corrected plant power, when the degradation is calculated from rated. For example, if the plant were rated at 400 MW, and the total power degradation from rated is 5.1 MW. Then, the plant would be expected to now produce only 394.9 MW if operated at the plant reference operating conditions. This power (394.9 MW) is called the corrected plant power.

In a similar manner, the corrected plant heat rate is equal to the rated plant heat rate plus the total of the equipment degradations in plant heat rate (191 Btu/kW-hr in Table 1-8). The current plant operating costs (electric sales revenues minus fuel costs at the reference operating conditions) are $671/hr higher than they would be if the plant was performing as rated and was operating at the reference operating conditions.

1.1.8 Optimization: "Where You Could Be"Once the degradation of the plant and its equipment is known, the plant operator is prepared to answer the question, "What is the best way to operate the plant so as to maximize plant profits?" The idea is to adjust the plant set-points that are under the control of the operator to make as much money as possible for the plant. The equipment degradation listed in Table 1-8 summarizes maintenance issues, but optimization is concerned with actions the operator can take to improve performance without maintenance.

An example of calculated optimization outputs for a combined-cycle power plant with two gas turbines is illustrated in Table 1-9.


Table 1-9 Example optimization outputs for a combined cycle power plant

Controllable Set-point Current Value Optimal Value Cost Savings ($/hr)

GT l Power 170 MW 161 MW 90GT 2 Power 150 MW 159 MW 88Inlet Chiller #1 On Off 12Inlet Chiller #2 On Off 11Duct Burner #1 Off Off 0Duct Burner #2 Off Off 0Number of Cooling Tower Fans On

7 6 21

Total Savings Possible 222

The Current Value column shows current plant operating data, and theOptimal Value column shows where the plant could operate if the operatortook the appropriate control actions. Finally the Cost Savings columnestimates the increase in plant operational profit that would be achieved ifthe operator took the suggested actions. This screen is different from thedegradation screen in Table 1-8 in that no maintenance actions are required,and the optimal operating conditions are achievable by operator action. Noone knows if the degradation in Table 1-8 is fully recoverable, but thecontrol actions suggested in Table 1-9 can be taken (assuming noenvironment or other operational limit on plant operation is violated), andthe cost savings achieved.

1.1.9 Controllable Loss DisplaysControllable loss displays are an alternate way to present the degradationand optimization data of tables 1-7 and 1-8. These displays are most oftenused for Rankine cycle plants where the expected or target values of plantperformance parameters do not vary widely with plant operating conditions.

Controllable loss displays show the current value of selected plantperformance parameters, their target values, and the cost incurred by notoperating the plant at these target values.


The advantage of controllable loss displays is that they are readily understandable summary of the plant performance status. If there is no degradation in plant equipment, the controllable loss display will show small losses and vice versa. The disadvantage is that they give little information as to the location of plant performance problems. Controllable loss displays are a very useful way to summarize plant status: they inform the operator if there is a plant performance problem.

The target values for controllable loss displays are generally based upon expected overall plant performance with no equipment degradation anywhere in the plant. Due to the regenerative nature of a Rankine cycle, degradation in one area of the plant will likely show up as deviations in several controllable loss parameters calculated from measured data in other areas of the plant. Thus, controllable loss parameters do not report degradation specific to individual plant equipment, but instead report a departure in overall plant performance from the values that the performance parameters would have if the entire plant were "new and clean".

For example, in order to achieve the target main steam temperature in a boiler, the economizers, the air preheater, and the feedwater heaters must all


Figure 1-4 Example controllable loss display for a fossil (Rankine cycle) plant

operate with their target performance. Degradation in any of these may cause the steam temperature to change. A change in the steam temperature may change the throttle pressure, which might change the steam turbine efficiency and the condenser pressure. Thus, many of the controllable loss parameters are related to each other, and several will likely change when one of them changes.

The target values used in controllable loss displays are a very different concept from the equipment degradation calculations described above where the expected performance of each equipment type depends upon the operational conditions that the equipment is exposed to and is independent of the degradation of other equipment in the plant.


