Realtime Heatrate

Coal-Fired Power Plant Performance Monitoring in Real-time

Sastry Munukutla, Director and Robert Craven, R&D Engineer

Center for Energy Systems Research (Formerly Center for Electric Power)

Summary

Technology for coal-fired power plant performance monitoring in real-time has been developed at the Center for Electric Power, Tennessee Technological University. Customized software, TTURTHRM TM (Tennessee Technological University Real-Time Heatrate Monitor), has been installed at several coal-fired units in the U.S.A. and one has been installed in India. The input data for the software is typically chosen from the already existing data available on the plant computer. All that is needed for the implementation of this technology in any unit is a PC running a Microsoft Windows 32 bit operating system, which communicates with the plant computer. For a typical 500MW coal-fired unit in the US.A., a 2% improvement in heatrate translates into an annual savings in fuel cost of U.S. $1.31 million under given conditions.

Introduction

Power plant performance monitoring in real-time affords the opportunity to optimize the performance of a unit continuously. Boiler efficiency, steam cycle heatrate, and net unit heatrate are the three primary performance indices. However, the net unit heatrate, which is the ratio of the rate of energy input (Btu or Kcal per hour) to the net power generated (KW), is the most important parameter. The net unit heatrate, which is the inverse of the unit efficiency, should be minimized. The current industry practice in many parts of the world is to conduct performance tests periodically. In many instances the performance tests are conducted only annually if at all.

Due to the use of modern control technology plant data from various instruments is available on plant computers on a continual basis. Except for alarm function most of the data is rarely used. However, by using part of the data, performance calculations can be made. Since the data is in real-time, the results from the calculation are also in real-time.

The Center for Electric Power, established in 1985, has embarked on the development of real-time performance monitoring technology since 1986. Several original contributions have been made to this field. For the last several years this technology has been successfully implemented in several coal-fired units in the U.S.A. and one unit in India. Currently negotiations are ongoing for further implementing this technology in China, South Korea, Taiwan, Botswana, India, and the U.S.A.

The technical discussion of the real-time performance monitoring methods is presented in the next section. The units at which this technology has already been implemented are listed in the following section. The cost-benefit analysis for a typical 500MW unit in the U.S.A. is presented next. The qualifications of the project managers are discussed in the subsequent section. Some information related to the cost and time needed for implementing this technology in a given unit is presented in the final section.

Technical Discussion

Calculations for performance monitoring in real-time are based on the well known output/loss method. The output/loss method of determining heatrate is an extension of the heat loss method for the determination of boiler efficiency as prescribed in ASME PTC 4.1[1]. Several published papers describe the output/loss method application to power plant performance monitoring [2, 3, 4, 5, 6, 7, 8].

The basic principle of the output/loss method is that the input to a system is the sum of the output and losses. If the entire coal-fired power plant were to be considered as a system, the input is the product of the coal flow rate (Mc) (1b or kg/hr) and the gross calorific value (H) of the fuel (Btu/lb or Kcal/Kg). The output is the heat transferred to the steam in the boiler, Qs (Btu/hr or Kcal/hr). The losses of the system include, heat loss due to unburned carbon in the fuel, heat loss due to heat in dry flue gas, heat loss due to moisture in the fuel, heat loss due to moisture from burning hydrogen in the fuel, heat loss due to moisture in the air, heat loss due to formation of carbon monoxide and heat loss due to surface radiation and convection. These losses, l, can be estimated per unit mass of fuel. We can, therefore, write the following equation:

M c*H = Q s + M c*l

(1)
In the above equation M c can be calculated by knowing H, Q S, and l. The real-time performance monitoring software known as, TTURTHRM TM, performs the calculations based on plant data. Once the coal flow rate is calculated, the following performance parameters can be calculated.

Boiler efficiency:

heatrate2_clip_image002

(2)
Steam cycle heatrate

heatrate2_clip_image004

(3)
Kwg - gross power generation

Net unit heatrate

heatrate2_clip_image006

(4)
K S - Station service power.

In addition to the above parameters other parameters can also be calculated: for example air preheater effectiveness, air preheater leakage, and flow rate of emissions such as CO 2 and SO 2.

