Water quality control device, water quality control method and water quality control program

Abstract

To provide a water quality control device capable of accurately predicting the residual chlorine concentration in a water channel distant from a chlorine injection point. The water quality control device (30) includes a change amount data acquisition unit (32) that acquires data pairs of amounts of change in the injection chlorine concentration and amounts of change in the control-target residual chlorine concentration, a model generation unit (34) that generates a model showing the relationship between the amount of change in the injection chlorine concentration and the amount of change in the control-target residual chlorine concentration based on the acquired data, a change amount prediction unit (43) that predicts the amount of change in the control-target residual chlorine concentration using the generated model, and an optimal chlorine injection concentration prediction unit (40) that calculates an optimal chlorine injection concentration based on the predicted amount of change in the control-target residual chlorine concentration.

Description

[Technical Field]

[0001] The present invention relates to a water quality control device, a water quality control method, and a water quality control program, and more particularly to a water quality control device, a water quality control method, and a water quality control program used in seawater utilization plants such as power plants. [Background technology]

[0002] As a countermeasure against biofilms and other attached organisms such as barnacles and mussels that attach to the seawater systems of plants that use seawater, such as thermal and nuclear power plants, there is a technology in which chlorine or sodium hypochlorite (hereinafter referred to as "chlorine") generated by electrolyzing seawater is injected into the water intake.

[0003] In relation to the above-mentioned technology, Patent Document 1 discloses a water quality monitoring system for monitoring chlorine concentration or the like, which estimates parameters that cannot be measured by a sensor based on measurement parameters successively acquired from the sensor. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2020-121241 Summary of the Invention [Problem to be solved by the invention]

[0005] Conventional techniques such as the technique disclosed in Patent Document 1 have the problem that it is difficult to accurately predict the residual chlorine concentration in a waterway that is distant from the chlorine injection point.

[0006] The present invention has been made in consideration of the above-mentioned problems, and aims to provide a water quality control device, a water quality control method, and a water quality control program that can accurately predict the residual chlorine concentration in a waterway away from a chlorine injection point. [Means for solving the problem]

[0007] <1> A water quality control device for a seawater utilization plant, comprising: A change amount data acquisition unit that acquires data of a set of change amounts of the injected chlorine concentration and change amounts of the control target residual chlorine concentration; A model generating unit that generates a model showing the relationship between the amount of change in the injection chlorine concentration and the amount of change in the control target residual chlorine concentration based on the acquired data; a change amount prediction unit that predicts a change amount of the control target residual chlorine concentration using the generated model; an optimal chlorine injection rate prediction unit that calculates an optimal chlorine injection concentration based on the predicted change in the control target residual chlorine concentration, Water quality control equipment.

[0008] <2> The set of data of the change amount of the injection chlorine concentration and the change amount of the control target residual chlorine concentration is Data obtained continuously for more than one year, Data obtained within one month prior to calculating the optimal chlorine injection concentration; <1> Water quality control equipment.

[0009] <3> The model is a linear model. <1> or <2> The water quality control device according to claim 1.

[0010] <4> The water quality control system method of the present invention is a water quality control system method for a seawater utilization plant, A change amount data acquisition step for acquiring a set of data of a change amount of the injection chlorine concentration and a change amount of the control target residual chlorine concentration; a model generation step of generating a model showing the relationship between the amount of change in the injection chlorine concentration and the amount of change in the control target residual chlorine concentration based on the acquired data; a change prediction step of predicting a change in residual chlorine concentration using the generated model; and an optimum chlorine injection rate prediction step of calculating an optimum chlorine injection concentration based on the predicted change in residual chlorine concentration.

[0011] <5> The water quality management program of the present invention is a water quality management program for a seawater utilization plant, A change amount data acquisition step for acquiring a set of data of a change amount of the injection chlorine concentration and a change amount of the control target residual chlorine concentration; a model generation step of generating a model showing the relationship between the amount of change in the injection chlorine concentration and the amount of change in the control target residual chlorine concentration based on the acquired data; a change amount prediction step of predicting a change amount of the control target residual chlorine concentration using the generated model; and an optimum chlorine injection rate prediction step of calculating an optimum chlorine injection concentration based on the predicted amount of change in the control target residual chlorine concentration. [Effects of the Invention]

