JPH0765725B2 - Thermal power plant automatic control device - Google Patents

Description

Description: TECHNICAL FIELD The present invention relates to a thermal power plant automatic control device, and particularly to a thermal power plant suitable for performing predictive control using a model representing the entire plant of a multivariable control system. The present invention relates to an automatic control device.

[Prior art]

In recent years, due to the day-night gap in power demand and the increase in nuclear power plants, the thermal power plants have been forced to start and stop and perform rapid load change operation every day. However, in a boiler, the response time of steam temperature change to fuel change is as long as ten minutes, and the response gain and time constant change significantly depending on the size of the load, making it difficult to control the steam temperature and shortening the startup time and load change. It was a big constraint on the rate improvement.

In order to eliminate such a restriction, as described in JP-A-57-16719, a controller has a built-in dynamic characteristic model of a boiler,
A method of predicting the future value of the main steam temperature and controlling the fuel in advance has been proposed. In this case, in order to reduce mutual interference between signals inside the boiler, it is desirable to apply the above predictive control method to the entire boiler.

[Problems to be solved by the invention]

However, when the entire boiler is modeled and the predictive calculation is executed, the increase in the calculation time becomes a problem due to the higher dimension of the model. This causes an increase in the number of repeated operations and an increase in the load factor especially for a system with a slow response, but there is a problem that a highly accurate prediction signal cannot be obtained if the sampling period is lengthened to prevent this.

An object of the present invention is to provide a thermal power plant automatic control device that realizes highly accurate prediction calculation without increasing the calculation time in the prediction control using a large-scale multivariable plant model.

[Means for solving problems]

In order to achieve the above object, the present invention incorporates a plurality of operation signals, control signals, and measurement signals into a plant model, and a thermal power plant automatic control for controlling a thermal power plant by a prediction signal calculated by the plant model. In the apparatus, the plant model is divided into a fuel system model, a steam system model, a ventilation system model, etc., and each of the divided models is subdivided into a sub-model with a fast response and a sub-model with a slow response. The sub-model having a slow response is subjected to the prediction calculation, and then the sub-model having a slow response is subjected to the prediction calculation.

[Action]

The present invention, if the operation signal of the plant is settled, or if the response of the plant to the change of the operation signal is sufficiently long, even if the sampling period of the plant model prediction calculation is sufficiently long, the prediction accuracy does not deteriorate. In order to realize this, we divided the print model into a fuel system model, a steam system model, a ventilation system model, etc., and further divided each model into several sub-models based on responsiveness. By subdividing, the sampling period according to the response time can be selected for each sub-model.

〔Example〕

Embodiments of the present invention will be described below with reference to the drawings. FIG. 2 is a block diagram showing the overall configuration of this control system.

In FIG. 2, the operation signal of the plant 100 is input to the state estimation unit 102 of the control device 101, and the state estimation value is output by this and the operation signal U1 of the plant 100. The state estimating unit 102 uses, for example, a Kalman filter described in Japanese Patent Laid-Open No. 57-16719, and is configured based on a plant model. The predicted value of this state is calculated by repeatedly calculating the predicted value in the prediction calculation unit 103 using the same plant model as that used in the state estimation unit. The predicted value and the target value r are compared with each other, and the control calculation unit 104 performs the control calculation to perform the control in advance.
Here, in the calculation of the predicted value in the prediction calculation unit 103, if the prediction time is long, the number of repetitions increases and the calculation time becomes long. Therefore, when the model scale becomes large, the load factor of the computer becomes high. However, the predicted time is proportional to the response time of the plant, so it cannot be shortened. In the case of a boiler, for example, the plant is divided into several sub-plants such as a steam generating part and a superheating part, and the response time is different for each sub-plant.

