CN112580890B - Method and system for predicting variable cost of power generation by blending and burning mixed coal of boiler for power generation - Google Patents
Method and system for predicting variable cost of power generation by blending and burning mixed coal of boiler for power generation Download PDFInfo
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- 238000010248 power generation Methods 0.000 title claims abstract description 91
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- 238000002485 combustion reaction Methods 0.000 claims abstract description 120
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Abstract
The invention discloses a method and a system for predicting the variable cost of power generation by blending and burning mixed coal of a boiler for power generation, wherein the coal quality parameters and the coal price indexes of the mixed coal are predicted by various single coal quality parameters, coal price indexes of various single coals and blending and burning proportion data of various single coals; predicting boiler efficiency when the mixed coal burns based on the coal quality parameters of the mixed coal, predicting boiler coal consumption of the mixed coal burning based on the boiler efficiency, and predicting coal consumption cost of mixed coal blending burning based on the boiler coal consumption and the coal price index of the mixed coal; predicting desulfurization and denitrification cost of mixed coal combustion based on the consumption of the mixed coal combustion boiler and the material price index; predicting the power consumption and the cost of the power plant when the mixed coal burns based on the power plant power consumption monitoring data; the variable power generation cost of the mixed coal combustion is predicted based on the coal consumption cost, the desulfurization and denitrification cost and the power plant power consumption cost, compared with the prior art, the variable power generation cost of the mixed coal combustion of the boiler can be accurately predicted, and a data basis is provided for the decision of the mixed combustion scheme.
Description
Technical Field
The invention relates to the technical field of boiler power generation, in particular to a method and a system for predicting the power generation variable cost of mixed coal blending combustion of a boiler for power generation.
Background
In order to reduce the power generation cost of the coal-fired power generating unit, thermal power enterprises purchase economic coal and inferior coal for blended combustion. The blending ratio of the economic coal and the inferior coal is determined, and a blending combustion scheme with the lowest price of a blending coal standard is pursued under the premise of considering the quality indexes of the blending coal such as moisture, ash, volatile matters, sulfur, low-grade heating value and the like to meet the requirements. The traditional coal blending method only focuses on the price of coal blending, and does not consider the influence of different coal blending schemes on the running cost of the unit. Only considering the coal blending method of the price of the fuel standard bill can bring about larger operation cost of the boiler system, and the enterprise benefit is damaged. The unit power generation costs include fixed costs and variable costs. How to perform power generation of the coal-fired power generation unit based on the blending ratio of the blended coal becomes cost accounting and becomes a difficult problem of blending coal blending combustion decision.
Disclosure of Invention
The invention provides a method and a system for predicting the variable cost of power generation by mixing and burning boiler mixed coal, which are used for solving the technical problem that the conventional cost prediction method cannot accurately calculate the variable cost of power generation.
In order to solve the technical problems, the technical scheme provided by the invention is as follows:
the method for predicting the power generation variable cost of the mixed coal blending combustion of the boiler for power generation comprises the following steps:
Acquiring various single coal quality parameters of mixed coal, coal price indexes of various single coals, blending ratio data of various single coals, material price indexes of desulfurization and denitrification and power plant power monitoring data; predicting coal quality parameters and coal price indexes of mixed coal according to various single coal quality parameters, various single coal price indexes and various single coal blending ratio data;
Predicting boiler efficiency when the mixed coal burns based on the coal quality parameters of the mixed coal, predicting boiler coal consumption of the mixed coal burning based on the boiler efficiency, and predicting coal consumption cost of mixed coal blending burning based on the boiler coal consumption and the coal price index of the mixed coal; predicting desulfurization and denitrification cost of mixed coal combustion based on the consumption of the mixed coal combustion boiler and the material price index; predicting the electricity consumption cost of the mixed coal during combustion based on the electricity consumption monitoring data;
the variable power generation cost in the process of mixed coal combustion is predicted based on coal consumption cost, desulfurization and denitrification cost and electricity consumption cost.
Preferably, the coal quality parameters of the mixed coal and the coal price index of the mixed coal are predicted according to various single coal quality parameters, various single coal price indexes and various single coal blending ratio data, and are realized by the following formulas:
Wherein Q ar,net,Qar,net,i is a mixed coal, the single coal receives a basic low-rank calorific value in kJ/kg, wherein i represents an i-th single coal, i=1, 2,3,..n, n is the total number of single coals, and k i represents the blending ratio of the i-th single coal; a ad,Aad,i is mixed coal, single coal air drying base ash, and the unit is; m ar,Mar,i is mixed coal, and the unit of the single coal receives the base water; v daf,Vdaf,i is mixed coal, single coal is dried to form ash-free volatile matters, and the unit is; s ar,Sar,i is mixed coal, and the unit of the base sulfur content received by single coal is shown as follows; HGI, HGI i are mixed coals respectively, and the single coal grindability coefficient; ST i is the melting point of mixed coal and single coal ash, and the unit is the temperature; p rl,prl,i is the unit price of mixed coal and single coal in the furnace, and the unit is yuan/t.
Preferably, the method for predicting the boiler efficiency in the mixed coal combustion based on the coal quality parameters of the mixed coal comprises the following steps:
Predicting fly ash combustibles of the mixed coal based on the coal quality parameters of the mixed coal and the relation between the fly ash combustibles;
predicting slag combustibles of the mixed coal based on the predicted fly ash combustibles of the mixed coal and the relationship between the fly ash combustibles and the slag combustibles;
predicting a discharge temperature difference when the mixed coal burns based on a predicted relation between fly ash combustibles of the mixed coal and the discharge temperature difference;
the boiler efficiency at the time of mixed coal combustion is predicted based on the predicted slag combustibles, fly ash combustibles, and discharge temperature difference.
Preferably, the relation between the coal quality parameter of the mixed coal and the fly ash combustible is obtained through the following steps:
Acquiring mixed coal quality data of a plurality of working conditions and corresponding fly ash combustibles from a boiler blending combustion test report, wherein the mixed coal quality data at least comprises basic low-level heating value Q ar,net, basic ash content A ad, basic water content M ar and dry ashless base volatile V daf;
Stepwise regression analysis is carried out on the coal quality data of the mixed coal under a plurality of working conditions and the corresponding fly ash combustible C fh, and a regression equation of the coal quality parameters and the fly ash combustible is fitted;
The relation between fly ash combustibles and slag combustibles of the mixed coal is obtained by the following steps:
Acquiring mixed coal quality data of a plurality of working conditions, corresponding fly ash combustibles and corresponding slag combustibles from a boiler blending combustion test report, wherein the mixed coal quality data at least comprises basic low-level heating value Q ar,net, received basic ash A ad and dry ashless basic volatile V daf;
Stepwise regression analysis is carried out on the fly ash combustible corresponding to the coal quality data of the mixed coal under a plurality of working conditions and the corresponding slag combustible, and a regression equation of the fly ash combustible and the slag combustible is fitted;
The relation between the fly ash combustible material of the mixed coal and the temperature difference of the discharge is obtained through the following steps:
Acquiring mixed coal quality data of a plurality of working conditions, corresponding fly ash combustibles, corresponding generator active power P qj and corresponding discharge temperature difference t ps from a boiler blending combustion test report, wherein the mixed coal quality data at least comprises basic low-level heating value Q ar,net, received basic ash A ad and dry ashless base volatile component V daf;
Stepwise regression analysis is carried out on the coal-mixed coal quality data, the corresponding fly ash combustible, the corresponding active power P qj of the generator and the corresponding discharge temperature difference t ps under a plurality of working conditions, and a regression equation of the fly ash combustible and the discharge temperature difference t ps is fitted.