1.2 ASME Test Codes

ASME Performance Test Codes provide test procedures that yield results of the highest level of accuracy consistent with the best engineering knowledge and practice currently available. The test procedures were developed by balanced committees of professional individuals representing all concerned interests. The test codes specify procedures, instrumentation, equipment operating requirements, calculation methods, and uncertainty analysis. When tests are run in accordance with an ASME code, the test results will be of the highest quality and the lowest uncertainty available.

The focus of the ASME test codes is to provide test specifications appropriate for verification of compliance with guarantee or warranty performance. As such, the absolute accuracy of measured performance is stressed as opposed to ease of testing. In general it is very difficult to implement the AMSE test code procedures as the basis of performance monitoring at an operating power plant.

The following table lists the test codes that are most closely related to power plant performance monitoring.

l. Concept of Performance Monitoring

Table 1-10 ASME Performance Test Codes closely related to performanceMonitoring

ASME Test Code DescriptionPTC l - 1999 General InstructionsPTC 2 - 1980(R1997) Code on Definitions and ValuesPTC 4.3 - 1968 (R1991) Air HeatersPTC 4.4- 1981 (R2003) Gas Turbine Heat Recovery Steam GeneratorsPTC 6 - 1996 Steam TurbinesPTC 6A - 2000 Appendix to PTC 6PTC 6 Report 1985 (R1997) Evaluation of Measurement Uncertainty in Performance

Tests of Steam TurbinesPTC 6S- 1988 (R1995) Procedures for Routine Performance Test of Steam

TurbinesPTC 8.2 - 1990 Centrifugal PumpsPTC 11 - 1984(R1995) FansPTC 12.1 -2000 Closed Feedwater HeatersPTC 12.2 - 1998 Steam Surface CondensersPTC 12.3 - 1997 DeaeratorsPTC 19.1 - 1998 Test UncertaintyPTC 22- 1997 Performance Test Code on Gas TurbinesPTC 23 - 1986 (R197) Atmospheric Water Cooling EquipmentPTC 46- 1997 Overall Plant PerformancePTC PM- 1993 Performance Monitoring Guidelines for Steam Power

Plants

page 3" 1 . C once p t o f Pe r f o r manc e Nlonitoring

1.3 Performance Testing versus Online Monitoring

A performance test is a one-time evaluation of equipment performance that relies on precision instrumentation installed specifically for that test. The equipment being tested is operated at conditions as close to design and, or guarantee as possible. The objective of a performance test is to measure the absolute capability of the equipment. The tests are often done to verify vendor guarantees on new or upgraded equipment.

The objective of performance monitoring is to detect changes in equipment performance (degradation) so that proper corrective action can be taken. The absolute value of performance is not necessarily important to performance monitoring; instead, repeatability of results is most important, so that changes over time can be evaluated.

The principal differences between testing and monitoring are summarized in Table l-l l below.

Table 1-11 Comparison of performance testing and online monitoring

Performance Test Online MonitoringObjective Absolute Performance Detect DegradationInstrumentation Type Precision Test Instruments Whatever Is AvailableMeasurement Requirement Accuracy RepeatabilityTest Interval One Time Event Repeated OftenTest Conditions Equipment Isolated and at Full Load Normal Plant Operation

The basic difference between performance monitoring and performance testing is that monitoring uses whatever instrumentation is continuously available at the plant to give the operators an indication of plant performance status. As such, monitoring data is usually not adequate for vendor guarantee testing, but is usually acceptable for tracking changes in equipment degradation. The fact that monitoring evaluations are repeated many times gives the engineer the opportunity to reject results that are not consistent with long-term trends.


The uncertainty of a measurement is considered to be the sum of two components called the bias and the random uncertainties. Accuracy is achieved only if both the bias and random uncertainties are small. However, repeatability is the long-term variation in bias error. Although the relative contributions of random and bias errors are unknown for most instruments, the ASME Performance Test Code Committee has estimated the repeatability as one-half the overall instrument uncertainty.

The conclusion is that even though installed plant instrumentation may not be adequate for precision tests, the repeatability of performance monitoring results often approaches the accuracy of precision tests. This means that degradation (change in performance) can be measured more accurately than absolute performance.