FIG. 1 is a block diagram showing a boiler plant model obtained by dividing N sub-plants. That is, the plant is 10
If sub-plant of 0 is a plant with a long response time and sub-plant 2 is a short plant,
For the sub-plant 1, an accurate prediction signal can be obtained even if the sampling period is lengthened (about 10 times the normal value) when the operation signal U1 is stable. That is, since it is possible to roughen the step of repeated calculation, it is possible to shorten the execution time of the prediction calculation. Plant 1 '
Is a system with a short response, the sampling is made short, and U1 shown by a chain line delayed by T _{D with} respect to the operation signal U1 is output as shown in FIG. 1 (b). This delay in T _D is not a problem as explained above even if the sampling of the plant 1 is lengthened. In the plant 2, since the response is fast, the step cannot be lengthened as described above.

Now, based on the above basic matters, an example in which one embodiment of the present invention is applied to a thermal power plant will be described.

First, the schematic configuration of the thermal power plant will be described with reference to FIG. In the figure, 81 is a boiler, 82 is a turbine, 83 is a generator, 84 is a water supply pump, 85 is a spray valve, and 86.
Is a fuel valve, 87 is a forced draft fan, and 88 is a gas recirculation fan. This is classified into four systems, that is, a combustion process 89, a steam process 90, an LNG gas process 91, and a ventilation process 92. FIG. 6 is a configuration diagram showing the overall configuration of a thermal power plant. In the figure, 301 is an air preheater for preheating combustion air with combustion exhaust gas, and 302 is a burner part, which is a system for adjusting the air-fuel ratio at each stage to perform denitration in the furnace. 303 is a W / B inlet air damper that adjusts the combustion air amount of each burner stage. 304 is a GM gas damper that adjusts the amount of combustion exhaust gas injected into the combustion air. A primary gas damper 305 adjusts the amount of combustion exhaust gas directly injected into the burner section. 306 is a condenser, 307 is a low-pressure feed water heater, 308
Is a deaerator, 309 is a water supply valve, 310 is a high-pressure feed water heater, 311 is an evaporator, 312 is a primary superheater, 313 is a first stage desuperheater, 314 is a secondary superheater, and 315 is a second stage. Desuperheater, 316 is a third superheater, 31
7 is a reheater.

FIG. 7 is a control block diagram of the plant automatic control system. In the figure, 201 is a master controller, 202 is a steam process system controller, 203 is a combustion process controller, and 205 is a ventilation process controller. These 201
~ 205 is a system level controller.

206 is a main turbine speed control controller, 207 is a feed water pump control controller, 208 is a secondary SH spray control controller, 209 is a primary SH spray control controller, and 210 is n.
A burner fuel flow rate controller, 211 is a p-burner fuel flow rate controller, 212 is a controller for performing air / gas flow rate control and burner control for each burner stage, 213 is a forced draft fan control controller, and 214 is a gas recirculation control controller. .

These 206 to 214 are device controllers. Adder 50
Is a boiler input command in which the plant load command from the central power supply station is corrected by the deviation of the main steam pressure, and is given to each system controller 202-205.

A function generator 215 is programmed to generate a feedwater flow rate command from a boiler input command that is an output of 50. A subtracter 216 compares the feed water flow rate of 66 with a command value and gives the deviation to a proportional-plus-integral calculator 217. The output of the calculator 217 is the feed water pump flow rate command, and the load distribution control circuit 218
Is distributed to each water supply pump control controller 207.

A function generator 219 programs the setting of the main steam temperature from the output boiler input command of the adder. twenty two
Reference numeral 0 denotes a subtractor, which compares the main steam temperature 52 with the set value and gives the deviation to the proportional-plus-integral calculator 221.

222 is for programming the set value of the outlet temperature of the second stage desuperheater from the boiler input command. Reference numeral 223 denotes an adder, which is a second stage stacker outlet temperature setting corrected from the main steam temperature deviation and is given to the desuperheater outlet temperature controller 208.

A function generator 224 programs the setting of the secondary SH outlet temperature from the boiler input command. 225 is a circuit that balances the spray amounts of the first and second stages by correcting the set value of the secondary SH outlet temperature from the correction amount of the second stage desuperheater outlet temperature due to the deviation of the main steam temperature. 226 is the secondary SH outlet temperature, which is compared with the set value by the subtractor of 227, and the deviation is given to the proportional-plus-integral calculator 228. Reference numeral 229 is a function generator that programs the setting of the outlet temperature of the first stage weight reducer from the boiler input command. Reference numeral 230 denotes an adder, which creates a first stage desuperheater outlet temperature setting corrected from the deviation of the secondary SH outlet temperature, and supplies it to the desuperheater outlet temperature controller 209.