The schematic of the system modeled by the output/loss method is shown in Figure 1. It is to be noted that this is a generic example. Deviations from this Such as trisector air heaters, PA fans, etc. can be easily taken into account. The TTURTHRM will be customized for each unit. Typical data needed for the calculations is given below in Table 1.

It is to be noted that certain data described above may not be available. For example cold reheat steam flow and hot reheat steam flow may not be available on the plant computer. However by performing energy balance on feedwater heaters, and extraction steam, these can often be calculated. Additional data such as CO 2 % in the stack and O2 % at air preheater gas side exit could be available. In such a case these data will be used in the calculation procedure.

 

Figure 1 Schematic of the System Modeled by the Output/Loss Method

fig1-1

Table 1 Data needed

 

Table 2 Sample Static Data Inputs

 

Symbol Data Units Description
FC 28.8 mass % Fixed Carbon
VM 21.6 mass % Volatile Matter
FM 11.5 mass % Fuel Moisture
Ash 39.27 mass % Ash
GCV 3530 kcal/kg Gross Calorific Value
S 0.53 mass % Sulfur in fuel
C1 43.4 constant for Prox 2 Ult conversion
C2 2.1 constant for Prox 2 Ult conversion
C3 2.86 constant for Prox 2 Ult conversion
UseProx 0 Flag for use of Proximate analysis (1 - True, 0-False)
C 39.49 mass % Carbon in fuel
H 2.63 mass % Hydrogen in fuel
O 5.72 mass % Oxygen in fuel
N 0.86 mass % Nitrogen in fuel
LOI_Flyash 0.235 % Percent unburned carbon in Flyash
LOI_BottomAsh 0 % Percent unburned carbon in BottomAsh
FLYASH 80 mass % % of ash which is fly ash
RELHUM 60 % Relative Humidity
COPPM 60 molar ppm CO concentration
BLRLEAK 1.5 % Boiler leakage
COALAIR 2 ratio Air to Fuel Ratio
MCR 4.79E+08 kcal/hr Maximum continuous rating of boiler
APHLeak_A 16.046 % leakage A
APHLeak_B 16.046 % leakage B
PAFTcor 5 Primary air fan temperature correction
FDFTcor 7 FD fan temperature correction

Table 3 Sample Dynamic Inputs

Symbol Data Units Description
OxyEcon 2.6025 % Oxygen Percent at economizer exit
OxyEcon 2.7625 % Oxygen Percent at economizer exit
CoalAirTemp 85.7 deg C Coal Air mixture temperature at Mill A
CoalAirTemp 85.6 deg C Coal Air mixture temperature at Mill B
CoalAirTemp 85.4 deg C Coal Air mixture temperature at Mill C
CoalAirTemp 85.4 deg C Coal Air mixture temperature at Mill D
CoalAirTemp 31.4 deg C Coal Air mixture temperature at Mill E
CoalAirTemp 28.2 deg C Coal Air mixture temperature at Mill F
SecnAir 277 deg C Secondary Air temperature at APH A
SecnAir 283 deg C Secondary Air temperature at APH B
TEconOut 350 deg C APH A inlet flue gas temperature
TEconOut 350 deg C APH B inlet flue gas temperature
PresFW 163 kg/cm2 Pressure of feedwater
TempFW 242 deg C Temperature of feedwater
MFW 687 metric T/hr Mass flow rate of feedwater
PresMS 147 kg/cm2 Pressure Main Steam
TempMS 539 deg C Throttle temperature
MMS 649 metric T/hr Mass flow rate of Main Steam
PresHRH 33.5 kg/cm2 Hot reheat pressure
TempHRH 540 deg C Temperature of Hot Reheat
PresCRH 36.1 kg/cm2 Pressure of cold reheat
TempCRH 348 deg C Temperature of cold reheat
MWGen 210 MW Load in MW generated
TFWout 243 deg C HPH 6 feedwater outlet temperature
PextStm 35.5 kg/cm2 Extraction Steam Pressure
TExtStm 349 deg C Extraction Steam Temperature

