CN101713536A - Control method of combustion system of circulating fluidized bed boiler - Google Patents

Abstract

The invention relates to a control method of a combustion system of a circulating fluidized bed boiler, which adopts multivariable expert intelligent self-calibration PID control and is provided with an on-line calculation module for the static characteristics of the circulating fluidized bed boiler. The on-line calculation module for the static characteristics of the circulating fluidized bed boiler calculates the coal supply quantity, the limestone quantity and the deslagging quantity for realizing the optimizing combustion of the boiler under different loads, the primary air quantity and the secondary air quantity are optimized and proportioned and are used as load feedforward signals which are applied to a main steam pressure control loop, a limestone quantity control loop, a bed pressure drop control loop, a bed temperature control loop and an oxygen quantity control loop, and each control loop adopts an expert intelligent self-calibration PID controller to form a multivariable combustion control system of a CFB boiler. The invention is provided with the calculation module for the static characteristics of the circulating fluidized bed boiler, which can accurately send out each regulation quantity instruction at real time and realize automatic control; the multivariable expert system is in consideration of the nonlinearity and the strong-coupling property of the combustion system of the boiler and ensures the performance robustness of the control system; and meanwhile, the PID parameters are automatically regulated according to the change of the characteristics of a controlled object, so the automatic combustion control system of the circulating fluidized bed boiler has stable robustness.

Description

A kind of control method of combustion system of circulating fluidized bed boiler

Technical field

The present invention relates to a kind of CFBB expert intelligence from the Tuning PID Controller method, particularly be that a kind of CFBB multivariable expert intelligence based on static characteristic is from the Tuning PID Controller method.

Background technology

Combustion technology of circulating fluidized is one of clean coal combustion technology, is coal and desulfurizing agent (as lime stone) are added in the bed of combustion chamber, from the furnace bottom air blast bed is suspended and carries out fluidized bed combustion.In today that environmental protection gets most of the attention, interior cheap desulfur technology of stove and because the low NO that low-temperature burning forms that fluidized bed combustion is intrinsic _XDischarging makes CFBB become first-selected heat power equipment in the sulphur coal area.

Though recirculating fluidized bed (CFB) boiler has dropped into commercial operation in a large number, and capacity constantly increases, but have many problems in CFBB actual motion and the operating process, distinct issues are exactly the automatic control problem of combustion system of circulating fluidized bed boiler and boiler combustion efficiency is lower, serious wear and the high problem of station service.Automatically controlling the reason that is difficult to realize is because combustion system of circulating fluidized bed boiler is a large time delay, close coupling, multivariable nonlinear system, influence each other between each variable, interact, the controlled variable that has is subjected to the common influence of several adjusting parameters simultaneously, dynamic characteristic is extremely complicated, because each regulated quantity setting value is difficult to accurately provide in real time, make control automatically be difficult to realize simultaneously, in actual motion, mostly be manual adjustments; Because CFBB can be in multi-modal operation down, the operations staff is a target with safety only in operating process, can not realize the optimization proportioning of each operational ton, thereby can not realize the optimization burning and the control of CFBB.

Combustion system of circulating fluidized bed boiler mainly contains two kinds of control schemes in the prior art, the classical PID control system that a kind of DCS of being based on system makes an amendment on the basis of coal-powder boiler slightly, be multiloop control system, or the expert control system of researching and developing recently based on advanced control strategy (such as fuzzy control).

For first kind of PID control, research direction mainly contains: 1) the PI controller of band compensation, and compensating parameter is to determine according to the recursive identification model; 2) based on PID, and be aided with that pure lag compensation is estimated, strategy such as tandem and feedforward; 3), propose based on the PID of exponential function compensation and two kinds of control algolithms of PID that switching compensates based on function in conjunction with the nonlinear Control theory; 4) at the close coupling relation of load and bed temperature, the someone has proposed decoupling zero and has coordinated control algolithm and parameter time varying algorithm, but vulnerability to jamming is poor, and the applicable object face is narrow; 5) compensation decoupling and controlling system; 6) main steam temperature adopts control that state variable control and conventional PID combine etc.