[0012] According to the present invention, it is possible to provide a water quality control device, a water quality control method, and a water quality control program that can accurately predict the chlorine concentration in a water channel away from a chlorine injection point. [Brief explanation of the drawings]

[0013] [Figure 1] FIG. 1 is a diagram showing the overall configuration of a seawater utilization plant according to this embodiment and the chlorine concentration at each point in the seawater utilization plant 1. [Figure 2] FIG. 2 shows the results of verifying the residual chlorine concentration change prediction model. [Figure 3] FIG. 3 is a functional block diagram of the water quality control device according to the embodiment of the present invention. [Figure 4] FIG. 4 is a block diagram showing an example of data flow when determining the optimum chlorine injection rate. [Figure 5] FIG. 5 is a diagram showing a screen of prediction software including a residual chlorine concentration change prediction model. [Figure 6] FIG. 6 is a flowchart showing the process flow of the water quality control method according to the embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0014] (Seawater utilization plant) An embodiment of the present invention will be described with reference to the drawings. FIG. 1 is a diagram showing the overall configuration of a seawater utilization plant 1 of this embodiment and the chlorine concentration and the like at various points in the seawater utilization plant 1. The block diagram indicated by arrow 101 in FIG. 1 shows the overall configuration of the seawater utilization plant 1. Hereinafter, this block diagram will be referred to as block diagram 101. The graph indicated by arrow 102 in FIG. 1 shows the chlorine concentration and the like at various points in the seawater utilization plant 1. Hereinafter, this graph will be referred to as graph 102. The horizontal axes of block diagram 101 and graph 102 indicate the same point in the seawater utilization plant 1.

[0015] As shown in block diagram 101, the seawater utilization plant 1 includes a condenser 2, a water intake channel 11, a water discharge channel 12, and a water quality control device 30. The condenser 2 is a device that cools steam that has passed through a steam turbine or the like and turns it back into water. The water intake channel 11 is a water channel that sends seawater from the sea 300 to the condenser 2. The water discharge channel 12 is a water channel that sends seawater from the condenser 2 to the sea 300.

[0016] The condenser 2 takes in seawater from the sea 300 via a water intake channel 11 and uses it as cooling water. The condenser 2 cools the steam with the taken-in seawater. The condenser 2 discharges the seawater cooling water after being used for cooling into the sea 300 via a water discharge channel 12.

[0017] (Chlorine injection point) Chlorine is injected into the taken-in seawater. The point where chlorine is injected into the taken-in seawater is called a chlorine injection point 121. The chlorine injection point 121 is located near the sea 300 in the intake channel 11.

[0018] (Water quality control device) The water quality control device 30 is a device that controls the water quality in the seawater utilization plant 1, such as determining the amount of chlorine to be injected.

[0019] (chlorine concentration) The horizontal axis of graph 102 indicates the location in seawater utilization plant 1. The vertical axis of graph 102 indicates the residual chlorine concentration. As shown in graph 102, the residual chlorine concentration 141 in the waterway decreases with increasing distance from chlorine injection point 121. The section indicated by arrow 161 in Figure 1 is the range 161 where measures against attached organisms are particularly necessary in managing the waterway.

[0020] (Measures against fouling organisms) In order to perform a desired level of antifouling measures in the area 161 where antifouling measures are required, it is preferable that the residual chlorine concentration 141 in the water channel at the condenser inlet point 122 is, for example, 0.04 mg / L or more.

[0021] (Agreed value) From the viewpoint of preventing seawater pollution, an agreed value 142 is usually set for the residual chlorine concentration 141 in the waterway at the discharge point 123. When the agreed value 142 is set, the residual chlorine concentration 141 in the waterway at the discharge point 123 must be kept below the agreed value 142.

[0022] With conventional technology, it is difficult to achieve the desired biofouling control measures without incurring a large amount of man-hours while still complying with the agreed-upon values, because it is difficult to accurately predict the residual chlorine concentration 141 in the waterway.

[0023] (Prediction of residual chlorine concentration) The water quality control device 30 of this embodiment can accurately predict the residual chlorine concentration 141 in the water channel at the condenser inlet point 122. In the following description, the residual chlorine concentration 141 in the water channel at the condenser inlet point 122 is referred to as the residual chlorine concentration to be controlled. If a connecting well is provided at the condenser inlet point 122, the residual chlorine concentration in the connecting well is referred to as the residual chlorine concentration to be controlled.