Table 4 Sample Outputs

Symbol Data Units Description
UnitLoad 210.000 MW Unit Load
GrossHTRT 2339.613 kcal/kw_hr Gross unit heat rate
DesignGrossHTRT 2251.762 kcal/kw_hr Design Gross Unit Heatrate
GrossHTRTdeviation -87.851 kcal/kw_hr Gross Unit Heatrate Deviation
CYCLHTRT 2020.955 kcal/kw_hr Cycle heat rate
DesignCYCLHTRT 1965.338 kcal/kw_hr Design Cycle heatrate
CYCLHTRTdeviation -55.617 kcal/kw_hr Cycle heatrate deviation
CRHflow 588.578 metric Tons/hr Computed CRH flow
BoilerEffn 86.380 % Actual Boiler efficiency
DesignBlrEffn 87.280 % Design Boiler efficiency
BlrEffnDeviation 0.900 % Boiler efficiency deviation
AsFiredCoalFlow 139.309 metric T/hr Computed Coal flow rate
UnburnedCarbonLoss 0.169 % Unburned carbon loss percentage
DryGasLoss 6.374 % Dry gas loss percentage
FuelMoistureLoss 2.193 % Fuel moisture loss percentage
HydrogenBurnLoss 4.481 % Hydrogen burn loss pecentage
AirMoistureLoss 0.151 % Air moisture loss percentage
CarbonMonoxideLoss 0.026 % Carbon monoxide loss
RadiationLoss 0.227 % Radiation loss
StackCO2Flow 201.253 metric T/hr Metric Stack CO2 flow rate
StackSO2Flow 1.477 metric T/hr Metric Stack SO2 flow rate
StackGasFlow 14603.900 standard m^3/min Flue gas standard volumetric flow rate
%O2APHexitA 5.219 % Percent O2 at Air Preheater exit A
%O2APHexitB 5.219 % Percent O2 at Air Preheater exit B
%CO2EconExit 14.395 % CO2 concentration at economizer exit
%CO2APH A exit 12.359 % Percent CO2 at Air Preheater exit A
%CO2APHB exit 12.359 % Percent CO2 at Air Preheater exit B
%CO2 Stack 12.359 % CO2 concentration at stack
STACK SO2 623.450 ppm SO2 concentration in stack gasses
CYCLHTRT 8019.789 Btu/kw_hr Cycle heat rate
GROSSHTRT 9284.324 Btu/kw_hr Gross unit heat rate
SCFM 515728.749 ft^3/min Flue gas standard volumetric flow rate
StackCO2Flow 443287.845 lb/hr Stack CO2 flow rate
StackSO2Flow 3252.582 lb/hr Stack SO2 flow rate
AFCOALFL 306847.354 lb/hr Coal flow rate
GasSideEffA 60.349 % Gas Side Air Preheater Efficiency A
GasSideEffB 68.745 % Gas Side Air Preheater Efficiency B
XRatioA 0.760 % Air Preheater Xratio A
XRatioB 0.871 % Air Preheater Xratio B

Units Modeled

 

Field Results

 

TTU does not perform field tests of power plants, and as such must rely on what performance metrics various plants are willing to share to support the technology.

Equation 1, discussed above, taught how to compute the coal flow rate; so a good check as to whether the calculation is useful would be to compare the computed coal flow rate with a measured coal flow rate. Figure 2 shows the results for one plant and shows a close correlation under normal load conditions. It is of note that the customer requested that a data filter be added such that when a sensor goes out of a prescribed range, a substitute value will be employed. Under this scenario, if the plant completely shuts down the heatrate program will indicate a "normal" heatrate. This explains why the dips in measured coal are not completely matched by equal sized dips in coal flow prediction.

fig2-2

Figure 2 Coal flow rate calculation versus two measurement techniques.

Another indication of the software's performance would be to compare it with another vendor's software. One client did such a test, but noted that the other vendor's software utilized a single static estimate of the coal composition. The solution for the comparison was to have both programs utilize the CEMS predicted coal calculated via TTURHTRM. Figure 3 shows the close matching of the two heatrates calculated by the two different programs over the course of about 12 days.

heatrate2_clip_image004

Figure 3 Comparison of TTURTHRM heatrate and another vendor using CEMS calculated coal.

