JPH06222191A - Operating method based on prediction of plant state - Google Patents

Abstract

PURPOSE:To shorten the time required for predicting a plant state in re- executing a predictive simulation. CONSTITUTION:A diagnostic device 4 constantly monitors a true plant to recognize any abnormal state of the true plant. When the diagnostic device recognizes an abnormal state and an operator requests that a predictive simulator 1 is re-operated for prediction, data in the predictive simulator 1 at the time of request of predictive re-operation are read from a data file 9 for re-executing prediction, and are used as initial values for the predictive simulator 1. Operation of the predictive simulator 1 is restarted based on the initial values.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a nuclear power plant, and more particularly to a plant state predictive operation method for providing operational support information for improving the operational reliability of the nuclear power plant.

[0002]

2. Description of the Related Art FIG. 8 is a functional block diagram showing a functional configuration of a conventional plant state predicting apparatus. Reference numeral 1 is a predictive simulator for operating a plant physical model at high speed, and 2 is an initial value for the predictive simulator 1. A real-time simulator 3 for collecting data, a data collecting device 3 for collecting real process data and operation data of a plant, and 4 a data collecting device 3
A diagnostic device for diagnosing an abnormal state that has occurred in a plant based on the actual plant data collected by 5 is a data file for recording internal data of the real-time simulator 2 as initial values for prediction simulation of the prediction simulator 1, and 6 is this An initial value selection device for selecting an optimum initial value from the data file 5, 7 is a device for displaying a plant state prediction calculation result, and 8 is an device for interfacing with a plant operator.

Next, the operation of this conventional plant state predicting apparatus will be described. The real-time simulator 2 always executes the plant simulation operation in real time, simulates the behavior of the real plant in real time, and periodically records the internal data thereof in the data file 5. Further, when an operation is performed by an operator in the actual plant, the information by the operation is input from the data collection device 3 and sequentially reflected in the calculation of the simulation. On the other hand, the diagnosis device 4 executes a plant abnormality diagnosis based on the actual process data input from the data collection device 3, and when an abnormality occurs, determines the cause of the abnormality, its scale, and the time of occurrence. When an abnormality is diagnosed by the diagnosis device 4, the initial value selection device 6 selects the initial value closest to the abnormality occurrence time identified by the diagnosis device 4 from the data file 5 as the initial value for prediction simulation. The prediction simulator 1 predicts the future state of the plant by executing a plant simulation operation at a speed of real time or more based on this initial value, and displays the prediction simulation result on the display device 7 as driving support information for the operator. . The operator instructs the prediction simulator 1 via the interface device 8 to execute, suspend, and re-execute the plant state prediction simulation.

Next, the operation of the conventional plant state predicting apparatus will be described in more detail. The real-time simulator 2 and the prediction simulator 1 execute a simulation calculation at every constant period Δt, and calculate a plant state change in a certain constant time width. When this time width is tC, (1) real-time simulator; tC = Δt (2) prediction simulator; tC << Δt. The prediction simulator 1 is capable of high-speed calculation,
The above relationships (1) and (2) can be realized. The behavior of a normal plant is, for example, when the horizontal axis is time t (real time scale) as shown in FIG. 9, at time t = −t1, t1, t2, t3 when the current time is t = 0. The plant state (voltage, current, etc.) at the time is V (-t1), V (t1), V
(T2) and V (t3). Here (1),
As the condition (2), the real-time simulator 2 and the prediction simulator 1 are operated in the time series state shown in FIG.
That is, the prediction simulator 1 can predict future states by high-speed calculation of tC << Δt, and the calculation up to the state of t = t3 is completed at the time of t = t1.