[0024] When predicting the control target residual chlorine concentration, the water quality control device 30 of this embodiment first predicts the amount of change in the control target residual chlorine concentration, and then predicts the amount of change in the chlorine injection concentration using the amount of change.

[0025] The amount of change in the control target residual chlorine concentration is calculated as follows. Change in the controlled residual chlorine concentration = f (change in the injected chlorine concentration, water temperature, current injected chlorine concentration) f denotes the residual chlorine concentration change amount prediction model f. The residual chlorine concentration change amount prediction model f is a model that predicts the amount of change in the residual chlorine concentration of the control target.

[0026] The data to be input to the residual chlorine concentration change prediction model f are the "amount of change in the injection chlorine concentration in chlorine injection," "water temperature when water is taken from the sea 300," and "current residual chlorine concentration at the condenser inlet point 122." When these data are input, the residual chlorine concentration change prediction model f outputs a predicted value of the residual chlorine concentration. The water temperature when water is taken from the sea 300 is called the intake water temperature.

[0027] (base data) The residual chlorine concentration change prediction model f can be generated based on data on past changes in the injected chlorine concentration and changes in the residual chlorine concentration. This data is called base data.

[0028] The residual chlorine concentration change prediction model f can be, for example, a linear model or a GAM (GAM: Generalized Additive Model). The linear model and the GAM are generated based on base data.

[0029] The base data may be data previously acquired in the seawater utilization plant 1 equipped with the water quality control device 30. The base data is preferably data acquired continuously for one year or more. By using data acquired continuously for one year or more as the base data, it is possible to generate a residual chlorine concentration change prediction model f that takes into account factors that repeatedly change throughout the seasons, such as temperature changes.

[0030] In the seawater utilization plant 1, the injection chlorine concentration at the chlorine injection point 121 and the residual chlorine concentration 141 in the water channel at the condenser inlet point 122 are usually continuously monitored. In the continuous monitoring, the residual chlorine concentration 141 in the water channel is obtained, for example, every 30 seconds. From the injection chlorine concentration at the chlorine injection point 121, the amount of change in the injection chlorine concentration at the chlorine injection point 121 can be calculated. From the residual chlorine concentration 141 in the water channel at the condenser inlet point 122, the amount of change in the residual chlorine concentration 141 in the water channel at the condenser inlet point 122 can be calculated. Data on the amount of change calculated in this way for one year or more is used as base data.

[0031] (latest data) Furthermore, in generating the residual chlorine concentration change prediction model f, the most recent data may be taken into consideration in addition to the base data. The most recent data may be, for example, data acquired within the most recent month, or more specifically, data from the most recent week. It is possible that the situation of the seawater utilization plant 1 has changed since the situation when the base data was acquired. Therefore, the residual chlorine concentration change prediction model f is corrected based on the most recent intake water temperature, injection chlorine concentration, residual chlorine concentration, etc. This allows the residual chlorine concentration change prediction model f to be a model that conforms to the current situation.

[0032] (Elapsed time) When acquiring the base data and the most recent data, the residual chlorine concentration can be the residual chlorine concentration after a predetermined time has elapsed since the chlorine injection. This is because a predetermined time must elapse after the chlorine injection before the effects of the injection can be seen. The predetermined time is preferably a short time such as 10 minutes, but several hours later. More specifically, it can be, for example, six hours later. This allows for a more accurate residual chlorine concentration change prediction model f to be obtained.

[0033] (Exclusion of singular values) Furthermore, when acquiring the base data and the most recent data, data for which the change in the injected chlorine concentration is greater than a predetermined value may be excluded. When the change in the injected chlorine concentration is large, the behavior of the change in the residual chlorine concentration may be different from when the change in the injected chlorine concentration is not large. Therefore, when the change in the injected chlorine concentration is larger than the normal practical range, that data is excluded from the data used to generate the residual chlorine concentration change prediction model f. This makes it possible to generate a residual chlorine concentration change prediction model f that is more in line with the actual situation. When the change in the injected chlorine concentration is large, it refers to when the change is, for example, ±0.25 mg / L or more.

[0034] (Verification of the residual chlorine concentration change prediction model) The verification results of the residual chlorine concentration change prediction model f will be described with reference to Fig. 2. Fig. 2 is a graph showing the actual measurement data of the change in residual chlorine concentration and the predicted values ​​output by the residual chlorine concentration change prediction model f. The horizontal axis of the graph in Fig. 2 represents the date. The vertical axis of the graph in Fig. 2 represents the change in residual chlorine concentration (ppm).

