JPH0834755B2 - Combustion control method - Google Patents

Description

Detailed Description of the Invention [0001] FIELD OF THE INVENTION The present invention relates to a combustion control method for a furnace and
And equipment, especially plant operation of NOx, unburned ash, etc.
Maintains maximum plant thermal efficiency under operational constraints
Combustion control method suitable for [0002] 2. Description of the Related Art Conventionally, combustion fire has been used as a combustion control method for a furnace.
Detects flame light and maximizes its light spectrum intensity
To control the ratio of fuel supply to air supply
How to get more heat energy with maximum efficiency
Method and apparatus "JP-A-56-1200224) and combustion fire
Efficiently adjust the optimum supply of combustion air according to the light intensity of the flame.
Method (“Combustion air supply amount control device”)
1814) and so on. Both of these maximize combustion efficiency
It is considered to be an effective technology for reducing NOx and reducing combustion.
A fuel that maximizes the heat absorption rate of the boiler while stabilizing
It does not realize firing control. On the other hand, there is a closed rule for controlling the NOx amount in the furnace.
The loop control method has not been adopted conventionally. The reason for this is
There is no technology to accurately measure the amount of NOx produced in the furnace
Therefore, the operation of fuel and air to control the amount of NOx in the furnace
This is because the amount could not be determined. Therefore, conventionally, the load
Determine the amount of fuel and air corresponding to the
Close the NOx while checking the measured NOx value at the furnace outlet.
It's just loop control. Therefore, coal type fluctuation, etc.
In plants where there are changes in fuel properties and coal supply fluctuations due to
Control of NOx was impossible. Further, regarding the combustion stability, conventionally, the furnace top has been used.
With the TV camera attached to the viewing window, you can take a picture of the flame inside the furnace.
Humans monitor the image on a monitor TV to stabilize combustion.
The method of evaluating the sex is adopted, and it is necessary to make an accurate evaluation.
Requires in-depth experience and individual differences can enter the evaluation
It has the disadvantage of high efficiency. As described above, in the prior art, particularly fuel
NOx in plants with changes in properties and fluctuations in coal supply
Parameters that are important for operation such as ash and unburned matter in ash under constraint conditions
Stable and maintain thermal efficiency at maximum value while suppressing
Such combustion control was impossible. [0006] OBJECTS OF THE INVENTION The object of the present invention is to introduce fuel into a furnace.
The amount of ash in the ash does not change in response to changes in supply amount, properties, and required load.
Stable and highly efficient combustion under the operational constraints of fuel
And a combustion control method that maximizes the thermal efficiency of the plant.
To provide. [0007] [Outline of the Invention]According to the present invention for achieving the above object
Combustion control method is used to control the fuel consumption before the boiler is actually operated.
And the trial operation amount of air and set the trial operation amount
Boiler furnace mouth based on quantity and model prepared in advance
Of unburned ash in the
The trial operation amount is corrected so that the minute satisfies the specified condition.
The trial when the unburned content in the ash satisfies the specified conditions.
The boiler thermal efficiency was calculated based on the manipulated variable.
The above trial was performed with the optimum operation amount that maximizes the boiler thermal efficiency.
Calculated by adding the correction to the manipulated variable, and calculated by this correction
The optimum operation amount is the fuel and the fuel for actually operating the boiler.
It is special to control the combustion of the boiler as the actual manipulated variable of air.
To collect. Furthermore, in order to improve the accuracy of boiler thermal efficiency
In addition, the combustion stability is evaluated before the boiler operation with the actual operation amount.
If the combustion condition meets the specified conditions, the
It is characterized by performing the combustion control. [0009] BEST MODE FOR CARRYING OUT THE INVENTION The following is a description prior to the description of the embodiments of the present invention.
An overview of the coal-fired power plant, which is one of the application targets of the invention
This will be described with reference to FIG. First, coal for burning in the boiler 1
Are stored in the coal bunker 2, and the feeder 4 and
It is supplied to the mill 5 by the driving motor 3 and crushed,
It is sent to Anna 6. Combustion air is fed by the forced draft fan 8.
It is sent to the air preheater 9, and one is used for transporting pulverized coal.
The air is passed through the next air fan 12 to the mill, and the other is used as combustion air.
Directly to the burner 6. In addition, the air preheater 9 has a bar
There is an Y-pass system, and the damper 10 controls the temperature of the primary air.
It is designed to be controlled. Also, the total air required for combustion
The amount of air is required by damper 7 and the amount of air required for pulverized coal transportation is damper 1
1 respectively controlled. On the other hand, the water supply system 13
The pressurized feed water becomes superheated steam in the boiler 1 and becomes main steam.
It is sent to the turbines 15 and 16 via the pipe 14. Turbine
15 and 16 rotate due to adiabatic expansion of superheated steam to generate electricity.
Generate electricity by machine 17. Also, it burns in the boiler 1 and water
The exhaust gas from the combustion that heats the steam and steam is sent to the chimney 19.
Although part of the gas is released to the atmosphere, a part of the gas is a gas recirculation fan.
It is returned to the boiler 1 by 18. Such a coal-fired power plant has a load requesting instruction.
In order to operate smoothly according to the regulations, each valve and
It is necessary to properly control the motor and motor. Figure 3 shows the conventional
Outline of automatic control system for thermal power plant that has been used from
The figure is shown. The outline of the function is explained below according to this figure.
It First, the load on the thermal power plant (output of the generator 17)
The request signal 1000 shows that the main steam pressure 1100 is a predetermined value.
(Constant value in a constant pressure plant and load in a transformer plant
(Main steam pressure compensation block)
100) Boiler input demand signal 300 to boiler 1
It becomes 0. This boiler input demant signal 3000 is
To the water supply flow rate control system 400 as the set value of the water flow rate 1200
Guided and used for controlling the feed water flow control valve 20
On the other hand, it is also used for determining the combustion amount demand 3100.
It Boiler entry led to main steam temperature compensation block 200
For the force demant signal 3000, the main steam temperature 1101 is predetermined.
Corrected to the value and determined the combustion amount demand 3100
Set. This fuel quantity demand signal 3100 is the total coal
The fuel flow rate control system 500 is used as the set value of the combustion flow rate 1201.
To control the drive motor 3 of the feeder 4
used. Further, the fuel amount demand signal 3100 is
Exhaust gas O in the ratio compensation block 300₂Excess rate becomes a predetermined value
And the total air flow demand signal 3200
Become. The air flow rate control system 600 has a total air flow rate of 1202
Controls the damper 7 so that is equal to this demand signal
I do. The above is the outline of the automatic control system for the coal-fired power plant.
In addition to this, the reheat steam temperature control system and turbine control
There is a valve control system etc., but omitted because it is not directly related to the present invention
I have. FIG. 1 shows the coal according to the present invention shown in FIGS.
The whole block diagram of the example applied to a thermal power plant is shown. Figure
3 that are the same as or equivalent to those in FIG. 3 are represented by the same symbols.
You In this example, the fine powder as shown in FIG.