A third metric for measuring the usefulness of TTURTHRM would be actual field tests that measure plant performance. A third vendor supplied that data for a series of tests conducted over a wide range of loads where the TTURTHRM performed well as shown in Figure 4

heatrate2_clip_image006_0000

Figure 4 Performance test comparison over a wide range of loads.

Benefit Analysis

Real-time heatrate can either be utilized as a tool for operator performance tweaking or as the central tool in a plant optimizing strategy. Several EPRI studies have pointed to 3-4% potential improvement in plants not currently employing optimization. For tweaking, the operator simply notes the heatrate before and after changing a control setting to determine if the change was for better or worse.

Cost Benefit

Benefit analysis will be presented based on the following information:

Base Loaded Unit, Generation 500 MW
Utilization Factor 0.75
Unit Heatrate 10,000 Btu/Kwh or 2,520 heatrate2_clip_image002_0002
Gross Calorific Value of Coal 10,000 Btu/lb or 5555 heatrate2_clip_image002_0002
Cost of Coal U.S. $40/ton

A 2% improvement in heatrate (decrease from 10,000 Btu/Kwh to 9,800 Btu/Kwh or from 2,520 Kcal/Kwh to 2,470 Kcal/Kwh) will result in savings in fuel cost of U.S. $1.31 million per year.

After implementing real-time performance monitoring, many units were able to improve heatrate by more than 2%. This results in considerable savings in fuel costs.

Other Benefits

There are several other benefits that can be realized from real-time performance monitoring. In many units coal blending is used. Many times the optimum blend ratio is not-known apriori. In such cases real-time performance monitoring would enable the operators to know as to which blend ratio leads to optimum performance. The same is true with taking decision on which coal to use among several available.

A real-time program is a great "what if" tool. If your plant is considering putting in new emissions cleaning systems such as SCRs or scrubbers but want to consider using "cleaned coal" instead. TTURTHRM can help. Simply acquire sufficient cleaned coal to perform a test and burn it while monitoring with TTURTHRM. If the dollar equivalent to the improvement in heatrate is greater than the additional cost of the cleaned coal and if the improved emissions targets are met then the capital outlook for the emissions cleaning systems are not required. Additional savings in less maintenance for the proposed equipment as well as reduced cost of ash disposal are a bonus.

Qualifications of Project Managers

Sastry Munukutla received Ph.D. in Mechanical Engineering from the University of Iowa. He is Professor of Mechanical Engineering and Director of the Center for Electric Power. He is an Associate Fellow of the American Institute of Aeronautics and Astronautics and Fellow of the American Society of Mechanical Engineers. He has been advisor/co-advisor of 9 Ph.D. and 28 Masters' students to completion. He has authored more than 160technical publications; which include journal articles, conference proceedings articles, and technical reports. His expertise is in the general area of fluid/thermal sciences with particular emphasis on energy conversion processes.

Robert Craven received a Bachelors Degree in Chemical Engineering from West Virginia University in 1984. He worked for 15 years as a researcher at WVU within the Center for Industrial Research Applications where his research resulted in co-authoring 6 patents. His three years with Tennessee Technological University as an R&D Engineer, maintaining the Center for Electric Powers heatrate code has taught him the nuances of working with various Powerplant's computer systems. He has 33 published technical papers and many reports and white papers to his credit.

Cost and Time

The cost of the project depends on several factors such as travel distance, from Cookeville, amount of work shared by the sponsoring agency, and the number of units to be modeled. Therefore, the cost of the project is negotiable.

The time needed to complete the project depends on the cooperation of the personnel from the sponsoring agency. Typically it would take between 4-6 weeks to develop the software, which is ready to be installed in a unit, after a snapshot of the relevant data is received from the unit. In most units the software installation is completed within one working day. The total project period is generally kept at one year even though the software can be installed and be running within three months at the most. The remaining time would be utilized for fine-tuning the software, validating the software by field tests, and implementing any changes suggested by the customer.

References