[0035] Figure 2 shows the actual measured values ​​of the change in the residual chlorine concentration to be controlled and the predicted values ​​output by residual chlorine concentration change prediction model f for one month. The base data used to create residual chlorine concentration change prediction model f was data from the most recent year. The plots on the graph are daily average values. The residual chlorine concentration to be controlled indicates the residual chlorine concentration in the connecting well.

[0036] As shown in Figure 2, the predicted values ​​output by residual chlorine concentration change prediction model f closely match the actual measured values. It was confirmed that the predicted values ​​output by residual chlorine concentration change prediction model f almost reproduce the actual measured values. Furthermore, the linear model showed higher reproducibility than the GAM.

[0037] (Functional block of water quality control device) The water quality control device 30 of this embodiment will be described with reference to Fig. 3. Fig. 3 is a functional block diagram of the water quality control device 30 of this embodiment. As shown in Fig. 3, the water quality control device 30 includes a change amount data acquisition unit 32, a residual chlorine concentration change amount prediction model generation unit 34, an optimal chlorine dosing rate prediction unit 40, and an input / output unit 36. The optimal chlorine dosing rate prediction unit 40 includes a control target residual chlorine concentration change amount prediction unit 42.

[0038] The change amount data acquisition unit 32 is a unit that acquires base data and the most recent data. Specifically, the change amount data acquisition unit 32 acquires the injection chlorine concentration at the chlorine injection point 121 and the residual chlorine concentration 141 in the water channel at the condenser inlet point 122. At this time, the change amount data acquisition unit 32 acquires data in the form of a set of the amount of change in the injection chlorine concentration and the amount of change in the residual chlorine concentration in the water channel when the change is made. The change amount data acquisition unit 32 includes, for example, a sensor provided at the chlorine injection point 121. This sensor is a sensor that measures the concentration of chlorine to be injected. The change amount data acquisition unit 32 also includes, for example, a sensor provided in a connecting well. This sensor is a sensor that measures the residual chlorine concentration in the water channel.

[0039] The residual chlorine concentration change amount prediction model generating unit 34 (model generating unit) is a part that generates a residual chlorine concentration change amount prediction model f. The residual chlorine concentration change amount prediction model generating unit 34 acquires base data, the most recent data, etc. The residual chlorine concentration change amount prediction model generating unit 34 generates a residual chlorine concentration change amount prediction model f by analyzing or learning the acquired data. The generated residual chlorine concentration change amount prediction model f can be a linear model, a GAM, etc.

[0040] The optimal chlorine injection rate prediction unit 40 is a unit that determines the chlorine injection rate that should be injected to achieve a target residual chlorine concentration. This chlorine injection rate is called the optimal chlorine injection rate. The optimal chlorine injection rate prediction unit 40 includes a residual chlorine concentration change amount prediction unit 42. The optimal chlorine injection rate prediction unit 40 predicts the optimal chlorine injection rate based on the amount of change in residual chlorine concentration predicted by the residual chlorine concentration change amount prediction unit 42 and the corresponding amount of change in the injected chlorine concentration. Note that the optimal chlorine injection rate prediction unit 40 may predict the optimal chlorine injection rate using a model such as an optimal chlorine injection rate prediction model. The optimal chlorine injection rate prediction model will be described later with reference to FIG. 4.

[0041] The residual chlorine concentration change prediction unit 42 (change prediction unit) predicts the amount of change in residual chlorine concentration required to achieve a target residual chlorine concentration and the amount of change in the injected chlorine concentration required to achieve that amount of change in residual chlorine concentration. This prediction is performed using a residual chlorine concentration change prediction model f.

[0042] The input / output unit 36 ​​is a section for inputting data required to determine the optimum chlorine injection rate and for outputting the determined optimum chlorine injection rate.

[0043] (Example of input and output to the model) An example of data input and output when determining the optimum chlorine injection rate will be described with reference to Fig. 4. Fig. 4 is a block diagram showing an example of data flow when determining the optimum chlorine injection rate. Fig. 4 illustrates a case where the residual chlorine concentration in the connecting well is set as the target value for the residual chlorine concentration.