Preferably, predicting boiler efficiency in mixed coal combustion based on predicted slag combustibles, fly ash combustibles and discharge temperature difference specifically comprises the steps of:
Based on the predicted exhaust temperature difference, the exhaust temperature during the combustion of the mixed coal is predicted by the following formula:
θpy＝tps+t0
wherein, theta py is the exhaust gas temperature; t ps is the discharge temperature difference; t 0 is the atmospheric temperature of the place;
based on the predicted fly ash combustibles and slag combustibles of the mixed coal, predicting the percentage of the average carbon content in the ash slag and the coal ash content by the following formula;
Wherein, The unit is the percentage of the average carbon content in ash slag and the coal ash content; alpha lz is the slag coefficient; alpha fh is the fly ash coefficient, C lz is the slag combustibles, C fh is the fly ash combustibles;
based on the predicted percentage of the average carbon content in the ash and the coal ash content, the mixed coal combustion is predicted by the following formula
The theoretical dry air quantity required at that time;
Wherein, Is the theoretical dry air quantity, and the unit is m 3/kg;
The calculation formula of K is as follows:
Based on the predicted theoretical dry air amount, the theoretical dry smoke amount is predicted by the following formula:
Wherein, The unit is m 3/kg which is the theoretical dry smoke quantity;
Based on the predicted theoretical dry smoke amount and the theoretical dry air amount, the actual dry smoke amount is predicted by the following formula:
Wherein V gy is the actual dry flue gas quantity, the unit is m 3/kg;AL is the air leakage rate of the air preheater, the unit is alpha is the excess air coefficient of the hearth;
based on the predicted theoretical dry air amount, the volume of water vapor in the flue gas generated by the combustion of the mixed coal is predicted by the following formula:
Wherein, The volume of water vapor in the flue gas is m 3/kg;dk, the absolute humidity of air is kg/kg, V daf is dry ash-free volatile component,/>To the 0.2319 power of V daf;
based on the predicted exhaust gas temperature and the actual dry gas amount, predicting the exhaust gas heat loss during the combustion of the mixed coal through the following formula;
Wherein,
1.51 Is the specific heat capacity of water vapor at constant pressure, and the unit is kJ/(kg.K); the constant pressure specific heat capacity of nitrogen in the dry flue gas is given by kJ/(kg.K); /(I) The constant pressure specific heat capacity of oxygen in the dry flue gas is shown as kJ/(kg.K); /(I)The constant pressure specific heat capacity of carbon dioxide in the dry flue gas is given as kJ/(kg.K); c p,gy is the constant pressure specific heat capacity of the dry flue gas, and the unit is kJ/(kg.K);
Based on the percentage of the average carbon content in the ash and the amount of the coal ash, the solid incomplete combustion heat loss when the mixed coal is combusted is predicted by the following formula:
Wherein q 4 is the solid incomplete combustion heat loss, and the unit is;
based on the predicted fly ash combustibles, slag combustibles, and exhaust gas temperatures, the ash physical heat loss upon coal blending combustion is predicted by the following equation:
Wherein q 6 is physical heat loss of ash, c lz is specific heat of the ash, and the unit is kJ/(kg.K); c fh is the specific heat of the fly ash, the unit is kJ/(kg.K), and t lz is the slag temperature;
The power of the outlet end of the generator during mixed coal combustion is obtained, and the heat dissipation loss of the boiler is predicted based on the following formula:
q 4 is the heat dissipation loss of the boiler, and the unit is; j 1 is the first coefficient of the boiler heat dissipation loss regression equation; j 2 is the second coefficient of the boiler heat dissipation loss regression equation; p qj is the power of the outlet end of the generator, and the unit is MW;
Based on predicted heat loss from flue gas, heat loss from incomplete combustion of solids, physical heat loss from ash, and heat loss from the boiler, the boiler efficiency is predicted by the following equation:
ηg＝100-q2-q4-q5-q6
Wherein η g is the boiler efficiency.
Preferably, the predicted boiler coal consumption for mixed coal combustion based on boiler efficiency is obtained by the following formula:
Bf＝bfPqj/1000
Wherein k 0,k1,k2 is the first, second and third coefficients of the steam turbine heat consumption regression equation, Q sr is the steam turbine heat consumption, the unit is GJ/h, and Q is the steam turbine heat consumption rate, the unit is kJ/kWh; b f is the power generation coal consumption, and the unit is g/kWh; η gd is the pipe efficiency; r h is a thermal equivalent value; 7000 is standard coal heat, the unit is kcal, B f is boiler coal consumption, and the unit is t/h.
Preferably, the desulfurization and denitrification cost of the mixed coal combustion is predicted based on the coal consumption of the boiler of the mixed coal combustion and the material price index, and is calculated by the following formula:
Ctlhs＝ctlhsPqj/1000
Ctltx＝Cshspshs+Ctlhsptlhs+Ctxjptxj/1000
Wherein, The standard oxygen content flue gas SO 2 concentration generated for complete combustion of sulfur is in mg/m 3; 6 is the reference oxygen content in units of; 3.5 is the oxygen content of the dry flue gas, and the unit is; /(I)The unit of the emission concentration limit value of the atmospheric pollutants of the thermal power generation boiler is mg/m 3;wshs, the unit is the purity of limestone; 100 is the molecular weight of limestone; 64 is sulfur dioxide molecular weight; 1.02 is the limestone demand coefficient; c shs is the consumption of the desulfurization material limestone, and the unit is t/h; c tlhs is a recent statistical value of desulfurization water consumption rate, and the unit is g/kWh; c tlhs is desulfurization water consumption, t/h; r 1,r2 is the first coefficient and the second coefficient of the denitration agent consumption regression equation respectively; c txj is the consumption of the denitration agent, and the unit is kg/h; p shs is the price of limestone in yuan/t; p tlhs is the desulfurization water consumption price, and the unit is yuan/t; p txj is the price of the denitration agent, and the unit is yuan/t; c tltx is desulfurization and denitrification cost, the unit is yuan/h, and S ar is the sulfur content of the mixed coal.
Preferably, the electricity consumption cost when the mixed coal is burnt is predicted based on the electricity consumption monitoring data, and is calculated by the following formula:
CD＝Pd×(t2Pqj 2+t1Pqj+t0)
Wherein, C D is the electricity consumption cost; p d is the power price of the Internet, P qj is the power of the outlet end of the generator, and the unit is MW; t 0、t1、t2 is the first, second, and third coefficients, respectively, of the fitted electricity consumption model in MW.
Preferably, the power generation variable cost when the mixed coal is burnt is predicted based on the coal consumption cost, the desulfurization and denitrification cost and the electricity consumption cost, and is calculated by the following formula:
Cf＝CD+Ctltx+Bfprl
Wherein c f is the electricity generation variable cost of the mixed coal; c f is the variable cost of power generation, the unit is yuan/h, P d is the online electricity price, and the unit is yuan/kWh; p rl is the coal price index of the mixed coal fed into the furnace.
A computer system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of any of the methods described above when the computer program is executed.
