CN113341765A - Coal-fired power plant CO for strictly controlling carbon emission2Flexible regulation and control method for trapping system - Google Patents
Coal-fired power plant CO for strictly controlling carbon emission2Flexible regulation and control method for trapping system Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 29
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 title claims abstract description 21
- 229910052799 carbon Inorganic materials 0.000 title claims abstract description 21
- 239000003245 coal Substances 0.000 claims abstract description 10
- 238000000605 extraction Methods 0.000 claims abstract description 9
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 9
- 230000003321 amplification Effects 0.000 claims abstract description 7
- 238000003199 nucleic acid amplification method Methods 0.000 claims abstract description 7
- 238000005070 sampling Methods 0.000 claims description 13
- 230000000694 effects Effects 0.000 claims description 11
- 238000005457 optimization Methods 0.000 claims description 5
- 238000005096 rolling process Methods 0.000 claims description 5
- 238000004088 simulation Methods 0.000 claims description 4
- 230000009471 action Effects 0.000 claims description 2
- 230000008878 coupling Effects 0.000 abstract description 2
- 238000010168 coupling process Methods 0.000 abstract description 2
- 238000005859 coupling reaction Methods 0.000 abstract description 2
- 239000011159 matrix material Substances 0.000 description 7
- 238000010586 diagram Methods 0.000 description 5
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 description 4
- 230000008859 change Effects 0.000 description 3
- 239000003546 flue gas Substances 0.000 description 3
- 238000010521 absorption reaction Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000004044 response Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 229910002091 carbon monoxide Inorganic materials 0.000 description 1
- 238000002485 combustion reaction Methods 0.000 description 1
- 230000003750 conditioning effect Effects 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 238000006386 neutralization reaction Methods 0.000 description 1
- 238000010248 power generation Methods 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- 239000002904 solvent Substances 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
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Abstract
The invention is suitable for the technical field of automatic thermal control, and provides a coal-fired power plant CO with strictly controlled carbon emission2The flexible regulation and control method of the trapping system comprises the following steps: step S1: selecting CO of large coal-fired power plant2Capturing the controlled variable and the control variable of the system; step S2: inputting M sequence signals for coal feeding amount, water feeding flow, main steam valve opening, barren solution flow and reboiler steam extraction flow under the condition of open loop; step S3: obtaining coal-fired power plant CO by using n4sid algorithm in MATLAB recognition toolbox2Collecting a system state space model; by establishing a prediction controller based on an amplification state space model, CO of the coal-fired power plant can be effectively processed2The method has the advantages of solving the control problems of strong coupling, large delay and strong system constraint of the trapping system, improving the dynamic regulation quality, increasing the soft constraint of the output variable to the performance index, and maintaining the trapping rate of the system at ymin，ymax]Greatly reduce CO2Fluctuation of the trapping rate, realizationStrict control of carbon emissions is achieved.
Description
Technical Field
The invention belongs to the technical field of automatic thermal control, and particularly relates to a CO (carbon monoxide) of a coal-fired power plant for strictly controlling carbon emission2A flexible regulation and control method for a trapping system.
Background
In order to realize the development goal of 'carbon peak reaching and carbon neutralization' at an early stage, the CO serving as a coal-fired power generating unit is required2Maximum single rowDischarging source to perform CO2Trapping and formulating strict CO2And (4) emission standard. Post combustion CO based on chemical solvent absorption2Trapping is the mainstream technology in the current pilot run due to its technical maturity.
Meanwhile, new energy sources such as solar energy and wind energy have the characteristics of discontinuity, volatility, uncertainty and the like, continuous and stable power supply is difficult to realize, and therefore the coal-fired thermal power generating unit needs to have deep peak regulation capacity to maintain the balance of supply and demand of a power grid, and the flue gas flow and the flue gas components of the unit can generate large fluctuation along with the load of the unit while the coal-fired thermal power generating unit carries out deep peak regulation, so that downstream CO can be subjected to large fluctuation2The stable operation of the capture system has certain influence and enables CO to be generated2The key indicator of capture rate fluctuates greatly.
Disclosure of Invention
The invention provides a coal-fired power plant CO with strictly controlled carbon emission2A flexible regulation and control method of a capture system, aiming at solving the problem of CO caused by deep peak shaving of a coal-fired thermal power generating unit2The capture rate, a key indicator, has a problem of large fluctuation.
