Operation support device, operation support method, and program

Abstract

To present an appropriate medicine injection rate.SOLUTION: An operation support device is provided with: a medicine injection rate plan setting unit that, on the basis of first information indicating a medicine injection rate according to the quality of raw water and second information indicating the transition of the quality of the raw water, sets a plan for the transition of the medicine injection rate; and an information generation unit that generates information indicating a post-correction plan for the transition of the medicine injection rate, obtained by correcting the plan for the transition of the medicine injection rate so that the quality of treated water obtained after the injection of medicine to the raw water satisfies a predetermined water quality standard and the cost for a water treatment process is reduced.SELECTED DRAWING: Figure 3

Description

Technical Field

[0001] Embodiments of the present invention relate to a driving support device, a driving support method, and a program.

Background Art

[0002] In a water purification plant, a raw water intake well, a chemical mixing tank, a flocculation tank, a sedimentation tank, etc. are provided for a water treatment process in which various treatments such as injecting chemicals into the raw water (water to be treated) flowing in from a river or the like are performed. Since it takes several hours from the inflow of the water to be treated until all the necessary treatments are completed, water quality management assuming the water quality state until several hours later is carried out.

[0003] In the above water quality management, the chemical injection rate of the chemicals (for example, flocculants, pH adjusters, etc.) injected into the water to be treated is generally determined based on the know-how such as the knowledge and experience of an operation manager who is proficient in the water treatment process.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Patent Document 2

Patent Document 3

Summary of the Invention

Problems to be Solved by the Invention

[0005] Even if the chemical injection rate of the chemicals injected into the water to be treated is determined based on the know-how such as the knowledge and experience of a skilled operation manager, it is not easy to optimize the water quality of the treated water obtained through the water treatment process. For example, the turbidity of the treated water may become higher than expected several hours later. Also, even if the turbidity can be reduced, the cost of chemicals such as flocculants may increase more than expected.

[0006] The problem to be solved by the invention is to provide an operation support device, an operation support method, and a program that can present an appropriate chemical injection rate.

Means for Solving the Problem

[0007] The operation support device according to the embodiment includes a chemical injection rate plan setting unit that sets a plan for the transition of the chemical injection rate based on first information indicating the chemical injection rate corresponding to the water quality of the raw water and second information indicating the transition of the water quality of the raw water, and an information generation unit that generates information indicating a plan for the transition of the chemical injection rate after correcting the plan for the transition of the chemical injection rate so that the water quality of the treated water obtained after injecting the chemical into the raw water satisfies a predetermined water quality standard while reducing the cost of the water treatment process.

Brief Description of the Drawings

[0008]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

Embodiments for Carrying Out the Invention

[0009] Hereinafter, embodiments will be described with reference to the drawings.

[0010] (Configuration of the System) FIG. 1 shows an example of the configuration of an entire water treatment system including an operation support device according to an embodiment.

[0011] The water treatment system shown in FIG. 1 is applied to a water purification plant and includes a pipe 1, an operation support device 101, a chemical injection device 102, a raw water quality meter 103, a raw water flow meter 104, a treated water quality meter 105, and the like.

[0012] The pipe 1 receives raw water from a river or the like as water to be treated. The pipe 1 supplies the raw water to a well for raw water (described later) or the like for a water treatment process 10 that performs various treatments such as injecting chemicals into the raw water.

[0013] The operation support device 101 acquires weather information indicating the weather, such as temperature, precipitation, and weather, from a weather information institution outside the water purification plant.

[0014] In addition, the operation support device 101 acquires various information including raw water quality information indicating the measured value of the quality of raw water (raw water quality), raw water flow rate information indicating the measured value of the flow rate of raw water, process information indicating the measured value of the quality of treated water (treated water quality) obtained through the water treatment process 10, and weather information from the chemical injection device 102, the raw water quality meter 103, the raw water flow meter 104, and an external institution. The operation support device 101 presents the acquired various information to the operation manager through the display unit, and uses these various information to predict the future water quality of the treated water obtained by injecting a predetermined chemical into the raw water and the cost of the water treatment process 10, and presents each prediction result to the operation manager through the display unit. The cost of the water treatment process 10 to be predicted includes at least the cost of the chemical, and may also include the cost of sludge disposal and the cost of filtration cleaning, etc.

[0015] In addition, when the operation support device 101 is designated a chemical injection rate for a predetermined chemical with reference to the various information presented from the operation support device 101 by the operation manager, the operation support device 101 transmits information indicating the designated chemical injection rate to the chemical injection device 102. The chemical injection device 102 injects the chemical into the raw water according to the designated chemical injection rate by a chemical injection pump (not shown) in the chemical injection device 102.

[0016] The raw water quality meter 103 measures the odor, colority, turbidity, hydrogen ion concentration index (pH), residual chlorine, water temperature, etc. of the raw water before being treated in the water treatment process 10, and supplies the raw water quality information indicating those measured values to the operation support device 101.

