CN102401371B - Reheated gas temperature optimization control method based on multi-variable predictive control - Google Patents

Abstract

The invention discloses a reheated gas temperature optimization control method based on multi-variable predictive control. According to the method, the whole hot steam temperature system is regarded as a two-in one-out multi-variable object, and the flow rate of reheated de-superheating jet water and the opening of a flue gas baffle plate are simultaneously controlled by adopting a multi-variable predictive control method; moreover, optimization of economical efficiency of the system is realized by adding a steady state target value of the opening of a reheated de-superheating jet water adjusting valve into optimization indexes of the conventional predictive control. By adopting the multi-variable predictive control method, coordination of side adjustment of flue gas and side adjustment of steam can be better realized, and the dynamic adjusting quality of the reheated steam temperature is further improved; and meanwhile, by adding the steady state target value of the de-superheating water adjusting valve into the conventional predictive control performance indexes, optimization of the de-superheating water jet quantity is realized, so that the circulating efficiency of a unit can be effectively improved.

Description

A kind of reheat steam temperature optimal control method based on multivariable prediction control

Technical field

The invention belongs to thermal technology's automation field, relate in particular to a kind of optimal control method of reheat steam temperature system.

Background technology

Reheat steam temperature is to need one of procedure parameter of key monitoring in thermal power unit operation process, and it is directly connected to security and the economy of unit operation.

But reheat steam temperature system is also one of system of more difficult control simultaneously.Main cause has 3 points: the one, no matter adopt steam side or fume side regulating measure, and reheat steam temperature all has significantly delays greatly characteristic; Secondly, consider that controllability and the control accuracy of fume side baffle plate (or burner pivot angle) adjusting is poor, generally adopt steam side water spray to regulate as auxiliary adjustment means simultaneously.How two kinds of regulative modes carry out work in phase, are problems.The 3rd, adopt spray desuperheating mode to regulate reheat steam temperature, can increase specific steam consumption, reduce unit cycle efficieny, therefore how in the situation that guaranteeing dynamic adjustments performance, reduce hot water spray amount more as far as possible, be also a difficult point.

Adopt at present conventionally two independently PID controller realize respectively fume side and steam tempering, many Switching Logic Control of Reheat Steam Temperature schemes based on Advanced Control Strategies such as single argument PREDICTIVE CONTROL, state variable controls, have only considered spray desuperheating mode in addition.These methods or the controller parameter difficulty of adjusting, more difficultly realizes that fume side regulates and the coordination of steam tempering; Do not consider the economy optimization problem of reheat steam temperature system.

Summary of the invention

Goal of the invention: for the problem and shortage of above-mentioned existing existence, this provides one can solve reheat steam temperature to regulate dynamic deviation, static deviation large, and injection flow rate is difficult to optimize, affect the reheat steam temperature optimal control method based on multivariable prediction control of the problems such as unit cycle efficieny.

Technical scheme: for achieving the above object, the present invention is by the following technical solutions: a kind of reheat steam temperature optimal control method based on multivariable prediction control, adopt multivariable predicting control method to control reheat steam temperature system, when this multivariable predicting control method comprises hot desuperheat spray flow and two variablees of gas baffle aperture again, by introducing again the steady-state target value of hot desuperheat water spray pitch aperture, realize the optimization to system economy, described multivariable predicting control method concrete steps are as follows:

1) obtain the step response model of reheat steam temperature object, under steady state condition, carry out reheat steam temperature open loop step response test take gas baffle aperture and desuperheating water pitch as input respectively, after filtering, the coefficient that obtains respectively both step response models is with wherein, N ₁and N ₂be respectively the time length of field of two step response models, N ₁and N ₂selection should guarantee to make the response of reheat steam temperature to approach steady-state value;