Generally, in order to perform a plant simulation at high speed, (a) initial value data including observable physical quantities is required. (B) When simulating a plant abnormality, it is necessary to set the event of this plant abnormality as a boundary condition. (C) It is necessary to set manual operation by an operator as a boundary condition. There are constraints. FIG. 7 shows a state change when an abnormal state occurs by operating the real-time simulator and the prediction simulator with these constraint conditions set. First, the plant is tracked by constantly operating the real-time simulator to obtain the initial values that are essential for simulation. That is, the internal data is periodically saved and used as the initial value data file. Next, it is assumed that an abnormal state occurs at t = 0 when the plant output is 100%. Since it takes time to determine an event in this abnormal state (here, t4 is required until t = tB), it is impossible to set the boundary conditions necessary for the real-time simulator in a timely manner. In the time simulation), the actual plant data (actual plant data) and the operating state after t = 0 are inconsistent with the 100% state. Then t =
The boundary condition can be set when the event can be determined at tB, but the condition setting needs to be set from t = 0 (at the time when the abnormal state occurs). Next, if the prediction execution is instructed at t = tB, the prediction simulator 1 sets the initial value file saved at t = 0 as the initial value, sets the abnormal event as the boundary condition, and executes the simulation from t = 0. Start. Since the prediction simulator 1 is capable of high-speed calculation, even if a simulation based on a past time is executed (t = 0 is t =
At t1 seconds before tB), the simulation result exceeds the real time from a certain time point (T = TN), and thereafter, the prediction simulation is performed. For example, when the prediction simulator is capable of calculating 10 times the real time (a plant state calculation of the actual time of 10 minutes is possible in the calculation time of 1 minute), the current (t
= TB) and an accident occurs 10 minutes before (t1 = 10 minutes) and the prediction simulator 1 is started, the prediction simulation starts from n minutes later. That is, (10+
If n) / 10 = n, catch up with real time after n = 10/9 minutes.

[0006]

Since the conventional plant state predicting apparatus is configured as described above, when an abnormality occurs in the plant, only the initial value at the time when the abnormal state occurs is present, so that it goes back to the past. Simulation is required. In particular, when re-running the prediction simulation after a long time has elapsed after the occurrence of an abnormality, it takes a considerable amount of time to obtain the state prediction result, and it is difficult to obtain the plant state prediction appropriately. It was
That is, when performing a predictive simulation of a plant, it is necessary to set manual operation by an operator as a boundary condition. For example, since the existence of t = tA (manual operation 1) shown in FIG. 7 is known, it is possible to set conditions in the prediction simulator 1. However, after starting the prediction simulator, for example, the existence of the manual operation 2 at time t = tC is unknown when the prediction simulator is started, and it is impossible to set conditions. Since this condition cannot be set, the values of the prediction result (prediction simulation) and the actual data (actual plant data) differ after time t = tC. Therefore, if a prediction result is to be obtained after t = tC, the prediction simulator must be restarted at t = 0 again at time t = tC.
The past tracking up to (during t5) occurred, and it took a long time to obtain the prediction result.

The present invention has been made in order to solve the above problems, and when the predictive simulation is re-executed, the predictive simulation can be executed without tracing back to the abnormal state occurrence time, and the operator manually operates. It is an object of the present invention to obtain a plant state predictive operation method capable of appropriately predicting the plant state even when the above is added.

[0008]

As shown in FIG. 1, a plant state predictive operation method according to the first aspect of the present invention is performed after an abnormal state occurs in an actual plant and the abnormal state is discriminated by a diagnostic device 4. When the operator makes a prediction restart request to the prediction simulator 1, the internal data of the prediction simulator at the time of the prediction restart request is reset as the initial value of the prediction simulator, and the prediction simulator is restarted. I did it. In the plant state predictive operation method according to the second aspect of the present invention, as shown in FIG. 3, after the abnormal state occurs in the actual plant and the abnormal state is discriminated by the diagnostic device, the operator re-executes the operation to the real-time simulator 3. When an operation request is made, the internal data of the prediction simulator 1 at the time of requesting the restart operation is reset as the initial value of the real-time simulator, and the real-time simulator is restarted. As shown in FIG. 5, the plant state predictive operation method according to the third aspect of the present invention predicts that the simulator operation is started after the abnormal state occurs in the actual plant and the abnormal state is discriminated by the diagnostic device, and the prediction is performed. After stopping the simulator 1 or the real-time simulator 2, the internal data of the prediction simulator at the time of determining the start of operation is reset as the initial value of the prediction simulator or the real-time simulator, and the prediction simulator or the real-time simulator is restarted. I did it.