For above-mentioned second kind of advanced control, research direction mainly contains: 1) dynamic decoupling self-correcting predictive algorithm, tentatively solve the multiple-input and multiple-output and the delay issue of CFB boiler combustion system, but the control effect is undesirable; 2) Smith prediction model reference adaptive decoupling and controlling system; Only be used in the CFB Boiler Steam Temperature Control object; 3) Active Disturbance Rejection Control (ADRC) theory, studies show that, uncertain at model, under variable working condition and the variable close coupling situation, ADRC control has better decoupling zero control performance, anti-interference and robustness, but the stability problem of ADRC closed-loop control system only is verified in emulation experiment, lacks strict theoretical foundation as guidance, simultaneously, the ADRC parameter tuning under the high-order extended state observer ESO still need improve; 4) Henderson and Mann propose CFB boiler expert control system first, carry out process and monitoring of tools, trend analysis and false data identification with expert system, utilize expertise and experience to determine the setting value in each loop, certain effect has been played in the coupling that reduces between variable; 5) fuzzy control and Fuzzy Adaptive PID Control are to be the based computer Based Intelligent Control with fuzzy set theory, fuzzy language variable and fuzzy logic inference.

Present existing CFB boiler control technology mainly is that the coupling phenomenon at main steam pressure and bed temperature has launched research, fully the characteristics of the multi-variable system of CFB boiler are not reflected, also not each regulated quantity setting value do not determined to carry out system, comprehensively research, operation from present CFBB, in these control systems, the automatic devoting rate of main steam pressure and bed temperature is not high, even very low, most of boiler user manual operation.

Combustion system of circulating fluidized bed boiler is a multiple-input and multiple-output, close coupling, nonlinear therrmodynamic system, wherein, interactional regulated variable has: main steam pressure, bed temperature, oxygen content, the bed pressure drop, interactional regulated quantity has: fuel quantity, primary air flow, secondary air flow, bed drain purge and lime stone amount, especially main steam pressure and bed temperature seriously are coupled, be difficult to go to describe its dynamic characteristic with precise math model, therefore solve very difficulty of its automatic control problem with conventional control theory, some advanced control technologys are then to having uncertainty models, research object highly non-linear and that complex task requires can obtain ideal control effect.

All there is certain difference in the CFBB of different boiler manufacturer production at aspects such as structure, performance characteristics and regulating measures, makes the operation mode difference of boiler.When structure control scheme, the boiler design parameter should be incorporated into, just can make the control scheme have more specific aim; CFBB is being given coal particle size and coal changes and under different load, and the tissue of the flowing of Dual-Phrase Distribution of Gas olid body, burning and conducting heat all can change in its stove, and the proportioning of corresponding first and second air quantity also can change; When the bed change in pressure drop, variation has taken place in the nowed forming in the CFBB, thereby the tissue of stove internal combustion, heat transfer is changed, regulated quantitys such as fuel quantity, first and second air quantity all can change, so have influence on some principal elements that each regulated quantity setting value is determined, when structure control scheme, must take in.