The invention has the following beneficial effects:
1. The invention relates to a method and a system for predicting the power generation variable cost of mixed coal of a boiler for power generation, wherein the method and the system are used for predicting the coal quality parameters and the coal price indexes of mixed coal through various single coal quality parameters, various single coal price indexes and various single coal mixing ratio data; predicting boiler efficiency when the mixed coal burns based on the coal quality parameters of the mixed coal, predicting boiler coal consumption of the mixed coal burning based on the boiler efficiency, and predicting coal consumption cost of mixed coal blending burning based on the boiler coal consumption and the coal price index of the mixed coal; predicting desulfurization and denitrification cost of mixed coal combustion based on the consumption of the mixed coal combustion boiler and the material price index; predicting the electricity consumption cost of the mixed coal during combustion based on the electricity consumption monitoring data; the variable power generation cost in the process of mixed coal combustion is predicted based on the coal consumption cost, the desulfurization and denitrification cost and the power consumption cost, and compared with the prior art, the variable power generation cost in the process of mixed coal combustion of a boiler can be accurately predicted, and a data basis is provided for the decision of a mixed combustion scheme.
In addition to the objects, features and advantages described above, the present invention has other objects, features and advantages. The invention will be described in further detail with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application. In the drawings:
FIG. 1 is a flow chart of a method for predicting power generation variable cost of a boiler blend coal combustion for power generation in accordance with a preferred embodiment of the present invention;
FIG. 2 is a flow chart of the operation of a system for predicting the power generation variable cost of a boiler blend firing for generating power in accordance with a preferred embodiment of the present invention.
Detailed Description
Embodiments of the invention are described in detail below with reference to the attached drawings, but the invention can be implemented in a number of different ways, which are defined and covered by the claims.
Embodiment one:
As shown in fig. 1, the present embodiment discloses a method for predicting the power generation variable cost of mixed coal blending combustion of a boiler for power generation, comprising the following steps:
the method for predicting the power generation variable cost of the mixed coal blending combustion of the boiler for power generation comprises the following steps:
Acquiring various single coal quality parameters of mixed coal, coal price indexes of various single coals, blending ratio data of various single coals, material price indexes of desulfurization and denitrification and power plant power monitoring data; predicting coal quality parameters and coal price indexes of mixed coal according to various single coal quality parameters, various single coal price indexes and various single coal blending ratio data;
Predicting boiler efficiency when the mixed coal burns based on the coal quality parameters of the mixed coal, predicting boiler coal consumption of the mixed coal burning based on the boiler efficiency, and predicting coal consumption cost of mixed coal blending burning based on the boiler coal consumption and the coal price index of the mixed coal; predicting desulfurization and denitrification cost of mixed coal combustion based on the consumption of the mixed coal combustion boiler and the material price index; predicting the electricity consumption cost of the mixed coal during combustion based on the electricity consumption monitoring data;
the variable power generation cost in the process of mixed coal combustion is predicted based on coal consumption cost, desulfurization and denitrification cost and electricity consumption cost.
In addition, in the present embodiment, a computer system is also disclosed, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the steps of any of the methods described above when executing the computer program.
The invention relates to a method and a system for predicting the power generation variable cost of mixed coal of a boiler for power generation, wherein the method and the system are used for predicting the coal quality parameters and the coal price indexes of mixed coal through various single coal quality parameters, various single coal price indexes and various single coal mixing ratio data; predicting boiler efficiency when the mixed coal burns based on the coal quality parameters of the mixed coal, predicting boiler coal consumption of the mixed coal burning based on the boiler efficiency, and predicting coal consumption cost of mixed coal blending burning based on the boiler coal consumption and the coal price index of the mixed coal; predicting desulfurization and denitrification cost of mixed coal combustion based on the consumption of the mixed coal combustion boiler and the material price index; predicting the electricity consumption cost of the mixed coal during combustion based on the electricity consumption monitoring data; the variable power generation cost in the process of mixed coal combustion is predicted based on the coal consumption cost, the desulfurization and denitrification cost and the power consumption cost, and compared with the prior art, the variable power generation cost in the process of mixed coal combustion of a boiler can be accurately predicted, and a data basis is provided for the decision of a mixed combustion scheme.
Embodiment two:
an embodiment two is an extended embodiment of the first embodiment, and in this embodiment, the proposed technical scheme is as follows: based on a big data analysis platform, digital coal yard data are collected, a model for predicting the efficiency of the coal-fired boiler and predicting the power generation variable cost based on coal quality prediction of mixed coal is built, and the model is applied to the decision of a blending combustion scheme. That is, this embodiment discloses a method for predicting the power generation variable cost of mixed coal blending combustion of a boiler for power generation, as shown in fig. 2, comprising the following steps:
Step one: digital coal yard data acquisition
Based on an enterprise digital coal yard system, the system realizes real-time automatic acquisition of the data of the coal quantity, coal price and coal quality analysis indexes of various coals in the digital coal yard. The coal quality analysis indexes comprise low-level heating value, ash content, moisture, volatile matters, sulfur content, grindability coefficient, ash melting point and the like.
Step two: blend firing scheme and parameter settings
The user selects n kinds of single coal for blending, and sets the upper limit value of blending proportion of the difficult-to-grind coal.
The user sets the coal quantity ratio k i of each blended single coal, namely k 1：k2：…：kn.
The user sets the values of working condition parameters, which comprise power generation P qj, excess air coefficient alpha of a furnace, air relative humidity d k, atmospheric temperature t 0, air absolute humidity d k, air leakage rate A L of an air preheater, slag coefficient alpha lz, fly ash coefficient alpha fh, pipeline efficiency eta gd and discharge concentration limit value of flue gas SO 2 Limestone purity w shs, recent statistical value c tlhs of desulfurization water consumption rate, limestone price p shs, desulfurization water consumption price p tlhs, denitration agent price p txj, internet electricity price p d and the like.
The user sets the constraint condition of the coal quality of the mixed coal, namely sets the data allowable range of the coal quality index of the mixed coal, such as low-level heating value, volatile matters, sulfur components, moisture and the like under different power generation loads.
Step three: mixed coal quality and coal price index prediction
The calculation formula of the coal quality analysis index of the mixed coal is as follows:
Wherein,
Q ar,net,Qar,net,i -mixed coal, single coal receives basic low-position heating value, kJ/kg
A ad,Aadi -Mixed coal, single coal air drying base ash%
M ar,Mar,i -mixing coal, single coal receives base moisture, percent
V daf,Vdaf,i -dry ash-free base volatile matter of mixed coal and single coal%
S ar,Sar,i -the mixed coal and single coal receive the sulfur content, percent
HGI, HGI i -coal blend, single coal grindability coefficient
ST, ST i -melting point of mixed coal and single coal ash, DEG C
The calculation formula of the coal mixing and charging standard coal unit price p rl is as follows:
p rl,prl,i -unit price of mixed coal and single coal into the furnace, unit/t.
Coal with a grindability coefficient of less than 64 is defined as difficult coal, coal with a grindability coefficient of greater than 86 is defined as easy coal, and grindability coefficient between 66 and 86 is defined as grindability coal.
Based on the calculation result of the coal quality index of the mixed coal and the constraint condition, the system gives a prompt whether the coal quality index of the mixed coal meets the constraint condition.
Step four: boiler efficiency prediction for mixed coal combustion
First step, determining a regression equation for fly ash combustible C fh
The method comprises the steps of selecting mixed coal quality data of mixed coal, wherein the input variable is mixed coal quality data of base low-level heating value Q ar,net, base ash content A ad, base water content M ar, dry ash-free base volatile component V daf and the like, outputting variable is fly ash combustible C fh, carrying out stepwise regression analysis based on a plurality of working condition data reported by a boiler blending combustion test, and finally determining a regression equation of the fly ash combustible C fh.