1.4 Curve Based Methods 1.4.1

Performance CurvesPerformance monitoring involves a comparison of the expected (new and clean) equipment performance to its current (measured) performance. The current performance is usually directly measured or is calculated from measured data. The prediction of expected equipment performance requires both a measurement of equipment operating conditions and a method or model to use to predict how the equipment performance changes as operating conditions change.

Curve based methods are a simple and reliable method to predict equipment performance changes as long as the operating conditions have not changed too much from the reference conditions. The basic concept behind curve based methods is to assemble a set of performance or correction curves that plot the variation in a specific equipment performance parameter (such as power, heat rate or efficiency) when one of the operating conditions changes. The total equipment performance fractional change is then computed by multiplying together the fractional changes for each operating condition, where each multiplying factor is generated using a separate correction curve.

Two equipment characteristics must be known in order to predict the expected performance of any plant equipment:

l. Rating specification for the equipment that includes both the rated performance and the reference operating conditions at which the rating applies.


2. A method or model, which could be in the form of performance curves, of equipment performance that can predict how the performance changes when any of the reference operating conditions change.

Table 1-12 is an example of the rating specifications for a heat recovery steam generator (HRSG), and Figures 1-5 through 1-8 are example performance curves for that same heat recovery steam generator. These curves may come from vendor performance guarantee tables, a computer model of the HRSG, or from measured data. Each curve shows how equipment performance will change if only one of the equipment operating conditions changes. When generating a performance curve it is assumed that all other equipment-operating conditions remain constant and equal to their reference values. Thus, figure 1-5 shows the variation of HP steam flow and HRSG effectiveness as the gas turbine exhaust temperature varies, but only if the other operating conditions (exhaust gas flow, exhaust gas composition, drum pressures, inlet feedwater temperature, HP steam temperature, and duct burner fuel flow) remain equal to their reference values as stated in Table 1-12.


Table 1-12 Ratings specification for the example heat recovery steam generator

Heat Recovery Steam Generator Rating Specification

Data

RATING:HP Steam Flow 511,700 lb/hrLP Steam Flow 88,300 lb/hrEffectiveness 93.4

REFERENCE OPERATING CONDITIONS:

Exhaust Gas Flow 3.200.000 lb/hrExhaust Gas Temperature 1135 FExhaust Gas Composition 10% H;0HP Drum Pressure 1900 psiaLP Drum Pressure 100 psiaInlet Feedwater Temperature 136 FHP Steam Temperature 1000 FDuct Burner Fuel Flow 0.00


I. Concept of Performance Monitoring page 44

Figure 1-5 Example HRSG performance (HP steam flow and HRSG effectiveness) versus changes in gas turbine exhaust gas

temperature


Figure 1-6 Example HRSG performance (HP steam flow and HRSG effectiveness) versus changes in gas turbine exhaust gas flow rate

"igure 1-7 Example HRSG performance (HP steam flow and HRSG Effectiveness versus changes in high-pressure steam drum pressure


Figure 1-8 Example HRSG performance (HP steam flow and HRSG effectiveness) versus changes in duct burner fuel energy input

1.4.2 Expected Performance from CurvesThe basic assumption behind the curve-based performance-prediction methodology is that the individual operating conditions impact equipment performance independently. When this assumption is true, the total impact in performance can be computed by combining the impacts of the individual parameters.

The methodology used to combine the individual impacts into a net impact on performance is to convert all the individual impacts into a fractional or percentage change in the performance parameter. The fractional change in HP steam flow when the exhaust temperature changes from the reference value, to some value is,

Fractional Change from to

where


is the look-up value of the HP steam flow from the HRSG exhaust temperature performance curve, Figure 1-5, at temperature

is the steam flow at the reference exhaust temperature from the same performance curve

The expected HP steam flow is the combination of all the fractional changes from all of the parameters that affect the HP steam flow.