Fuel quantity, primary air flow, secondary air flow, lime stone amount and bed drain purge are five important regulated quantitys of CFB boiler combustion system, when boiler load changes, to provide five regulated quantity setting values optimizing proportioning according to the boiler combustion state, realize that the optimization burning of CFB boiler is regulated.For existing CFB boiler of being on active service, though when boiler startup is debugged, the commissioning staff has provided the variation relation of fuel quantity B with load R: B _Given=f (R) has also provided primary air flow and the secondary air flow relation with load R: Q _{1 is given}=f (R), Q _{2 is given}=f (R), load instruction and fuel quantity curve that these functions obtain by field trial, the load instruction is determined with the secondary air flow curve with primary air flow curve and load instruction, but these curves are at test coal and the specific coal particle size of giving thereof, after changing for coal particle size and coal, variation has taken place in burning of coal rate and calorific value, variation has also taken place in the dispensing curve of primary air flow and secondary air flow, although the unit that has is aided with the variation that coal is considered in calorific value correction or main steam pressure correction, but can only adjusting coal-supplying amount, the correction of coal supply calorific value can not optimize one of burning according to ature of coal that changes and size distribution proportioning realization correctly thereof, secondary air flow, can not in time provide each regulated quantity setting value, limited the varying duty speed of CFB unit greatly, simultaneously, do not consider the lime stone composition yet, the bed pressure drop, desulfuration efficiency and exhaust gas temperature are to coal-supplying amount, primary air flow, secondary air flow, the lime stone amount, the influence of regulated quantitys such as bed drain purge setting value.

Summary of the invention

At the deficiencies in the prior art and defective, the purpose of this invention is to provide a kind of CFBB multivariable expert intelligence based on static characteristic from the Tuning PID Controller method.

The present invention is achieved through the following technical solutions:

In the CFB boiler control system, the online computing module of CFB boiler static characteristic is set, this module is by gathering the boiler load instruction, gather operation coal and size distribution thereof, the lime stone composition, bed pressure drop and exhaust gas temperature etc., according to boiler structure and performance design parameter, in conjunction with the Under Variable Conditions of Steam Turbine principle, adopt the CFBB energy balance, material balance and charcoal amount equilibrium principle, calculating provides the coal-supplying amount that can guarantee the boiler optimization burning, lime stone amount and bed drain purge, and the required primary air flow of optimization proportioning, secondary air flow, they are applied to the main steam pressure control loop as the load feed-forward signal respectively, lime stone amount control loop, the bed temperature control loop, oxygen amount control loop and bed pressure drop control loop, so that follow load disturbance fast, improve the load adaptability of CFBB; Each control loop adopts expert intelligence from the Tuning PID Controller device, constitutes CFBB multivariable expert intelligence from the Tuning PID Controller system.When closed-loop system was disturbed, the characteristic parameter identifier was discerned each broad sense controlled device $y=\left[\begin{array}{c}{p}_0\\ T_b\\ O_2\\ p_l\\ {\mathrm{SO}}_2\end{array}\right]$ A plurality of characteristic parameters of systematic error e: dynamic overshooting amount σ _i, regulate time t _sWith rise time t _r, at comparator, these parameters and each characteristic of correspondence pre-set parameter being compared, the multivariable expert system is sent in its bias, and expert system is online to be inferred by eliminating the due correction amount delta K of each each parameter of bias PID controller _Pi, Δ K _IiWith Δ K _Di, finish real-time online from adjusting each PID controller parameter, PID controller output control signal $u=\left[\begin{array}{c}B\\ Q_1\\ Q_2\\ G_{\mathrm{pz}}\\ B_{\mathrm{lime}}\end{array}\right],$ Control to each broad sense controlled device, till the characteristic parameter of the response curve of controlled process reaches setting value.

A kind of control method of adjusting PID certainly provided by the invention based on the CFBB multivariable expert intelligence of static characteristic, in this control technology scheme, can accurately provide each regulated quantity instruction in real time, and non-linear, the close coupling of consideration CFB boiler combustion system, realized that the burning of CFB boiler is controlled automatically.

CFBB multivariable expert intelligence of the present invention is from adjusting the PID combustion control system as shown in Figure 1, in this control system, form five closed loop inner loopings by conventional PI controller and controlled device, the closed loop external loop is by the characteristic parameter identifier, comparator, the multivariable expert system, conventional PID controller and multivariable broad sense controlled device are formed, in external loop, conventional PID controller and broad sense controlled device become controlled device, the characteristic parameter identifier is a measurement mechanism, expert system then is a controller, and the decoupling zero between each loop is finished in expert system.