Determining a regression equation of the slag combustibles C lz
The input variables are the base low-level heating value Q ar,net received by the mixed coal, the base ash content A ad received by the mixed coal, the dry ash-free base volatile component V daf and the fly ash combustible C fh, the output variables are the slag combustible C lz, stepwise regression analysis is carried out based on a plurality of working condition data reported by a boiler blending combustion test, and a regression equation of the slag combustible C lz is finally determined.
Third step, determining a regression equation of the exhaust gas temperature theta py
The method comprises the steps of selecting an input variable of active power P qj of a generator, receiving a base low-level heating value Q ar,net of mixed coal, receiving base ash A ad, drying ash-free base volatile matters V daf and fly ash combustible matters C fh, and performing stepwise regression analysis based on a plurality of working condition data reported by a boiler blending combustion test, wherein the output variable is a discharge temperature difference t ps, which is the deviation of a discharge temperature and an air supply temperature, and finally determining a regression equation of the discharge temperature difference t ps. The calculation formula of the exhaust gas temperature theta py is as follows:
θpy＝tps+t0
fourth, predicting the percentage of the average carbon content in the ash and the coal ash
Taking a predicted value of the fly ash combustible C fh and a predicted value of the slag combustible C lz, and taking the percentage of the average carbon content in ash slag and the coal ash contentThe calculation formula of (2) is as follows:
-percentage of the average carbon content in the ash to the amount of coal ash,%;
Alpha lz -slag coefficient;
alpha fh -fly ash coefficient;
fifth step, predicting theoretical dry air quantity
Theoretical dry air quantityThe calculation formula of (2) is as follows:
Theoretical dry air quantity, m 3/kg;
Wherein the calculation formula of K is as follows:
Sixth step, predicting theoretical dry smoke volume
Theoretical dry smoke volumeThe calculation formula of (2) is as follows:
-theoretical dry smoke quantity, m 3/kg;
Seventh step, predicting the actual dry smoke volume V gy
The actual dry smoke volume V gy is calculated as follows:
v gy -actual dry smoke, m 3/kg;
a L -air leakage rate of the air preheater,%;
eighth step, the water vapor volume in the flue gas is predicted
Volume of water vapor in flue gasThe calculation formula of (2) is as follows:
-the volume of water vapour in the flue gas, m 3/kg;
d k -absolute humidity of air, kg/kg;
Ninth step, predicting heat loss q of exhausted smoke 2
The calculation formula of the smoke exhaust heat loss q 2 is as follows:
Wherein,
1.51-Constant pressure specific heat capacity of steam, kJ/(kg. K);
-constant pressure specific heat capacity of nitrogen in dry flue gas, kJ/(kg·k);
-constant pressure specific heat capacity of oxygen in dry flue gas, kJ/(kg·k);
-constant pressure specific heat capacity of carbon dioxide in dry flue gas, kJ/(kg·k);
c p,gy -constant pressure specific heat capacity of dry flue gas, kJ/(kg.K);
tenth step, predicting solid incomplete combustion Heat loss q 4
Neglecting the heat loss rate of the pebble coal of the medium speed coal mill, the calculation formula of the solid incomplete combustion heat loss q 4 is as follows:
q 4 -solid incomplete combustion heat loss,%;
Eleventh step, predicting physical heat loss q of ash 6
The calculation formula of the ash physical heat loss q 6 is as follows:
c lz -specific heat of slag, kJ/(kg.K);
c fh -specific heat of fly ash, kJ/(kg. K);
Twelfth step, predicting heat dissipation loss q of boiler 5
Fitting an exponentiation equation of the power generation power variation of the random set of the heat dissipation loss q 5 of the boiler according to the boiler co-firing test data:
q 4 -loss of heat dissipation of boiler,%;
j 1 -coefficient of regression equation 1;
j 2 -coefficient 2 of regression equation;
P qj -generator outlet end power, MW;
The loss of the combustible gas from incomplete combustion is ignored, i.e., q 3 is set to 0.
Thirteenth step, predicting boiler efficiency η g
The calculation formula of the boiler efficiency eta g is as follows:
ηg＝100-q2-q4-q5-q6
Step five: prediction of boiler coal consumption by mixed coal combustion
1. Regression equation for determining steam turbine heat rate q
Based on the latest monitoring data of the heat rate of the steam turbine, a regression equation of the heat rate Q sr of the steam turbine is obtained:
wherein k 0,k1,k2 is the coefficient of regression equation
The calculation formula of the turbine heat rate q is as follows:
Q sr -turbine heat consumption, GJ/h;
q-turbine heat rate, kJ/kWh;
2. Predicting generating coal consumption b of unit f
The calculation formula of the boiler coal consumption b f is as follows:
b f -generating coal consumption, g/kWh;
η gd -pipeline efficiency, which is 98% -99%;
R h, a thermal equivalent value, is taken to be a fixed value 4.1868kJ/kcal;
7000—standard coal calorific value, kcal;
3. predicting boiler coal consumption B f
The calculation formula of the boiler coal consumption B f is as follows:
Bf＝bfPqj/1000
B f, boiler coal consumption, t/h;
step six: desulfurization and denitrification cost prediction for mixed coal combustion
Sulfur dioxide concentration in dry flue gas produced by combustion of mixed coalPrediction
Sulfur complete combustion of 1kg coal blend produces SO 2 emission concentrationThe calculation formula is as follows:
-standard oxygen content flue gas SO 2 concentration generated by complete combustion of sulfur, mg/m 3;
6-reference oxygen content,%;
3.5-oxygen content of dry flue gas,%;
Second step, the consumption C shs of the desulfurization material limestone is predicted
The calculation formula of the consumption C shs of the desulfurization material limestone is as follows:
-the atmospheric pollutant emission concentration limit value of the thermal power generation boiler, mg/m 3;
w shs —limestone purity,%;
100—limestone molecular weight;
64-sulfur dioxide molecular weight;
1.02-limestone demand factor;
C shs, the consumption of the desulfurization material limestone, t/h;
Third step, prediction of desulfurization water consumption C tlhs
Because the water meter measurement of the desulfurization water consumption is lacking in the field, the prediction of the desulfurization water consumption C tlhs is carried out based on the historical statistical data of the desulfurization water consumption rate, and the calculation formula is as follows:
Ctlhs＝ctlhsPqj/1000
c tlhs, taking the recent statistical value of the desulfurization water consumption rate, g/kWh;
C tlhs, desulfurization water consumption, t/h;
Fourth step, predicting the consumption of the denitration agent C txj
The consumption C txj of the denitration agent such as liquid ammonia or urea can obtain a regression equation of the consumption C txj of the denitration agent along with the change of the consumption B f of the coal according to historical data, such as:
Wherein the method comprises the steps of
R 1,r2 -regression equation coefficients;
C txj -consumption of denitration agent, kg/h;
Fifthly, predicting desulfurization and denitrification cost C tltx
The calculation formula of the desulfurization and denitrification cost C tltx is as follows:
Ctltx＝Cshspshs+Ctlhsptlhs+Ctxjptxj/1000
p shs -limestone price, yuan/t;
p tlhs -desulphurizing water consumption price, yuan/t;
p txj -price of denitration agent, yuan/t;
c tltx, environmental protection treatment cost, yuan/h;
step seven: power generation variable cost prediction for mixed coal combustion
Determining a regression equation of the power consumption of the power plant
And carrying out regression equation fitting of the power consumption of the power plant based on the latest power consumption monitoring data of the power plant:
t 0,t1,t2 -regression equation coefficients;
P d -the power plant electric active power, kW;
Second step, power generation variable cost C f prediction
The calculation formula of the variable power generation cost C f of the mixed coal is as follows:
Cf＝Pdpd+Ctltx+Bfprl
p d -Internet price, yuan/kWh;
c f, the variable cost of power generation, yuan/h;
The calculation formula of the electricity generation variable cost c f of the mixed coal is as follows:
step eight: predictive computation result application of mixed coal combustion
The prediction results of the boiler efficiency and the power generation variable cost of the mixed coal combustion are saved to a database, and the prediction results are applied to the comparative analysis of the mixed coal combustion scheme of the boiler.