[0009]

In the plant state predictive operation method according to the first aspect of the present invention, when the operator issues a predictive restart operation 1 to the predictive simulator after the diagnostic device 4 determines the abnormal state of the actual plant, the predictive restart operation is performed. The internal data of the prediction simulator at the time of operation request is reset as the initial value of the prediction simulator. And after resetting the initial value,
Restart this predictive simulator. In the plant state predictive operation method according to the second aspect of the present invention, when the operator requests the real-time simulator 3 to restart after the abnormal state of the actual plant is determined by the diagnostic device 4, The internal data of the prediction simulator 1 is reset as the initial value of the real-time simulator. Then, after resetting the initial value, the real-time simulator is restarted. In the plant state predictive operation method according to the third aspect of the present invention, after the diagnosis device 4 determines the abnormal state of the actual plant, it is determined that the operation of the simulator has started, and after the predictive simulator 1 or the real-time simulator 2 is stopped, The internal data of the prediction simulator at the time of determining the operation start is reset as the initial value of the prediction simulator or the real-time simulator. Then, after resetting the initial value, the prediction simulator or the real-time simulator is restarted.

[0010]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a functional block diagram of a plant state prediction device for explaining an embodiment (embodiment 1) of the first invention. In FIG. 1, 1 is a prediction simulator that calculates a plant physical model at high speed, and 2 is this prediction simulator 1.
A real-time simulator for creating initial values for use, 3 is a data collecting device for collecting actual process data and operation data of the plant, and 4 is an abnormality that has occurred in the plant based on the actual plant data collected by the data collecting device 3. A diagnostic device for diagnosing the state, 5 is a data file that records the internal data of the real-time simulator 2 as an initial value for the prediction simulation of the prediction simulator 1, and 9 is used when the prediction simulator 1 is re-executed. A data file to be recorded as an initial value for prediction simulation, 6 is an initial value selection device for selecting an optimal initial value from the data file 5 and the prediction re-execution data file 9, and 7 is a device for displaying the result of the state prediction calculation of the plant. , 8 is an interface where the plant operator inputs data. It is a device. FIG. 2 is a functional block diagram for explaining the plant state prediction method of the first embodiment. In the first embodiment, when the predictive simulation is re-executed, the internal data itself of the predictive simulation is the initial value file (the predictive re-execution data file 9 in FIG. 1) after the predictive activation (after t = t0 in FIG. 7). Is saved as. Therefore, at the time of re-execution of the prediction simulation, the initial value data of t = tC in FIG. 7 may be used, and the past tracking during t5 is unnecessary. In FIG. 2, the internal data is periodically output from the real-time simulator 2 to the data file 5. In addition, the initial value selection device 6
Selects the one close to t = t0 in FIG. 7 from the data file 5 at the time of the first prediction start (selected initial value 20). Further, the initial value selection device 6 selects a value close to t = tC in FIG. 7 from the prediction re-execution data file 9 when the prediction simulation is re-executed (selected initial value 20). The selected initial value 20 is saved in the prediction re-execution data file 9 via the prediction simulator 1 (d in FIG. 2).