Compared with prior art, the substantive distinguishing features that the present invention gives prominence to also is: owing to be provided with the online computing module of CFBB static characteristic, can provide the setting value of each regulated quantity of CFBB real-time and accurately, and quick and precisely follow load variations; Each regulating loop adopts expert intelligence from the Tuning PID Controller device, its need not accurately identification controlled device Mathematical Modeling, can solve the control of Complex Nonlinear System again, adjust, proofread and correct, optimize the PID controller parameter with methods such as the pattern-recognition in the artificial intelligence, reasonings, finish the On-line Control task simultaneously, intelligent controller have from adjust, from comprehensive and monitor three kinds of running statuses, change the automatic adjusting pid parameter from adjusting according to plant characteristic, make control system have stability robustness; Performance robustness from comprehensive assurance control system; Monitor state is guaranteed the control system safe and reliable operation; The multivariable expert system can be by means such as identification, emulation, and measures such as employing self-correcting feedforward decoupling zero are carried out decoupling zero control to the multi-variable system of this close coupling of CFBB.

Description of drawings

Fig. 1 is that multivariable expert intelligence of the present invention is from the Tuning PID Controller system

Fig. 2 is the static characteristic computing module of multivariable expert intelligence of the present invention in the Tuning PID Controller system

The specific embodiment

Below in conjunction with accompanying drawing the specific embodiment of the present invention is made detailed description

Embodiment 1

As described in Fig. 1 and 2, a kind of control method of combustion system of circulating fluidized bed boiler comprises online computing module of boiler static characteristic and multivariable expert intelligence from the Tuning PID Controller system, and the concrete grammar of this control is as follows:

At first, the online computing module of CFBB static characteristic is set, calculates and provide coal-supplying amount, lime stone amount and the bed drain purge that can guarantee the burning of CFB boiler optimization under the different load, and optimize required primary air flow and the secondary air flow of proportioning; They are applied to main steam pressure control loop, lime stone amount regulating loop, bed pressure drop control loop, bed temperature control loop and oxygen amount control loop as the load feed-forward signal respectively;

Secondly, adopt expert intelligence from the Tuning PID Controller device each control loop, constitute a kind of recirculating fluidized bed (CFB) boiler multivariable expert intelligence from the Tuning PID Controller system based on static characteristic.

In implementing technique scheme of the present invention, the online computing module of its static characteristic is to instruct according to unit load, by gathering operation coal and size distribution thereof, lime stone composition, bed pressure drop and exhaust gas temperature, in conjunction with CFB boiler structure and performance design parameter, adopt CFB boiler energy balance, material balance and charcoal amount equilibrium principle to calculate.The equilibrium equation group is as follows:

Energy-balance equation:

[B(1-q ₄)(Q _dy+V _kI _k-V _yI _y)-G _pzc _pzT _pz-B _lim?estone·1830]φ＝Q ₁ (1)

Material balance equation:

$B(C_g+A_{\mathrm{ar}})+2.5{\mathrm{BS}}_{\mathrm{ar}}{\mathrm{\η}}_{{\mathrm{so}}_2}+0.56B_{\mathrm{lim\; estone}}-G_{\mathrm{pz}}-R_c-B(1-q_4)V_y\mathrm{\ρ}(1-\mathrm{\η})=0---\left(2\right)$

Carbonaceous amount equilibrium equation:

BC _g-R _c-G _pzC _pz-B(1-q ₄)V _yρ(1-η)C _fh＝0 (3)

In the following formula, each symbol implication is as follows:

B, B _{Lim estone}, G _Pz, R _c-be respectively the combustion rate of fuel quantity, lime stone amount, bed drain purge and coke;

Q _Dy, C _g, A _Ar, S _Ar-be respectively the low heat valve of fuel, fixed carbon, ash and the sulphur of as fired basis;

V _k, V _y, I _k, I _y-be respectively air capacity and exhaust gas volumn (Nm ³/ kg coal), air enthalpy and flue gas enthalpy (kJ/kg);

φ, Q ₁-boiler is protected hot coefficient and is effectively utilized heat;

C _Pz, C _Fh, q ₄-deslagging carbon content, carbon content of fly ash, mechanical imperfect combustion loss;

ρ, η-furnace outlet material carrying rate, separator total efficiency of separation;

c _Pz-desulfuration efficiency, deslagging specific heat capacity.