2) controller relevant parameter is set, comprises sampling time T _s, prediction step number P, fume side baffle controls step number M ₁, desuperheating water pitch control step number M ₂, output error weight matrix Q, control matrix R, control inputs error weight matrix S, T _scan use empirical rule T ₉₅/ T _s=5～15 choose, wherein, and T ₉₅for transient process rises to for 95% adjusting time; General P elects the rise time that equals reheat steam temperature step response as; M ₁and M ₂select 1 or 2; Q=diag (q ₁..., q _p), $R=\mathrm{diag}(r_1,...,r_{M_1+M_2}),S=\mathrm{diag}(S_1,...,S_{M_1+M_2});$

After controller parameter is determined, adopt the described forecast model of formula (1) to predict following reheat steam temperature system output: ${\tilde{y}}_{\mathrm{PM}}\left(k\right)={\tilde{y}}_{P0}\left(k\right)+{\mathrm{A\ΔU}}_M\left(k\right)---\left(1\right)$

Wherein, ${\tilde{y}}_{\mathrm{PM}}\left(k\right)=\left[\begin{array}{c}\tilde{y}(k+1|k)\\ .\\ .\\ .\\ \tilde{y}(k+P|k)\end{array}\right],{\tilde{y}}_{P0}\left(k\right)=\left[\begin{array}{c}{\tilde{y}}_0(k+1|k)\\ .\\ .\\ .\\ {\tilde{y}}_0(k+P|k)\end{array}\right],\tilde{y}(k+i|k),i=1,...,P$ Be illustrated in the predicted value of the reheat steam temperature of k moment to the following k+i moment, be illustrated in the initial value of the reheat steam temperature prediction of k moment to the following k+i moment;

A=[A ₁a ₂], wherein,

ΔU _M(k)＝[Δu ₁(k|k)…Δu ₁(k+M ₁-1|k) Δu ₂(k|k)…Δu ₂(k+M ₂-1|k)] ^T，

Wherein Δ u ₁(k+i|k), i=0 ..., M ₁-1, Δ u ₂(k+i|k), i=0, _..., M ₂-1 is illustrated respectively in the gas baffle aperture of k moment to the following k+i moment and the estimated value of desuperheating water pitch controlled quentity controlled variable increment;

For expressing conveniently, use y _irepresent represent to utilize the predicted value of forecast model to following P sampling instant reheat steam temperature;

3) controller state initializes, and, under certain steady state condition, detects current time reheat steam temperature measured value y (k), and makes y ₀=y _i=y (k), i=1 ..., P, wherein, y ₀for utilizing the predicted value of forecast model to current time reheat steam temperature;

4) calculate reheat steam temperature prediction deviation e=y (k)-y ₀;

5) carry out feedback compensation, y _i+ h _ie → y _i, i=1 ..., P, wherein, h _ifor correction coefficient, be taken as 1;

6) calculate gas baffle controlled quentity controlled variable increment Delta u ₁and desuperheating water pitch controlled quentity controlled variable increment Delta u (k) ₂(k), getting performance index function is formula:

$J\left(k\right)={\left|\right|w_P\left(k\right)-{\tilde{y}}_{\mathrm{PM}}\left(k\right)\left|\right|}_Q^2+{\left|\right|{\mathrm{\ΔU}}_M\left(k\right)\left|\right|}_R^2+{\left|\right|U_M\left(k\right)-U_0\left|\right|}_S^2---\left(2\right)$

Wherein, w _p(k)=[w (k+1) ... w (k+P)] ^tfor the reference target value vector of following reheat steam temperature, U ₀for the steady-state target value vector of control inputs, U _m(k)=U _m(k-1)+T Δ U _m(k), T=diag (T ₁, T ₂),

By in forecast model formula (2) substitution formula (1), and by extreme value necessary condition try to achieve:

${\mathrm{\ΔU}}_M\left(k\right)={(A^T\mathrm{QA}+R+T^T\mathrm{ST})}^{-1}[A^{T}Q(w_P\left(k\right)-{\tilde{y}}_{P0}\left(k\right))+T^{T}S(U_0-U_M(k-1))]---\left(3\right)$