Expected HP Steam Flow from Performance Curves:

where is the expected value of the HP steam flow, at the exhaust

temperature exhaust flow , drum pressure , and duct burner fuel flow is the rated value of the HP steam flow, which occurs at the reference exhaust temperature

is the value read from the exhaust temperature performance curve at temperature

is the value read from the exhaust temperature performance

curve at temperature

is the value from the exhaust flow rate performance curve at temperature is the value from the exhaust flow rate performance curve at temperature

is the value from the drum pressure performance curve at

temperature is the value from the drum pressure performance curve at

temperature

is the value from the duct burner fuel flow performance

curve at temperature

is the value from the duct burner fuel flow performance curve at

temperature


As an example, consider what happens to the HRSG performance when the gas turbine exhaust conditions change, such as when the exhaust temperature into the sample HRSG changes from its reference value of 1135 F to 1100 F. and the exhaust flow reduces from 3200 klb/hr to 2800 klb hr. The exhaust temperature performance curve (Figure 1-5) gives HP steam flow values of 511.7 klb/hr at the reference temperature (1135 F), and 480.6 klb/hr at exhaust temperature equal to 1100 F. The exhaust flow performance curve (Figure 1-6) gives HP steam flow values of 511.7 klb/hr at the reference flow (3200 klb/hr), and 448.5 klb/hr at exhaust flow equal to 2800 klb/hr. Thus, the expected HP steam flow at the new exhaust conditions is equal to:

Notice, only two terms out of four possible change factors are included in the calculation because the drum pressure and duct burner fuel flow did not change, and their contributions to the calculation would equal unity (1.0).The expected HRSG effectiveness i at the new gas turbine exhaust conditions would be calculated in the same manner, except that the calculation must use curve look-up values for the effectiveness instead of the steam flow.

1.4.3 Additive Performance FactorsSome operational parameters are not best represented by fractional changes in performance, but instead by incremental changes in performance. An addition of a quantity of energy to a system will likely cause the outputs of the system to increase by an additive amount that is proportional to the quantity of energy added. For example, a given amount of water or steam injected into a gas turbine will increase the gas turbine power by an increment that is proportional to the amount of steam/water injected, but is not closely related to the power level of the gas turbine without the steam/water injection. It would make little sense in this case to use a multiplier on the reference gas turbine power. In this situation, it would be


n on-intuitive to express this impact as a multiplier on the reference gasturbine power. Instead, this impact is better presented by adding anincrement of power proportional to the amount of steam/water that isinjected. This argument also applies to other situations such as adding ductburner fuel energy added to an HRSG, steam, and to admission or extractionfrom a steam turbine where the flow rate is not directly related to the throttleflow.

Note also that if the impact of water injection on gas turbine power isexpressed using the water-to-fuel ratio as the independent parameter insteadof a specified water injection flow rate, then the effect on performance isbetter represented as a multiplicative factor. This is because the waterinjection has been normalized back to rated conditions by dividing the quantity of water injection by the quantity of fuel flow. Additive correction factors generally are only used to represent discrete quantities being added to or taken from the equipment or system. Thus, gas turbine vendors have the option of expressing the effect of water injection on gas turbine performance as an additive factor (when the amount of water injection is plotted versus gas turbine power) or as a multiplicative factor (when water to fuel ratio is plotted versus gas turbine power).

HRSG vendors have the same option on duct burner fuel energy. If the duct burner fuel energy were expressed as a fraction of the input exhaust gas energy, the performance effect would be multiplicative.

Additive changes in performance are computed by adding the increment in performance calculated from the performance curves to the reference performance value. For example, the performance increment when the duct burner fires at level equal to some value, wF , instead of firing at the reference duct burner firing level is:

Performance Increment = {Curve D B (w F) - Curve D B (0) } (1.5)

Where Curve D B (w F) is the value from the HRSG performance versus duct burner firing curve (Figure 1-8) at the x-axis value equal to w F . The rated HRSG performance occurs at a duct burner firing level equal to the reference value, which equals zero. Thus, Curve D B (0) is the HRSG performance at the reference duct burner firing level.

If the duct burner in the example HRSG fires at a level equal to 200 mmBTU hr when all other operating conditions remain at their reference values, the expected HP steam flow would be:


1.4.4 Expected Performance from CurvesIn summary, the expected equipment performance at actual operating conditions can be calculated from a set of performance curves of the equipment performance versus equipment operating conditions by the following formula,

Expected Performance from Performance Curves:



where Performance e x p is the expected equipment performance at the actual

operating conditions, if the equipment performs with rated capability

Performance rated is the expected or rated equipment performance at the reference operating conditions (expected equals rated at the reference operating conditions)

is a mathematical operator indicating that all the terms in the

following parenthesis are to be multiplied together, one term for each performance curve until terms from all the performance curves are included in the final product.

is a mathematical operator indicating that all the following

terms are to be added together, one term for each additive performance increment until terms from all the additive performance increments are included in the final sum.