[0017] The raw water flow meter 104 measures the flow rate of the raw water before being treated in the water treatment process 10, and supplies the raw water flow rate information indicating the measured value to the operation support device 101.

[0018] The treated water quality meter 105 measures the odor, colority, turbidity, pH, residual chlorine concentration, water temperature, etc. at a plurality of points for the treated water treated in the water treatment process 10, and supplies the process information indicating those measured values to the operation support device 101.

[0019] Note that the driving support device 101 and the chemical injection device 102 may be realized as a single computer or as individual computers. Further, some or all of the respective functions of the driving support device 101 and the chemical injection device 102 may be realized as a program executed by a processor such as a central processing unit provided in one or more computers.

[0020] (Configuration related to the water treatment process 10) Fig. 2 shows an example of the configuration related to the water treatment process 10.

[0021] In Fig. 2, as an example of the configuration related to the water treatment process 10, a receiving well 11, a chemical mixing tank 12, a floc formation tank 13, a sedimentation tank 14, etc. are provided.

[0022] The receiving well 11 receives raw water (water to be treated) and stabilizes it as incoming water. In this receiving well 11, powdered activated carbon may be injected into the water to be treated. In that case, the chemical injection device 102 performs a powdered activated carbon injection process of injecting powdered activated carbon into the water to be treated. When the powdered activated carbon injection process is performed, the powdered activated carbon injected into the water to be treated adsorbs odor substances and dissolved organic substances contained in the raw water. The water to be treated that has undergone the adsorption process in the receiving well 11 is led to the chemical mixing tank 12.

[0023] The chemical mixing tank 12 receives the water to be treated sent from the receiving well 11. In this chemical mixing tank 12, a flocculant is injected into the water to be treated. That is, the chemical injection device 102 performs a flocculant injection process of injecting a flocculant into the water to be treated. The flocculant injected into the water to be treated flocculates suspended substances (turbidity) such as clay, bacteria, and algae contained in the water to be treated and the powdered activated carbon injected in the receiving well 11, and generates fine flocs. The water to be treated into which the flocculant has been injected in the chemical mixing tank 12 is led to the floc formation tank 13.

[0024] The flocculation formation tank 13 receives the water to be treated sent from the chemical mixing tank 12. In this flocculation formation tank 13, larger and heavier flocs are formed from the flocs generated by the injection of the flocculant. The water to be treated in which the larger and heavier flocs are formed is led to the sedimentation tank 14.

[0025] The sedimentation tank 14 receives the water to be treated sent from the flocculation formation tank 13. In this sedimentation tank 14, the flocs settle, and the treated water after the flocs settle flows out from the outlet. The treated water flowing out from the outlet of the sedimentation tank 14 becomes the measurement target of the treated water quality meter 105.

[0026] In addition, on the downstream side of the sedimentation tank 14, a filtration tank, a water purification tank, a water distribution tank, etc. (not shown) are provided. The treated water quality meter 105 may be provided not only on the outlet side of the sedimentation tank 14 but also, for example, on the outlet side of the filtration tank.

[0027] (Configuration of the operation support device 101) FIG. 3 shows an example of the configuration of the operation support device 101 shown in FIG. 1.

[0028] The operation support device 101 shown in FIG. 3 includes a control unit 201, an operation unit 217, a communication unit 218, a storage unit 219, a display unit 220, a water quality management value database (DB) 221, and an actual value database (DB) 222.

[0029] The control unit 201, the operation unit 217, the communication unit 218, the storage unit 219, and the display unit 220 are connected to each other so as to be communicable via bus wiring.

[0030] Further, the control unit 201 is connected so as to be able to access the water quality management value database 221 and the actual value database 222.

[0031] The control unit 201 is composed of at least one processor and has, as various functions, a chemical injection rate table setting unit 210, a raw water quality scenario setting unit 211, a chemical injection rate plan setting unit 212, a water quality prediction unit 213, a cost evaluation unit 214, an optimal injection rate determination unit 215, and an information generation unit 216. These functions are realized as programs.

[0032] The operation unit 217 is a device that receives operations for an operation manager to input information.

[0033] The communication unit 218 is a device that communicates with the outside of the operation support device 101. For example, the communication unit 218 receives weather information supplied from a weather information institution and transmits it to the control unit 201, or receives raw water quality information supplied from the raw water quality meter 103, raw water flow rate information supplied from the raw water flow meter 104, and process information supplied from the treated water quality meter 105, respectively, and transmits them to the control unit 201, or transmits information indicating the chemical injection rate transmitted from the control unit 201 to the chemical injection device 102.

[0034] The storage unit 219 is a device that stores programs executed by the control unit 201, data indicating the results of processing, data used for processing, and the like. For example, individual calculation results calculated by the control unit 201 are stored in the storage unit 219 so that the control unit 201 can refer to those calculation results later.

[0035] The display unit 220 is a display device that displays information. For example, the display unit 220 displays raw water quality information, raw water flow rate information, process information, and weather information transmitted from the control unit 201, or displays information indicating the processing results of the control unit 201. For example, it displays information indicating the predicted results of the future water quality of the treated water and the predicted results of the cost of the water treatment process. Furthermore, it displays information indicating the optimal injection rate described later.