The system utilizes an optimal algorithm to call the boiler efficiency of mixed coal combustion and the power generation variable cost prediction calculation program when the optimizing calculation of the mixed coal blending combustion scheme is carried out, so that the scheme optimizing with the lowest power generation cost or the highest power generation efficiency based on the mixed coal blending combustion target is realized.
Embodiment III:
The third embodiment is a preferred embodiment of the third embodiment, and in this embodiment, a subcritical condensing steam turbine generator unit with a certain installed capacity of 300MW is taken as an example for explanation. The boiler is a single steam drum, one-time intermediate reheating, solid slag discharging, W-shaped flame burning mode, open-air capping, subcritical pressure and natural circulation coal-fired boiler. The boiler is designed to be locally anthracite, and the grindability coefficient HGI is 68. The blending mode of the boiler is blending of a coal conveying belt. The denitration system adopts a Selective Catalytic Reduction (SCR) denitration device, and the desulfurization system adopts FGD wet flue gas desulfurization.
The invention discloses a method for predicting the power generation variable cost of mixed coal blending combustion of a boiler for power generation, which comprises the following steps:
Step one: digital coal yard data acquisition
Based on an enterprise digital coal yard system, the system realizes real-time automatic acquisition of coal quantity, price of a coal standard bill entering a furnace and coal quality analysis index data of various coals of the digital coal yard. The coal quality analysis index comprises the received low-level heating value, air-dry base ash content, received base moisture, air-dry base moisture, dry ash-free base volatile matters and received base sulfur.
Step two: blend firing scheme and parameter settings
2 Kinds of coal, jincheng kinds of coal and local car coal, are selected, and the upper limit value of the blending ratio of the difficult-to-grind coal is set to 25%. The grinding coefficient (HGI) of Jincheng is 45, and the Jincheng coal is judged to be difficult to grind according to the Hardgkin grindability coefficient, and the local car coal is the grindability coal. Setting the blending ratio of Jincheng coal and local car coal to be 1:4.
The setting of the working condition parameters of the boiler is as follows: the power generation power Pqj is 280MW, the excess air coefficient d of the hearth is 1.29, the atmospheric temperature t 0 is 20 ℃, the absolute air humidity dk is 0.01kg/kg, the air leakage rate A L of the air preheater is 5.5%, the slag coefficient alpha lz is 10, the fly ash coefficient alpha fh is 90, the pipeline efficiency eta gd is 99%, and the emission concentration limit value of the flue gas SO 2 is 99The value of (3) is 50mg/m 3, the value of limestone purity w shs is 87%, the recent statistical value of desulfurization water consumption rate is 0g/kWh, the value of limestone price p shs is 66.25 yuan/t, the value of desulfurization water consumption price p tlhs is 0 yuan/t, the value of denitration agent price p txj is 3000 yuan/t, and the value of Internet power price p d is 0.42 yuan/kWh.
The constraint conditions of the coal quality index are set as the variation ranges of dry ashless base volatile components, received base low-position heating value and total moisture under different load regions.
Step three: mixed coal quality and coal price index prediction
The coal quality index of the mixed coal is obtained by carrying out linear weighted calculation according to the blending ratio of Jincheng coal to local automobile coal of 1:4, wherein the coal quality index comprises the received base low-grade heat value, air-dried base ash content, received base moisture, dried ashless base volatile, grindability coefficient and price of a furnace charging standard list, and the following table shows that:
step four: boiler efficiency prediction for mixed coal combustion
Step one: regression equation for determining fly ash combustibles C fh
The input variables are mixed coal quality data such as the base low-level heating value Q ar,net received by mixed coal, the base ash content A ad received by the mixed coal, the base water content M ar received by the mixed coal, the dry ash-free base volatile component V daf, the grindability coefficient HGI and the like, the output variables are fly ash combustible C fh, gradual regression analysis is carried out based on the blending test data of Jincheng coal and local coal, and a regression equation of the fly ash combustible C fh, namely C fh＝4.79566+0.00148457Qar,net -0.482232HGI, is finally determined.
When the predicted value Q ar,net of the coal blending index is 19600kJ/kg, HGI is 65, and the predicted value of the fly ash combustible is 2.55 percent according to the regression equation.
Step two: regression equation for determining slag combustibles C lz
The input variables are the base low-level heating value Q ar,net received by the mixed coal, the base ash content A ad received by the mixed coal, the dry ash-free base volatile component V daf and the grindability coefficient HGI, the output variables are the slag combustible C lz, gradual regression analysis is carried out based on the blending burning test data of Jincheng coal and local coal, and finally the regression equation of the slag combustible C lz is determined, namely C lz = 10.6699-0.101785HGI.
When the HGI of the mixed coal is 65, the predicted value of the slag combustible is 4.05 percent according to the regression equation.
Step three: regression equation for determining smoke exhaust temperature theta py
The method comprises the steps of selecting an input variable of active power P qj of a generator, receiving a base low-position heating value Q ar,net of mixed coal, receiving base ash A ad, drying ash-free base volatile matters V daf and fly ash combustible matters C fh, and performing stepwise regression analysis on the output variable of deviation of exhaust gas temperature and supply air temperature, namely a discharge temperature difference t ps, based on Jincheng coal and local coal blending test data, and finally determining a regression equation of the discharge temperature difference t ps, namely t ps＝174.758-0.110731Pqj-5.50378Vdaf. The calculation formula of the exhaust gas temperature theta py is as follows:
θpy＝tps+t0
When P qj is 280MW and V daf is 6.4%, t 0 is calculated according to a regression equation to obtain that t ps is 108.53 ℃, and the predicted value of the smoke exhaust temperature theta py is 128.53 ℃.
Step four: predicting the percentage of average carbon content in ash to the amount of coal ash
Substituting parameter values such as a setting value 10 of a slag coefficient alpha lz, a setting value 90 of a fly ash coefficient alpha fh, a predicted value 2.55% of fly ash combustible, a predicted value 4.05% of slag combustible and the like into a formula to calculate to obtainThe predicted value of (2) was 2.78%.
Step five: predicting theoretical dry air quantity
When V daf is 6.4%, K is 0.2659. The predicted value of Q ar,net was 19600kJ/kWh, the predicted value of A ad was 28.2%,The predicted value of 2.78% of the equivalent parameter value is substituted into a calculation formula of the theoretical dry air quantity to obtain/>The predicted value of (2) was 5.14m 3/kg.