Targeting the furnace of a coal-fired boiler, the furnace is divided into five areas (internal bar
The zone is divided into 3 areas)
It The subscripts added to the quoted numbers in Fig. 1 correspond to the above divided areas.
Indicates the number that was made. The process signal for each area is
Because it is simple, it is expressed as the total value before and after the furnace can.
1 differs from the conventional one in that the following functions are added.
Is Rukoto. (1) Flame image measurement function block 4000 (2) Stage-wise NOx estimation function block 4100 (3) Functional block 4200 for estimating the unburned carbon content in each ash (4) Stepwise combustion diagnosis function block 4300 (5) Combustion gas temperature estimation function block 4400 (6) Fuel / air distribution calculation block 4500 for each stage Hereinafter, the outline of this embodiment will be described with reference to this drawing. The flame image measuring block 4000 is a burner.
The representative burner fire of the burner stage with the shooting camera installed for each stage
Flame information 1305₁~ 1305₃And two-dimensional shading
Image 1306₁~ 1306₃Is to be converted to. Step by step
The NOx estimation function block 4100 is used to remove the furnace from each burner stage.
Burner flame information 1305 NOx generated to reach the mouth₁~
1305₃, Coal supply amount 1300₁~ 1300₃, Primary air volume 1
301₁~ 1301₃, Secondary air amount 1302₁~ 130
2₃, Tertiary air amount 1303₁~ 1303₃, Actor Air 1
310 and NOx1304 at the furnace outlet
To estimate. Block function for estimating unburned ash content
4200 is a two-dimensional gray image signal 1306₁~ 1306₃
The flame feature parameter is calculated based on
The unburned content in ash in each region is estimated by an estimation model using
(Details are described in Japanese Patent Application No. 59-110837). Next step
Combustion diagnosis function block 4300 is different from combustion stability diagnosis.
The usual factors are estimated by the following method.
There are two methods. That is, the two-dimensional grayscale image signal 1306
₁~ 1306₃From the feature parameters focused on the flame shape
Calculated and created from now on
There are methods based on characteristic parameters. More about the former
Is described in Japanese Patent Application No. 59-184657. Special about the latter
It is described in Japanese Patent Application No. 59-174998. Combustion gas temperature estimation function
Block 4400 indicates the combustion gas intensity of each area shown in FIG.
Degree information 1306₁~ 1306_FiveCombustion of each area based on
Gas temperature estimated value 1402₁~ 1302_FiveTo calculate. Figure 5
Is a burner for each stage Fuel / air distribution calculation function block 4
500 for requested fuel demand 3100
Environmental regulation values such as furnace outlet NOx1304, coal ash
The unburned content in ash, which is important for the effective use of
Desulfurization equipment that should be considered in terms of main engine protection
Inlet temperature (corrosion tends to occur at low temperatures), water walls and wipes
Heat flux of radiant superheater (Metal burns out when it exceeds the specified value
The plant operation restrictions such as
However, the heat flowing into the furnace and the amount of heat generated are the best
Absorbed by metal or internal fluid of water wall and radiant superheater
Each bar to maximize the thermal efficiency of the boiler.
Nadan fuel distribution command 3311₁~ 3311₃, Primary air volume target
Value 3320₁~ 3320₃, Secondary air amount target value 3330₁
~ 3330₃, Tertiary air amount target value 3340₁~ 3340₃as well as
Determine after-air amount target value 3350 from NO port
It The NOx estimator for each stage described above in this functional block
Noh block 4100, function block for estimating unburned ash content
The output of the 4200 is a restriction on NOx and unburned matter, respectively.
It is used to check the conditions and has a combustion gas temperature estimation function block.
4400 output, water wall outlet fluid temperature 1308, can wall
Metal temperature 1309₁~ 1309_FiveMeasures boiler thermal efficiency
Used as a correction signal for the furnace heat transfer model to calculate
It The step-by-step combustion diagnosis function block 4300 is
In the example, it is positioned as a combustion state monitoring function.
In the event of an abnormality, the output signal is an alarm, CRT display
Make it possible for the device to know the cause and status of the abnormality.
It Hereinafter, each functional block will be described in detail.
It FIG. 6 shows a flame image measuring function block 400.
An example of 0 is shown. In this embodiment, the representative bar of each stage burner group is
Anna's flame image 1305₁~ 1305₃Image guide
Imaging device ITV via IG and image fiber IF
And convert it to a video signal,
Converted to digital data by digital converter A / D
It This data is stored in the frame memory FM,
Dimensional grayscale image signal 1306₁~ 1306₃As shown in Figure 1
Stage-wise NOx estimation function block 4100, stage-wise unburned ash content
Estimation function block 4200, combustion diagnosis function block for each stage
It is shared by 4300. The image guide IG is
Inside the furnace because it is important to grasp the flame at the root of the front burner
Need to be inserted into the machine and can withstand a temperature of about 1500 ℃
Coat the image fiber IF with material and cool it
(The details are described in Japanese Utility Model Application No. 59-15458.)
). FIG. 7 shows the NOx estimation function block 41 for each stage.
Example of No. 00 is shown. NOx reduction amount estimation model 4101
Then burner flame information for each stage 1305₁~ 1305₃Based on
The flame characteristic parameters of each stage and calculate the parameters.
Burner unit NOx reduction amount 4105 as a function of₁~ 4
105₃Is estimated. For more information on thisSpecial
Wish sho 59-92872"Combustion condition monitor"
It Next, in the burner simplex NOx estimation model 4102,
Level of coal supply 1300₁~ 1300₃And primary air amount 130
1₁~ 1301₃, Secondary air amount 1302₁~ 1302₃, 3
Next air amount 1303₁~ 1303₃And after air 1310
To burner air ratio 4109₁~ 4109₃Seeking burner
Estimate the amount of simplex NOx produced before it is reduced.
NOx reduction amount of the above burner alone 4105₁~ 4105₃The difference
Pull out and burner unit NOx concentration 4106₁~ 4106₃Recommend
Set. In the NOx estimation model 4103 for each stage,
Burner amount using the burner air ratio and burner average air ratio
Effect of NOx retention in the furnace on the body NOx concentration
And NOx regeneration effect by air injection from NO port
NOx estimated value 1501 for each stage based on the considered model₁~
1501₃To calculate. Furnace NOx estimation model 4104
Then, the NO for each stage obtained by the NOx estimation model for each stage 4103
The primary estimated value of x is the NOx measurement value 1304 at the furnace outlet
Error correction signal 4108₁~ 4108₃Corrected with
Ox estimated value 1501₁~ 1501₃Is to calculate. Up
Pre-stage NOx estimation model 4103 and furnace NOx estimation model
For details of Le 4104, see Japanese Patent Application No. 59-118296.
It is being eaten. FIG. 8 is a block diagram showing a fuel / air distribution calculation function for each stage.
An example of a rack 4500 is shown. The operation is shown below using this figure.