[0044] The optimum chlorine injection rate is determined using an optimum chlorine injection rate prediction model, which takes the target value of the residual chlorine concentration, the current residual chlorine concentration, and other input items and outputs the optimum chlorine injection rate.

[0045] Specifically, the input items are the target value Y of the residual chlorine concentration in the connecting well and the current value. The current values ​​are the current residual chlorine concentration in the connecting well and the current intake water temperature. The input items may be entered into the optimal chlorine injection rate prediction model by, for example, an operator of the water quality control device 30.

[0046] Additionally, data on the residual chlorine concentration in the connecting well, intake water temperature, and injection chlorine concentration for the past week or so should be prepared in advance. These data may be input in advance into the optimal chlorine injection rate prediction model or the residual chlorine concentration change prediction model. Alternatively, they may be input together with the current values ​​when calculating the optimal chlorine injection rate.

[0047] The residual chlorine concentration in the connecting well may be measured using a continuous residual chlorine concentration analyzer. The intake water temperature and injection chlorine concentration can be obtained from the plant data management system. These data, for example, every 30 seconds, can be input into the optimal chlorine injection rate prediction model or the residual chlorine concentration change prediction model in the form of a CSV file.

[0048] The optimum chlorine injection rate prediction model predicts the optimum chlorine injection concentration (mg / L) based on the residual chlorine concentration change amount predicted by the residual chlorine concentration change prediction model and the corresponding change amount of the injection chlorine concentration.

[0049] (prediction software) Prediction software including a residual chlorine concentration change prediction model will be described with reference to Fig. 5. Fig. 5 is a diagram showing a screen of the prediction software. In the example shown in Fig. 5, the prediction software constitutes part of a chlorine injection prediction system. The prediction software shown in Fig. 5 uses a linear model as the residual chlorine concentration change prediction model f. The residual chlorine concentration change prediction model f used by the prediction software is not limited to a linear model, and for example, a GAM can also be used.

[0050] The operation of using prediction software to find the optimal chlorine injection concentration can be done in the following three steps (1) to (3): (1) enter the parameters required for prediction, (2) click the prediction execution (linear model) button, and (3) the optimal chlorine injection concentration for achieving the target residual chlorine concentration is displayed. Figure 5 shows the display areas corresponding to each step as (1) to (3).

[0051] The prediction software determines the injection concentration at the point where the input target value (B) of the junction well residual chlorine concentration intersects with the prediction formula (A) based on the linear model as the optimal injection concentration. In the example shown in Figure 5, the current optimal injection concentration is 0.42 mg / L. In addition to the optimal injection concentration, the prediction software may also display the estimated error range (C) of the predicted value. The estimated error range of the predicted value is the expected daily fluctuation range of the residual chlorine concentration when chlorine is injected at the optimal injection concentration. The estimated error range of the predicted value can be calculated using statistical methods based on the learning data used to generate the prediction model.

[0052] In this way, the prediction software can determine the optimum chlorine injection concentration with simple operations. The prediction software described above can also be operated as a standalone program. By operating the prediction software as a standalone program, information leakage can be prevented.

[0053] (Water quality management method) The processing flow of the water quality management method of this embodiment will be described with reference to Figure 6. Figure 6 is a flow diagram showing the processing flow of the water quality management method of this embodiment. In the following description and drawings, S1 means step 1. The same applies to S2 and subsequent steps.

[0054] (S1) S1 is a change amount data acquisition step in which the change amount data acquisition unit 32 acquires base data and the most recent data.

[0055] (S2) S2 is a residual chlorine concentration change amount prediction model generation step (model generation step). In S2, the residual chlorine concentration change amount prediction model generation unit 34 generates a residual chlorine concentration change amount prediction model f based on the data acquired in S1 and the like.

[0056] (S3) S3 is the most recent data input step. In S3, as described with reference to Fig. 4, residual chlorine concentration data from the most recent week or so is input. This improves the prediction accuracy of the residual chlorine concentration change prediction model f.

[0057] (S4) S4 is a step of inputting the target and current values ​​of the residual chlorine concentration. In S4, the target and current values ​​of the residual chlorine concentration are input to, for example, prediction software. The current values ​​are the current residual chlorine concentration value and the current intake water temperature value, as described with reference to FIG.

[0058] (S5) S5 is a residual chlorine concentration change prediction step, in which the residual chlorine concentration change prediction model f is used to predict the residual chlorine concentration change.