Step six: prediction of theoretical dry smoke
Will beWhen 5.14m 3/kg is substituted into a calculation formula of theoretical dry smoke quantityThe predicted value of (2) was 5.04m 3/kg.
Step seven: predicting the actual dry smoke volume V gy
When the set value of α is 1.29 and the set value of A L is 5.5%, it willPredicted value of 5.14m 3/kg,/>The predicted value of V gy is calculated to be 6.93m 3/kg by substituting parameter values such as 5.04m 3/kg into a calculation formula of the actual dry smoke quantity.
Step eight: predicting vapor volume in flue gas
When the set value of alpha is 1.29, the set value of A L is 5.5%, the set value of d k is 0.01kg/kg, the predicted value of V daf is 6.4%, the predicted value of M ar is 7.2%,The predicted value of 5.14m 3/kg and other parameter values are substituted into a calculation formula of the water vapor volume in the flue gas, and the/> iscalculatedThe predicted value of (2) was 0.77m 3/kg.
Step nine: predicting heat loss q of exhausted smoke 2
The calculation formula of the smoke exhaust heat loss q 2 is as follows:
substituting the predicted temperature of the smoke exhaust theta py into a dry smoke specific heat calculation formula at 128.53 ℃ to obtain Is 1.30 kJ/(kg.K),/>Is 1.32 kJ/(kg.K),/>Is 1.74 kJ/(kg.K), and c p,gy is 1.37 kJ/(kg.K).
The set point for t 0 is 20 c,The predicted value of q 2 is calculated to be 5.88% by substituting the predicted value of 0.77m 3/kg,Qar,net with the calculated formula of the heat loss of the exhaust smoke with the parameter values of 19600kJ/kg and the like.
Step ten: predicting solid incomplete combustion heat loss q 4
Neglecting the heat loss rate of the pebble coal of the medium speed coal mill, setting the predicted value of A ad to 28.2 percent,And the predicted value of Q ar,net is 19600kJ/kg and the like are substituted into the calculation formula of the solid incomplete combustion heat loss Q 4, so that the predicted value of Q 4 is calculated to be 1.35%.
Step eleven: predicting physical heat loss q of ash 6
The calculation formula of the ash physical heat loss q 6 is as follows:
The specific heat c lz of slag in the solid-state slag-discharging pulverized coal boiler is 0.96 kJ/(kg.K), the specific heat c fh of fly ash is 0.82 kJ/(kg.K), and t lz is 800 ℃. The parameter values of the setting value of t 0, the setting value of slag coefficient alpha lz, the setting value of fly ash coefficient alpha fh, the predicted value of Q ar,net, 19600kJ/kg, the predicted value of A ad, 28.2%, the predicted value of smoke exhaust temperature theta py, the predicted value of 128.53 ℃ and the like are substituted into a calculation formula of ash physical heat loss q 6, and the predicted value of ash physical heat loss q 6 is calculated to be 0.11%.
Step twelve: predicting boiler heat dissipation loss q 5
Fitting an exponentiation equation of the power generation power variation of the random set of the heat dissipation loss q 5 of the boiler according to the boiler co-firing test data:
Substituting the set value 280MW of P qj into the exponentiation equation, and calculating to obtain the predicted value of the boiler heat dissipation loss q 5 to be 0.47%.
Step thirteen: predicting boiler efficiency eta g
The predicted value of the boiler efficiency calculated according to the prediction formula of the boiler efficiency eta g is 92.19%.
Step five: prediction of boiler coal consumption by mixed coal combustion
Step one: regression equation for determining steam turbine heat rate q
Based on the latest monitoring data of the heat rate of the steam turbine, a regression equation of the heat rate Q sr of the steam turbine is obtained:
The calculation formula of the turbine heat rate q is as follows:
q＝1000(-3.9911/Pqj+8.5782-0.0012Pqj)
Substituting the set value 280MW of P qj into a calculation formula of the steam turbine heat rate q, and calculating to obtain the predicted value of the steam turbine heat rate q to be 8228kJ/kWh.
Step two: predicting generating coal consumption b of unit f
Parameter values such as a predicted value 8228kJ/kWh of the steam turbine heat consumption rate q, a predicted value 92.19% of the boiler efficiency and the like are substituted into a calculation formula of the boiler coal consumption b f, and the predicted value of the unit power generation coal consumption b f is 307.77g/kWh.
Step three: predicting boiler coal consumption B f
Substituting the set value 280MW of P qj and the predicted value 307.77g/kWh of the unit power generation coal consumption B f into a calculation formula of the boiler coal consumption B f, and calculating to obtain the predicted value 86.18t/h of the boiler coal consumption B f.
Step six: desulfurization and denitrification cost prediction for mixed coal combustion
Step one: sulfur dioxide concentration in dry flue gas produced by combustion of mixed coalPrediction
Substituting the predicted value of the received base sulfur content Sar of 0.56% and the predicted value of V gy of 6.93m 3/kg into sulfur of 1kg of mixed coal to completely burn SO as to generate SO 2 emission concentrationCalculating to obtain the concentration/> of sulfur dioxide in the dry flue gasIs 1385.28mg/m 3.
Step two: prediction of limestone consumption C shs
Limiting the emission concentration of SO 2 in flue gasThe predicted value of V gy is 6.93m 3/kg, the predicted value 86.18t/h of the boiler coal consumption B f is substituted into the calculation formula of the consumption Cshs of the desulfurization material limestone, and the predicted value of the consumption Cshs of the desulfurization material limestone is 1.4608t/h.
Step three: prediction of desulfurization water consumption C tlhs
When the set value of the desulfurization water consumption rate is 0g/kWh, the predicted value of the desulfurization water consumption C tlhs is 0t/h.
Step four: prediction of denitration agent consumption C txj
The consumption C txj of the denitration agent liquid ammonia can obtain a regression equation of the change of the consumption C txj of the denitration agent along with the consumption B f of the coal according to historical data, namely
Substituting the predicted value 86.18t/h of the boiler coal consumption B f into a regression equation, and calculating to obtain the predicted value of the liquid ammonia consumption C txj, wherein the predicted value is 168.341kg/h.
Step five: prediction of desulfurization and denitrification cost C tltx
The calculation formula of the desulfurization and denitrification cost C tltx is as follows:
Ctltx＝66.25Cshs+3000Ctxj/1000
substituting the predicted value 1.4608t/h of the consumption Cshs of the limestone and the predicted value 168.341kg/h of the consumption C txj of the liquid ammonia into the above formula, and calculating to obtain the predicted value of the desulfurization and denitrification cost C tltx which is 601.801 yuan/h.
Step seven: power generation variable cost prediction for mixed coal combustion
Step one: regression equation for determining power consumption of power plant
And carrying out regression equation fitting of the power consumption of the power plant based on the latest power consumption monitoring data of the power plant:
And substituting the set value 280MW of P qj into a regression equation of the power consumption of the power plant, and calculating to obtain the predicted value of the power consumption of the power plant to be 10037kW.
Step two: power generation variable cost C f prediction
The set value of the online electricity price p d is 0.42 yuan/kWh, the predicted value of the electricity consumption of a power plant is 10037kW, the predicted value of the desulfurization and denitrification cost C tltx is 601.801 yuan/h, the predicted value of the boiler coal consumption B f is 86.18t/h, the parameter values of the price of a charging standard price of 910 yuan/t and the like are substituted into a calculation formula of the variable electricity generation cost C f, and the predicted value of the variable electricity generation cost C f of the mixed coal is 83241.141 yuan/h.