Explain the work. Optimal manipulated variable search start condition check unit 45
In 01, the fuel amount demand 3100 at a predetermined cycle,
NOx estimate for each stage 1400₁~ 1400₃、 Unburned part
Estimated value 1401₁~ 1401₃, Furnace outlet exhaust gas concentration 13
11₁~ 1311_nIs compared with a preset specified value,
If the specified value is not exceeded, the fuel allocation instruction for each stage calculated last time
3310₁~ 3310₃, Primary air amount target value 3320₁
~ 3320₃, Secondary air amount target value 3330₁~ 333
0₃, Tertiary air target value 3340₁~ 3340₃And Huata
Air amount target value 3350 (above, 4 kinds of commands and target values
The operation amount is abbreviated as a whole)
However, if any value exceeds the specified value, the optimum operation amount
A new optimum operation is performed according to the following procedure by the search command 1601.
Let the quantity search start. That is, start of trial operation
Is the start condition in the optimum operation amount start condition check unit 4501.
It is performed when is established. First, search command
1601 operates the optimum manipulated variable search unit 4502
Row operation 1602 is performed for each stage NOx prediction model 4503, each stage is unburned
Minute prediction model 4504, furnace exit exhaust gas concentration prediction model
In addition to 4505, each model
Every step NOx predicted value 1603₁~ 1603₃、 Unburned part
Predicted value 1604₁~ 1604₃, Furnace exit exhaust gas concentration prediction
Measured value 1605₁~ 1605_n, Furnace heat transfer model output 160
6₁~ 1606_mTo calculate. Then these calculated values are
The face constraint condition check unit 4507 satisfies the specified constraint condition.
Let me check if I am adding and if I am not satisfied
If so, repeat the above calculation until the conditions are met.
return. If the conditions are satisfied, the thermal efficiency calculation unit 4508
More furnace heat transfer model output 1606₁~ 1606_mTo
Calculate the boiler thermal efficiency based on the
The constant unit 4509 determines whether the calculated value is the highest value.
If it is not the highest value, the above trial operation is repeated. Most
When it reached a high value, it corresponded to the highest value of its thermal efficiency
The operation amount is set to the optimum operation amount via the optimum operation amount output unit 4510.
To output. The stage-by-stage NOx prediction model 450
3, Stage unburned component prediction model 4504, Furnace exit exhaust gas concentration
Multiple regression analysis method as a method of constructing the degree prediction model 4505
Application Japanese Patent Application No. 56-80932 "Boiler Combustion Monitoring
Control method ". According to this method, the optimum manipulated variable and N for each stage are appropriately set.
Ox estimated value 1400₁~ 1400₃, Optimum manipulated variable and ash per charcoal
Medium unburned content estimated value 1401₁~ 1401₃， Optimal amount of operation and fire
Furnace exit exhaust gas concentration 1311₁~ 1311_nEach of the former
Multiple regression analysis is performed using the explanatory variable and the latter as the dependent variables.
The model can be modified and the characteristics of the furnace can be changed.
Can also adapt each model. Also the furnace
The heat transfer model 4506 is also compatible with the optimum operation amount
Combustion gas temperature estimated value 1402₁~ 1402_Five， Water wall
Tar temperature 1309₁~ 1409_Five, Water wall outlet fluid temperature 13
Modifying the model with accumulated data for each of the 08
Allows the furnace model to be adapted to the furnace characteristics
It FIG. 9 shows the fuel / air distribution calculation function block for each stage.
4500 shows another embodiment of the rack 4500. This example shows NOx for each stage
Prediction model 4503, Stage unburned component prediction model 4504
Optimal without using the furnace outlet exhaust gas concentration prediction model 4505
The trial operation 1602 from the operation amount search unit 4502 is directly
Output to the process side and constraints based on the actual response signal
FIG. 8 shows that the check unit 4507 checks conditions.
Different from the above example, the procedure up to the output of the optimum manipulated variable is the same.
It is like. FIG. 10 shows the fuel / air distribution meter for each stage described above.
The operation of the arithmetic function block 4500 is shown in a flow chart.
It is a thing. If the system works for the first time,
The optimum operation amount is calculated and output by the procedure described above. Twice
In the case of the operation after the eye, first, the present fuel amount demand L
And the demand L * when the optimum operation amount was calculated last time
The absolute value of this difference is the specified value ε_LA place that has changed beyond
In the case of a
Therefore, the optimum operation amount is recalculated. Above fuel demand
The deviation between is the specified value ε_LFurnace outlet NOx in the following cases
Whether operational constraints such as concentration are met
Is checked by the optimum operation amount search start condition check unit 4501.
If you are satisfied, continue to output the previous optimum operation amount.
Force, and if not satisfied, compare with the previous operation amount output.
All of the above operational constraints (eg NOx concentration at the furnace outlet)
Check if there has been a change in the
If there is a change, a new optimum manipulated variable is searched, and if there is no change,
If this is the case, it is considered to be due to the estimation error of the estimation model.
The applicable estimation model (eg NOx estimated value at the furnace outlet)
Does not satisfy the constraint conditions, the NOx estimation function block for each stage
Estimated model in C.4100)
Correction using multiple regression analysis method based on process data
It And in this case, subtract the optimal operation amount calculated last time.
Continue to output. That is, the above start condition is not satisfied
Also, the difference between the current value of fuel demand and the previous value exceeds the specified value.
If so, the trial operation is started and this is in normal fuel.
Is also done in. The search algorithm for the optimum manipulated variable shown in this figure
Before discussing gorythm, first of all
On the furnace heat transfer model used for checking and thermal efficiency calculation
explain. Figure 11 shows a furnace heat transfer model of a pulverized coal burning boiler.
Show. In this example, the furnace is vertically upward (how the combustion gas flows
Direction) and divide each area into lumped constants
Of. In the figure, the firing in the furnace treated as a lumped parameter
Gas and water wall heat transfer tube metal (hereinafter abbreviated as metal) and heat transfer
Fluid for heat pipe internal fluid (hereinafter abbreviated as internal fluid) / heat transfer professional
Seth. The relationship between these process quantities is mass, motion
A non-linear physical model based on conservation laws of quantity and energy
I do. However, the flow time constants of combustion gas and internal fluid are
Since the heat transfer time constants are small compared to those of the combustion gas and internal
Flow characteristics of the part fluid is steady flow (acceleration does not occur in the fluid
Flow) and approximate static characteristics. First, the symbols used in the equations will be described.