In implementing technique scheme of the present invention, the boiler in the equilibrium equation group effectively utilizes heat Q ₁Determine as follows:

According to the design parameter of CFB boiler ECR operating mode, as superheater outlet pressure p _Gr, superheater outlet steam temperature t _Gr, specified main steam flow D _Gr, drum operating pressure p _b, heat flow D again _Zr, reheater outlet pressure p _Zr2, reheater inlet pressure p _Zr1, reheater inlet steam temperature t _Zr1, feed pressure p _Gs, feed temperature t _Gs, boiler maximum continuous rating D _{Gr, max}With steam turbine initial steam pressure p ₀Deng, be boiler 100% load (R=100%) operating mode with the ECR operating mode, employing Under Variable Conditions of Steam Turbine principle calculates each flow, the pressure and temperature under the boiler different load, calculates boiler by (4) formula and effectively utilizes heat Q ₁:

Q ₁＝D _gr(h″ _gr-h _gs)+D _zr(h″ _zr-h′ _zr)+D _pw(h _pw-h _gs) (4)

In the following formula, D _Gr, D _Zr, D _PwBe respectively the flow of superheated steam, reheated steam, sewer, kg/h;

H " _Gr, h _GsBe respectively the enthalpy of superheater outlet steam and boiler feedwater, kJ/kg;

H " _Zr, h ' _ZrBe respectively reheater entry and exit steam enthalpy, kJ/kg;

h _PwBe the enthalpy of sewer, kJ/kg.

In implementing technique scheme of the present invention, related coal supply size distribution mainly is to describe with two parameters in the online computing module of its static characteristic: coal supply particle mean size d ₀With particle diameter d _pThe mass percent that the coal of＜0.5mm is shared; Deslagging carbon content C in its equilibrium equation group _PzWith bed pressure drop p _l, feeding granularity is relevant, can be expressed as:

C _pz＝k _dc·f(p _l) (5)

Its $f\left(p_l\right)={(0.6+\frac{p_{l0}-p_l}{5000})}^{0.5}/200$ p _l0＝16000-20000 (6)

Its k _DcBe emulsion zone coke average grain diameter d _C1To the influence coefficient of deslagging carbon content, can be expressed as:

$k_{\mathrm{dc}}=0.25041{\stackrel{\‾}{d}}_{c1}^2-0.0011469{\stackrel{\‾}{d}}_{c1}+0.00058741---\left(7\right)$

The average grain diameter d of coke behind the primary fragmentation _c: (d _c) ³=(d ₀) ³/ n ₁(8)

In the formula (8), n ₁Be the primary fragmentation constant, relevant with fuel characteristic.

Coke behind the primary fragmentation is divided into two parts: particle diameter d _CiThe coke of＜0.5mm burns in upper furnace, its average grain diameter d _C2=(0.5/2) mm, quality share x _C2Coke average grain diameter in the emulsion zone burning is d _C1, the quality share is 1-x _C2, the average grain diameter d of the coke of emulsion zone then _C1Following calculating:

$\frac{1}{{\stackrel{\‾}{d}}_c}=\frac{1-x_{c2}}{{\stackrel{\‾}{d}}_{c1}}+\frac{x_{c2}}{{\stackrel{\‾}{d}}_{c2}}---\left(9\right)$

d _C2Mass percent, be calculated as follows:

(x _c2) ³＝(x _i，0.25) ³·n ₁ (10)

In implementing technique scheme of the present invention, carbon content of fly ash can followingly calculate in the equilibrium equation group:

$C_{\mathrm{fh}}=\frac{e^{-\mathrm{Rav}\·V_{\mathrm{daf}}\·H_l^{1.3}/\left(100(T_b+273.15)\right)}}{6}\·\frac{10000}{p_l}---\left(11\right)$

In the following formula, R _AvActivity for fuel; H _lBe furnace height, m; T _bBe bed temperature, ℃.

