JPH04214120A - Combustion control method - Google Patents

Abstract

PURPOSE:To provide a combustion control method which maximizes a thermal efficiency in a plant by realizing stable and highly efficient combustion under such limited conditions in a practical operation as the content of unburnt substances in ash with respect to variations in the supply amount and properties of fuel to be charged into a furnace and also variations in required loads. CONSTITUTION:A trial manipulation variable for fuel and air is set prior to a boiler operation in an actual manipulation variable and, by using the trial manipulation variable thus preset for a model furnace prepared in advance, NOx at the exit of the furnace or unburnt substances in ash at the exit of the furnace are evaluated. The trial manipulation variable in which the unburnt substances in ash at the exit of the furnace meet predetermined limited conditions, and in which a thermal efficiency in the boiler that is calculated under such a condition becomes highest, is determined by computation, and this trial manipulation variable thus obtained is applied to the actual manipulation variable for a boiler operation. By this method, the boiler operation is stabilized and the thermal efficiency in the boiler can be maximized under such limited conditions in a practical operation as the density of NOx and the content of unburnt substances in ash at the exit of the boiler with respect to variations in the amount and properties of fuel to be supplied to the boiler or variations in required loads.

Description

[Detailed description of the invention]

0001

FIELD OF THE INVENTION The present invention relates to a combustion control method and apparatus for a furnace, and in particular to a method and apparatus for controlling combustion in a furnace, particularly for maintaining maximum thermal efficiency of a plant under constraints on plant operation such as NOx and unburned content in ash. This invention relates to a suitable combustion control method.

0002

[Prior Art] Conventionally, as a combustion control method for a furnace, heat energy is generated by detecting the light of the combustion flame and controlling the ratio of the fuel supply amount and the air supply amount so that the light spectrum intensity is maximized. (``Combustion Control Method and Apparatus'' Japanese Patent Application Laid-Open No. 56-1200224) and a method to efficiently adjust the optimum supply amount of combustion air according to the light intensity of the combustion flame (``Combustion Air Supply''). Quantity control device (Japanese Patent Application Laid-open No. 151814/1983). All of these are considered effective technologies for maximizing combustion efficiency, but low N
This method does not realize combustion control that maximizes the heat absorption rate of the boiler while achieving oxygen conversion and stabilizing combustion.

On the other hand, a closed-loop control method for controlling the amount of NOx in a furnace has not been adopted in the past. The reason for this is
This is because there is no technology to accurately measure the amount of NOx generated in the furnace, so it has not been possible to determine the operating amounts of fuel and air to control the amount of NOx in the furnace. Therefore, conventionally, the fuel amount and air amount corresponding to the load are determined by program control, and NOx is simply controlled in a closed loop while observing the actual measured NOx value at the furnace outlet. Therefore, N
Control of Ox was not possible.

[0004] Regarding combustion stability, conventional methods have been adopted in which a television camera attached to the top of the furnace is used to capture an image of the flame inside the furnace, and a person monitors the image on a monitor television to evaluate the stability of combustion. The drawback is that accurate evaluation requires deep experience and there is a large possibility that individual differences will be incorporated into the evaluation.

[0005] As mentioned above, in the conventional technology, NOx
It has been impossible to control combustion in a way that maintains stability and thermal efficiency at its highest value while keeping operationally important parameters such as heat and unburned content in the ash within constraint conditions.

[0006]

OBJECT OF THE INVENTION The object of the present invention is to provide stable and high performance fuel to the furnace under the operational constraints of unburned content in the ash against changes in the amount and properties of fuel fed into the furnace and changes in the required load. The purpose of the present invention is to provide a combustion control method that realizes efficient combustion and maximizes the thermal efficiency of a plant.

[0007]

SUMMARY OF THE INVENTION The present invention sets trial manipulated variables for fuel and air prior to boiler operation using actual manipulated variables, and uses the set trial manipulated variables to calculate furnace outlet NOx, Or evaluate the unburned content in the ash at the furnace outlet,
the unburned content in the ash at the furnace outlet satisfies predetermined constraints, and
A feature of this method is that the trial operation amount for which the boiler thermal efficiency calculated under the conditions is the largest is determined by calculation, and the trial operation amount is used as the actual operation amount for boiler operation.

Furthermore, in order to improve the accuracy of the boiler thermal efficiency, the combustion stability should be evaluated before the boiler is operated with the actual operation amount, and if the combustion state satisfies predetermined conditions, the above combustion control should be performed. There are characteristics.

[0009]

DESCRIPTION OF THE PREFERRED EMBODIMENTS Prior to describing embodiments of the present invention, an outline of a coal-fired power plant to which the present invention is applied will be explained with reference to FIG.

First, coal to be burned in the boiler 1 is stored in a coal bunker 2, is supplied to a mill 5 by a feeder 4 and a drive motor 3, and is sent to a burner 6 after being pulverized. Combustion air is sent by a forced draft fan 8 to an air preheater 9, on the one hand to the mill via a primary air fan 12 for transporting pulverized coal, and on the other hand directly to the burner 6 as combustion air. Further, the air preheater 9 has a bypass system, and the temperature of the primary air is controlled by a damper 10. Also, the total amount of air required for combustion is determined by damper 7, and the amount of air required for transporting pulverized coal is determined by damper 11.
Each is controlled by On the other hand, the feed water pressurized by the water supply system 13 becomes superheated steam in the boiler 1 and is sent to the turbines 15 and 16 via the main steam pipe 14. turbine 1
5 and 16 are rotated by adiabatic expansion of superheated steam, and a generator 17 generates electricity. Further, the combustion exhaust gas that is combusted in the boiler 1 and gives heat to water and steam is sent to the chimney 19 and released into the atmosphere, but a part of the gas is passed through the gas recirculation fan 1.
8 is returned to the boiler 1.

[0011] In order to smoothly operate such a coal-fired power plant in response to load demand commands, it is necessary to appropriately control each valve, damper, and motor. FIG. 3 shows a schematic diagram of a conventional thermal power plant automatic control system. An overview of its functions will be explained below with reference to this figure. First, the load (output of the generator 17) request signal 1000 to the thermal power plant is corrected so that the main steam pressure 1100 becomes a predetermined value (a constant value in a constant pressure plant, a value according to the load in a variable pressure plant) ( Main steam pressure compensation block 1
00) becomes the boiler input demand signal 3000 to the boiler 1. This boiler input demand signal 3000 is guided to the feed water flow rate control system 400 as a set value for the feed water flow rate 1200, and is used to control the feed water flow rate control valve 20, and is also used to determine the combustion amount demand 3100. The boiler input demand signal 3000 led to the main steam temperature compensation block 200 is corrected so that the main steam temperature 1101 becomes a predetermined value, and determines the combustion amount demand 3100. This fuel quantity demand signal 3100 is guided to the fuel flow control system 500 as a set value for the total coal combustion flow rate 1201, and is used to control the drive motor 3 of the feeder 4. Further, the fuel quantity demand signal 3100 is corrected by the air-fuel ratio compensation block 300 so that the exhaust gas O2 excess rate becomes a predetermined value, and becomes the total air flow rate demand signal 3200. Air flow control system 600 controls damper 7 so that total air flow 1202 is equal to this demand signal.