It (1) Symbol F: Mass flow rate (kg / S) P: Pressure (KPa) T: Temperature (℃) H: Specific enthalpy, calorific value (kJ / kg) Q: Amount of heat held, amount of heat transfer (kJ / s) U: Heat flux (kJ / (s.m²)) ρ: Density (kg / m³) α: convection heat transfer coefficient (kJ / (m². ℃ .s)) β: radiant heat transfer coefficient (kJ / (m²・ (° K / 100)
^Four・ S)) C: Constant pressure specific heat (kJ / kg. ° C) X: Dryness (-) W: Moisture content in coal (-) ν: Ash content in coal (-) μ: excess air ratio (-), concentration (%) ε: Passage rate of floating ash at the furnace exit (-) λ: Flow path friction coefficient (-) k: combustion ratio (-) g: Gravitational acceleration (m / s²) R: Gas constant (kg.m / (kg ・ ° K)) A: Heat transfer area, flow path cross-sectional area (m²) D: Channel diameter (m) V: Channel volume (m³) ΔZ: Channel length, channel head difference (m) K_T: Overall effect of combustion gas composition on gas temperature
Coefficient (-) K_R: Overall effect of combustion gas composition on gas constant
Coefficient (-) K: Combustion gas composition factor and above K_TAnd K_RSeki
Coefficient for approximating the coefficient (-) φ: Combustion gas and heat transfer tube metal in different divided areas
Shape factor for radiation heat transfer (-) (2) Subscript (I) Subscript indicating the relationship between objects g: Combustion gas m: heat transfer tube metal s: Fluid inside heat transfer tube c: pulverized coal l: ignition oil pa: Primary air (pulverized coal carrier air) sa: Secondary air ta: tertiary air f: heating element by combustion gm: Heat transfer from combustion gas to heat transfer tube metal ms: Heat transfer from heat transfer tube metal to internal fluid sg: Flow from heat transfer tube internal fluid to combustion gas and heat transfer ash: ash a: Total air flowing into the furnace ao: The fuel that has flowed into the furnace is required for complete combustion.
Required air atm: Atmosphere 0: Excess oxygen in combustion gas (Ii) Subscript indicating the location i: Furnace section i (1): In front of the can of the i section of the furnace i (2): After the can of the i section of the furnace in: Combustion gas in i-section and transmission in all sensations
Heat tube metal ni: combustion gas in all sections and transmission in i section
Heat tube metal j: Burner stage SH: Radiant superheater F: Inside the furnace FX: Downstream of furnace exit SH (1): Combustion gas contact part of radiant superheater SH (2): Radiant heat receiving part of radiant superheater (Iii) Subscript indicating reference value, state transition, etc. gr: reference value of state quantity related to combustion gas sr: Reference value of state quantity related to fluid inside heat transfer tube r: reference value for composition of fuel and combustion gas gv: State value related to evaporation of water and superheat gmr: basis for heat transfer from combustion gas to heat transfer tube metal
Quasi value msr: Base for heat transfer from heat transfer tube metal to internal fluid
Quasi value SB: Subcool boiling start point state value Next, the formula of the furnace model is shown. 1. Fuel / air heat input / heat generation characteristic model (1) Amount of heat generated by combustion [0025] [Equation 1] [0026] (Equation 2) [0027] [Equation 3] [0028] [Equation 4] [0029] (Equation 5) (2) Quantity of heat of fuel and air [0031] [Equation 6] [0032] (Equation 7) [0033] (Equation 8) [0034] [Equation 9] [0035] [Equation 10] 2. Model for heat transfer and flow characteristics on combustion gas side 2.1 Heat transfer characteristics on the combustion gas side (1) Combustion gas temperature [0037] [Equation 11] [0038] [Equation 12] [0039] [Equation 13] [0040] [Equation 14] [0041] (Equation 15) (2) Heat transfer between combustion gas and metal [0043] [Equation 16] [0044] [Equation 17] [0045] [Equation 18] [0046] [Formula 19] [0047] [Equation 20] [0048] [Equation 21] [0049] [Equation 22] [0050] [Equation 23] [0051] [Equation 24] [0052] [Equation 25] 2.2 Flow characteristics of combustion gas (1) Combustion gas flow rate [0054] [Equation 26] [0055] [Equation 27] (2) Combustion gas pressure [0057] [Equation 28] [0058] [Equation 29] [0059] From equations (28) and (29) [0060] [Equation 30] [0061] [Equation 31] [0062] [Equation 32] [0063] 3. Metal / Internal fluid side heat transfer / flow characteristic model 3.1 Metal / Internal fluid side heat transfer characteristics (1) Metal temperature [0064] [Expression 33] [0065] (2) Heat transfer from metal to internal fluid and atmosphere [0066] [Equation 34] [0067] f_s: Convective heat transfer between metal and internal fluid in two-phase flow
Achievement rate correction factor [0068] [Equation 35] [0069] [Equation 36] [0070] [Equation 37] [0071] (3) Internal fluid temperature and dryness [0072] [Equation 38] [0073] [Formula 39] [0074] [Formula 40] 3.2 Flow characteristics of internal fluid (1) Internal fluid pressure [0076] [Formula 41] [0077] [Equation 42] 4. Overall characteristic model in furnace (1) Air excess rate [0079] [Equation 43] [0080] [Equation 44] [0081] [Equation 45] [0082] [Equation 46] [0083] [Equation 47] [0084] Residual oxygen concentration (wt%) [0085] [Equation 48] (2) Furnace outlet combustion gas flow rate [0087] [Equation 49] [0088] [Equation 50] [0089] [Equation 51] (3) Influence coefficient by composition of combustion gas [0091] [Equation 52] [0092] [Equation 53] [0093] [Equation 54] [0094] [Equation 55] Next, the furnace outlet NOx prediction mode in FIG.
The Dell 4503 will be described. Operation with NOx at the furnace outlet
Since it is difficult to describe the relationship with quantity with a physical formula,
It is practical to use a statistical method such as a regression analysis method.
Next, regarding the configuration example of the prediction model by the multiple regression analysis method
explain. In the multiple regression analysis method, the explanatory variable is x_i(I = 1 to 1
m), with the dependent variable as y [0096] [Equation 56] When the following functional relation is established, [0098] [Equation 57] The partial regression coefficient β₀, Β₁… Β
_mIs a method of determining so that the deviation between y and Y is minimized.
It In the furnace outlet NOx model, it is possible to predict NOx for each stage.
Applying this method, the NOx predicted value for each stage is calculated as [0100] [Equation 58] [0101] [Equation 59] [0102] [Equation 60] [0103] Where x₁~ X_m: Manipulated variable β₀₁~ Β_mi(I = 1 to 3):
Predicted by partial regression coefficient, the furnace outlet NOx [0104] [Equation 61] Where F_c,_i: I-stage pulverized coal flow rate Predict by. A step for determining the partial regression coefficient of equations (58) to (60)
The NOx estimation function block 4 for each stage is used as the NOx data for each stage.
100-stage NOx estimated value of 1400₁~ 1400₃To
To use. [0107] In a model 4504 for predicting unburned content in ash at a furnace outlet
In the same way as above, the multiple regression analysis method
The predicted fuel content is [0108] [Equation 62] [0109] [Equation 63] [0110] [Equation 64] Where β ′₀₁~ Β '_mi(I = 1 to 3): Partial regression coefficient The unburned content in the ash at the furnace outlet is calculated by the following formula [0112] [Equation 65] Predict by For determining the partial regression coefficient of the equations (7) ′ to (9) ′
The unburned content data for each stage is as follows:
NOx estimated value 1401 for each stage according to₁~ 14
01₃To use. In the furnace outlet exhaust gas concentration prediction model 4505
In addition, CO, SO, dust concentration, etc. at the furnace outlet
Estimate exhaust gas concentration by multiple regression model as above
In this case, it is possible to estimate the concentration for each stage.