[0059] (S6) S6 is an optimal chlorine injection rate prediction step, in which the optimal chlorine injection rate is predicted taking into consideration the target and current values ​​of the residual chlorine concentration input in S4 as well as the residual chlorine concentration change amount predicted in S5.

[0060] (S7) S7 is an output value setting step. In S7, the optimum chlorine injection rate predicted in S6 is set, for example, in the water quality control device 30. Specifically, the optimum chlorine injection rate is set, for example, in an electrolysis device that generates chlorine. The step ends at S7. Note that the order of the above steps is an example. The order of the steps can be changed as appropriate.

[0061] (Water Quality Management Program) The water quality control method using the water quality control device is realized by software. When realized by software, the programs constituting this software are installed on a computer that serves as the water quality control device. The programs may be recorded on removable media and distributed to users, or may be distributed by being downloaded to the user's computer via a network. Furthermore, these programs may be provided to the user's computer as a web service via a network without being downloaded.

[0062] The above describes an embodiment of the present invention. The present invention is not limited to the above embodiment, and various modifications, variations, and combinations are possible. For example, the change amount data acquisition unit 32 and the residual chlorine concentration change amount prediction model generation unit 34 may be provided separately from the water quality control device 30.

[0063] When the injection concentration is predicted from the residual chlorine concentration to be controlled as in the past, the injection concentration may be overestimated. This is thought to be due to the small contribution of changes in the injection concentration to the residual chlorine concentration. In contrast, the present disclosure predicts the residual chlorine concentration using the relationship between the amount of change in the injection chlorine concentration and the amount of change in the residual chlorine concentration. Therefore, it is possible to accurately predict the residual chlorine concentration in waterways far from the chlorine injection point. [Explanation of symbols]

[0064] 1 Seawater utilization plant 2 Condenser 11 Intake channel 12 Spillway 30 Water quality control equipment 32 Change amount data acquisition section 34 Residual chlorine concentration change prediction model generation unit 36 Input / output section 40 Optimal chlorine injection rate prediction section 42 Control target residual chlorine concentration change amount prediction unit 42 Residual chlorine concentration change prediction unit 121 Chlorine injection point 122 Condenser inlet point 123 Outlet Point 141 Residual chlorine concentration in waterways 142 Agreement value 300 Sea

Claims

1. A water quality control device for a seawater utilization plant, comprising: A change amount data acquisition unit that acquires data of a set of change amounts of the injected chlorine concentration and change amounts of the control target residual chlorine concentration; A model generating unit that generates a model showing the relationship between the amount of change in the injection chlorine concentration and the amount of change in the control target residual chlorine concentration based on the acquired data; a change amount prediction unit that predicts a change amount of the control target residual chlorine concentration using the generated model; an optimal chlorine injection rate prediction unit that calculates an optimal chlorine injection concentration based on the predicted change in the control target residual chlorine concentration, Water quality control equipment.

2. The set of data of the change amount of the injection chlorine concentration and the change amount of the control target residual chlorine concentration is Data obtained continuously for more than one year, Data obtained within one month prior to calculating the optimal chlorine injection concentration. The water quality control device according to claim 1.

3. The model is a linear model. The water quality control device according to claim 1 or 2.

4. A water quality control device method for a seawater utilization plant, comprising: A change amount data acquisition step for acquiring a set of data of a change amount of the injection chlorine concentration and a change amount of the control target residual chlorine concentration; a model generation step of generating a model showing the relationship between the amount of change in the injection chlorine concentration and the amount of change in the control target residual chlorine concentration based on the acquired data; a change prediction step of predicting a change in residual chlorine concentration using the generated model; an optimal chlorine injection rate prediction step of calculating an optimal chlorine injection concentration based on the predicted change in residual chlorine concentration, Water quality control equipment method.

5. 1. A water quality management program for a seawater utilization plant, comprising: A change amount data acquisition step for acquiring a set of data of a change amount of the injection chlorine concentration and a change amount of the control target residual chlorine concentration; a model generation step of generating a model showing the relationship between the amount of change in the injection chlorine concentration and the amount of change in the control target residual chlorine concentration based on the acquired data; a change amount prediction step of predicting a change amount of the control target residual chlorine concentration using the generated model; an optimal chlorine injection rate prediction step of calculating an optimal chlorine injection concentration based on the predicted change amount of the control target residual chlorine concentration, Water quality management program.

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