Next, the operation of the apparatus according to the first embodiment will be described. The real-time simulator 2 always executes the plant simulation operation in real time, simulates the behavior of the real plant in real time, and periodically records the internal data thereof in the data file 5. Also, when the operation is performed by the operator in the actual plant, the information is input from the data collection device 3 and reflected in the sequential simulation calculation.
On the other hand, the diagnosis device 4 executes a plant abnormality diagnosis based on the actual process data input from the data collection device 3, and when an abnormality occurs, determines the cause of the abnormality, its scale, and the time of occurrence. When the diagnostic device 4 diagnoses an abnormality, the initial value selection device 6 selects the initial value closest to the abnormality occurrence time identified by the diagnostic device 4 from the data file 5 as the initial value for the first prediction simulation. The prediction simulator 1 starts the plant simulation calculation at a speed higher than the real time based on this initial value. Since there is a delay in the abnormality identification processing of the diagnostic device 4, the predictive simulation starts retroactively from the time of abnormality occurrence. Since the prediction simulation is executed at a speed higher than the real time, the simulation time will catch up with the current time at some point, and after this point, the future state will be a prediction simulation. From this point onward, the prediction simulator 1 periodically records the internal data in the prediction re-execution data file 9. When the operator performs a prediction re-execution operation from the interface device 8 when the actual plant behavior and the prediction state differ from each other because the manual operation is executed by the operator, the initial value selection device 6 uses the prediction re-execution data. From the file 9, the data file closest to the time when the manual operation of the operator is executed is selected as the selected initial value A for the prediction simulation, and the re-execution of the prediction simulation is started. As a result, the prediction re-execution does not have to start back to the abnormal state occurrence time, and the plant state prediction result can be immediately displayed on the display device 7 to be provided to the operator.

FIG. 3 is a functional block diagram of a plant state predicting apparatus for explaining an embodiment (Embodiment 2) of the second invention, and FIG. 4 is a functional block diagram for explaining the operation of the above apparatus. . In the first embodiment, the prediction simulator 1
Has described the case where the data is periodically recorded using the data file for prediction re-execution. However, as shown in FIG. 4, when the simulation of the prediction simulator 1 reaches the current time, the internal data of the prediction simulator 1 is transferred in real time. Output as the selected initial value A (e in FIG. 4) for the simulator 2, and the real-time simulator 2 uses this initial value to start the real-time simulation and always reflect the operation performed in the real plant in real time. Run the simulation. When the operator requests the prediction re-execution, the internal data of the real-time simulator 2 at that time can be used as the initial value for prediction re-execution, and the future state of the plant can be predicted immediately.

FIG. 5 is a functional block diagram of a plant state predicting apparatus for explaining an embodiment (Embodiment 3) of the third invention, and FIG. 6 is a flow chart for explaining the operation of the above apparatus. In the first and second embodiments, the prediction simulation is restarted when the operator requests the prediction re-execution. However, as shown in FIG. 3, the presence or absence of the manual operation by the operator is determined based on the information of the data collection device 3. By providing the determination device 11 for determining, when the determination device 11 detects the execution of the manual operation, the prediction simulation that has been executed until then is interrupted, and a command to automatically re-execute the prediction simulation is newly issued. It becomes possible to provide the plant state prediction information. Next, the operation of the determination device 11 in the device of FIG. 5 will be described. First, the determination device 11
Determines whether or not a manual operation has occurred after the predictive simulation based on the data from the data collection device 3 (step S10). If a manual operation has occurred (YES in step S10), a stop signal is output to the prediction simulator 1 (step S11), and the internal data in the prediction simulator 1 at the time when the manual operation occurs is used as a prediction re-execution data file. 9 is selected (step S12), the internal data is set to the initial value, and the simulation is started from the time when the manual operation occurs. In the third embodiment, when the manual operation occurs, the prediction simulator is stopped and the internal data selected from the prediction re-execution data file is selected as the initial value of the prediction simulator 1. However, the real-time simulator is stopped when the manual operation occurs. Then, the internal data selected from the data file for prediction re-execution may be selected as the initial value for the real-time simulator.