The invention is realized by the following steps that the carbon emission of the coal-fired power plant CO is strictly controlled2The flexible regulation and control method of the trapping system comprises the following steps:
step S1: selecting CO of large coal-fired power plant2Capturing the controlled variable and the control variable of the system;
step S2: inputting M sequence signals for coal feeding amount, water feeding flow, main steam valve opening, barren solution flow and reboiler steam extraction flow under the condition of open loop;
step S3: obtaining coal-fired power plant CO by using n4sid algorithm in MATLAB recognition toolbox2Collecting a system state space model;
step S4: increasing an integral effect, and considering the influence of the undetectable disturbance and the model mismatch on the state space model;
step S5: according to the coal-fired power station CO2Capturing input and output data and an amplification state space equation of the system at the previous moment, and estimating state quantity by using a Kalman filter;
step S6: estimating future P time domain coal-fired power plant CO according to the amplified state space model and the state estimation value2An output characteristic of the capture system;
step S7: setting relevant parameters of a controller;
step S8: setting performance indexes of a predictive controller, and increasing output soft constraint on a trapping rate;
step S9: solving the performance index by adopting a quadratic programming quadprog solver, and calculating the optimal input quantity difference value in the future M moment;
step S10: calculating the optimal control quantity at the current moment;
step S11: outputting the optimal control quantity and collecting CO of the coal-fired power plant2The output of the system is captured, and thereafter, within each sampling period, steps S8 through S11 are repeatedly performed.
Preferably, in step S1, the main steam pressure, the intermediate point enthalpy, the unit power generation, the capture rate and the reboiler temperature are selected to be CO of the large-scale coal-fired power plant2The controlled variables of the trapping system are selected from coal feeding amount, water feeding flow, main steam valve opening, lean solution flow and reboiler steam extraction flow as corresponding control variables.
Preferably, the historical sampling value of the controlled variable is used as input, the historical sampling value of the controlled variable is used as output, and the n4sid algorithm in the MATLAB toolbox is used for obtaining the CO of the coal-fired power plant2And capturing a discrete state space model of the system, and verifying by using model simulation data.
Preferably, according to large coal-fired power station CO2Capturing input data and output data of the system at the previous moment, and estimating CO of the coal-fired power plant at the current moment by using a Kalman filter2The state quantity of the system is trapped.
Preferably, a rolling optimization method is used for carrying out optimization solution on future time domain controlled variables, and trapping rate soft constraints are introduced into the performance indexes.
Preferably, the system also comprises a model prediction controller which calculates the optimal control quantity at the current moment meeting the system constraint condition by rolling and optimizing the performance index
Preferably, the method further comprises the following steps:
a first delay module for inputting CO of coal-fired power plant2Collecting a sampling value of the control variable of the whole system at the previous moment;
a second delay module for inputting CO of coal-fired power plant2And collecting a sampling value of the controlled variable of the whole system at the previous moment.
Preferably, also comprises
A Kalman filter for estimating CO of the coal-fired power plant at the current moment according to input-output data of the system at the previous moment2Capturing a state quantity of the system;
CO of large coal-fired power station2And the trapping system model outputs the controlled variable under the action of the optimal control variable at the current moment.
Compared with the prior art, the invention has the beneficial effects that: the invention relates to a coal-fired power plant CO with strictly controlled carbon emission2The flexible regulation and control method of the trapping system can effectively process CO in the coal-fired power plant by establishing a prediction controller based on an amplification state space model2The method has the advantages of solving the control problems of strong coupling, large delay and strong system constraint of the trapping system, improving the dynamic regulation quality, increasing the soft constraint of the output variable to the performance index, and maintaining the trapping rate of the system at ymin，ymax]Greatly reduce CO2The fluctuation of the trapping rate realizes the strict control of carbon emission.
