JP3202265B2 - Method for controlling circulation flow rate of absorption tower in wet flue gas desulfurization unit - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a wet flue gas desulfurization apparatus, and more particularly to a control apparatus suitable for appropriately controlling the circulation flow rate of an absorption tower to reduce the power of an absorption tower circulation pump at a low load.

[0002]

2. Description of the Related Art A wet flue gas desulfurization apparatus is as shown in FIG. 8, in which an inlet exhaust gas 30 comes into gas-liquid contact with an absorbent supplied from an absorbent circulation line 31 in an absorption tower 33, and SO ₂ in the exhaust gas. Is fixed in the absorption liquid in the form of sulfite, and the exhaust gas is discharged from the chimney through the discharge line 34.

[0003] The absorbing liquid having absorbed SO ₂ flows down from the tower to the circulation tank 35. The circulating tank 35 is supplied with an absorbent through an absorbent slurry flow control valve 36, and the liquid having recovered the SO ₂ absorption performance is supplied to the absorption tower 33 by the absorption tower circulation pump 18. Part of the circulating fluid is withdrawn line 3
The sulfite in the absorbing solution is oxidized and recovered as gypsum in a later step.

[0004] As a control method of this type of wet flue gas desulfurization apparatus, for example, Japanese Patent Application Laid-Open No. Sho 60-110320 is disclosed.
No. 1 described in the above item. In this control method,
According to the simulation model 38, the optimum PH value signal 39 of the absorbing liquid circulating through the absorption tower and the optimum number of operating the absorption tower circulating pumps 18 according to the load amount of the exhaust gas flowing into the absorption tower as shown in FIG. The signal 17 is set, and when the load is stabilized, the number obtained by subtracting 1 from the optimum number of operation is set, and a certain increment is added to the above-mentioned optimum PH value to obtain a set value of PH. Accordingly, only when the desulfurization rate satisfies the target value, the supply amount of the absorbent and the number of pumps are controlled based on the changed set value.

However, in this control system, it is essential that the simulation model can accurately reproduce the behavior of the actual machine. In the desulfurization apparatus, the desulfurization performance, exhaust gas flow rate, inlet SO ₂ concentration, the absorption liquid PH and liquid -
Although it is governed by the gas ratio, the desulfurization performance differs depending on the oxidation state in the absorbing solution, that is, the concentration of sulfite even at the same PH.

FIG. 7 shows the relationship between the oxidation state and the desulfurization performance.
As is apparent from the figure, in order to accurately predict the change in the desulfurization rate due to the change in the operating conditions by simulation, the oxidation state, that is, the concentration of sulfite, is required, and this cannot be measured online.

In view of the uncertainty of the sulfite oxidation rate, it is necessary to correct the data by manual analysis.
No consideration has been given to the complexity of the driving operation and the possibility of human error due to the intervention of the operator in the data correction work.

[0008]

In the above-mentioned prior art, the optimum number of operating absorber circulation pumps is determined by a simulation model. However, attention is paid to the accuracy of the simulation model. If the accuracy declines, the required desulfurization rate cannot be maintained.If the operating conditions change drastically, it is necessary to correct the coefficients of the simulation model, etc., based on the manual analysis of the liquid composition. However, there is a problem that the burden on the operator increases.

An object of the present invention is to solve the above-mentioned problems and to provide a method for controlling the circulation flow rate of an absorption tower of a wet flue gas desulfurization apparatus capable of maintaining a desulfurization rate near a target value using only information that can be measured online. It is in.

[0010]

SUMMARY OF THE INVENTION The above object is, exhaust gas flow rate can be measured online, absorption liquid PH, inlet SO ₂ concentration, based on the desulfurization rate setting value, determine the absorption tower circulating flow demand previous value, in this, The deviation between the desulfurization rate and the set value of the desulfurization rate and the correction amount by the self-adjustment type fuzzy inference corresponding to the change rate of the deviation are added to make the entire flow rate demand, and the circulation amount of the absorption tower exceeding this demand is controlled by the pump unit number By ensuring the pump speed control, stable operation with a constant desulfurization rate is achieved without operator intervention.

[0011] The leading value of the circulating flow demand on the absorption tower based on the on-line measured amount is operated so as to change the flow demand, which is the base for maintaining the desulfurization rate at the target value, in accordance with the change of the operation state. If the system is operated with the circulation flow rate of the absorption tower serving as the base, a deviation occurs between the desulfurization rate and the desulfurization rate set value. If the circulating flow rate of the absorption tower is changed by the feedback correction amount based on the self-adjustment type fuzzy inference based on this deviation, the deviation decreases, and the desulfurization rate does not deviate from the target.