And substituting the predicted value of C f with 83241.141 yuan/h and the set value of P qj with 280MW into a calculation formula of the electricity generation variable cost C f, and calculating to obtain the electricity generation variable cost predicted value of 0.297 yuan/kWh.
Step eight: predictive computation result application of mixed coal combustion
The user checks the predicted value of the electricity generation variable cost and the electricity generation degree electricity variable cost, and can further modify the settings of the blending burning scheme, such as blending burning proportion, blending burning coal type, working condition parameter setting and the like. After the user saves the modified blending burning scheme, the manual triggering power generation can become the execution of the calculation program. The user can compare and analyze the blend effect prediction indexes of various blend schemes.
The system utilizes an optimal algorithm to call the boiler efficiency of mixed coal combustion and the power generation variable cost prediction calculation program when the optimizing calculation of the mixed coal blending combustion scheme is carried out, so that the scheme optimizing with the lowest power generation cost or the highest power generation efficiency based on the mixed coal blending combustion target is realized.
In summary, the method and the system for predicting the power generation variable cost by blending the mixed coal of the boiler for power generation predict the coal quality parameters and the coal price indexes of the mixed coal through various single coal quality parameters, various single coal price indexes and blending ratio data of various single coals; predicting boiler efficiency when the mixed coal burns based on the coal quality parameters of the mixed coal, predicting boiler coal consumption of the mixed coal burning based on the boiler efficiency, and predicting coal consumption cost of mixed coal blending burning based on the boiler coal consumption and the coal price index of the mixed coal; predicting desulfurization and denitrification cost of mixed coal combustion based on the consumption of the mixed coal combustion boiler and the material price index; predicting the electricity consumption cost of the mixed coal during combustion based on the electricity consumption monitoring data; the variable power generation cost in the process of mixed coal combustion is predicted based on the coal consumption cost, the desulfurization and denitrification cost and the power consumption cost, and compared with the prior art, the variable power generation cost in the process of mixed coal combustion of a boiler can be accurately predicted, and a data basis is provided for the decision of a mixed combustion scheme.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. The method for predicting the power generation variable cost of the mixed coal blending combustion of the boiler for power generation is characterized by comprising the following steps of:
acquiring various single coal quality parameters of mixed coal, coal price indexes of various single coals, blending ratio data of various single coals, material price indexes of desulfurization and denitrification and power plant power monitoring data; predicting the coal quality parameters and the coal price indexes of the mixed coal according to various single coal quality parameters, various single coal price indexes and various single coal blending ratio data;
Predicting boiler efficiency when the mixed coal burns based on the coal quality parameters of the mixed coal, predicting boiler coal consumption of the mixed coal burning based on the boiler efficiency, and predicting coal consumption cost of mixed coal blending burning based on the boiler coal consumption and the coal price index of the mixed coal; predicting desulfurization and denitrification cost of the mixed coal combustion based on the boiler coal consumption of the mixed coal combustion and the material price index; predicting the electricity consumption cost of the mixed coal during combustion based on the electricity consumption monitoring data;
predicting the variable power generation cost when the mixed coal burns based on the coal consumption cost, the desulfurization and denitrification cost and the power consumption cost;
predicting the boiler efficiency in the mixed coal combustion based on the coal quality parameters of the mixed coal, comprising the following steps:
predicting fly ash combustibles of the blended coal based on the coal quality parameters of the blended coal and the relationship between the fly ash combustibles;
predicting slag combustibles of the blended coal based on predicted fly ash combustibles of the blended coal and a relationship between the fly ash combustibles and slag combustibles;
Predicting a discharge temperature difference when the mixed coal burns based on a predicted relation between the fly ash combustibles of the mixed coal and the discharge temperature difference;
And predicting the boiler efficiency when the mixed coal burns based on the predicted slag combustibles, fly ash combustibles and discharge temperature difference.
2. The method for predicting the power generation variable cost of the mixed coal blending combustion of the boiler for power generation according to claim 1, wherein the prediction of the coal quality parameters of the mixed coal and the coal price index of the mixed coal according to various single coal quality parameters, various single coal price indexes and blending combustion proportion data of various single coals is realized by the following formulas:
Wherein Q ar,net,Qar,net,i is the mixed coal, the single coal receives the basic low-level calorific value, the unit is kJ/kg, wherein i represents the i-th single coal, i=1, 2,3,..n, n is the total number of single coals, and k i represents the blending ratio of the i-th single coal; a ad,Aad,i is the ash content of the air drying base of the mixed coal and the single coal respectively, and the unit is; m ar,Mar,i is the water content of the mixed coal and the single coal, and the unit is; v daf,Vdaf,i is the volatile component of the ash-free base of mixed coal and single coal drying, and the unit is; s ar,Sar,i is that the mixed coal and the single coal receive base sulfur respectively, and the unit is; HGI, HGI i are the coal blend, single coal grindability coefficient separately; ST i is the melting point of mixed coal and single coal ash, and the unit is the temperature; p rl,prl,i is the unit price of mixed coal and single coal in the furnace, and the unit is yuan/t.
3. The prediction method for the power generation variable cost of the mixed coal blending combustion of the boiler for power generation according to claim 2, wherein the relation between the coal quality parameter of the mixed coal and the fly ash combustible is obtained by the following steps:
Acquiring mixed coal quality data of a plurality of working conditions and corresponding fly ash combustibles from a boiler blending combustion test report, wherein the mixed coal quality data at least comprises basic low-level heating value Q ar,net, basic ash content A ad, basic water content M ar and dry ashless base volatile V daf;
Stepwise regression analysis is carried out on the coal quality data of the mixed coal under a plurality of working conditions and the corresponding fly ash combustible C fh, and a regression equation of the coal quality parameters and the fly ash combustible is fitted;
The relation between the fly ash combustible and the slag combustible of the mixed coal is obtained through the following steps:
Acquiring mixed coal quality data of a plurality of working conditions, corresponding fly ash combustibles and corresponding slag combustibles from a boiler blending combustion test report, wherein the mixed coal quality data at least comprises basic low-level heating value Q ar,net, received basic ash A ad and dry ashless basic volatile V daf;
Stepwise regression analysis is carried out on fly ash combustible materials corresponding to the coal quality data of the mixed coal under a plurality of working conditions and corresponding slag combustible materials, and a regression equation of the fly ash combustible materials and the slag combustible materials is fitted;
the relation between the fly ash combustible material of the mixed coal and the discharge temperature difference is obtained through the following steps:
Acquiring mixed coal quality data of a plurality of working conditions, corresponding fly ash combustibles, corresponding generator active power P qj and corresponding discharge temperature difference t ps from a boiler blending combustion test report, wherein the mixed coal quality data at least comprises basic low-level heating value Q ar,net, received basic ash A ad and dry ashless base volatile component V daf;
stepwise regression analysis is carried out on the coal-mixed coal quality data, the corresponding fly ash combustible, the corresponding active power P qj of the generator and the corresponding discharge temperature difference t ps under a plurality of working conditions, and a regression equation of the fly ash combustible and the discharge temperature difference t ps is fitted.