Drawings
FIG. 1 is a schematic diagram of the process steps of the present invention;
FIG. 2 is a schematic structural view of the present invention;
FIG. 3 shows CO of a large coal-fired power plant of the present invention2A schematic flow diagram of the capture system;
FIG. 4 is a graph of the effect of the main steam pressure control on the variation of a given value according to the present invention;
figure 5 is a graph illustrating the effect of the present invention on intermediate point enthalpy control when a given value is changed;
FIG. 6 is a diagram showing the effect of controlling the generator set power quantity when the set value is changed according to the present invention;
FIG. 7 is a graph showing the effect of controlling the amount of coal supplied when a given value is changed according to the present invention;
FIG. 8 is a diagram illustrating the effect of controlling the amount of water supplied when a given value is changed according to the present invention;
FIG. 9 is a diagram illustrating the effect of the main steam valve opening control when the given value changes according to the present invention;
FIG. 10 is a graph showing the effectiveness of trapping rate control according to the present invention when a given value is varied;
FIG. 11 is a graph showing the effect of reboiler temperature control on a given value change in accordance with the present invention;
FIG. 12 is a graph illustrating the effect of lean flow control on a given value change in accordance with the present invention;
figure 13 is a graph showing the effect of reboiler extraction flow control on a given value change according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, the present invention provides a technical solution: coal-fired power plant CO for strictly controlling carbon emission2The flexible regulation and control method of the trapping system comprises the following steps:
step S1: selecting as CO of large coal-fired power station2The controlled variable and the control variable of the trapping system are selected from main steam pressure, an intermediate point enthalpy value, unit generating capacity, trapping rate and reboiler temperature which are CO of the large-scale coal-fired power station2The controlled variable y (k) of the trapping system selects the coal feeding quantity, the water feeding flow, the opening of a main steam valve, the flow of lean solution and the steam extraction flow of a reboiler as corresponding control variables u (k);
step S2: under the condition of open loop, inputting M sequence signals into the coal feeding amount, the water feeding flow, the opening of a main steam valve, the flow of lean solution and the steam extraction flow of a reboiler, and acquiring dynamic response data of main steam pressure, an intermediate point enthalpy value, unit generating capacity, a trapping rate and reboiler temperature. The dynamic response of parameters such as the generating capacity and the trapping rate of the unit needs to cover the main operation condition of the unit;
step S3: obtaining coal-fired power plant CO by using n4sid algorithm in MATLAB recognition toolbox2Trapping system state space model, e.g. formula (1)
x(k+1)＝Ax(k)+Bu(k)
y(k)＝Cx(k)+Du(k) (1)
wherein ,
step S4: in order to realize the adjustment without difference, an integral function is added to the formula (1), and the influence of the undetectable disturbance and the model mismatch on the state space model is considered to construct an amplification state space model shown in the formula (2);
step S5: according to the coal-fired power station CO2Capturing input and output data of the system at the previous moment and an amplification state space equation in the formula (2), and estimating a state quantity x by using a Kalman filtere(k) As shown in formula (3)
xe(k+1|k)＝Aexe(k)+BeΔu(k)
Pe(k+1|k)＝AePe(k)Ae T+Qn
Lx＝Pe(k+1|k)Ce T[CePe(k+1|k)Ce T+Rn]-1
xe(k+1)＝xe(k+1|k)+Lx[y(k-1)-Cexe(k+1|k)]
Pe(k+1)＝(I-LxCe)Pe(k+1|k)
(3)
in the formula ,xe(k +1| k) is the state estimate at time k to time k + 1; x is the number ofe(k) and xe(k +1) is the state quantities at the time of k and the time of k +1 respectively; p is a radical ofe(k) Estimating a covariance matrix for the posteriori; qn and RnCovariance matrices of state quantities and measured value noise, respectively; l isxAn optimal Kalman gain is obtained; y (k-1) is the measured value of the output variable at time k-1.