The above is an overview of the coal-fired power plant automatic control system. In addition, there are a reheat steam temperature control system, a turbine control valve control system, etc., but these are omitted because they are not directly related to the present invention.

FIG. 1 shows an overall configuration diagram of an embodiment in which the present invention is applied to the coal-fired power plant shown in FIGS. 2 and 3. In the figures, the same or equivalent parts as in FIG. 3 are represented by the same symbols. In this embodiment, the furnace of a pulverized coal-fired boiler as shown in FIG. 4 is targeted, and the case is shown in which the furnace is divided into five regions (the inner burner zone is three regions). The subscripts attached to the reference numbers in FIG. 1 indicate the numbers corresponding to the divided areas. For simplicity, the process signal for each region is expressed as the sum of the values before and after the furnace can. What is different from the conventional system in FIG. 1 is that the following functions have been added. (1) Flame image measurement function block 4000 (2) Every stage N
Ox estimation functional block 4100 (3) Unburned content in ash estimation functional block for each stage 4200 (4) Combustion diagnosis functional block for each stage 4300 (5) Combustion gas temperature estimation functional block 440
0(6) Stage-by-stage fuel/air distribution calculation block 4500 and the following, an outline of this embodiment will be first described using this diagram.

The flame image measurement block 4000 captures representative burner flame information 13051 to 13053 for each burner stage using a photographing camera installed at each burner stage, and converts each of them into two-dimensional grayscale images 13061 to 13063. The stage-by-stage NOx estimation function block 4100 estimates NOx generated from each burner stage to the furnace outlet using burner flame information 13051 to 13053 and coal feed amount 13001 to 130.
03, Primary air amount 13011-13013, Secondary air amount 13021-13023, Tertiary air amount 13031-13
033, Actaair 1310 and furnace outlet NOx 130
This is estimated based on each measurement value of 4. The unburned content in the ash estimation functional block 4200 for each stage calculates flame characteristic parameters based on the two-dimensional grayscale image signals 13061 to 13063, and estimates the unburned content in the ash in each region using an estimation model using these parameters. (For details, please refer to the patent application published in 1983.
-110837). Next, in the stage-by-stage combustion diagnosis function block 4300, combustion stability is diagnosed and abnormal factors are estimated, and there are two methods for this. That is, two-dimensional gray image signals 13061 to 130
63, calculate the characteristic parameters focusing on the flame shape,
There are two methods: a method that is created from now on, and a method that is based on characteristic parameters that focus on the flame area. Details of the former are described in Japanese Patent Application No. 184657/1983. The latter is described in Japanese Patent Application No. 59-174998. The combustion gas temperature estimation functional block 4400 calculates estimated combustion gas temperatures 14021 to 13025 for each area based on the combustion gas brightness information 13061 to 13065 for each area shown in FIG. FIG. 5 shows a burner per stage fuel/air distribution calculation function block 4500 that calculates the requested fuel quantity demand 31.
00, environmental regulation values such as furnace outlet NOx 1304, unburned content in ash (usually 5
% or less), desulfurization equipment inlet temperature that should be considered from the perspective of protecting the main engine (corrosion tends to occur at low temperatures),
While satisfying the plant operation constraints such as the heat flux of the water wall and radiant superheater (if it exceeds the specified value, there is a risk of burning out the metal), the water wall and fuel distribution commands 33111 to 33113 for each burner stage so that it is absorbed by the metal or internal fluid of the radiant superheater, that is, the boiler thermal efficiency is maximized.
, primary air amount target value 33201 to 33203, secondary air amount target value 33301 to 33303, tertiary air amount target value 3
After air amount target value 3350 is determined from 3401 to 33403 and the NO port. Among these functional blocks, the outputs of the stage-by-stage NOx estimation function block 4100 and the stage-by-stage unburned content estimation function block 4200 are each NOx
The output of the combustion gas temperature estimation function block 4400, the water wall outlet fluid temperature 1308, and the can wall metal temperature 13091 to 13 are used to check the constraint conditions regarding unburned content.
095 is used as a correction signal for the furnace heat transfer model for calculating boiler thermal efficiency. Note that the stage-by-stage combustion diagnosis function block 4300 is positioned as a combustion state monitoring function in this embodiment, and in the event of an abnormality, its output signal is used to inform the cause and situation of the abnormality using an alarm, CRT display, etc. be able to do so.

Each functional block will be explained in detail below.

FIG. 6 shows a flame image measurement function block 400.
An example of 0 is shown below. In this embodiment, flame images 13051 to 13053 of the representative burner of each stage burner group are sent to the photographing device IT via the image guide IG and the image fiber IF.
V and converts it into a video signal, which is then converted into digital data by an analog-to-digital converter A/D. This data is stored in frame memory FM and
Figure 1 as dimensional grayscale image signals 13061 to 13063
It is shared by the stage-by-stage NOx estimation functional block 4100, the stage-by-stage unburned content in ash estimation functional block 4200, and the stage-by-stage combustion diagnosis functional block 4300 shown in FIG. In addition, Image Guide IG
Because it is important to grasp the flame at the base of the representative burner, it must be inserted into the furnace, and the image fiber IF is coated with a material that can withstand temperatures of about 1500°C and has a structure that cools it. (For details, see Jitsugan 59-154
(mentioned in No. 58).

FIG. 7 shows the NOx estimation function block 41 for each stage.
An example of 00 is shown below. NOx reduction amount estimation model 4101
Then, the flame characteristic parameters of each stage are calculated based on the burner flame information 13051 to 13053 for each stage, and the NOx reduction amount of each burner is calculated as a function of the parameter.
41053 is estimated. For details, please contact Reception No. 11-84-1041 "Combustion condition monitoring device"
It is stated in Next, burner single NOx estimation model 4
In 102, the amount of coal feeding at each stage is 13001 to 13003, the amount of primary air is 13011 to 13013, and the amount of secondary air is 130.
21~13023, tertiary air amount 13031~13033
and after air 1310 to burner air ratio 41091
~ 41093 is calculated, the amount of NOx produced by the burner alone is estimated, and the amount of NOx produced by the burner itself before being reduced is subtracted from this, and the amount of NOx reduced by the burner alone, 41051 ~ 41053, is subtracted to obtain the NOx of the burner itself.
Estimate concentrations 41061 to 41063. The stage-by-stage NOx estimation model 4103 uses the burner air ratio of each stage and the burner average air ratio to estimate the reduction effect during NOx accumulation in the furnace and the NOx regeneration effect due to air injection from the NO port on the burner single NOx concentration. The estimated NOx values 15011 to 15013 for each stage are calculated based on a model that takes into account the following. In the furnace NOx estimation model 4104, the first estimated value of the NOx for each stage obtained by the NOx estimation model for each stage 4103 is converted into an error correction signal 410 using the measured value of NOx at the furnace outlet 1304.
81 to 41083, the estimated NOx value for each stage is 15011.
~15013 is calculated. Details of the above-mentioned stage-by-stage NOx estimation model 4103 and furnace NOx estimation model 4104 are described in Japanese Patent Application No. 118296/1982.