[0014]

As described above, according to the first aspect of the present invention, when the prediction re-operation request is made, the internal data of the prediction simulator at the time of the prediction re-operation request is reset as the initial value of the prediction simulator. Therefore, when the prediction simulation is re-executed, there is an effect that the time for predicting the plant state can be shortened. According to the second aspect of the invention, when the re-operation request is made, the internal data of the prediction simulator at the time of the re-operation request is reset as the initial value of the real-time simulator. Moreover, there is an effect that the time for predicting the state of the plant can be shortened. According to the third aspect of the present invention, after the abnormal state is determined, it is determined that the simulator is in operation, the prediction simulator or the real-time simulator is stopped, and then the internal data of the prediction simulator at the time of the operation start determination is predicted as described above. Since it is set again as the initial value of the simulator or the real-time simulator, there is an effect that the time for predicting the plant state can be shortened when the predictive simulation is re-executed.

[Brief description of drawings]

FIG. 1 is a functional block diagram of a plant state prediction device for explaining an embodiment of the first invention.

FIG. 2 is a functional block diagram for explaining the operation of the apparatus of FIG.

FIG. 3 is a functional block diagram of a plant state prediction device for explaining an embodiment of the second invention.

FIG. 4 is a functional block diagram for explaining an operation of the apparatus of FIG.

FIG. 5 is a functional block diagram of a plant state prediction device for explaining an embodiment of the third invention.

6 is a flowchart showing the operation of the determination device of FIG.

FIG. 7 is a diagram showing a plant state in time series when an abnormality occurs.

FIG. 8 is a functional block diagram showing a functional configuration of a conventional plant state prediction device.

9 is a diagram illustrating a plant state predictive operation method by the apparatus of FIG.

FIG. 10 is a diagram illustrating a plant state predictive operation method similar to FIG. 9.

[Explanation of symbols]

 1 prediction simulator 2 real-time simulator 3 data collection device 4 diagnostic device 5 data file 6 initial value selection device 7 display device 8 interface device 9 prediction re-execution data file 11 judgment device

Continuation of the front page (51) Int.Cl. ⁵ Identification code Office reference number FI technical display area // G06F 15/20 D 8724-5L

Claims (3)

[Claims] 1. A real-time simulator for simulating a current plant operating state, a predictive simulator for simulating a future plant operating state, and a diagnostic device for diagnosing an abnormal state based on collected real plant data. In a plant state prediction device that sets at least initial values including boundary conditions such as abnormal conditions and manual operations, operates a real-time simulator and a prediction simulator, and transmits the plant operation support information to the driver. When an abnormal state occurs in the, and the abnormal condition is discriminated by the diagnostic device, when the operator makes a prediction restart request to the prediction simulator, the internal data of the prediction simulator at the time of the prediction restart request is displayed. Reset it as the initial value of the above prediction simulator, and restart this prediction simulator. A plant state predictive operation method characterized by the above. 2. A real-time simulator for simulating the operating state of the plant at the present time, a predictive simulator for simulating the operating state of the plant in the future, and a diagnostic device for diagnosing an abnormal state based on the collected data of the actual plant. In a plant state prediction device that sets at least initial values including boundary conditions such as abnormal conditions and manual operations, operates a real-time simulator and a prediction simulator, and transmits the plant operation support information to the driver. After an abnormal condition occurs in the system and the diagnostic device determines the abnormal condition, when the operator requests a re-operation to the real-time simulator, the internal data of the predictive simulator at the time of the re-operation request is changed to the actual data described above. Reset it as the initial value of the time simulator and restart this real time simulator. And a plant state predictive operation method characterized by: 3. A real-time simulator for simulating the operating state of the plant at the present time, a predictive simulator for simulating the operating state of the plant in the future, and a diagnostic device for diagnosing an abnormal state based on the collected data of the actual plant. In a plant state prediction device that sets at least initial values including boundary conditions such as abnormal conditions and manual operations, operates a real-time simulator and a prediction simulator, and transmits the plant operation support information to the driver. After the abnormal state occurs in the and the abnormal state is discriminated by the diagnostic device, it is determined that the simulator starts operating, and after stopping the prediction simulator or the real-time simulator, the internal data of the prediction simulator at the time of the start determination is displayed. Reset as the initial value of the above-mentioned prediction simulator or real-time simulator, A plant state predictive operation method, characterized in that the predictive simulator or the real-time simulator is restarted.