4. The method for predicting variable cost of power generation by blending and burning mixed coal for power generation according to claim 3, wherein predicting the boiler efficiency at the time of burning mixed coal based on the predicted slag combustibles, fly ash combustibles and discharge temperature difference comprises the steps of:
Based on the predicted exhaust temperature difference, the exhaust temperature of the mixed coal during combustion is predicted by the following formula:
θpy＝tps+t0
wherein, theta py is the exhaust gas temperature; t ps is the discharge temperature difference; t 0 is the atmospheric temperature of the place;
Based on the predicted fly ash combustibles and slag combustibles of the mixed coal, predicting the percentage of the average carbon content in the ash slag and the coal ash content by the following formula;
Wherein, The unit is the percentage of the average carbon content in ash slag and the coal ash content; alpha lz is the slag coefficient; alpha fh is the fly ash coefficient, C lz is the slag combustibles, C fh is the fly ash combustibles;
based on the predicted percentage of the average carbon content in the ash and the coal ash content, the theoretical dry air amount required by the mixed coal combustion is predicted by the following formula;
Wherein, Is the theoretical dry air quantity, and the unit is m 3/kg;
The calculation formula of K is as follows:
Based on the predicted theoretical dry air amount, a theoretical dry smoke amount is predicted by the following formula:
Wherein, The unit is m 3/kg which is the theoretical dry smoke quantity;
based on the predicted theoretical dry smoke amount and theoretical dry air amount, the actual dry smoke amount is predicted by the following formula:
Wherein V gy is the actual dry flue gas quantity, the unit is m 3/kg;AL is the air leakage rate of the air preheater, the unit is alpha is the excess air coefficient of the hearth;
Based on the predicted theoretical dry air amount, the volume of water vapor in the flue gas generated by the mixed coal combustion is predicted by the following formula:
Wherein, The volume of water vapor in the flue gas is m 3/kg;dk, the absolute humidity of air is kg/kg, V daf is dry ash-free volatile component,/>To the 0.2319 power of V daf;
based on the predicted exhaust gas temperature and the actual dry gas amount, predicting the exhaust gas heat loss during the combustion of the mixed coal through the following formula;
Wherein,
1.51 Is the specific heat capacity of water vapor at constant pressure, and the unit is kJ/(kg.K); the constant pressure specific heat capacity of nitrogen in the dry flue gas is given by kJ/(kg.K); /(I) The constant pressure specific heat capacity of oxygen in the dry flue gas is shown as kJ/(kg.K); /(I)The constant pressure specific heat capacity of carbon dioxide in the dry flue gas is given as kJ/(kg.K); c p,gy is the constant pressure specific heat capacity of the dry flue gas, and the unit is kJ/(kg.K);
Based on the percentage of the average carbon content in the ash and the amount of the coal ash, the solid incomplete combustion heat loss when the mixed coal is combusted is predicted by the following formula:
Wherein q 4 is the solid incomplete combustion heat loss, and the unit is;
based on the predicted fly ash combustibles, slag combustibles, and exhaust gas temperatures, the ash physical heat loss upon combustion of the coal blend is predicted by the following equation:
Wherein q 6 is physical heat loss of ash, c lz is specific heat of the ash, and the unit is kJ/(kg.K); c fh is the specific heat of the fly ash, the unit is kJ/(kg.K), and t lz is the slag temperature;
The power of the outlet end of the generator during mixed coal combustion is obtained, and the heat dissipation loss of the boiler is predicted based on the following formula:
q 4 is the heat dissipation loss of the boiler, and the unit is; j 1 is the first coefficient of the boiler heat dissipation loss regression equation; j 2 is the second coefficient of the boiler heat dissipation loss regression equation; p qj is the power of the outlet end of the generator, and the unit is MW;
Based on the predicted heat loss from the flue gas, heat loss from incomplete combustion of solids, physical heat loss from ash, and heat loss from the boiler, the boiler efficiency is predicted by the following equation:
ηg＝100-q2-q4-q5-q6
Wherein η g is the boiler efficiency.
5. The method for predicting the power generation variable cost of a mixed coal combustion of a boiler for power generation according to claim 1, wherein predicting the boiler coal consumption of the mixed coal combustion based on the boiler efficiency is obtained by the following formula:
Bf＝bfPqj/1000
Wherein k 0,k1,k2 is the first, second and third coefficients of the steam turbine heat consumption regression equation, Q sr is the steam turbine heat consumption, the unit is GJ/h, and Q is the steam turbine heat consumption rate, the unit is kJ/kWh; b f is the power generation coal consumption, and the unit is g/kWh; η gd is the pipe efficiency; r h is a thermal equivalent value; 7000 is standard coal heat, the unit is kcal, B f is boiler coal consumption, the unit is t/h, and eta g is boiler efficiency; p qj is the generator active power.
6. The method for predicting the power generation variable cost of mixed coal combustion of a boiler for power generation according to claim 1, wherein the prediction of the desulfurization and denitrification cost of the mixed coal combustion based on the boiler coal consumption of the mixed coal combustion and the material price index is calculated by the following formula:
Ctlhs＝ctlhsPqj/1000
Ctltx＝Cshspshs+Ctlhsptlhs+Ctxjptxj/1000
Wherein, The standard oxygen content flue gas SO 2 concentration generated for complete combustion of sulfur is in mg/m 3; 6 is the reference oxygen content in units of; 3.5 is the oxygen content of the dry flue gas, and the unit is; /(I)The unit of the emission concentration limit value of the atmospheric pollutants of the thermal power generation boiler is mg/m 3;wshs, the unit is the purity of limestone; 100 is the molecular weight of limestone; 64 is sulfur dioxide molecular weight; 1.02 is the limestone demand coefficient; c shs is the consumption of the desulfurization material limestone, and the unit is t/h; c tlhs is a recent statistical value of desulfurization water consumption rate, and the unit is g/kWh; c tlhs is desulfurization water consumption, t/h; r 1,r2 is the first coefficient and the second coefficient of the denitration agent consumption regression equation respectively; c txj is the consumption of the denitration agent, and the unit is kg/h; p shs is the price of limestone in yuan/t; p tlhs is the desulfurization water consumption price, and the unit is yuan/t; p txj is the price of the denitration agent, and the unit is yuan/t; c tltx is desulfurization and denitrification cost, the unit is Yuan/h, S ar is the sulfur content of the mixed coal, V gy is the actual dry flue gas amount, B f is the boiler coal consumption, and P qj is the active power of the generator.
7. The method for predicting the power generation variable cost of the mixed coal blending combustion of the boiler for generating power according to claim 1, wherein the power consumption cost when the mixed coal is combusted is predicted based on the power consumption monitoring data and is calculated by the following formula:
CD＝Pd×(t2Pqj 2+t1Pqj+t0)
Wherein, C D is the electricity consumption cost; p d is the power price of the Internet, P qj is the power of the outlet end of the generator, and the unit is MW; t 0、t1、t2 is the first, second, and third coefficients, respectively, of the fitted electricity consumption model in MW.
8. The prediction method for the power generation variable cost of the mixed coal blending combustion of the boiler for power generation according to claim 1, wherein the power generation variable cost when the mixed coal is predicted to be burned based on the coal consumption cost, the desulfurization and denitrification cost and the electricity consumption cost is calculated by the following formula:
Cf＝CD+Ctltx+Bfprl
Wherein c f is the electricity generation variable cost of the mixed coal; c f is the variable cost of power generation, and the unit is yuan/h; p rl is a coal price index of the mixed coal entering the furnace, B f is the coal consumption of the boiler, P qj is the active power of the generator, and C D is the electricity consumption cost; c tltx is the desulfurization and denitrification cost.
9. A computer system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method of any of the preceding claims 1 to 8 when the computer program is executed.
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