FIG. 8 shows an embodiment of the stage-by-stage fuel and air distribution calculation functional block 4500. The operation will be explained below using this figure. Optimal operation amount search start condition checking unit 45
01, the fuel quantity demand 3100 at a predetermined period,
The estimated NOx values for each stage 14001 to 14003, the estimated unburned content values for each stage 14011 to 14013, and the furnace outlet exhaust gas concentration 13111 to 1311n are compared with preset specified values, and if they do not exceed the specified values, the previously calculated values are compared. Stage-by-stage fuel distribution commands 33101 to 33103, primary air amount target values 33201 to 33203, secondary air amount target values 33301
~33303, tertiary air target value 33401~33403
and fat air amount target value 3350 (hereinafter, the four types of commands and target values are collectively referred to as the manipulated variable), and if any value exceeds the specified value, the optimum manipulated variable is output. The search command 1601 causes a search for a new optimal operation amount to be started in the following procedure. That is, the trial operation is started when the start condition is satisfied in the optimum operation amount start condition checking unit 4501. first,
The optimum operation amount search unit 4502 is activated by the search command 1601, and the trial operation 1602 is performed by the stage-by-stage NOx prediction model 450.
3. In addition to each stage unburned content prediction model 4504 and furnace outlet exhaust gas concentration prediction model 4505, each model predicts each predicted value, that is, each stage NOx predicted value 16031 to 1603.
3. Calculate the unburned content prediction values 16041 to 16043 for each stage, the furnace exit exhaust gas concentration prediction values 16051 to 1605n, and the furnace heat transfer model outputs 16061 to 1606m. Next, these calculated values are used by the operational constraint condition checking unit 4507.
It is checked whether the prescribed constraint conditions are satisfied, and if the conditions are not satisfied, the calculation by the above trial operation is repeated until the conditions are satisfied. If the conditions are satisfied, the thermal efficiency calculation unit 4508 outputs the furnace heat transfer model output 1606.
The boiler thermal efficiency is calculated based on 1 to 1606m, and the thermal efficiency maximum point determination unit 4509 determines whether the calculated value is the maximum value. If it is not the highest value, repeat the above trial operation. When the maximum value is reached, the manipulated variable corresponding to the highest value of thermal efficiency is output as the optimal manipulated variable via the optimal manipulated variable output section 4510. Note that the NOx prediction model 450 for each stage
3. As a construction method for the stage-by-stage unburned content prediction model 4504 and the furnace outlet exhaust gas concentration prediction model 4505, it can be realized by Japanese Patent Application No. 80932/1983 entitled ``Boiler Combustion State Monitoring and Control Method'' which applies multiple regression analysis.

According to this method, the optimum operation amount and N for each stage are determined as appropriate.
Multiple regression with the former as an explanatory variable and the latter as a dependent variable: Ox estimated value 14001 to 14003, optimal operating amount and estimated unburned content in coal/ash 14011 to 14013, optimal operating amount and furnace outlet exhaust gas concentration 13111 to 1311n. Each model can be modified through analysis, and each model can be adapted to changes in furnace characteristics. In addition, regarding the furnace heat transfer model 4506, the optimum operation amount and the corresponding estimated combustion gas temperature values 14021 to 14025 are also included.
, water wall metal temperatures 13091 to 14095, and water wall outlet fluid temperature 1308 by modifying the model to adapt the furnace model to the furnace characteristics.

FIG. 9 shows another embodiment of the per-stage fuel/air distribution calculation function block 4500. In this example, each stage has NOx
Prediction model 4503, stage-by-stage unburned content prediction model 4504,
The point in FIG. 8 is that the trial operation 1602 from the optimum operation amount search unit 4502 is output directly to the process side without using the furnace outlet exhaust gas concentration prediction model 4505, and the condition is checked in the constraint condition check unit 4507 based on the actual response signal. Unlike the example shown in , the procedure up to the output of the optimum manipulated variable is the same.

FIG. 10 is a flowchart showing the operation of the stage-by-stage fuel/air distribution calculation function block 4500 described above. When the system operates for the first time, the optimum operation amount is calculated and output according to the procedure described above. In the case of the second and subsequent operations, first the current fuel amount demand L
and the demand L* when calculating the optimal operation amount last time, and if the absolute value of this difference changes beyond the specified value εL, there is a risk that the current operation amount will deviate from the point of maximum efficiency. Recalculate the optimal operation amount from If the deviation between the above fuel demands is less than the specified value εL, the furnace outlet N
The optimal manipulated variable search start condition check unit 4501 checks whether operational constraints such as Ox concentration are satisfied, and if they are satisfied, the previous optimal manipulated variable is continued to be output; if not, Compared to the previous manipulated variable output, the operational constraints mentioned above (for example, the furnace outlet NOx
If there is a change, a new optimum operation amount is searched for. If there is no change, it is assumed that this is due to an estimation error by the estimation model, and the corresponding The coefficients of the estimated model (for example, the estimated model in the stage-by-stage NOx estimation function block 4100 if the furnace outlet NOx estimated value does not satisfy the constraint conditions) are calculated using multiple regression analysis based on the related process data. Correct it. In this case, the optimal manipulated variable calculated last time is output continuously. That is, even if the above-mentioned start condition is not satisfied, if the difference between the current value and the previous value of fuel demand exceeds a specified value, a trial operation is started, and this is also performed when using normal fuel. Before describing the search algorithm for the optimal manipulated variable shown in this figure, we will first explain the furnace heat transfer model used to check operational constraints and calculate thermal efficiency. Figure 11 shows a furnace heat transfer model for a pulverized coal-fired boiler. In this example, the furnace is divided into five parts in the vertically upward direction (flow direction of combustion gas), and each region is approximated as a lumped constant coefficient. The figure shows the flow and heat transfer process of the combustion gas in the furnace, the water wall heat exchanger tube metal (hereinafter abbreviated as metal), and the heat exchanger tube internal fluid (hereinafter abbreviated as internal fluid), which are treated as lumped constant coefficients. The relationship between these process quantities is a nonlinear physical model based on the conservation laws of mass, momentum, and energy. However, since the flow time constants of combustion gas and internal fluid are smaller than their heat transfer time constants, the flow characteristics of combustion gas and internal fluid are treated as steady flow (flow that does not produce acceleration in the fluid) and are not static characteristics. Approximate.

First, the symbols used in the formula will be explained.