In implementing technique scheme of the present invention, the relation of furnace outlet material carrying rate and unit load R can be expressed as follows in the equilibrium equation group:

ρ＝2.7943R ²-0.45375R+0.40775 R＝0～1.2 (12)

CFBB separator gross efficiency η can be expressed as follows in the equilibrium equation group:

$\mathrm{\η}={\mathrm{\η}}_0-e^{-a_1\·u^m}---\left(13\right)$

Wherein, η ₀=-0.0005d ₉₉+ 1.04 (14)

$a_1=k\·a_{1,d_{50}=30},$ $a_{1,d_{50}=30}=1.2556---\left(15\right)$

$k=3.05E-5\·d_{50}^2-0.007485\·d_{50}+1.1971---\left(16\right)$

$m=0.00024305\·d_{50}^2+0.018683\·d_{50}+0.58676---\left(17\right)$

Primary air flow Q ₁Can be expressed as follows with the functional relation of load, coal:

$Q_1=\left\{\begin{array}{cc}(1-k_{V_{\mathrm{daf}}})P_1^0{Q}_1^0& R\≤50\%\\ (1-k_{V_{\mathrm{daf}}})(0.44+0.56R)Q_1^0& R\≥50\%\end{array}\right.---\left(18\right)$

Wherein, $k_{V_{\mathrm{daf}}}=\left\{\begin{array}{cc}0.0125V_{\mathrm{daf}}+0.688& V_{\mathrm{daf}}\&GreaterEqual;24\\ 1.0& V_{\mathrm{daf}}<24\end{array}\right.---\left(19\right)$

Q ₁Be the rated condition flow of wind next time, P ₁ ⁰Value be taken as 72%, V _DafBe fuel combustible basis volatile matter.

In implementing the above-mentioned technology case of the present invention case, secondary air flow Q ₂Can be expressed as follows with the functional relation of load, coal:

$Q_2=\left\{\begin{array}{cc}{P}_2^0\&CenterDot;k_{V_{\mathrm{daf}}}\&CenterDot;Q_2^0& R\&le;50\%\\ (-0.7+1.7R)\&CenterDot;k_{V_{\mathrm{daf}}}\&CenterDot;Q_2^0& R\&GreaterEqual;50\%\end{array}\right.---\left(20\right)$

Wherein, Q ₂Be the flow of secondary wind under the rated condition, P ₂ ⁰Value be taken as 15%.

In implementing technique scheme of the present invention, main steam pressure, bed temperature, oxygen amount, bed pressure drop and SO ₂Content is five regulated variables, and coal-supplying amount, primary air flow, secondary air flow, bed drain purge and lime stone amount are five regulated quantitys, and they influence each other, and are interrelated, constitutes CFB boiler multivariable control system.In the multivariable expert system, adopt the correction amount delta K of each parameter of controller of five main control loops of multivariable self-correcting feedforward decoupling zero measure online self-tuning _Pi, Δ K _IiWith

On the basis of the control method of above-mentioned a kind of combustion system of circulating fluidized bed boiler, those skilled in the art can obtain the combination of corresponding system software and software, and can realize that a kind of CFBB multivariable expert intelligence based on static characteristic is from the Tuning PID Controller method, other technology contents that relates in this manual and technical term should be understood and realization with passing through with technological means according to the common practise of this area, also can implement by rational analysis ratiocination method.