[0012]

FIG. 1 shows a specific embodiment of a method for controlling the circulation flow rate of an absorption tower based on a self-adjusting fuzzy inference of a wet flue gas desulfurization apparatus according to the present invention. In the figure, reference numeral 6 denotes a flow rate demand leading value calculator, which is an exhaust gas flow meter 1, a PH meter 2, and an inlet SO.
_{(2) The} following calculation is performed using the respective output signals of the concentration meter 3 and the desulfurization rate set value 4.

FIG. 9 shows the desulfurization rate η. In order for the desulfurization rate η to reach the _set value η _set , the equations (1) and (2) shown in FIG. 9 become the equations (3) shown in FIG. 9, and the flow rate demand signal 11 is obtained from this equation.

On the other hand, the inlet SO ₂ concentration meter 3 and the outlet SO ₂
From the output signal of the densitometer 5, a desulfurization rate signal 9 is obtained by using a subtractor 7a and a divider 8, and a desulfurization rate setting device 4 is obtained by a subtractor 7b.
And a desulfurization rate deviation signal 10 between the desulfurization rate signal 9 and the desulfurization rate signal 9 is obtained and input to the self-adjusting type fuzzy calculator 13.

The self-adjustment type fuzzy calculator 13 performs the following calculations. When the deviation signal of the desulfurization rate e _n, the change in the desulfurization rate deviation and .DELTA.e _n, shown in FIG. 10 (4) and (5).

[0016] FIG. 2 Menbashitsupu function of e _n and Δe _n
As shown. The meaning of the symbols in the figure is shown below. NB: negative and large, NM: negative and slightly large, NS: negative and small, ZO: almost zero, PS: positive and small, P
M: positive and slightly large, PB: positive and large

[0017] The status of e _n and .DELTA.e _n, an example of a control law for determining the incremental H _n of to be corrected absorption tower circulating flow in FIG. In the figure, for example, if e _n = PS and Δe _n =
Reading as NM if H _n = NS, referred to as this control rules. Next, the control performance is evaluated at each sampling time, and a control rule is modified or newly created based on the evaluation result. Information such as control deviation and the rate of change at that time,
That is, the control state is directly evaluated, and the correction amount of the control rule is fed back.

FIG. 4 shows an example of the correction amount of the control rule.
In the figure, for example, an e _n = PS in .DELTA.e _n = amount of correction of PB if rule P _n = PB. P _n is the amount of rule modification, and indicates the output that should have been added to the control output in the past. Based on this _Pn , a control rule deemed responsible for the current control state is modified or newly created.

The control state at the sampling time n is the past control operation A (1), A (2),..., A (n−
Several control actions, which are caused by the overall influence of 1) and have a greater influence than others, can be selected. Among these control operations, the operation A (n-j) before sampling j, which seems to be the most responsible, is specified by the parameter j.

The control rule R (n-j) that infers the operation A (n-j) before j sampling is modified by the modification amount Pn specified in FIG. R (n
Assuming that -j) is a rule represented by the index shown in FIG. 10, the modified rule R * (n) is represented by equation (6) shown in FIG. The replacement of the control rules is performed by the logic of equation (7) shown in FIG. According to the above procedure, the self-adjustment type fuzzy computing unit 13 can advance the learning of the control rules online.

FIG. 6 shows a method of determining the basic increment of the manipulated variable. In the figure, two control rules (rule 1 and rule 2) are shown as examples, and a representative amount of the desulfurization rate deviation is X and a representative amount of the deviation change is Y. The fuzzy sets relating to the values of X = X 'and Y = Y' are A ₁ and B ₁ for rule ₁ and A ₂ and B ₂ for rule 2. The fuzzy set of the increment of the operation amount determined from Rule 1 is C ₁ , the one corresponding to Rule 2 is C ₂ , and the respective membership functions are μ _c1 and μ _c2 . At this time, Expression (8) shown in FIG. 12 from Rule 1 and Expression (9) shown in FIG. 12 from Rule 2 are obtained, and the basic operation amount satisfying Rule 1 and Rule 2 using w ₁ and w _2. Find the incremental membership function μ _c *.

The barycentric coordinate Z * of μc * is calculated by the equation (11) shown in FIG. 12 with reference to FIG. This value Z * is set as a basic increment H of the operation amount. Actually, four control rules are involved in the values of X 'and Y', but H is determined by the same procedure. Therefore, the current manipulated variable is U (n)
, The manipulated variable U (n) at the next time point (n + 1)
+1) to U (n + 1) = U (n) + K · H (n)... (12) where K: control gain, H (n): manipulated variable incremental

As described above, the self-adjustment type fuzzy computing unit 13 performs the computations shown in the equations (4) to (12) every sampling time, and inputs the flow rate demand correction signal 14 to the adder 12. The adder 12 adds the flow demand preceding value signal 11 and the flow demand correction signal 14 to output a flow demand signal 15, and outputs the flow demand signal 15.
To enter. As shown in FIG. 6, the pump number setting unit 16 determines the required number of pumps so as not to reduce the circulating flow demand, and uses this as the optimum operating number signal 17 to determine the number of the absorption tower circulating pumps 18.