(1) Symbol F: Mass flow rate (kg/S) P: Pressure (KPa) T: Temperature (°C) H: Specific enthalpy, calorific value (kJ/kg) Q:
Amount of heat retained, amount of heat transferred (kJ/s) U: Heat flux (kJ/
(s.m2)) ρ: Density (kg/m3) α: Convective heat transfer coefficient (kJ/(m2.℃.s)) β
: Radiation heat transfer coefficient (kJ/(m2・(°K/100)
4.s)) C: Specific heat at constant pressure (kJ/kg.℃) X: Dryness (-) W: Moisture content in coal (-) ν: Ash content in coal (-) μ: Excess air ratio (-), concentration (%) ε: Passage rate of suspended ash at the furnace outlet (-) λ: Channel friction coefficient (-) k: Combustion ratio (-) g: Gravitational acceleration (m/s2) R: Gas constant (kg.m/(kg・°K))A
: Heat transfer area, channel cross-sectional area (m2) D : Channel diameter (m) V : Channel volume (m3) ΔZ: Channel length, channel water head difference (m) KT : Gas temperature depending on composition of combustion gas Overall influence coefficient (-) on the gas constant KR: Overall influence coefficient (-) on the gas constant due to the composition of combustion gas K: Composition factor of combustion gas and the above KT and KR
Coefficient (-) for approximating the relationship between Subscript g : Combustion gas m : Heat exchanger tube metal s : Heat exchanger tube internal fluid c : Pulverized coal l : Ignition oil pa : Primary air (pulverized coal carrying 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 the heat transfer tube metal to the internal fluid sg : Flow and heat transfer from the heat transfer tube internal fluid to the combustion gas ash : Ash content a : Total air ao that has flowed into the furnace : Complete combustion of the fuel that has flowed into the furnace Air required to carry out ATM: Atmosphere 0: Excess oxygen in combustion gas (ii) Subscript i indicating location: Section i of the furnace (1): Front can of section i of the furnace i (2)
: After the can of the i section of the furnace : Combustion gas in the i section and heat transfer tube metal in all sections ni : Combustion gas in all sections and heat transfer tube metal in the i section j : Burner stage SH : Radiation superheater F : Furnace interior FX : Furnace outlet downstream part SH (1) : Combustion gas contact part SH of radiation superheater (2
) : Reference value of radiation heat receiving part (iii) of radiation superheater, subscript indicating 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 : Fuel, combustion gas Reference value gv regarding the composition of: State value g regarding moisture evaporation and superheating
mr: Reference value for heat transfer from the combustion gas to the heat transfer tube metal msr: Reference value for heat transfer from the heat transfer tube metal to the internal fluid SB: State value of the subcool boiling start point Next, the formula for the furnace model is shown.

1. Fuel/air heat input/heat generation characteristic model (
1) Amount of heat generated by combustion

[0025]

[Math 1]

[0026]

[Math 2]

[0027]

[Math 3]

[0028]

[Math 4]

[0029]

[Math 5]

(2) Heat capacity of fuel/air

[0031]

[Math 6]

[0032]

[Math 7]

[0033]

[Math. 8]

[0034]

[Math. 9]

[0035]

[Math. 10]

2. Combustion gas side heat transfer/flow characteristics model 2
．． 1 Heat transfer characteristics on the combustion gas side (1) Combustion gas temperature

[0037]

[Math. 11]

[0038]

[Math. 12]

[0039]

[Math. 13]

[0040]

[Math. 14]

[0041]

[Math. 15]

(2) Amount of heat transfer between combustion gas and metal

004
3]

[Math. 16]

[0044]

[Math. 17]

[0045]

[Math. 18]

[0046]

[Math. 19]

[0047]

[Math. 20]

[0048]

[Math. 21]

[0049]

[Math. 22]

[0050]

[Math. 23]

[0051]

[Math. 24]

[0052]

[Math. 25]

2.2 Flow characteristics of combustion gas (1) Flow rate of combustion gas

[0054]

[Math. 26]

[0055]

[Math. 27]

(2) Combustion gas pressure

[0057]

[Math. 28]

[0058]

[Math. 29]

[0059] From equations (28) and (29),

[0060]

[Math. 30]

[0061]

[Math. 31]

[0062]

[Math. 32]

3. Metal/internal fluid side heat transfer/flow characteristics model 3.1
Metal/internal fluid side heat transfer characteristics (1) Metal temperature

[0064]

[Math. 33]

[0065] (2) Amount of heat transferred from metal to internal fluid and atmosphere

006
6]

[Math. 34]

fs: Correction coefficient of convective heat transfer coefficient between metal and internal fluid in two-phase flow state

[0068]

[Math. 35]

[0069]

[Math. 36]

[0070]

[Math. 37]

[0071] (3) Internal fluid temperature/dryness

[0072]

[Math. 38]

[0073]

[Math. 39]

[0074]

[Math. 40]

3.2 Flow characteristics of internal fluid (1) Internal fluid pressure

[0076]

[Math. 41]

[0077]

[Math. 42]

4. Overall characteristic model in the furnace (1) Excess air ratio

[0079]

[Math. 43]

[0080]

[Math. 44]

[0081]

[Math. 45]

[0082]

[Math. 46]

[0083]

[Math. 47]

[0084] Residual oxygen concentration (weight%)

[0085]

[Math. 48]

(2) Furnace outlet combustion gas flow rate

[0087]

[Math. 49]

[0088]

[Number 50]

[0089]

[Math. 51]

(3) Influence coefficient due to composition of combustion gas

0
091]

[Math. 52]

[0092]

[Math. 53]

[0093]

[Math. 54]

[0094]

[Math. 55]

Next, the furnace outlet NOx prediction model 4503 in FIG. 8 will be explained. Since it is difficult to describe the relationship between the furnace outlet NOx and the manipulated variable using a physical formula, it is practical to use a statistical method such as multiple regression analysis. Next, a configuration example of a prediction model based on multiple regression analysis will be described. The multiple regression analysis method uses explanatory variables as xi (i=1
~m), with y as the dependent variable, and between the two

[0096]

[Number 56]

When the following functional relationship holds true, this can be expressed as

00
98]

[Math. 57]

It is expressed by the following formula, and the partial regression coefficients β0, β1...
This is a method of determining βm so that the deviation between y and Y is minimized. In the furnace outlet NOx model, this method is applied to predict NOx for each stage, and the predicted NOx value for each stage is calculated using the following formula:

01
00]

[Number 58]

[0101]

[Math. 59]

[0102]

[Number 60]

Here, x1 to xm: manipulated variables β01 to βmi (i=1 to
3): Predict using the partial regression coefficient, and calculate the NOx at the furnace outlet using the following formula:

[0104]

[Number 61]

[0105] Here Fc,i: Pulverized coal flow rate of i stage Predict by.

The stage-by-stage NOx data for determining the partial regression coefficients of equations (58) to (60) include the stage-by-stage NOx estimated values 14001 to 14001 by the stage-by-stage NOx estimation function block 4100.
14003 is used.