So, $\mathrm{\ΔU}\left(k\right)={\left[\begin{array}{cc}{\mathrm{\Δu}}_1\left(k\right)& {\mathrm{\Δu}}_2\left(k\right)\end{array}\right]}^T=d_1(w_P\left(k\right)-{\tilde{y}}_{P0}\left(k\right))+d_2(U_0-U_M(k-1))---\left(4\right)$

Wherein, d ₁=L (A ^tqA+R+T ^tsT) ^-1a ^tq, L=diag (θ ₁θ ₂),

${\mathrm{\θ}}_i={\left[\begin{array}{cccc}1& 0& ...& 0\end{array}\right]}_{1\×M_i},i=\mathrm{1,2},$

d ₂＝L(A ^TQA+R+T ^TST) ^-1T ^TS，

7) calculate gas baffle controlled quentity controlled variable u ₁(k)=u ₁(k-1)+Δ u ₁, and desuperheating water pitch controlled quentity controlled variable u (k) ₂(k)=u ₂(k-1)+Δ u ₂(k);

8) if u _i(k) >u _max, make so u _i(k)=u _max, Δ u _i(k)=u _max-u _i(k-1), i=1,2;

If u _i(k) <u _min, make so u _i(k)=u _min, Δ u _i(k)=u _min-u _i(k-1), i=1,2; Wherein, u _maxand u _minbe respectively higher limit and the lower limit of controlled quentity controlled variable;

9) output u ₁and u (k) ₂(k), calculate and upgrade reheat steam temperature prediction of output value: y ₁→ y ₀, y _i+ a _1iΔ u ₁(k)+a _2iΔ u ₂(k) → y _i, i=1 ..., P, then, within each sampling period, repeats the 4th) and step to the 9) step.

The present invention enters as one two the Multivariable singly going out using reheat steam temperature entire system, adopt multivariable prediction control technology, control gas baffle (or burner pivot angle) and injection flow rate simultaneously, that can tackle preferably on the one hand reheat steam temperature object delays greatly characteristic, can also realize preferably on the other hand the coordination of two kinds; In addition, by add the steady-state target value of desuperheating water pitch in PREDICTIVE CONTROL performance indications, can effectively reduce desuperheat injection flow rate, thereby realize the optimization to reheat steam temperature system economy.

Beneficial effect: compared with prior art, the present invention has the following advantages: by adopting multivariable predicting control method, can realize better the coordination of fume side adjusting and steam tempering, further improve the dynamic adjustments quality of reheat steam temperature; By add the steady-state target value of desuperheating water pitch in conventional PREDICTIVE CONTROL performance indications, realize the optimization to desuperheat injection flow rate simultaneously, thereby can effectively improve the cycle efficieny of unit.

Accompanying drawing explanation

Fig. 1 is reheat steam temperature Optimal Control System schematic diagram of the present invention;

Fig. 2 is the reheat steam temperature optimal control design sketch in the specific embodiment of the invention.

The specific embodiment

Below in conjunction with the drawings and specific embodiments, further illustrate the present invention, should understand these embodiment is only not used in and limits the scope of the invention for the present invention is described, after having read the present invention, those skilled in the art all fall within the application's claims limited range to the modification of the various equivalent form of values of the present invention.

1) obtain the step response model of reheat steam temperature object.

If reheat steam temperature dynamic characteristic can be by y (s)=G (s) U (s)=[G ₁(s) G ₂(s)] [u ₁(s) u ₂(s)] ^trepresent.Wherein, G ₁(s) be the transfer function of reheat steam temperature to gas baffle aperture (%/℃), g ₂(s) be the transfer function of reheat steam temperature to desuperheating water pitch aperture (%/℃), $G_2\left(s\right)=\frac{-0.4}{{(1+85s)}^6};$

By on-the-spot step response test, the coefficient that can obtain respectively reheat steam temperature object step response model is respectively: [a ₁₁..., a _1,60]=[0,0,0,0,0,0,0,0,0.0001,0.0002,0.0004 ..., 0.2673,0.2720,0.2764,0.2806], [a ₂₁..., a _2,60]=[0,0,0,0 ,-0.0005 ,-0.0013 ,-0.0027 ,-0.0049 ,-0.0083 ... ,-0.3967 ,-0.3972 ,-0.3976 ,-0.3979];