Step S6: based on the model of the amplification state space and the state estimate xe(k) Estimating future P time domain coal fired power plant CO2Output characteristics of the trap system, as shown in equation (4)
Yp＝Fxxe(k)+ΦΔU (4)
wherein ,
step S7: setting controller-related parameters, including the prediction time domain NpControl time domain M, output error weight matrix Q, control weight matrix R and state quantity covariance matrix QnCovariance matrix R of measured value noisenAnd a relaxation variable matrix ρ. Sampling period TsThe selection of (A) generally conforms to Shannon's sampling theorem, and an empirical rule T can be used95/TSIs selected from 5 to 15, wherein T95The conditioning time for the transition process to rise to 95%; the prediction time domain P should contain the real dynamic part of the object as much as possible; m is generally 3-5; wherein, Ts30 seconds, P20, M5, Q diag ([90e1, 0.78e1, 8.0, 8.5e6, 6e 6)])，R＝diag([9900，200，8300，80，180])，Qn＝eye(9)，Rn＝eye(9)，ρ＝diag([1，1，1，500，1])
Step S8: setting a performance index of the predictive controller, and increasing output soft constraint on the trapping rate, as shown in formula (5):
s.t.umin≤u(k)≤umax,Δumin≤Δu(k)≤Δumax
ymin-ε(k+i)≤ycapture(k+i|k)≤ymax+ε(k+i),1≤i≤Np
0≤ε(k+i)≤εmax (5)
wherein ε (k + i) is the relaxation variable; epsilonmaxIs the maximum value of the relaxation variable; Σ ═ epsilon (k +1) … epsilon (k + N)p)]T(ii) a Rho is a corresponding weight matrix; y ismin and ymaxRespectively capture rate in the future NPMinimum and maximum values within a time; Δ umin and ΔumaxAmplitude constraints for the system primary input variables; Δ umin and ΔumaxRate constraints for the system primary input variables;
in the formula, the constraint of the input and output variables is Deltaumax＝[5；15；0.03；20；10]T；Δumin＝[-5；-15；-0.03；-20；-10]T；umin＝[20；200；0.4；100；30]T；umax＝[120；600；1；700；250]T; minimum value y of trapping ratemin89%, maximum trapping rate ymax91%, maximum value ε of relaxation variablesmax＝0.5％
Step S9: solving the performance index by adopting a quadratic programming quadprog solver, and calculating the optimal input quantity difference value delta U in the future M moment;
step S10: calculating an optimum control amount u (k) at the current time, u (k-1) + Δ u (k); (ii) a
Step S11: outputting the optimal control quantity and collecting CO of the coal-fired power plant2The output of the system is captured, and thereafter, within each sampling period, steps S8 through S11 are repeatedly performed.
In the present embodiment, as shown in FIG. 1, the model predictive controller, the first delay module, the second delay module, the Kalman filter, and the method of the present invention are providedCO of large coal-fired power station2Capturing a system model; CO of large coal-fired power station2Obtaining delay variables u (k-1) and y (k-1) by an input variable u (k) and an output variable y (k) of the trapping system through a first delay unit and a second delay unit respectively; obtaining the estimated value x of the state quantity at the current moment by the delay variables u (k-1) and y (k-1) through a Kalman filtere(k) (ii) a The inputs of the model predictive controller are respectively given values y of the current momentr(k) The controlled variable y (k-1) at the previous moment and the state quantity estimated value x at the current momente(k) And calculating the optimal control variable u (k) at the current moment by using the rolling optimization performance index.
In the present embodiment, as shown in FIG. 3, a large coal-fired power plant CO2The trapping system comprises: main units such as a boiler, a steam turbine, a generator, an absorption tower, a separation tower and the like; the main variables include: coal feeding amount, water feeding flow, main steam valve opening, lean solution flow, reboiler steam extraction flow, main steam pressure, intermediate point enthalpy value, unit generating capacity, trapping rate and reboiler temperature.
In the present embodiment, as shown in FIGS. 4-13, u is the initial steady state operating condition1＝56.5333kg/s、u2＝397.630kg/s、u3＝86.31％、u4＝497.680kg/s、u5＝131.5056kg/s、y1＝21.3693MPa、y2＝2722.1325kJ/kg、y3＝432.9270MW、y4＝90％、y5The operation is stable for 10 minutes under the condition of 392.2K, the given values are respectively 24.8430MPa, 2674.4886kJ/kg, 552.790MW, 90 percent and 392.2K, after the operation is carried out for 100 minutes, the given values are respectively 24.01MPa, 2702.4781kJ/kg, 506.896MW, 90 percent and 392.2K, and the total simulation time of the system is 210 minutes.