[0107] As for the prediction model 4504 of unburned content in the ash at the furnace outlet, the predicted value of the unburned content in the ash for each stage is calculated using the following formula using the multiple regression analysis method as described above.

[0108]

[Number 62]

[0109]

[Number 63]

[0110]

[Number 64]

[0111] Here, β'01 to β'mi (i = 1 to 3): Obtained using the partial regression coefficient, and the unburned content in the ash at the furnace outlet is calculated using the following formula.

[0112]

[Number 65]

Prediction is made by [0113].

The stage-by-stage unburned content data for determining the partial regression coefficients in equations (7)' to (9)' include the stage-by-stage NOx estimated value 1401 by the stage-by-stage unburned content estimation function block 4200.
1 to 14013 are used.

[0115] Regarding the furnace outlet exhaust gas concentration prediction model 4505, the concentration of exhaust gas such as CO, SO, soot and dust at the furnace outlet can be estimated using a multiple regression model in the same manner as described above. Since this cannot be estimated, the relationship between each thrust gas concentration at the furnace outlet and the manipulated variable is modeled using the relational expression (2)', and the partial regression coefficient is determined using the measured value of the exhaust gas concentration.

Next, an embodiment of the operational constraint checking unit 4507 described with reference to FIGS. 8, 9, and 10 will be described below (note that the constraint conditions regarding exhaust gas are omitted here because it is a cylinder unit only).

[0117]

[Number 66]

[0118]

[Number 67]

[0119]

[Number 68]

[0120]

[Number 69]

[0121]

[Number 70]

[0122] Here, NOxFX : Furnace outlet NOx concentration UBCFX : Unburned matter in the ash at the furnace outlet NOxU : Furnace outlet NOx concentration upper limit value NOxL
: Furnace outlet NOx concentration lower limit value UBCU : Furnace outlet upper limit value of unburned content in ash Tg, FX : Furnace outlet gas temperature Tg, FXU : Furnace outlet gas temperature lower limit value Ugm, i
: Water wall metal heat flux Ugm, iU in area i : Area i
Water wall metal heat flux upper limit value Ugm, SH: Radiation superheater metal heat flux Ugm, SHU of area i: Radiation superheater metal heat flux upper limit value of area i The above equation (68) lowers the denitrification equipment inlet air temperature. If the temperature is too high, low-temperature corrosion of the metal parts of the equipment is likely to occur, so the constraint conditions for preventing this are converted into the furnace outlet gas temperature. Further, equations (69) and (70) are conditions for preventing metal burnout.

On the other hand, examples of constraints imposed on the trial operation 1602 described in FIGS. 8 to 10 when determining the optimum operation amount are shown below.

[0124]

[Math. 71]

[0125]

[Number 72]

[0126]

[Number 73]

[0127]

[Number 74]

[0128]

[Number 75]

Here, Fc,i: pulverized coal flow rate Fpa,i in area i: primary air flow rate Fsa,i
: 〃 Secondary air flow rate Fta,i : 〃
tertiary air flow rate Fc,iU: Upper limit value of pulverized coal flow rate Fc,iL: 〃
Lower limit value Fpa, iU: Upper limit value of primary air flow rate Fpa, iL: Lower limit value Fsa, iU: Upper limit value of secondary air flow rate F of
sa, iL: 〃 〃 lower limit value Fta, iU: 〃 tertiary air flow rate upper limit value Ft
a, iL: 〃 〃 Lower limit value Next, the thermal efficiency η of the thermal efficiency calculation unit 4508 shown in FIGS. Calculated using the following formula.

[0130]

[Number 76]

Here, Qms,i: Amount of heat transferred from the water wall metal in area i to the internal fluid Qms, SH: Amount of heat transferred from the radiant superheater metal to the internal fluid Qf,i: Pulverized coal and ignition oil fuel were combusted Amount of heat generated by this Qc,i: Amount of heat held by pulverized coal in area i Ql,i:
〃 Ignition oil retained heat Qpa,i: 〃
The amount of heat held in the primary air Qsa,i: The amount of heat held in the secondary air Ata,i: The amount of heat held in the tertiary air When defined as the ratio of the amount of heat absorbed by the inner metal, it becomes as shown in equation (77).

[0132]

[Number 77]

Here, Qc, gm, i: Convective heat transfer amount (kJ/s) from the combustion gas in region i to the water wall metal Qe, gm, in: Convection heat transfer amount from the combustion gas in region i to the entire region (water wall and radiation Superheater) Amount of radiant heat transfer to metal (kJ/s)Q
c, gm, SH: Amount of convective heat transfer from the combustion gas in region i to the radiant superheater metal (kJ/s) Next, an example of the calculation method of the calculation application section of the optimal operation amount in the flow of Fig. 10 will be described. show.

FIG. 12 is a flowchart showing an algorithm for determining the optimal manipulated variable using the complex method, which is a method of nonlinear programming. This algorithm uses (
This is to search for the manipulated variable that maximizes the thermal efficiency η shown in equation 11). This algorithm will be explained below using FIG. 12.

■ step 1: Initial simplex formation Initial trial point X(1,i) (i=10-22) is (
It is assumed that all the constraints in equations 71) to (75) are satisfied, and the 13-dimensional space spanned by the manipulation vector A polygon (this is called a simplex) is formed, and this is used as an initial simplex. As this formation method, one point is the initial trial point X (1, i
), and the remaining (K-1) points are uniformly random numbers rj (j=
2 to K) using the following formula.

[0136]

[Number 78]

[0137] However, 0≦rj≦1, and Ximin and Ximax are the lower and upper limits of the manipulated variables shown in equations (71) to (75).

X(j,i) determined in this way is (7
Although the constraints of equations 1) to (75) are satisfied, (66) to
The constraint condition of equation (70) is not necessarily satisfied. In that case, the trial point is moved in the direction of the center of gravity of the already determined point to the midpoint between the trial point and the center of gravity. In this way, all points are ultimately determined.

■ Step 2: Calculation step of thermal efficiency
The manipulated variable X (j, i) (i = 10 to 22,
Thermal efficiency is calculated using equation (11) for each point of the simplex formed by j=1 to K).

■ step 3: Calculate the center of gravity The center of gravity of the simplex defined by (K-1) points excluding the point with the lowest thermal efficiency among the points of the simplex
Find Gi. If we now assume that the lowest point of efficiency is j=1, then XG
i is expressed by the following formula.

[0141]

[Number 79]

[0142] Also, the distance ΔX from the lowest efficiency point to the center of gravity
Gi is expressed by the following formula.

[0143]

[Number 80]

[0144] Step 4: Determination of a new trial point The direction of a new trial is taken from the lowest thermal efficiency point to the direction of the center of gravity.The point extended from the center of gravity by αi times the distance ΔXGi between the two is set as the new trial point, and this is set as X(K+1 , i), then

0
145]

[Math. 81]

It is expressed as: The value of αi is 1.3
is considered to be good based on experience. When the new trial point violates the operation amount constraint conditions (71) to (75) (71 in the figure
), the trial point is set on the constraint condition (72 in the figure).