2) controller relevant parameter is set, makes sampling time T _s=20 seconds, prediction step number P=60, controlled step number M ₁=M ₂=2, output error weight matrix Q=I ₆₀, control matrix $R=\mathrm{diag}(r_{u_1}{I}_2,r_{u_2}{I}_2)=\mathrm{diag}(\mathrm{0.2,0.2},$ $0.0),$ Desuperheating water control inputs error weight coefficient $S=\mathrm{diag}(s_{u_1}{I}_2,s_{u_2}{I}_2)=\mathrm{diag}\left(\mathrm{0,0,0.3,0.3}\right).$ Can obtain:

$A={\left[\begin{array}{cc}0& 0\\ 0& 0\\ .& .\\ .& .\\ .& .\\ & .\\ 0.2720& .\\ & .\\ 0.2764& 0.2720\\ 0.2806& 0.2764\end{array}\right]}_{60\&times;2},A={\left[\begin{array}{cc}0& 0\\ 0& 0\\ .& .\\ .& .\\ .& .\\ & .\\ -0.3972& .\\ & .\\ -0.3976& -0.3972\\ -0.3979& -0.3976\end{array}\right]}_{60\&times;2}$

3) controller state initializes, and, under certain steady state condition, detects current time reheat steam temperature measured value y (k), and the prediction initial value y of current reheat steam temperature and following 60 steps _i, i=0 ..., 60 are set to the reheat steam temperature measured value y (k) of current time.Then, within each sampling period, repeat the 4th) step to the 9) step;

4) calculate reheat steam temperature prediction deviation e=y (k)-y ₀;

5) carry out feedback compensation: y _i+ h _ie → y _i, i=1 ... 60, wherein, get correction coefficient h _i=1, i=1 ... 60;

6) calculate gas baffle controlled quentity controlled variable increment Delta u by formula (4) ₁and desuperheating water pitch controlled quentity controlled variable increment Delta u (k) ₂(k);

$\mathrm{\&Delta;U}\left(k\right)={\left[\begin{array}{cc}{\mathrm{\&Delta;u}}_1\left(k\right)& {\mathrm{\&Delta;u}}_2\left(k\right)\end{array}\right]}^T=d_1(w_P\left(k\right)-{\tilde{y}}_{P0}\left(k\right))+d_2(U_0-U_M(k-1))$

Wherein, d ₁=L (A ^tqA+R+T ^tsT) ^-1a ^tq

$={\left[\begin{array}{cccccccccc}0& 0& 0& 0& 0& -0.0001& ...& 0.1579& 0.1653& 0.1722\\ 0& 0& 0& -0.0001& -0.0004& -0.0012& ...& 0.0047& 0.0043& 0.0038\end{array}\right]}_{2\&times;60},$

$d_2=L{(A^T\mathrm{QA}+R+T^T\mathrm{ST})}^{-1}{T}^{T}S=\left[\begin{array}{cccc}0& 0& -0.0232& 0.2444\\ 0& 0& 0.9911& -0.0371\end{array}\right],U_0={\left[\begin{array}{cccc}0& 0& 0& 0\end{array}\right]}^T;$

7) calculate gas baffle controlled quentity controlled variable u ₁(k)=u ₁(k-1)+Δ u ₁, and desuperheating water pitch controlled quentity controlled variable u (k) ₂(k)=u ₂(k-1)+Δ u ₂(k);

8) if u _i(k) >100, makes u so _i(k)=100, Δ u _i(k)=100-u _i(k-1), i=1,2;

If u _i(k) <0, makes u so _i(k)=0, Δ u _i(k)=-u _i(k-1), i=1,2;

9) output u ₁and u (k) ₂(k), calculate and upgrade reheat steam temperature prediction of output value: y ₁→ y ₀, y _i+ a _1iΔ u ₁(k)+a _2iΔ u ₂(k) → y _i, i=1 ..., 60.