231 is a function generator that programs a fuel flow rate command from a boiler input command. Reference numeral 233 is a circuit for correcting the constant play control from the correction amount of the set value of the outlet temperature of the first stage desuperheater.

Reference numeral 234 is a circuit for distributing the fuel command between the M burner and the P burner. Reference numeral 235 is a subtractor, and the generator 73 compares the fuel flow rate of the M burner with the command value, and the proportional-plus-integral calculator 236 makes a command to the fuel flow rate controller 210 of the M burner.

A subtractor 237 compares the command values of the P burner fuel flow rate from the generator 75, and the proportional-plus-integral calculator 238 makes a command to the P-burner fuel flow rate controller.

239 is a function generator that programs the air flow rate command from the boiler input command. 240 is exhaust gas O from the boiler input command
₂ A function generator that programs the set values of the concentration. 241
Is a subtracter, which compares the exhaust gas O ₂ concentration (58) with a set value, inputs the proportional value into the proportional-integral calculator 242, and corrects the air flow rate command value by the correction circuit 243. 244 is a subtracter, which compares the total air flow rate (63) with the command value and inputs it to the proportional integrator 245 to create an air flow rate correction value for each burner stage,
It is given to the controller that controls the air and gas flow rates and burner control for each burner stage of step 2. Reference numeral 247 is a circuit for obtaining the optimum number and pattern of burners from the boiler input command and controlling the number of burners at each stage. Reference numeral 248 is a circuit for preventing an imbalance between the air amount and the fuel when the burners are extinguished.

A function generator 249 programs the setting value of the exit draft of the forced draft fan from the boiler input command. 250 is a subtracter, which compares the set value with the draft draft fan outlet (100a), creates a command of the draft fan fan blade by the proportional-plus-integral calculator 251 and sends the push draft fan controller via the load distribution circuit 252. Give a command to 213.

253 is a function generator that programs the set value of the draft gas recirculation fan outlet from the boiler input command. 254 is a subtractor, which compares the set value with the gas circulation fan outlet draft 1060, creates a command for the gas recirculation fan inlet damper with the proportional-plus-integral calculator 255, and supplies the gas recirculation fan controller via the load distribution circuit 256. Give command to 214.

Here, it is necessary to improve the controllability of the main steam temperature control that causes the operation to be limited due to the fluctuation of the process signal at the time of start / stop and load change. That is, for the main steam temperature control system having a long time constant, the desuperheater spray amount and the fuel flow rate may be manipulated prior to the fluctuation of the steam temperature.
Therefore, the future value of the main steam temperature is predicted, and the operation signal is output based on this predicted value. The change of the main steam temperature due to the operation of the fuel valve and the spray valve is based on the change of the operation signal.
The flow rate changes with a short time constant, and the main steam temperature changes due to the change in the flow rate. That is, in FIG. 6, the change in the SH spray flow rate due to the operation of the SH spray valve 85 is represented by the operating end model 1'in FIG. 3 (a). This operating end model is generally represented by dead time and first-order delay. The change in fuel due to the operation of the fuel valves 86a and 86b is represented by the operation model 1 in FIG. 3 (a). Further, as can be seen from FIG. 3 (), the main steam temperature, that is, the inlet temperature of the turbine 2 is mainly determined by the fuel flow rate and the SH spray flow rate, so these relationships are expressed by the plant model 1. The plant model 1 can be represented by, for example, a physical model 7 of the secondary and tertiary superheaters 24,316. The time relationship of the signals of each part is shown in FIG. 3 (b). From the above, the operating end model is calculated at a fast sampling cycle, and the prediction calculation in the plant model 1 is performed when the fuel flow rate and SH spray flow rate are sufficiently stable. However, since this prediction calculation has a long time constant,
This makes it possible to roughen the steps of repeated calculation and calculate the predicted value in a short time.