[0147] Step 5: Constraint condition confirmation If the new trial point violates the operational constraints of equations (66) to (70), all information regarding trial point X (K+1, i) is invalidated. Return to the previous step 4 and determine a new trial point. After setting the sum αi /2 as αi, start
Return to ep4.

■ step 6: Calculate thermal efficiency Efficiency η(K+1) corresponding to new trial point X(K+1,i) is (14
) Calculate using the formula.

[0149] Step 7: Determining whether the maximum thermal efficiency has been reached Among the thermal efficiencies corresponding to the new trial point and each point constituting the original simplex, calculate the highest and lowest values as ηmax, respectively.
and ηmin, and the specified value is εη, it is determined whether the efficiency has reached the maximum point according to the following equation.

[0150]

[Number 82]

If the highest point is reached, proceed to step 9; if not, proceed to step 8.

[0152] Step 8: Create a new simplex from the K points created by excluding the operating point showing the lowest efficiency among the points composing the simplex from which the new simplex is formed and adding new trial points. form and ste
Return to p3.

■ step 9: Determination of optimal operation amount st
If it is determined that the highest efficiency point has been reached in ep7, the manipulated variable corresponding to the optimal efficiency ηmax is set as the optimal manipulated variable.

FIG. 13 shows another embodiment of the optimum manipulated variable search algorithm. This embodiment will first be described using FIG. 13.

[0155] Step 1 It is determined whether or not the search is the first time. If it is the first time, the fuel amount in each region of the manipulated variables is maintained at the current state and the process proceeds to step 3. If it is the first time, the process proceeds to step 2.

■Step 2 The distribution of fuel amount in each region is changed within a range that satisfies the constraint shown by equation (6). However, the total amount of fuel is set to be the fuel amount demand.

■ step 3 The amount of air in each region is varied in predetermined steps within a range that satisfies the constraint conditions shown in equations (71) to (75),
Satisfies operational constraints (66) to (70) and (7)
6) Search for the value that maximizes the thermal efficiency shown by the formula, and store the thermal efficiency value, fuel amount, and air amount.

[0158] Step 4 If the fuel amount distribution change operation has not been completed over the entire range of the constraint conditions in equation (6), the process returns to step 1, and when the search has been completed in the entire range, the process proceeds to step 5.

Step 5 Among the data sets of thermal efficiency, fuel amount, and air amount stored in step 3, the set of fuel amount and air amount with the highest thermal efficiency is set as the optimum manipulated variable.

14 and 15 show an example of the algorithm of step 3 in FIG. 13. In this example, as shown in Figure 15, three combustion modes are assumed using the air ratio of the burner stage and NO port as parameters, and the following are shown in descending order of combustion efficiency: normal combustion, two-stage combustion, denitrification combustion, and NOx concentration combustion. Focusing on the following, in descending order of NOx, are denitrification combustion, two-stage combustion, and normal combustion, and using the current combustion mode as a starting point, we trial-manipulated the air ratio in a method suitable for that mode to reduce NOx at the furnace outlet.
It is adjusted to a value that maximizes combustion efficiency based on concentration and other operational constraints. The contents of this process will be explained below with reference to FIG.

[0161] In step 1 in Figs. 14 and 15, if the current NOx concentration NOx at the furnace outlet exceeds its upper limit NOxU, the process branches to step 2 and subsequent steps in which the NOx concentration is lowered and the combustion efficiency is lowered. If the upper limit value is not exceeded, in step 22, compare the current value and lower limit value NOxL.
If it is below the lower limit, increase the NOx concentration,
The process moves to step 23 and subsequent steps to increase combustion efficiency. If the NOx concentration does not exceed either the upper or lower limits, the operation amount is maintained at the current level and the process is terminated. Below, first, a case where the current NOx concentration exceeds the upper limit value NOxU will be explained.

In step 2, it is determined which of the three aforementioned combustion modes the current combustion mode belongs to, and the process branches to the corresponding processing step based on the determination result. First, the case of normal combustion mode will be explained below.

[0163] ■ Step 3 The NOx reduction amount for each burner stage is controlled by changing the ratio of tertiary air and secondary air without changing the burner air ratio for each stage 3, 4, and 5, and the NOx concentration at the furnace outlet is controlled. It is checked whether operational constraints including constraints are satisfied, and if they are not satisfied, the processes of steps 3 to 5 are repeated, and if they are satisfied, the process moves to step 6.

[0164] Steps 6, 7, and 8 Calculate the thermal efficiency η, and store the value and the value of the manipulated variable at that time. and 3
If the trial operation over the entire range of the ratio between the secondary air amount and the secondary air amount is not completed, the process moves to step 3 to repeat the processing from step 3 to step 7, and when it is completed, the process moves to step 8.
The largest value η(1, max) of the thermal efficiencies calculated through the processing up to step 7 and the manipulated variable u1 at that time are stored, and the process moves to step 9.

[0165] Steps 9, 10, and 11 With the air amount in the furnace constant, the burner air ratio of each stage is decreased by the same ratio, and at the same time, the after air is increased, and it is checked whether the operational constraints are satisfied. If the condition is not satisfied, repeat steps 9 to 11, and if the condition is satisfied, proceed to step 12.

■ step 12, 13, 14 thermal efficiency η
Calculate and store the value and the value of the manipulated variable at that time. Then, if the trial operation over the entire range of burner air ratios is not completed, steps 9 to 13 are repeated.
Proceed to step 9, and when finished, proceed to step 14, st
The largest value η(2, max) of the thermal efficiencies calculated in the processing up to ep13 and the manipulated variable u2 at that time are stored, and the process moves to step 15.

[0167] Steps 15, 16, 17 Increase the air ratio of the M burner stage shown in FIG. 6, conversely decrease the air ratio of the P burner stage, and check whether the operational constraints are satisfied. If you are not satisfied, step 1
Repeat steps 5 to 17, and if satisfied, step
Move to p18. (2) Steps 18, 19, and 20 Calculate the thermal efficiency η and store the value and the value of the manipulated variable at that time. If the trial operation over the entire range of burner air ratios is not completed, the process moves to step 15 to repeat the processes from step 15 to step 19, and when it is completed, the process moves to step 20. The large value η(3, max) and the manipulated variable u3 at that time are stored, and the process moves to step 21.

[0168] Step 21 The manipulated variable for the largest one among the thermal efficiency maximum values η(1, max) to η(3, max) obtained in steps 8, 14, and 20 described above is set as the optimal manipulated variable.

[0169] If it is determined in step 2 that the current mode is two-stage combustion, an optimum operation amount within the range from two-stage combustion to denitrification combustion mode is searched for in steps 9 to 21. On the other hand, in the case of denitrification combustion, the air ratio is trial-manipulated in the denitrification combustion mode and step 15 to step
Find the optimal manipulated variable using the procedure on page 21.