Claims (9)

1. the control method of a combustion system of circulating fluidized bed boiler, comprise that recirculating fluidized bed (CFB) online computing module of boiler static characteristic and multivariable expert intelligence are from adjusting the PID combustion control system, its method is that the online computing module of CFB boiler static characteristic is set, calculating provides the coal-supplying amount of CFB boiler optimization burning under the different load, lime stone amount and bed drain purge, and optimize proportioning primary air flow and secondary air flow, again it is applied to the main steam pressure control loop as the load feed-forward signal, lime stone amount control loop, bed pressure drop control loop, bed temperature control loop and oxygen amount control loop; Secondly, each control loop adopts expert intelligence from the Tuning PID Controller device, constitutes CFBB multivariable expert intelligence from adjusting the PID combustion control system.

2. the control method of a kind of combustion system of circulating fluidized bed boiler as claimed in claim 1, when when closed-loop system is disturbed, the characteristic parameter identifier is discerned each broad sense controlled device $y=\left[\begin{array}{c}{p}_0\\ T_b\\ O_2\\ p_l\\ {\mathrm{SO}}_2\end{array}\right]$ A plurality of characteristic parameters of systematic error e: dynamic overshooting amount σ _i, regulate time t _sWith rise time t _r, at comparator, these parameters and each characteristic of correspondence pre-set parameter being compared, the multivariable expert system is sent in its bias, and expert system is online to be inferred by eliminating the due correction amount delta K of each each parameter of bias PID controller _Pi, Δ K _IiWith Δ K _Di, finish real-time online from adjusting each PID controller parameter, PID controller output control signal $u=\left[\begin{array}{c}B\\ Q_1\\ Q_2\\ G_{\mathrm{pz}}\\ B_{\mathrm{lime}}\end{array}\right],$ Control to each broad sense controlled device, till the characteristic parameter of the response curve of controlled process reaches setting value.

3. the control method of a kind of combustion system of circulating fluidized bed boiler as claimed in claim 1, the online computing module of its static characteristic is to instruct according to unit load, by gathering operation coal and size distribution thereof, lime stone composition, bed pressure drop and exhaust gas temperature, in conjunction with CFB boiler structure and performance design parameter, adopt CFB boiler energy balance, material balance and charcoal amount equilibrium principle to calculate, the equilibrium equation group is as follows:

Energy-balance equation:

[B(1-q ₄)(Q _dy+V _kI _k-V _yI _y)-G _pzc _pzT _pz-B _limestone·1830]φ＝Q ₁ (1)

Material balance equation:

$B(C_g+A_{\mathrm{ar}})+2.5{\mathrm{BS}}_{\mathrm{ar}}{\mathrm{\&eta;}}_{{\mathrm{so}}_2}+0.56B_{\mathrm{limestone}}-G_{\mathrm{pz}}-R_c-B(1-q_4)V_y\mathrm{\&rho;}(1-\mathrm{\&eta;})=0---\left(2\right)$

Carbonaceous amount equilibrium equation:

BC _g-R _c-G _pzC _pz-B(1-q ₄)V _yρ(1-η)C _fh＝0 (3)

In the following formula, each symbol implication is as follows:

B, B _Limestone, G _Pz, R _c-be respectively the combustion rate of fuel quantity, lime stone amount, bed drain purge and coke;

Q _Dy, C _g, A _Ar, S _Ar-be respectively the low heat valve of fuel, fixed carbon, ash and the sulphur of as fired basis;

V _k, V _y, I _k, I _y-be respectively air capacity and exhaust gas volumn (Nm ³/ kg coal), air enthalpy and flue gas enthalpy (kJ/kg);

φ, Q ₁-boiler is protected hot coefficient and is effectively utilized heat;

C _Pz, C _Fh, q ₄-deslagging carbon content, carbon content of fly ash, mechanical imperfect combustion loss;

ρ, η-furnace outlet material carrying rate, separator total efficiency of separation;

, c _Pz-desulfuration efficiency, deslagging specific heat capacity.