Since it is not possible to obtain
Is modeled by the relational expression (2) ′ to calculate the exhaust gas concentration
The partial regression coefficient is obtained using the measured values. Next, in the operation described in FIG. 8, FIG. 9 and FIG.
An example of the constraint condition check unit 4507 is shown below (note that
Here, since it is a single cylinder, the constraint conditions regarding exhaust gas are omitted.
It ). [0117] [Equation 66] [0118] [Equation 67] [0119] [Equation 68] [0120] [Equation 69] [0121] [Equation 70] Here, NOx_FX: NOx concentration at furnace outlet UBC_FX: Unburned content in ash at furnace exit NOx_U: Upper limit of NOx concentration at furnace outlet NOx_L: Lower limit of NOx concentration at furnace outlet UBC_U: Upper limit value of unburned matter in ash at furnace exit T_g,_FX: Furnace outlet gas temperature T_g,_FXU: Lower limit of furnace outlet gas temperature U_gm,_i: Water wall metal heat flux in region i U_gm,_iU: Water wall metal heat flux upper limit of region i U_gm,_SH: Radiation superheater metal heat flux in region i U_gm,_SHU: Radiation superheater metal heat flux upper limit of region i The above equation (68) is installed when the temperature of the denitration unit inlet air is too low.
Prevents low temperature corrosion of installed metal parts, as it is easy to cause
The constraint conditions for the
It Also, equations (69) and (70) prevent metal burnout.
This is a requirement. On the other hand, when determining the optimum manipulated variable,
Examples of constraints imposed on trial operation 1602 described in FIGS.
Is shown below. [0124] [Equation 71] [0125] [Equation 72] [0126] [Equation 73] [0127] [Equation 74] [0128] [Equation 75] Where F_c,_i: Flow rate of pulverized coal in area i F_pa,_i: Primary air flow rate of 〃 F_sa,_i: 〃 secondary air flow rate F_ta,_i: 〃 tertiary air flow rate F_c,_iU: 〃 pulverized coal flow rate upper limit F_c,_iL: 〃 lower limit value of 〃 F_pa,_iU: Upper limit of primary air flow rate of 〃 F_pa,_iL: 〃 lower limit value of F_sa,_iU: Upper limit of secondary air flow rate of 〃 F_sa,_iL: 〃 lower limit value of F_ta,_iU: Upper limit of tertiary air flow rate of 〃 F_ta,_iL: 〃 lower limit value of Next, the thermal efficiency of the thermal efficiency calculation unit 4508 shown in FIGS. 8 and 9
η is the total calorific value of the calorific value and heat input in all areas of the furnace
And the ratio of the amount of heat absorbed by the fluid inside this metal
Then, the calculation is performed using the following formula. [0130] [Equation 76] Here Q_ms,_i: Heat transfer from water wall metal in region i to internal fluid Q_ms,_SH: Heat transfer from radiant superheater metal to internal fluid Q_f,_i: Due to combustion of pulverized coal and ignition oil fuel
Amount of heat generated Q_c,_i: Heat quantity of pulverized coal in area i Q_l,_i: Heat capacity of ignition oil of 〃 Q_pa,_i: Heat capacity of primary air in 〃 Q_sa,_i: Heat capacity of secondary air possession of 〃 A_ta,_i: Heat capacity of tertiary air In addition, as a way of thinking about thermal efficiency,
Total amount of heat and heat input and heat absorbed by this metal
When defined as the ratio of quantities, it becomes as shown in equation (77). [0132] [Equation 77] Here, Q_c,_gm,_i: Pair of combustion gas in region i to water wall metal
Flow heat transfer (kJ / s) Q_e,_gm,_in: From the combustion gas in region i to the entire region (water wall and
Radiant superheater) Radiant heat transfer to metal (kJ / s) Q_c,_gm,_SH: Radiant superheater metal from combustion gas in region i
Heat transfer to the convection (kJ / s) Next, in the calculation application unit of the optimum operation amount in the flow of FIG.
An example of the calculation method will be shown. FIG. 12 is a block diagram showing one method of nonlinear programming.
Algorithm to determine the optimum manipulated variable using the simplex method
Is a flow. This algorithm
Is expressed by Eq. (11) under the constraints of Eqs. (66) to (75) above.
This is to search for the manipulated variable that maximizes the indicated thermal efficiency η.
It Hereinafter, this algorithm will be described with reference to FIG.
I do. Step 1: Formation of initial simplex The initial trial points X (1, i) (i = 10 to 22) are (71) to (7
Assuming that all the constraints in equation (5) are satisfied, the operation vector
In the 13-dimensional space spanned by X, K angle (K =
However, K is generally about twice the order of the operation vector.
Form a polygon (this is called simplex)
And make this the initial simplex. How to form this
As a method, one point is the initial trial point X (1, i), and the remaining
(K-1) points are uniform random numbers r_jusing (j = 2 to K)
Determined by the following formula. [0136] [Equation 78] However, 0 ≦ rj ≦ 1, and X_iminAnd X
_imaxIs the lower and upper limits of the manipulated variables shown in Eqs. (71) to (75).
is there. X (j, i) thus determined is (71)-
Although the constraint condition of Eq. (75) is satisfied, the constraint condition of Eqs. (66) to (70) is satisfied.
The matter is not always satisfied. If so, then
The trial point and the center of gravity of the trial point toward the center of gravity of the already determined point
Move to the midpoint of. In this way, ultimately everything
Determine the point. Step 2: Calculation of thermal efficiency The manipulated variable X (j, i) obtained in step 1 (i = 10 to 2)
2, j = 1 to K) at each point of the simplex
On the other hand, the thermal efficiency is calculated using equation (11). Step 3: Calculation of center of gravity Among the points of the simplex, the point with the lowest thermal efficiency
Defined by (K-1) points excluding
Center of gravity X_GiAsk for. The lowest efficiency point is now j = 1
And X_GiIs expressed by the following equation. [0141] [Equation 79] The distance ΔX from the lowest efficiency point to the center of gravity
_GiIs expressed by the following equation. [0143] [Equation 80] Step 4: Determination of new trial point From the lowest thermal efficiency point to the direction of the center of gravity,
And the distance between them is ΔX_GiΑ_iDoubled from the center of gravity
Let the point be a new trial point, and let this be X (K + 1, i), [0145] [Equation 81] It is represented by α_iThe value of is 1.3
Experientially good. New trial point is a constraint on the amount of operation
Cases (71) to (75) that infringe (7 in the figure₁) Is the trial point
Due to constraints (7 in the figure)₂). Step 5: Confirm constraint conditions The new trial point violates the operational constraints of Eqs. (66) to (70).