In the present embodiment, as can be seen from the simulation results of fig. 4 to 13, the strict carbon emission coal-fired power plant CO proposed by the present invention2The flexible regulation and control method of the capture system can realize CO under the condition that the working condition of the thermal power generating unit changes in a large range2The strict regulation and control of the trapping rate enables the trapping rate to quickly track a given value and greatly reduce the fluctuation amplitude (strictly maintained at 89 percent and 91 percent)]In between) to reduce coal-fired power plantsCO2CO of clean flue gas of capture system2And (4) discharging the amount. Meanwhile, the control method provided by the invention can also realize the rapid adjustment of other control variables such as the generating capacity of the unit, the main steam pressure, the intermediate point enthalpy value, the reboiler temperature and the like, so that the control method is suitable for industrial application.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (8)
1. Coal-fired power plant CO for strictly controlling carbon emission2The flexible regulation and control method of the trapping system is characterized in that: the method comprises the following steps:
step S1: selecting CO of large coal-fired power plant2Capturing the controlled variable and the control variable of the system;
step S2: inputting M sequence signals for coal feeding amount, water feeding flow, main steam valve opening, barren solution flow and reboiler steam extraction flow under the condition of open loop;
step S3: obtaining coal-fired power plant CO by using n4sid algorithm in MATLAB recognition toolbox2Collecting a system state space model;
step S4: increasing an integral effect, and considering the influence of the undetectable disturbance and the model mismatch on the state space model;
step S5: according to the coal-fired power station CO2Capturing input and output data and an amplification state space equation of the system at the previous moment, and estimating state quantity by using a Kalman filter;
step S6: estimating future P time domain coal-fired power plant CO according to the amplified state space model and the state estimation value2An output characteristic of the capture system;
step S7: setting relevant parameters of a controller;
step S8: setting performance indexes of a predictive controller, and increasing output soft constraint on a trapping rate;
step S9: solving the performance index by adopting a quadratic programming quadprog solver, and calculating the optimal input quantity difference value in the future M moment;
step S10: calculating the optimal control quantity at the current moment;
step S11: outputting the optimal control quantity and collecting CO of the coal-fired power plant2The output of the system is captured, and thereafter, within each sampling period, steps S8 through S11 are repeatedly performed.
2. The CO of claim 1 for coal-fired power plant with strict control of carbon emission2The flexible regulation and control method of the trapping system is characterized in that: in the step S1, the main steam pressure, the intermediate point enthalpy value, the unit generating capacity, the capture rate and the reboiler temperature are selected to be large-scale coal-fired power station CO2The controlled variables of the trapping system are selected from coal feeding amount, water feeding flow, main steam valve opening, lean solution flow and reboiler steam extraction flow as corresponding control variables.
3. The CO of claim 1 for coal-fired power plant with strict control of carbon emission2The flexible regulation and control method of the trapping system is characterized in that: taking the historical sampling value of the controlled variable as input and the historical sampling value of the controlled variable as output, and obtaining the CO of the coal-fired power plant by using an n4sid algorithm in an MATLAB tool box2And capturing a discrete state space model of the system, and verifying by using model simulation data.
4. The CO of claim 1 for coal-fired power plant with strict control of carbon emission2The flexible regulation and control method of the trapping system is characterized in that: according to the CO of a large coal-fired power station2Capturing input data and output data of the system at the previous moment, and estimating CO of the coal-fired power plant at the current moment by using a Kalman filter2The state quantity of the system is trapped.
5. The CO of claim 1 for coal-fired power plant with strict control of carbon emission2The flexible regulation and control method of the trapping system is characterized in that: and optimizing and solving the future time domain controlled variable by using a rolling optimization method, and introducing trapping rate soft constraint into the performance index.
6. The CO of claim 1 for coal-fired power plant with strict control of carbon emission2The flexible regulation and control method of the trapping system is characterized in that: the model predictive controller is used for calculating the optimal control quantity at the current moment meeting the system constraint condition through rolling optimization performance indexes.
7. The CO of claim 1 for coal-fired power plant with strict control of carbon emission2The flexible regulation and control method of the trapping system is characterized in that: further comprising:
a first delay module for inputting CO of coal-fired power plant2Collecting a sampling value of the control variable of the whole system at the previous moment;
a second delay module for inputting CO of coal-fired power plant2And collecting a sampling value of the controlled variable of the whole system at the previous moment.
8. The CO of claim 1 for coal-fired power plant with strict control of carbon emission2The flexible regulation and control method of the trapping system is characterized in that: further comprising:
a Kalman filter for estimating CO of the coal-fired power plant at the current moment according to input-output data of the system at the previous moment2Capturing a state quantity of the system;
CO of large coal-fired power station2And the trapping system model outputs the controlled variable under the action of the optimal control variable at the current moment.
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