CurveValue( i ) is the value off the performance curve at operating condition i

Note that the above formula can be used to predict the performance at any set of operating conditions when the performance is known at any other set

of operating conditions. Simply define the reference conditions to be equal to the operating conditions where the performance is known, and the rated performance to be equal to that known performance value.

Predicted Performance at (1) Given Test Performance at (2) :

page 53 1. Concept of Performance Monitoring

where

Performance(l ) is the predicted equipment performance at the operating conditions (1) if the equipment performs with the same capability as the known or test performance at conditions (2)

Performance(2) is the known or test equipment performance at the operating conditions (2)



is a mathematical operator indicating that all the terms in the

following parenthesis are to be multiplied together, one term for each performance curve until terms from all the performance curves are included in the final product.

is a mathematical operator indicating that all the following

terms are to be added together, one term for each additive performance increment until terms from all the additive performance increments are included in the final sum.

CurveValue( i ) is the value off the performance curve at operating condition i

If the example HRSG is operated at inlet exhaust gas temperature of 1100 F. and inlet gas flow rate of 2800 Klb/hr, and with the duct burner consuming 200 mmBtu/hr of fuel, the expected HP steam flow rate would be:

1.4.5 Correction Factors


The traditional method to account for operational and environmental effects on equipment performance is the correction factor method. This method was developed by equipment vendors to enable their customers to predict the performance of the vendor's equipment at various operating conditions, and to avoid the need to provide the physically based computer models of equipment performance from which the curves are usually derived.

The methodology is to apply independent correction factors for each operational and environmental effect. For example, gas turbine base-load power is known to be dependent upon inlet air temperature, inlet air pressure, inlet air humidity, inlet pressure loss, exhaust pressure loss, steam injection rate, water injection rate and fuel type. The gas turbine vendor would rate the engine power at a given set of these conditions, and provide correction curves for each of these operational and environmental effects. Each correction curve would quantify the change or percent change in engine performance that would result when the given operational or environmental condition changes.

The basic assumption of this curve-based methodology is that the individual operating conditions have independent impacts on equipment performance. This means that the total impact on performance can be computed by combining the individual parameter impacts.

A correction curve is simply a normalized performance curve. The equipment output parameter (Y axis on the performance curve) value is divided by its rated value. This forces the Y-axis value to equal unity (1.0) at the X-axis value equal to the reference value. The advantage of correction curves is that the value read directly from the plot is equal to the correction factor needed to predict performance at the reference conditions given performance at some other operating condition. There is no need for the user to divide by the rated performance value to obtain a correction factor. The disadvantage is that the absolute value of performance is not available from the curve.


Correction factors are defined as the fractional change in performance from rated when an operational condition changes from the reference conditions. They are often used in performance testing to predict the equipment performance at the reference conditions when the performance was measured at conditions other than the reference conditions. This predicted performance at reference conditions is called the corrected performance.


Figure 1-9 Correction factor curve for the effect of exhaust gas temperature on HP steam flow, this curve is equal to the curve in Figure 1-5 divided by the rated HP

steam flow

is a mathematical operator indicating the product of

all the following terms (each term multiplied by the next term)

page 59 I. Concept of Performance Monitoring

Expected Performance at Test Conditions from Correction Factors:

where

is a mathematical operator indicating the sum of all

the following terms (each term added to the next term)


Performance r a t e d is the expected or rated performance at the reference operating conditions

Performance e x p is the expected performance at test operating conditions if the equipment performs with rated capability

Correct ionFactors are the values from the correction curves at the test operating conditions

Addi tiveCorrect ions are the values off the additive correction curves at the test operating conditions

The correction factor curves, just like performance curves, can be used to predict equipment performance at any operating condition given the performance at one other operating condition. The formula for the predicted equipment performance at operating condition (1), given known performance at operating condition (2) is below.