If so, all information about trial point X (K + 1, i)
Invalidate and return to the previous step 4 to determine a new trial point. That
Pipe α_i/ 2 is newly α_iSave it and return to step 4. Step 6: Calculation of thermal efficiency The efficiency η (K + 1) corresponding to the new trial point X (K + 1, i) is (1
Calculate using formula 4). Step 7: Determination of reaching the highest point of thermal efficiency Corresponds to the new trial points and the points that make up the original simplex.
The highest and lowest values of the thermal efficiency_maxOver
And η_minAnd the specified value is ε_ηThe highest efficiency
Whether or not it has arrived is determined according to the following equation. [0150] [Equation 82] If the highest point is reached, do not proceed to step 9
If so, go to step 8. Step 8: Formation of new simplex The lowest of the points that make up the original simplex
It was done by excluding the operating points that show efficiency and adding new trial points.
Form a new simplex from K points and go to step 3
Return. Step 9: Determination of optimum manipulated variable Optimal when it is determined in step 7 that the maximum efficiency point has been reached
Efficiency η_maxThe operation amount corresponding to is the optimum operation amount. FIG. 13 shows the optimum manipulated variable search algorithm.
Another embodiment will be described. Regarding this embodiment, first, referring to FIG.
Explain. Step 1 It is judged whether the search is the first time.
The amount of fuel in each area is maintained as it is and the process proceeds to step 3
If so, proceed to step 2. Step2 The distribution of fuel quantity in each region is within the range that satisfies the constraint condition shown in Eq. (6).
Change within the circle. However, the total fuel amount is the fuel amount
To be Step3 The amount of air in each region must be within the range that satisfies the constraint conditions shown in Eqs. (71) to (75).
Change in the predetermined steps in the
The constraint conditions (66) to (70) are satisfied and the thermal efficiency shown in (76) is
Search for the value that maximizes the thermal efficiency value and the amount of fuel and air
Remember. Step4 The operation to change the distribution of the fuel amount is performed over the entire range of the constraint condition of Eq. (6).
If not completed, return to step 1 and search in all areas
When is completed, proceed to step 5. Step 5 of the data of thermal efficiency, fuel quantity, and air quantity stored in step 3
The fuel amount and air amount of the group with the highest thermal efficiency
Use the optimum amount of operation. FIG. 14 and FIG. 15 show the steps 3 of FIG.
It shows an example of the Gorythm. This example is shown in FIG.
The burner stage and NO port air ratio are parameters as shown in
Assuming three combustion modes as
Shown are normal combustion, two-stage combustion, denitration combustion, NOx concentration
Shown in ascending order are denitration combustion, two-stage combustion, and normal combustion.
Paying attention to the above, the air ratio is changed from the current combustion mode as the starting point.
NOx concentration at the furnace outlet by trial operation using a method suitable for each mode
Best combustion efficiency under other operational constraints
It is something to adjust to such a value. Below, follow the instructions in Figure 14.
The processing contents of will be described. In step 1 of FIGS. 14 and 15, the current fire
NOx concentration at furnace outletNO _XFX Is the upper limit NOx_UBeyond
If this is the case, decrease the NOx concentration and decrease the combustion efficiency.
If the process does not exceed the upper limit, branch to the process after step 2
Is the current value and lower limit NOx in step 22_LAnd compare the lower limit
If it is less than the value, increase NOx concentration and increase combustion efficiency.
Then, the process proceeds to step 23 and subsequent steps in the following direction. NOx concentration is high
If neither of the lower limits is exceeded, the manipulated variable remains unchanged.
Hold and end the process. Below, the current NOx concentration is the upper limit
Value NOx_UExplain the case when the value exceeds. In step 2, the current combustion mode is described above.
Determine which of the three belong and based on the determination result
And branch to the corresponding processing step. First, normal combustion mode
The case will be described below. Step 3, 4, 5 Without changing the burner air ratio for each stage,
The NOx reduction amount for each burner stage is controlled by changing the ratio.
Control, including NOx concentration NOx concentration at furnace outlet
Check whether the usage restrictions are satisfied
If not satisfied, repeat steps 3-5.
Return, and if satisfied, move to step 6. Steps 6, 7 and 8 Calculates the thermal efficiency η and stores the value and the manipulated value at that time
I do. And over the entire range of the ratio of the amount of tertiary air to the amount of secondary air
If the trial operation is not completed, repeat steps 3 to 7.
To return, go to step3, and when finished, move to step8, st
Largest thermal efficiency calculated by processing up to ep7
Value η (1, max) and manipulated variable u at that time¹Remember step 9
Move on to. Steps 9, 10, 11 The burner air ratio of each stage is the same ratio with the furnace air amount being constant.
Rate and decrease after-air at the same time
Check if the constraint conditions are satisfied and satisfy
If not, repeat steps 9 to 11 and be satisfied
If so, go to step 12. Step 12, 13, 14 Calculates the thermal efficiency η and stores the value and the manipulated value at that time
I do. The trial operation over the entire burner air ratio range was completed.
If not completed, st to repeat the processing from step 9 to step 13.
Move to ep9, move to step14 when finished, until step13
The largest value η (2, ma
x) and the manipulated variable u at that time²Memorize and move to step 15
It Steps 15, 16 and 17 The air ratio of the M burner stage shown in FIG.
The air ratio of the stage is reduced to meet the operational constraints.
Check if there is a st
Repeat the processing of ep15 to 17, and if satisfied, st
Move to ep18. step18,19,20 Calculates the thermal efficiency η and stores the value and the manipulated value at that time
I do. And the trial operation over the entire range of burner air ratio
If it is not completed, repeat steps 15 to 19
Go to step15, and if finished, move to step20, step1
Largest value of thermal efficiency calculated by processing up to 9
η (3, max) and manipulated variable u at that time³Memorize
Move to 21. Step21 Maximum thermal efficiency η obtained in steps 8, 14 and 20 above
For the largest of (1, max) to η (3, max)
The operation amount is the optimum operation amount. In step 2, the current mode is two-stage combustion.
If judged, the range from the two-stage combustion to the denitration combustion mode
Search for the optimum manipulated variable in steps 9 to 21.
It On the other hand, in the case of denitration combustion, in denitration combustion mode
Optimum in the procedure of step 15 to step 21 by trial operation of air ratio
Calculate the manipulated variable. As described above, when the current NOx concentration exceeds the upper limit value,
The lower limit value NOx_LIs below
The case will be described. At step 23, the combustion mode is determined,
It branches to each process based on the judgment result, but first, denitration combustion
The case of the mode will be described. Steps 24, 25, 26 Increase the air ratio of P burner and decrease the air ratio of M burner
Perform trial operation while keeping the air ratio of the entire burner constant.
Check whether the operational constraints are satisfied.
If you are not satisfied, go to steps 24-26.
Repeatedly, if satisfied, move to step 27. Steps 27, 28, 29 Calculates the thermal efficiency η and stores the value and the manipulated value at that time
I do. The burner air ratio is the same in the P stage and the M stage (2
Repeat steps 24 to 28 until the step combustion mode is reached, etc.