4. the control method of a kind of combustion system of circulating fluidized bed boiler as claimed in claim 3, the coal supply size distribution in the online computing module of its static characteristic is to describe with two parameters: coal supply particle mean size d ₀With particle diameter d _pThe mass percent that the coal of＜0.5mm is shared.

5. the control method of a kind of combustion system of circulating fluidized bed boiler as claimed in claim 3, the deslagging carbon content C in its equilibrium equation group _PzWith bed pressure drop p _l, feeding granularity is relevant, can be expressed as:

C _pz＝k _dc·f(p _l) (4)

Its kdc is emulsion zone coke average grain diameter d _C1To the influence coefficient of deslagging carbon content, can be expressed as:

$k_{\mathrm{dc}}=0.25041{\stackrel{\&OverBar;}{d}}_{c1}^2-0.0011469{\stackrel{\&OverBar;}{d}}_{c1}+0.00058741---\left(5\right)$

6. the control method of a kind of combustion system of circulating fluidized bed boiler as claimed in claim 3, the relation of furnace outlet material carrying rate and unit load R can be expressed as follows in its equilibrium equation group:

ρ＝2.7943R ²-0.45375R+0.40775 R＝0～1.2 (6)

7. the control method of a kind of combustion system of circulating fluidized bed boiler as claimed in claim 3, CFBB separator gross efficiency η can be expressed as follows in its equilibrium equation group:

$\mathrm{\&eta;}={\mathrm{\&eta;}}_0-e^{-a_1\&CenterDot;u^m}---\left(7\right)$

Wherein, η ₀=-0.0005d ₉₉+ 1.04 (8)

$a_1=k\&CenterDot;a_{1,d_{50}=30},a_{1,d_{50}=30}=1.2556---\left(9\right)$

$k=3.05E-5\&CenterDot;d_{50}^2-0.007485\&CenterDot;d_{50}+1.1971---\left(10\right)$

$m=0.00024305\&CenterDot;d_{50}^2+0.018683\&CenterDot;d_{50}+0.58676---\left(11\right)$

8. the control method of a kind of combustion system of circulating fluidized bed boiler as claimed in claim 1, its primary air flow Q ₁Can be expressed as follows with the functional relation of load, coal:

$Q_1=\left\{\begin{array}{cc}(1-k_{V_{\mathrm{daf}}})P_1^0{Q}_1^0& R\&le;50\%\\ (1-k_{V_{\mathrm{daf}}})(0.44+0.56R)Q_1^0& R\&GreaterEqual;50\%\end{array}\right.---\left(12\right)$

Wherein, $k_{V_{\mathrm{daf}}}=\left\{\begin{array}{cc}0.0125V_{\mathrm{daf}}+0.688& V_{\mathrm{daf}}\&GreaterEqual;24\\ 1.0& V_{\mathrm{daf}}<24\end{array}\right.---\left(13\right)$

Q ₁ ⁰Be the rated condition flow of wind next time, P ₁ ⁰Value be taken as 72%, V _DafBe fuel combustible basis volatile matter.

9. the control method of a kind of combustion system of circulating fluidized bed boiler as claimed in claim 1, its secondary air flow Q ₂Can be expressed as follows with the functional relation of load, coal:

$Q_2=\left\{\begin{array}{cc}{P}_2^0\&CenterDot;k_{V_{\mathrm{daf}}}\&CenterDot;Q_2^0& R\&le;50\%\\ (-0.7+1.7R)\&CenterDot;k_{V_{\mathrm{daf}}}\&CenterDot;Q_2^0& R\&GreaterEqual;50\%\end{array}\right.---\left(14\right)$

Wherein, Q ₂Be the flow of secondary wind under the rated condition, P ₂ ⁰Value be taken as 15%.

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