Predicted Performance at Operating Conditions (1):

Performance ( I ) is the predicted performance at operating conditions (1), if the equipment performs with the same capability as the known or test performance at operating conditions (2)

Performance (2) is the known or test performance at operating conditions (2)

Performance rated is the rated performance at the reference operating conditions

Correct ionFacotrs( l ) are the values off the correction curves at operating conditions (1)

Correct ionFacotrs(2) are the values off the correction curves at operating conditions (2)


where

Addi tiveFacotrs( l ) are the values off the additive correction curve at operating condition (1)

Addi tiveFacotrs(2) are the values off the additive correction curve at operating condition (2)

Because the correction factor curves are based upon a rated performance value at reference operating conditions, the prediction of performance at some operating conditions (1) requires the knowledge of both the rated performance as well as the performance at operating conditions (2).

1.4.6 Percent Change Correction FactorsSometimes the variations in equipment performance with operating conditions are presented as a percentage change in performance versus the percentage change in the operating condition. These curves are fully normalized performance curves where the y-axis is equal to the change in equipment performance (equipment performance minus the rated performance) divided by the rated performance, and the x-axis is equal to the change in reference condition (current operating condition minus the reference operating condition) divided by the reference condition. An example of such a performance curve is shown in Figure 1-10.


The use of these percentage change correction curves is essentially the same as that for correction curves, except that the correction factor must be calculated from the curve look-up value in the following manner,

1.5 Model-Based Performance Analysis

The correction curves that equipment vendors supply to customers are based upon physically based computer models of the equipment performance, and are a convenient way for vendors to transmit the results of complex computer analysis to their customers. However, in this time of powerful computers on every desk, it is not necessary to simplify the analysis into a few curves. Why not use the computer codes directly to calculate expected and corrected performance?

Computer software programs like GateCycleIM, Pepse™ and GTMaster™, contain complex, physically based models of equipment performance that


Figure 1-10 An HRSG percent change correction curve for the HP steam flow versus exhaust gas temperature

can be used in place of correction curves. In fact, equipment vendors often use these computer codes to create the correction curves.

Some advantages of using the computer codes (model-based analysis) instead of performance or correction curves are listed below:

• Interaction of varying operating conditions can be modeled,

• Physically based models can allow wide variations (far from reference) in operating conditions,

• Physically based models can compute impacts of parameters for which no curves are available.

• Physically based models give detailed information about the expected performance, not available from curves. This additional information may help the engineer diagnose problems.

The individual equipment operating conditions may not have independent effects on equipment performance, which is an assumption of the curve-based method. In other words, the assumption that the overall effect of changes in all the operating conditions can be computed by multiplying the correction factors together may is not valid over a wide range of operating conditions. As long as each correction factor is near unity, the method words very well; but when correction factors get far from 1.0, their product may not represent the true performance change in the equipment.

Computer models can handle wide variations in environmental parameters and operational modes for which curves do not exist or do not accurately model. In particular, as conditions change over a broad range, the interactions between environmental parameters become more and more important, and computer codes are often built specifically to handle these interactions.

Computer models can compute corrections for parameters that the vendor may not have supplied correction curves for. For example, if the gas turbine uses varying amounts of water injection or switches from natural gas to oil fuel, the exhaust gas compositions will change. These changes are handled directly by computer models, but seldom accounted for in correction curves.


The methodology for model-based performance analysis is,

1. Build a computer model of the equipment being monitored. The procedure to build such a model is specific to the software used.

2. Test the model versus vendor guarantee data and/or plant-measured data over a wide range of operating conditions. Correct the model where necessary.

3. At each performance monitoring calculation interval input the measured equipment operating conditions into the model

4. Run the model and obtain the expected equipment performance as a model output.

5. Evaluate degradation by comparing the expected performance from the model to the measured performance.

The following figures illustrate the use of physically based computer code analysis for the example heat recovery steam generator used in the chapter on performance curves.

The computer model in Figure 1-11 was constructed to replicate the actual steam/water flow path in an existing HRSG. The actual surface areas of the tube bundles were obtained from vendor information and input into the computer model. Then the design-point heat transfer coefficient in each tube bank was adjusted so that the model prediction matches the rating specification for the HRSG. This resulted in a design point model of the HRSG.