[0170] The case where the current NOx concentration exceeds the upper limit value has been described above, but next, the case where it falls below the lower limit value NOxL will be described.

In step 23, the combustion mode is determined, and the process branches to each process based on the determination result. First, the case of the denitrification combustion mode will be explained.

[0172] Step 24, 25, 26 Increase the air ratio of the P burners, decrease the air ratio of the M burner, and perform a trial operation while keeping the air ratio of the entire burner constant, and check whether the operational constraints are satisfied. If not satisfied, repeat steps 24 to 26, and if satisfied, proceed to step 27.

■ step 27, 28, 29 thermal efficiency η
Calculate and store the value and the value of the manipulated variable at that time. Then, steps 24 to 28 are repeated until the burner air ratio becomes equal in the P stage and the M stage (two-stage combustion mode), and when they become equal, the process moves to step 29, and the maximum thermal efficiency among the thermal efficiencies calculated up to step 28 is η( 1', max) and the manipulated variable u1' at that time, and proceed to step 30.

[0174] Steps 30, 31, and 32 Increase the air ratio of each stage burner by the same ratio, reduce the after air, and when the operational constraints are met, step
Move to p33.

[0175] ■ step 33, 34, 35 thermal efficiency η
Calculate and store the value and the value of the manipulated variable at that time. Then, continue until the after air reaches 0 (normal combustion mode).
Repeat steps 30 to 34, and when it reaches 0, step
The maximum thermal efficiency calculated up to p34 is η(2',
max) and the manipulated variable u2' at that time are determined, stored, and the process moves to step 36.

■ Steps 36 to 4 By changing the ratio of the tertiary air amount to the secondary air amount for each stage, the maximum value η(
3', max) and the operating amount u3' at that time,
Proceed to step 42.

■ step 42 η(1', max) obtained in steps 29, 35, and 41
The maximum value of ~η(3', max) and the manipulated variable at that point are determined, and this is set as the optimal manipulated variable.

As mentioned above, in the explanation of FIGS. 10 to 15, when determining whether or not the result of the trial operation satisfies the operational constraints, as shown in FIG. There is a method of predicting the response to trial operations using a stage-by-stage NOx prediction model, a stage-by-stage unburned content prediction model, and a furnace outlet exhaust gas concentration prediction model. There is a method that uses the actual response of the plant in addition to the plan.

Next, the combustion gas temperature estimation function block 44
00 will be explained. As shown in Figure 17, an image guide IG with a structure similar to that shown in Figure 6 is installed near the center of the side of each stage of the furnace, and the combustion gas brightness of each stage is split into light via an image fiber IF. Lead to the tube LDV,
Here, the light is branched and guided to imaging devices ITV1 and ITV2 via monochromatic filters FL1 and FL2 of different wavelengths, respectively. The image capturing device converts the luminance information after passing through these filters into a video signal, and after converting each into digital data by analog-digital converters A/D1 and A/D2, two-dimensional data is stored in frame memories FM1 and FM2, respectively. It is stored as brightness/concentration image data. Next, the brightness ratio calculation unit IRC calculates the brightness ratio between corresponding pixels of both image data. Using this brightness ratio, the temperature calculation unit TC calculates the temperature at a point corresponding to each pixel of the two-dimensional image and the average value of the entire screen using the two-color pyrometer method. The calculation method will be explained in detail below. First, the two-color pyrometer method will be explained. In FIG. 17, the two-dimensional digital luminance density images obtained through the monochromatic filters FL1 and FL2 with wavelengths λ1 (cm) and λ2 (cm), respectively, are I1 (i, J), I2 (i, J) (The brightness level is, for example, 0 to 255. Here, (i, j) indicates the (x, y) coordinates of the pixels that make up the image, and the number of horizontal and vertical pixels that make up the image is M, respectively. If N, i=0~(M-1)
, j=0 to (N-1). ), the temperature T(i, j) at the coordinates (i, j) of the image is given by Wien's equation.
The relationship between and each of the above luminance data is expressed by equations (83) and (8
4) It can be expressed by the following equation.

[0180]

[Number 83]

[0181]

[Math. 84]

[0182] Here, ε: Radiation T: Temperature (°K) C1: 3.7403×10-5 erg・c
m2/sC2: 1.4387cm・°Kλ1
, λ2: Wavelength (cm) Taking the ratio of equations (83) and (84), we get (85)
The formula is obtained.

[0183]

[Number 85]

[0184] Here

[0185]

[Number 86]

[0186]

[Number 87]

The brightness ratio calculation unit IRC in FIG. 17 calculates the brightness ratio I1(i,j)/I2(i,j) of equation (85), and using this result, the temperature calculation unit TC calculates (85) to The temperature at each point at coordinates (i, j) is calculated based on equation (87).

[0188] The average temperature Tav is determined by the following equation.

[0189]

[Number 88]

The combustion gas temperature in each region can be estimated using the above equation (88).

Next, in the furnace heat transfer model 4506 of the optimal operation amount determination algorithm shown in FIGS. 9 and 18, (
The combustion ratio kji shown in equation 1) has a strong correlation with the combustion temperature in regions i and j, and can be expressed as a function f thereof as shown in the following equation.

[0192]

[Math. 89]

Here, Tj: Average combustion temperature of region j Ti: Average combustion temperature of region i As a simple example of the equation (89), a multiple regression equation such as the following equation is effective.

[0194]

[Number 90]

Here, b0 to b3: Partial regression coefficient By the way, if the above-mentioned combustion temperature is considered to be equivalent to the burner flame temperature for the burner stage, and the combustion gas temperature for the region other than the burner stage, then , the burner flame temperature was measured using the two-color thermometer method, which also includes the extraction of the burner flame image, as described in Japanese Patent Application No. 118298/1982, and the combustion gas temperature was measured using the previously mentioned Figure 17,
It can be estimated by the two-color pyrometer method shown in equations (83) to (88). In summary, the combustion ratio can be estimated based on burner flame information and combustion gas brightness information as a result of trial operations being applied to the plant. However, in the case of the optimal manipulated variable determination algorithm shown in Figure 8, the plant response to the trial operation is predicted by a model, so the model that predicts the flame temperature and combustion gas temperature for the trial operation is the same as the two-color pyrometer method described above. will be needed instead of. A practical method for making this prediction is to constantly update the display of the correspondence between combustion amount and air amount, flame temperature, and combustion gas temperature by learning the operation results, and use this correspondence table whenever necessary. .

[Modified Examples/Applications of the Invention and Their Effects] FIG. 18 shows a modified example of FIG. 9, in which the actual response results of the combustion gas temperature and can wall metal temperature to the trial operation 1602 are measured, and these values are The furnace heat transfer model 4506 is configured to calculate thermal efficiency using the furnace heat transfer model 4506.
The model for calculating the combustion gas temperature and water wall metal temperature in 506 is not required, and the model can be simplified.