The time relationship of the above model calculation will be described with reference to FIG. In FIG. 8, C ₁ is the operating end model 1, C _{2 in} FIG.
The operating end model 1 ', C ₃ shows the model calculation timing of plant model 1. FIG. 8 (a) shows that the load factor of the computer is high because all model calculations are performed in the same sampling cycle in the conventional example. Figure 8 (b) is an embodiment according to the present invention, the operating end model output in four sampling converged, for performing the operations of the plant model 1 using the output, T ₂ sampling period from T ₁ It shows that the load factor can be greatly extended and the load factor can be greatly reduced.

On the other hand, the gas O ₂ signal is used as an index to maintain stable combustion and efficiency, but it rapidly changes depending on the ratio of fuel and air amount, and the signal fluctuation greatly depends on the state of the furnace. The estimation process is performed to accurately grasp

The gas O ₂ signal is produced by the combustion process 89 of FIG. That is, the plant model 2 in FIG. 4 simulates the combustion process 9 and is mainly determined by the fuel flow rate and air flow rate signals. Since the response of the plant model 2 is short, it is not necessary to predict for a long time like the prediction of the main steam temperature, and the number of repeated calculations can be small. Therefore, it is not necessary to set the sampling period particularly long.

The predicted signals of the main steam temperature and the gas O ₂ signal calculated above are used for the main steam temperature 52 and the gas O ₂ signal 58 in FIG. 8 in an actual control system.

It is possible to similarly divide the turbine and the water supply system into sun plants, select a sampling cycle according to the response time, and prevent the load on the entire computer from increasing.

Further, as described above, the model can be divided into individual microcontrollers for storing each model in order to perform prediction. That is, in the control system shown in FIG. 7, the steam process controller 202 has a main steam temperature prediction model, and the combustion process controller 203 has a predictive model.
By storing a prediction model of gas O ₂ and performing a prediction calculation for each, a control system with high processability can be realized. In this embodiment, the plant 1'in FIG. 1 is assigned to the operating end model and the plant 1 is assigned to the plant model. However, the plant 1'is not necessarily limited to the operating end, and a process with a quicker response than the plant 1 is used. It is the corresponding part.

〔The invention's effect〕

As described above, according to the present invention, since the model of the entire thermal power plant is divided into the fuel system model, the steam system model, the ventilation system model, etc., the signal competition between the systems is reduced, The system can be simplified.

In addition, since the prediction calculation of the slow response submodel is executed after the prediction calculation of the fast response submodel ends, the calculation time can be shortened and accurate prediction calculation can be performed in a short time. The optimum sampling period can be selected according to the response time for each sub-model. As a result, there is no need to prepare any hardware for high-speed processing, and the economic effect is great.

[Brief description of drawings]

FIG. 1 is a diagram showing a model division configuration example according to the present invention, and FIG.
FIG. 5 is a block diagram shown for explaining the overall flow of the control device, FIGS. 3 and 4 are diagrams showing a model configuration example, and FIG.
FIG. 6 is a diagram showing a schematic configuration of a thermal power plant, FIG. 6 is a diagram showing an overall configuration of a thermal power plant, FIG. 7 is a block diagram showing a plant control device, and FIG. 8 is an explanatory diagram shown for explaining its operation. Is. 1,2,…, N …… Plant model with slow response, 1 ′, 2 ′,…, N ′ …… Plant model with fast response.

Claims (1)

[Claims] 1. A thermal power plant automatic control system for controlling a thermal power plant according to a prediction signal obtained by incorporating a plurality of operation signals, control signals, and measurement signals into a plant model and calculating the plant model, wherein the plant model is , A fuel system model, a steam system model, a ventilation system model, etc., and each of the divided models is subdivided into a sub-model with a fast response and a sub-model with a slow response, and the sub-model with a fast response. The thermal power plant automatic control device is characterized in that the sub-model having a slow response is subjected to the prediction calculation after the prediction calculation is performed.