Next, the predictions (off-design mode in GateCycle™) of the HRSG model were compared to vendor warrantee data over a range of operating conditions to verify model accuracy. If necessary, corrections were made to the design-point model, and the verification process repeated until the predictions of the HRSG model matched the vendor data to within one percent over the entire operating range of the HRSG. The resulting model can then be used to give predictions of the expected performance of the HRSG as operating conditions change.

F-.gure 1-11 shows the output of the model when the reference operatingconditions from Table 1-12 are input to the computer model. Notice that themodel predicts the rated steam flows to three digits of accuracy or better. Inaddition to predicting the rated steam flows, the model also computes thecomplete temperature distributions within the HRSG. Figure 1-12 is a plot of these temperature distributions.


The upper straight line in Figure 1-12 is the exhaust gas temperature as the gas goes from the HRSG inlet to the stack. The lower set of straight lines is the corresponding steam/water temperature distribution. There is one steam/water straight line for each tube bundle modeled in the HRSG. The computer code only predicts the inlet and outlet conditions for each tube bundle, and does not predict temperature distributions within a tube bundle. A straight line is drawn from one predicted point to another.

Notice on the left hand side of the plot (at zero on the x-axis), the gas enters at a temperature of 1135 F, where the corresponding steam temperature is 1000 F. On the right hand side of the plot the gas exit (stack) temperature is 206 F, while the inlet feedwater temperature is 136 F. The closer the gas exit temperature is to the feedwater inlet temperature the higher the effectiveness of the HRSG.


Figure 1-12 Temperature profile from GateCycle™ for the example HRSG at

reference conditions

Figure 1-13 Model-based prediction (from GateCycle™) of the HRSG performance at exhaust gas temperature equal to 1100 F, and exhaust gas flow equal to 2800

Klb/hr

Figure 1-13 shows the predicted HRSG performance when the exhaust gas inlet temperature and flow rate are changed to 1100 F and 2800 mmBtu/hr respectively. Notice that when using model-based analysis, all operating conditions are input to the model and the output accounts for changes in all the operating conditions at once. Interactions between the inputs can be predicted only if all changes in operating conditions are input to the model.

Figure 1-13 shows the model-based prediction of HP steam flow and effectiveness. How do these compare to the curve-based method? Table 1-13 below compares the model-based results to the curve-based results for the situation where the exhaust gas temperature and flow change from 1135 F and 3200 klb/hr to 1100 F and 2800 klb/hr respectively.


predicted Performanceafter exhaust gas flow &

temperature changeCurve-BasedMethodModel Based Method

HP Steam Flow (klb/hr) 420421HRSG Effectiveness (%)92.892.9

Table 1-13 Comparison of results between curve-based and model-based methods for a change in HRSG inlet conditions

Thus, the curve-based and the model-based methods yield approximated equal predicted performance values when exhaust gas temperature and flow change over a relatively narrow range. Changes in exhaust conditions of this size could be expected to occur as a result of ambient temperature changes on the order of 40 F.

Figure 1-14 Predicted HRSG performance (from GateCycle™) when exhaust gas temperature, exhaust gas flow, and duct burner fuel flow all change from reference

Now let's add a significant change in duct burner firing level, from zero at the reference conditions to the maximum possible for this HRSG (200 mmBtu/hr), and once again compare the predictions of the curve-based method to the model based method.


Predicted Performance after exhaust gas flow & temperature & duct firing level all changeCurve-Based MethodModel Based MethodHP

Steam Flow (klb/hr)612614HRSG Effectiveness (%)94.595.1

Table 1-14 Comparison of results between curve-based and model-based methods

for high duct-burner firing situation

Notice that differences between the curve-based method and the model-based method begin to become important, at least for effectiveness, as the changes in operating conditions get larger. Since, the curves for this example were calculated from the model, all of the differences in calculated results are due to the simplifying assumptions inherent in the curve-based method. In other words, the curve-based method is based upon the model, and is a simplification to the model that makes it possible to predict performance without needing to run the computer code.


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