As shown in Figure 2, when time, solid line part is that reheat steam temperature setting value step reduces in 1 ℃ of situation, adopts the optimal control effect curve of the present invention to reheat steam temperature system.Can find out, when due to various disturbances, reheat steam temperature departs from the situation of setting value, and the present invention, by coordinate to control gas baffle aperture (or burner pivot angle) and desuperheating water pitch aperture simultaneously, can make reheat steam temperature rapidly, steadily, zero deflection return to setting value; Under this external steady state condition, can close desuperheating water pitch or desuperheating water pitch is adjusted to certain less opening value that user specifies, thereby can effectively reduce injection flow rate, improve unit entirety cycle efficieny; As shown in Figure 2, when time, dotted portion has shown that controller parameter changes the impact on optimal control effect.Can find out, under the definite condition of Q, with determine that baffle plate regulates and the size of water spray adjusting speed control. with larger, control action changes milder, but the adjusting time of reheat steam temperature is also longer.In addition, with relative size determined that baffle plate regulates and water spray regulates the size of two kinds of control actions relativity in Switching Logic Control of Reheat Steam Temperature. determine that water spray pulls back to the speed of setting value.Other parameter constants, it is faster that larger desuperheating water pulls back to the speed of setting value, otherwise slower.Conventionally get $s_{u_1}=0,s_{u_2}=0.3~0.5.$

Claims (1)

1. the reheat steam temperature optimal control method based on multivariable prediction control, it is characterized in that: adopt multivariable predicting control method to control reheat steam temperature system, when this multivariable predicting control method comprises hot desuperheat spray flow and two variablees of gas baffle aperture again, by introducing again the steady-state target value of hot desuperheat water spray pitch aperture, realize the optimization to system economy, described multivariable predicting control method concrete steps are as follows:

1) obtain the step response model of reheat steam temperature object, under steady state condition, carry out reheat steam temperature open loop step response test take gas baffle aperture and desuperheating water pitch as input respectively, after filtering, the coefficient that obtains respectively both step response models is with wherein, N ₁and N ₂be respectively the time length of field of two step response models, N ₁and N ₂selection should guarantee to make the response of reheat steam temperature to approach steady-state value;

2) controller relevant parameter is set, comprises sampling time T _s, prediction step number P, fume side baffle controls step number M ₁, desuperheating water pitch control step number M ₂, output error weight matrix Q, control matrix R, control inputs error weight matrix S, T _scan use empirical rule T ₉₅/ T _s=5～15 choose, wherein, and T ₉₅for transient process rises to for 95% adjusting time; General P elects the rise time that equals reheat steam temperature step response as; M ₁and M ₂select 1 or 2; Q=diag (q ₁..., q _p), $R=\mathrm{diag}(r_1,...,r_{M_1+M_2}),S=\mathrm{diag}(S_1,...,S_{M_1+M_2});$

After controller parameter is determined, adopt the described forecast model of formula (1) to predict following reheat steam temperature system output: ${\tilde{y}}_{\mathrm{PM}}\left(k\right)={\tilde{y}}_{P0}\left(k\right)+{\mathrm{A\&Delta;U}}_M\left(k\right)---\left(1\right)$

Wherein, ${\tilde{y}}_{\mathrm{PM}}\left(k\right)=\left[\begin{array}{c}\tilde{y}(k+1|k)\\ .\\ .\\ .\\ \tilde{y}(k+P|k)\end{array}\right],{\tilde{y}}_{P0}\left(k\right)=\left[\begin{array}{c}{\tilde{y}}_0(k+1|k)\\ .\\ .\\ .\\ {\tilde{y}}_0(k+P|k)\end{array}\right],\tilde{y}(k+i|k),i=1,...,P$ Be illustrated in the predicted value of the reheat steam temperature of k moment to the following k+i moment, be illustrated in the initial value of the reheat steam temperature prediction of k moment to the following k+i moment;