Stage-by-stage combustion diagnosis function block 4 shown in FIG.
Regarding 300, a patent application was filed in 1846 in 1984 as a diagnostic method.
If No. 57 is adopted, trial operation 16 in Figure 8
It can be configured to add a function to predict the flame area for 02, diagnose the combustion stability with respect to the predicted value, and invalidate the trial operation as inappropriate if it is determined to be abnormal. If No. 59-174998 is adopted, a function is added to predict the flame shape for the trial operation 1602 in FIG. 8, and the combustion stability is diagnosed based on the predicted value. It can be configured to invalidate the trial operation as inappropriate, and it is possible to prevent disturbances that would cause combustion to become unstable in the boiler.

[0198]

Effects of the Invention According to the present invention, operational constraints such as NOx concentration at the furnace outlet and unburned content in ash can be adjusted in response to changes in the amount and properties of fuel supplied to the furnace or changes in required load. It is fundamentally stable and can maximize boiler thermal efficiency.

[Brief explanation of the drawing]

FIG. 1 is an overall configuration diagram of an embodiment in which the present invention is applied to a coal-fired power plant.

FIG. 2 is a schematic diagram 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 diagram of the burner structure.

FIG. 6 is an explanatory diagram of a flame image measurement functional block.

FIG. 7 is an explanatory diagram of a stage-by-stage NOx estimation functional block.

FIG. 8 is a stage-by-stage fuel/air distribution calculation function.

FIG. 9 is another embodiment of the stage-by-stage fuel/air distribution calculation function block.

FIG. 10 is an explanatory example of the operation of the 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 example of an algorithm for determining the optimum manipulated variable in the stage-by-stage fuel/air distribution calculation function block.

FIG. 13 is another embodiment of the optimum manipulated variable determination algorithm in the stage-by-stage fuel/air distribution calculation function block.

FIG. 14 is another embodiment of the optimal manipulated variable determination algorithm in the stage-by-stage fuel/air distribution calculation function block.

FIG. 15 is another embodiment of the optimal manipulated variable determination algorithm in the stage-by-stage fuel/air distribution calculation function block.

FIG. 16 is another embodiment of the optimal manipulated variable determination algorithm in the stage-by-stage fuel/air distribution calculation function block.

FIG. 17 is an explanatory diagram of a method for estimating the temperature of combustion gas.

FIG. 18 is another embodiment of the stage-by-stage fuel/air distribution calculation function block.

[Explanation of symbols]

4000... Flame image measurement function block, 4100... NOx estimation function block for each stage, 4200... Function block for estimating unburned content in ash for each stage, 4300... Function block for evaluating combustion stability for each stage, 4400... Function block for estimating combustion gas temperature, 4
500...Fuel/air distribution calculation function block for each stage.

Claims (14)

[Claims] 1. In a combustion control method that adjusts the operating amounts of fuel and air in at least one or more boiler combustion regions so that the unburned content in the ash at the boiler furnace mouth satisfies a constraint, prior to operating the boiler with the actual operating amount, Set trial operation amounts for fuel and air, and use the set trial operation amounts to calculate furnace outlet NOx or
Evaluate the unburned content in the ash at the furnace outlet, calculate the trial operation amount such that the unburned content in the ash at the furnace outlet satisfies predetermined constraint conditions, and the boiler thermal efficiency calculated under those conditions is the largest, and A combustion control method characterized in that a trial operation amount is used as an actual operation amount for boiler operation. 2. In a combustion control method that adjusts the operating amount of fuel and air in the combustion region of at least one boiler so that NOx at the outlet of the boiler furnace satisfies constraint conditions, combustion stability is determined prior to boiler operation with the actual operating amount. If the combustion state satisfies predetermined conditions, trial operation amounts for fuel and air are set, and using the set trial operation amounts, the furnace outlet NOx or the furnace outlet is determined by a pre-prepared model. Evaluate the unburned content in the ash, calculate the trial operation amount such that the unburned content in the ash at the furnace outlet satisfies predetermined constraint conditions, and the boiler thermal efficiency calculated under those conditions is maximized, and perform the trial operation. A combustion control method characterized in that the amount is used as the actual operation amount for boiler operation. 3. In claim 1 or 2, an estimated value of unburned content in ash at a furnace exit is estimated based on a flame image using a prediction model for predicting unburned content in ash at a furnace exit, which predicts unburned content in ash at a furnace exit. and a trial operation amount. 4. In claim 3, the estimated value of unburned content in the ash at the furnace outlet is defined as a high-intensity area of the burner flame, and the oxidation flame is formed in different areas with the burner axis as the boundary. Distance between centers of gravity, shape of the oxidizing flame, burner 1
A combustion control method characterized in that estimation is performed using an estimation model using at least one of four air amounts. 5. A combustion control method according to claim 2, characterized in that the combustion stability is evaluated based on a ratio of a burner flame area to an area of a high brightness region in the flame. 6. In claim 2, the combustion stability evaluation is defined as a high-intensity area of the burner flame, the center of gravity of the oxidizing flame, the distance between the centers of gravity of the oxidizing flame formed in different areas with the burner central axis as the 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. Claims 1 or 2 provide a furnace in which the maximum point of boiler thermal efficiency is determined using fuel and air amounts as manipulated variables, and the combustion gas temperature in the furnace, the heat transfer tube metal temperature, and the heat transfer tube metal internal fluid temperature are estimated. A combustion control device method characterized by calculating boiler thermal efficiency using a heat transfer model. 8. Claim 7 is characterized in that the furnace heat transfer model is corrected based on the difference between the estimated combustion gas temperature, the measured water wall metal temperature, the internal body temperature at the water wall outlet, and the calculated value of the model. Combustion control method. 9. A combustion control method according to claim 8, characterized in that the estimated combustion gas temperature is calculated based on brightness information of the combustion gas. 10. A combustion control method according to claim 7, characterized in that the boiler thermal efficiency is calculated as a ratio of heat absorption into the heat exchanger tube metal to the sum of the amount of heat input to the furnace and the amount of heat generated by combustion. 11. A combustion control method according to claim 7, characterized in that the boiler thermal efficiency is calculated as a ratio of heat absorption into the heat exchanger tube metal to the sum of the amount of heat input to the furnace and the amount of heat generated by combustion. 12. A combustion control method according to claim 7, characterized in that the furnace heat transfer model is calculated as a function of a flame temperature that is estimated based on flame image information. 13. Claim 1 or 2 provides a furnace heat transfer model for estimating the boiler thermal efficiency from the combustion gas temperature in the furnace, the temperature of the internal fluid of the heat transfer tube metal from the temperature of the relevant tube metal, the calculation results of the model, the fuel and A combustion control method characterized in that calculation is performed based on the amount of air. 14. A combustion control method according to claim 13, characterized in that the combustion gas temperature is estimated based on the brightness of the combustion gas.