When it becomes low, move to step 29 and calculate up to step 28
Maximum thermal efficiency η (1 ', max) and at that time
Point operation amount u¹′ Is obtained and the process proceeds to step 30. Step 30, 31, 32 While increasing the air ratio of each stage burner by the same ratio,
When tare is reduced and operational constraints are met
Then move to step 33. Step 33, 34, 35 Calculates the thermal efficiency η and stores the value and the manipulated value at that time
I do. And the after air becomes 0 (normal combustion mode)
Repeat steps 30 to 34 until it reaches 0, and when it reaches 0, st
Maximum thermal efficiency calculated up to ep34 η (2 ', m
ax) and the manipulated variable u at that time²Ask for ′ and remember them
Then, move to step 36. Steps 36 to 41 Change the ratio of the amount of tertiary air to the amount of secondary air for each stage to improve the thermal effect.
Maximum value η (3 ′, max) of the rate and the manipulated variable u at that time³′
Is stored, and the process proceeds to step 42. Step42 η (1 ′, max) 〜η obtained in steps 29, 35, 41
Determine the maximum value of (3 ', max) and the manipulated variable at that time
And set this as the optimum operation amount. As described above, in the explanation of FIG. 10 to FIG.
Whether the result of the operation satisfies the operational constraints
As mentioned above, when deciding whether or not to do so, as shown in FIG.
, Stage-wise NOx prediction model, stage-wise unburned component prediction model, fire
For trial operation using the furnace outlet exhaust gas concentration prediction model
How to predict response and diagram9Use a prediction model as shown in
Directly plan trial operation amountToIn addition to
There is a method of using a response. Next, the combustion gas temperature estimation function block 44
00 will be described. As shown in FIG. 17, shown in FIG.
Image guide IG with the same structure as
Installed near the center of the side surface of each stage, to set the combustion gas brightness of each stage.
It leads to the optical branch pipe LDV via the image fiber IF,
Here, the light is split and monochromatic filters with different wavelengths are used.
FL₁, FL₂Via the imaging device ITV₁, ITV₂Lead to
Ku. In the image pickup device, the luminance information after passing through these filters is
Convert to video signal and convert each to analog-digital
Bowl A / D₁, A / D₂Converted into digital data by
After that, each frame memory FM₁, FM₂2D brightness
Store as light image data. Next, the brightness ratio calculator IRC
Calculate the luminance ratio of corresponding pixels of both image data with
It Two-dimensional image by two-color pyrometer method using this brightness ratio
The temperature of the point corresponding to each pixel of and the average value of the entire screen
The calculation is performed by the calculation unit TC. The calculation method is as follows
explain. First, the two-color pyrometer method will be described. FIG.
Single color filter FL in 7₁, FL₂Each wavelength
Λ₁(Cm), λ₂(Cm) obtained through each filter
The two-dimensional digital brightness grayscale image₁(I, J),
I₂(I, J) (brightness level is, for example, 0 to 25)
5. Here, (i, j) is the pixel (x,
y) Indicates the coordinates, and indicates the number of horizontal and vertical constituent pixels of the image.
If M and N respectively, i = 0 to (M-1), j = 0 to
(N-1). ), Then the image
The temperature T (i, j) at the mark (i, j) and the brightness of each of the above
The relationship with the frequency data can be expressed by equations (83) and (84).
Wear. [0180] [Equation 83] [0181] [Equation 84] Here ε: Radioactivity T: Temperature (° K) C₁: 3.7403 × 10^-Fiveerg cm²/ S C₂1.4387 cm · ° K λ₁, Λ₂: Wavelength (cm) Taking the ratio of Eqs. (83) and (84) and rearranging yields Eq. (85).
It [0183] [Equation 85] Here [0185] [Equation 86] [0186] [Equation 87] In the brightness ratio calculation unit IRC of FIG.
Degree ratio I₁(I, j) / I₂(I, j) is calculated and the result is
In the temperature calculation unit TC, the coordinates are calculated based on equations (85) to (87).
(I, j) Calculate the temperature at each point. Average temperature T_avIs calculated by the following equation. [0189] [Equation 88] Using the above equation (88), the combustion gas temperature in each region
Can be estimated. Next, the optimum manipulated variable determination shown in FIGS.
In the furnace heat transfer model 4506 of the constant algorithm,
Combustion ratio k shown in equation (1)_jiIs the combustion of regions i and j
It has a strong correlation with temperature, and their relationship is
It can be expressed as the number f. [0192] [Equation 89] Here, T_j: Average combustion temperature in region j T_i: Average combustion temperature in region i As a simple example of equation (89), there is a multiple regression equation such as
It is effective. [0194] [Equation 90] Here, b₀~ B₃: Partial regression coefficient By the way, the above combustion temperature is
For areas other than the flame temperature and burner stage, the combustion gas
The burner flame temperature is a special application if it is considered to be equivalent to the
Including the burner flame image extraction described in Sho-59-118298
The two-color thermometer method and the combustion gas temperature are the same as those shown in FIG.
It can be estimated by the two-color pyrometer method shown in equation (8). Since
Summarizing above, the combustion ratio is calculated by adding the trial operation to the plant.
Burner flame information and combustion gas brightness information
Can be estimated based on. But shown in Figure 8
In the case of the optimal manipulated variable determination algorithm,
The plant response to the
The model for predicting flame temperature and combustion gas temperature
It is necessary instead of the two-color pyrometer method. As this prediction method
Combustion temperature, flame temperature, combustion gas temperature
Corresponding display is updated and placed by learning the operation results at all times.
It is practical to use this correspondence table whenever necessary.
Target. [0196] [Modifications / Applications of the Invention and Their Effects] FIG. 18 shows a modification of FIG. 9 for the trial operation 1602.
Measures actual response results of combustion gas temperature and can wall metal temperature
Then, using those values, the furnace heat transfer model 4506
It is configured to calculate thermal efficiency and is a furnace heat transfer model.
Model for calculation of combustion gas temperature and water wall metal temperature of 4506
Is unnecessary and the model can be simplified. Combustion diagnosis function block 4 for each stage shown in FIG.
Japanese Patent Application No. Sho 59-184657 for 300
If adopted, the trial operation 1602 in FIG.
Add a function to predict the flame area to
If the combustion stability is judged to be abnormal and it is judged to be abnormal,
The trial operation can be configured to be invalid and invalid, and diagnostic
When Japanese Patent Application No. 59-174998 is adopted as the method,
Predict flame shape for trial operation 1602 in 8
Function to diagnose combustion stability against the predicted value.
If it is determined to be abnormal, the trial operation is unsuitable.
Can be configured to disable combustion to the boiler.