This control method basically uses a flow rate demand correction signal 14 which is a feedback correction signal obtained by subjecting a flow rate demand leading value signal 11 and a desulfurization rate deviation signal 10 to signal processing by a self-adjusting type fuzzy calculator 13. The demand signal 15 is obtained, and is characterized in that a flow rate leading value is obtained from an online measurement signal and that feedback correction is performed using self-adjustment type fuzzy inference.

As shown in FIG. 7, in the desulfurization apparatus, the SO ₂ in the exhaust gas is absorbed, and the desulfurization rate varies greatly depending on the concentration of sulfite generated in the absorbing solution, that is, the oxidation state. .

Therefore, even if the same desulfurization rate deviation occurs, the value of the circulation flow rate of the absorption tower that must be increased or decreased to maintain the desulfurization rate at the target value varies depending on the oxidation state. That is, when the feedback correction is performed by a normal PI controller, the proportional gain and the integration time are usually constant, so that the above-described adaptive correction due to the difference in the oxidation state is impossible.

In the self-adjusting fuzzy computing unit 13, FIG.
The feedback correction amount is basically determined on the basis of the control rule shown in FIG.
Thus, the desulfurization rate is maintained close to the target in all operating states.

As described above, in the present invention, the self-adjusting type fuzzy operation unit operates as if it were a skilled operator, so that the desulfurization rate can be controlled to be close to the target value even in a special operation state.

According to the present invention, by installing an arithmetic unit for correcting the demand for the circulation flow rate of the absorber using self-adjustment type fuzzy inference, the control rule can be changed online while observing the change behavior of the desulfurization rate, that is, the control characteristic. It is possible to determine the number of operating pumps for the absorption tower circulating pump, so that it is possible to control the circulation flow rate of the absorption tower by a seasoned operator who is familiar with the behavior of the plant. Changes, the desulfurization rate change behavior also fluctuates greatly, the desulfurization rate is maintained at the target value,
In addition to ensuring stable desulfurization performance, there is an effect that by appropriately controlling the circulation flow rate of the absorption tower, the power of the absorption tower circulation pump at low load can be reduced.

[Brief description of the drawings]

FIG. 1 is a control system diagram showing an embodiment of a method for controlling a circulation flow rate of an absorption tower according to the present invention.

FIG. 2 is an explanatory diagram of a membership function.

FIG. 3 is an explanatory diagram illustrating an example of a control rule.

FIG. 4 is an explanatory diagram showing an example of a correction amount of a control rule.

FIG. 5 is an explanatory diagram showing the principle of fuzzy inference.

FIG. 6 is a principle diagram for setting the number of circulation pumps.

FIG. 7 is an explanatory diagram showing the relationship between PH, oxidation state, and desulfurization rate.

FIG. 8 is a control system diagram showing a conventional absorption tower circulation flow rate control method.

FIG. 9 is a diagram showing a mathematical expression.

FIG. 10 is a diagram showing a mathematical expression.

FIG. 11 is a diagram showing a mathematical expression.

FIG. 12 is a diagram showing a mathematical expression.

[Explanation of symbols]

1 ...... exhaust flowmeter 3 ...... inlet SO ₂ concentration meter 4 ...... desulfurization rate setter 5 ...... outlet SO ₂ concentration meter 6 ...... flow demand prior value calculator 12 ...... adder 13 ...... self-regulating fuzzy Arithmetic unit

──────────────────────────────────────────────────続 き Continued on front page (58) Field surveyed (Int.Cl. ⁷ , DB name) B01D 53/50 B01D 53/77

Claims (1)

(57) [Claims] In a wet flue gas desulfurization device for absorbing and removing sulfur oxides in flue gas from a boiler or the like, a desulfurization rate is calculated from output signals of an inlet and outlet SO ₂ concentration meter, and a difference between the desulfurization rate and a target value is calculated. Based on the deviation signal and the rate-of-change signal of the deviation signal, calculate the demand correction signal of the absorption tower circulation flow rate using self-adjustment type fuzzy inference, and calculate the absorption tower circulation flow demand advance value from the online measurement signal, A method of controlling a circulation flow rate of an absorption tower in a wet flue gas desulfurization apparatus, comprising determining a circulation flow rate of an absorption tower based on a sum signal of a demand correction signal and a demand advance signal.