A=[A ₁a ₂], wherein

ΔU _M(k)＝[Δu ₁(k|k)…Δu ₁(k+M ₁-1|k) Δu ₂(k|k)…Δu ₂(k+M ₂-1|k)] ^T，

Wherein Δ u ₁(k+i|k), i=0 ..., M ₁-1, Δ u ₂(k+i|k), i=0 ..., M ₂-1 is illustrated respectively in the gas baffle aperture of k moment to the following k+i moment and the estimated value of desuperheating water pitch controlled quentity controlled variable increment;

For expressing conveniently, use y _irepresent represent to utilize the predicted value of forecast model to following P sampling instant reheat steam temperature;

3) controller state initializes, and, under certain steady state condition, detects current time reheat steam temperature measured value y (k), and makes y ₀=y _i=y (k), i=1 ..., P, wherein, y ₀for utilizing the predicted value of forecast model to current time reheat steam temperature;

4) calculate reheat steam temperature prediction deviation e=y (k)-y ₀;

5) carry out feedback compensation, y _i+ h _ie → y _i, i=1 ..., P, wherein, h _ifor correction coefficient, be taken as 1;

6) calculate gas baffle controlled quentity controlled variable increment Delta u ₁and desuperheating water pitch controlled quentity controlled variable increment Delta u (k) ₂(k), getting performance index function is formula:

$J\left(k\right)={\left|\right|w_P\left(k\right)-{\tilde{y}}_{\mathrm{PM}}\left(k\right)\left|\right|}_Q^2+{\left|\right|{\mathrm{\&Delta;U}}_M\left(k\right)\left|\right|}_R^2+{\left|\right|U_M\left(k\right)-U_0\left|\right|}_S^2---\left(2\right)$

Wherein, w _p(k)=[w (k+1) ... w (k+P)] ^tfor the reference target value vector of following reheat steam temperature, U ₀for the steady-state target value vector of control inputs, U _m(k)=U _m(k-1)+T Δ U _m(k), T=diag (T ₁, T ₂),

By in forecast model formula (2) substitution formula (1), and by extreme value necessary condition try to achieve:

${\mathrm{\&Delta;U}}_M\left(k\right)={(A^T\mathrm{QA}+R+T^T\mathrm{ST})}^{-1}[A^{T}Q(w_P\left(k\right)-{\tilde{y}}_{P0}\left(k\right))+T^{T}S(U_0-U_M(k-1))]---\left(3\right)$

So, $\mathrm{\&Delta;U}\left(k\right)={\left[\begin{array}{cc}{\mathrm{\&Delta;u}}_1\left(k\right)& {\mathrm{\&Delta;u}}_2\left(k\right)\end{array}\right]}^T=d_1(w_P\left(k\right)-{\tilde{y}}_{P0}\left(k\right))+d_2(U_0-U_M(k-1))---\left(4\right)$

Wherein, d ₁=L (A ^tqA+R+T ^tsT) ^-1a ^tq, L=diag (θ ₁θ ₂),

${\mathrm{\&theta;}}_i={\left[\begin{array}{cccc}1& 0& ...& 0\end{array}\right]}_{1\&times;M_i},i=\mathrm{1,2},$

d ₂＝L(A ^TQA+R+T ^TST) ^-1T ^TS，

7) calculate gas baffle controlled quentity controlled variable u ₁(k)=u ₁(k-1)+Δ u ₁, and desuperheating water pitch controlled quentity controlled variable u (k) ₂(k)=u ₂(k-1)+Δ u ₂(k);

8) if u _i(k) >u _max, make so u _i(k)=u _max, Δ u _i(k)=u _max-u _i(k-1), i=1,2;

If u _i(k) <u _min, make so u _i(k)=u _min, Δ u _i(k)=u _min-u _i(k-1), i=1,2; Wherein, u _maxand u _minbe respectively higher limit and the lower limit of controlled quentity controlled variable;

9) output u ₁and u (k) ₂(k), calculate and upgrade reheat steam temperature prediction of output value: y ₁→ y ₀, y _i+ a _1iΔ u ₁(k)+a _2iΔ u ₂(k) → y _i, i=1 ..., P, then, within each sampling period, repeats the 4th) and step to the 9) step.