Preventing any disturbance that may cause instability
Can be. [0198] According to the present invention, the fuel supplied to the furnace
Of the furnace for changes in the quantity and properties of the
Operational restrictions such as NOx concentration at the outlet and unburned ash content
Stable and maximize boiler thermal efficiency under certain conditions
it can.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is an overall configuration diagram of an embodiment in which the present invention is applied to a coal-fired plant. FIG. 2 is a schematic view of a coal-fired power plant. FIG. 3 is a conventional control system diagram of a coal-fired power plant. FIG. 4 is an example of a furnace model of a pulverized coal boiler. FIG. 5 is a burner structure diagram. FIG. 6 is an explanatory diagram of a flame image measurement function block. FIG. 7 is an explanatory diagram of a NOx estimation function block for each stage. FIG. 8 is a fuel / air distribution calculation function for each stage. FIG. 9 is another embodiment of the fuel / air distribution calculation function block for each stage. FIG. 10 is an operation explanation example of a fuel / air distribution calculation function block for each stage. FIG. 11 is an explanatory diagram of a furnace heat transfer model. FIG. 12 is an embodiment of an optimum manipulated variable determination algorithm in the fuel / air distribution calculation function block for each stage. FIG. 13 is another embodiment of the optimum manipulated variable determination algorithm in the fuel / air distribution calculation function block for each stage. FIG. 14 is another embodiment of the optimum manipulated variable determination algorithm in the fuel / air distribution calculation function block for each stage. FIG. 15 is another embodiment of the optimum manipulated variable determination algorithm in the fuel / air distribution calculation function block for each stage. FIG. 16 is another embodiment of the optimum manipulated variable determination algorithm in the fuel / air distribution calculation function block for each stage. FIG. 17 is an explanatory diagram of a method for estimating the temperature of combustion gas. FIG. 18 is another embodiment of the fuel / air distribution calculation function block for each stage. [Explanation of reference numerals] 4000 ... Flame image measurement function block, 4100 ... Stage NOx estimation function block, 4200 ... Stage ash unburnt content estimation function block, 4300 ... Stage combustion stability evaluation function block, 4400 ... Combustion gas Temperature estimation function block, 4
500 ... Fuel / air distribution calculation function block for each stage.

   ─────────────────────────────────────────────────── ─── Continued front page    (72) Inventor Yoshihiro Shimada             5-2-1 Omika-cho, Hitachi City, Ibaraki Prefecture             Ceremony company Hitachi Ltd. Omika factory (72) Inventor Nobuo Kurihara             4026 Kuji Town, Hitachi City, Ibaraki Prefecture             Hitachi Research Laboratory (72) Inventor Mitsuyo Nishikawa             4026 Kuji Town, Hitachi City, Ibaraki Prefecture             Hitachi Research Laboratory (72) Inventor Yoshio Sato             4026 Kuji Town, Hitachi City, Ibaraki Prefecture             Hitachi Research Laboratory (72) Inventor Atsumi Watanabe             4026 Kuji Town, Hitachi City, Ibaraki Prefecture             Hitachi Research Laboratory

Claims (1)

[Claims] 1. In a combustion control method for adjusting the manipulated variables of fuel and air in at least one or more boiler combustion areas so that the unburned ash content in the boiler furnace throat satisfies a predetermined condition, (a) the fuel and air (B) estimating unburned ash content in the boiler furnace throat based on the set trial operation amount and a model prepared in advance, and (c) estimating the ash content in the ash. The trial operation amount is corrected so that the unburned content satisfies a predetermined condition, and (d) the boiler thermal efficiency is calculated based on the trial operation amount when the predetermined condition is satisfied, and (e) the calculated value. In order to maximize the boiler thermal efficiency,
A combustion control method is characterized in that an optimum manipulated variable is obtained by correcting the trial manipulated variable, and (f) combustion of the boiler is controlled by using the optimum manipulated variable as a manipulated variable of fuel and air for actually operating the boiler. . 2. In a combustion control method for adjusting the manipulated variables of fuel and air in the combustion region of at least one or more boilers so that NOx at the boiler furnace outlet satisfies a constraint condition, combustion stability prior to boiler operation with actual manipulated variables When the combustion state satisfies a predetermined condition, a trial manipulated variable of fuel and air is set, and the set trial manipulated variable is used to prepare a furnace outlet NOx or a furnace outlet according to a model prepared in advance. Evaluate the unburned content in ash, the unburned ash content in the furnace outlet ash satisfies the predetermined constraint condition, and the trial operation amount that maximizes the boiler thermal efficiency calculated under that condition is calculated, and the trial operation amount is calculated. A combustion control method, wherein the amount is used as an actual operation amount for boiler operation. 3. In Claim 1 or 2, the uncombusted content in the furnace ash is estimated based on the flame image, and the uncombusted content in the ash is estimated based on the flame image. And a trial manipulated variable for correction. 4. The center of gravity of the oxidative flame, in which the estimated value of unburnt content in the ash in the furnace outlet is defined as the high-luminance region of the burner flame in Claim 3, and the oxidative flame formed in different regions with the burner axis as a boundary. Center of gravity distance, shape of the oxidative flame, burner 1
A combustion control method characterized by estimating by an estimation model using at least one of the following four air amounts. 5. The combustion control method according to claim 2, wherein the combustion stability is evaluated based on the ratio of the burner flame area and the area of the high brightness region in the flame. 6. In claim 2, the combustion stability evaluation is defined as the center of gravity of the oxidative flame, which is defined as the high-luminance region of the burner flame, the distance between the centers of gravity of the oxidative flames formed in different regions with the burner central axis as a boundary, A combustion control method, characterized in that evaluation is performed using at least one of the thickness of an oxidizing flame, the average brightness of an oxidizing flame, and the temporal fluctuation of the above parameters. 7. A furnace for estimating combustion gas temperature, heat transfer tube metal temperature, heat transfer tube metal internal fluid temperature in a furnace, wherein the boiler thermal efficiency maximum point determination is fuel and air amount as manipulated variables, according to claim 1 or 2. A combustion control device method, characterized in that a boiler heat efficiency is calculated using a heat transfer model. 8. In Claim 7, the furnace heat transfer model is modified based on the combustion gas temperature estimated value, the water wall metal temperature measured value, the difference between the water wall outlet internal body temperature and the calculated value of the model. Combustion control method. 9. The combustion control method according to claim 8, wherein the estimated value of the combustion gas temperature is calculated based on the brightness information of the plug combustion gas. 10. The combustion control method according to claim 7, wherein the boiler thermal efficiency is calculated as a ratio of the heat absorption to the heat transfer tube metal with respect to the sum of the heat input to the furnace and the heat generation due to combustion. 11. The combustion control method according to claim 7, wherein the boiler thermal efficiency is calculated as a ratio of the heat absorption to the heat transfer tube metal with respect to the sum of the heat input to the furnace and the heat generation due to combustion. 12. The combustion control method according to claim 7, wherein the furnace heat transfer model is calculated as a function of the flame temperature estimated based on the flame image information for the rate at which the fuel injected into the furnace burns. 13. In Claim 1 or 2, the furnace heat transfer model for estimating the boiler heat efficiency from the combustion gas temperature in the furnace, the heat transfer tube metal internal fluid temperature from the corresponding tube metal temperature, the calculation result of the model and the fuel, A combustion control method characterized in that calculation is performed based on the amount of air. 14. The combustion control method according to claim 13, wherein the combustion gas temperature is estimated based on the brightness of the combustion gas.