[0036] The water quality management value database 221 stores information on management values (upper limit values) indicating water quality standards that are restrictive constraints that must be observed as water quality criteria. For example, it stores information on the management value of the turbidity at the outlet of the sedimentation basin of the water treatment process 10. The management value is not necessarily fixed and may be variable. When it is variable, for example, it may be configured such that the management value changes according to the raw water quality (e.g., turbidity). In that case, the management value may be changed using a correspondence table (table) showing the correspondence between the raw water quality and the management value. The management value can be read by the control unit 201 from the water quality management value database 221.

[0037] The performance value database 222 is a database for storing measurement values (performance values) obtained from the raw water quality meter 103, the raw water flow meter 104, and the treated water quality meter 105, respectively. In the performance value database 222, past raw water quality information, past raw water flow information, past process information, past weather information, and the chemical injection rate actually adopted in the past are stored in an associated state along the time series. The information stored in the performance value database 222 is updated periodically.

[0038] (Various functions of the control unit 201) Next, each of the various functions of the control unit 201, namely, the chemical injection rate table setting unit 210, the raw water quality scenario setting unit 211, the chemical injection rate plan setting unit 212, the water quality prediction unit 213, the cost evaluation unit 214, the optimal injection rate determination unit 215, and the information generation unit 216 will be described.

[0039] In the water purification plant, various chemicals such as powdered activated carbon for removing odor substances and dissolved organic substances contained in the raw water, flocculants for removing turbidity, and oxidants for adjusting the hydrogen ion concentration index (pH value) of the water to be treated are used for injection. Here, to avoid complicating the explanation, it will be described assuming that the chemical used for injection is mainly a flocculant. Also, there are various indicators representing water quality, but here, to avoid complicating the explanation, it will be described assuming that the indicator representing water quality is mainly turbidity.

[0040] · Chemical injection rate table setting unit 210 The chemical injection rate table setting unit 210 sets a chemical injection rate list (first information) indicating the chemical injection rate corresponding to the raw water quality according to the operation of the operation unit 217 by the operation manager. The chemical injection rate list is information based on the chemical injection rate table used in the water purification plant indicating the chemical injection rate corresponding to the raw water quality. The chemical injection rate list reflects know-how such as the knowledge and experience of skilled operation managers.

[0041] Fig. 4 shows an example of the chemical injection rate list. As shown in Fig. 4, the chemical injection rate list shows the relationship between the raw water turbidity [degree] representing the turbidity of the raw water and the coagulant injection rate [mg / L] representing the injection rate of the coagulant injected into the chemical mixing tank 12. In the example of Fig. 4, the raw water turbidity [degree] is divided into each certain range, and different "coagulant injection rates [mg / L]" are assigned to each range of the raw water turbidity [degree]. As the raw water turbidity [degree] increases, the coagulant injection rate [mg / L] increases in order to further reduce the turbidity of the treated water after coagulant injection.

[0042] · Raw water quality scenario setting unit 211 The raw water quality scenario setting unit 211 sets a raw water quality scenario (second information) indicating the transition of the raw water quality over a certain period according to the operation of the operation unit 217 by the operation manager. The set raw water quality scenario is either input by the operation manager through the operation unit 217 indicating the transition of the raw water quality over a certain period, or selected from a plurality of pre-prepared raw water quality scenarios.

[0043] Fig. 5 shows an example of a graph representing the raw water quality scenario. The horizontal axis of the graph in Fig. 5 represents time (time), and the vertical axis represents the raw water turbidity [degree]. Fig. 5 shows an example of setting the transition of the raw water turbidity for 24 hours after the present.

[0044] In Fig. 5, the raw water turbidity is plotted every hour, and the change in the raw water turbidity is represented by connecting the plots with lines. However, the method of representing the change in the raw water turbidity is not limited to this example. For example, the plots may be represented at intervals shorter than one hour, or the change in the raw water turbidity may be continuously represented only by lines without using plots.

[0045] As shown in Fig. 5, the raw water turbidity 501 steadily changes at 2 [NTU] in the first half (12 hours) of 24 hours, and then steadily changes at 8 [NTU] in the second half (12 hours).

[0046] Note that the time range of the raw water quality scenario is not limited to 24 hours. It may be 12 hours, 36 hours, 72 hours, etc., and the time range may be changed as appropriate. In addition, the setting of the raw water quality scenario may be performed not only for turbidity but also for other indicators such as odor, chromaticity, pH, and water temperature.

[0047] · Chemical injection rate planning and setting unit 212 The chemical injection rate planning and setting unit 212 sets a plan for the change in the chemical injection rate (hereinafter sometimes referred to as the "planned injection rate") based on the chemical injection rate list (first information) set by the chemical injection rate table setting unit 210 and the raw water quality scenario (second information) set by the raw water quality scenario setting unit 211.

[0048] Fig. 6 shows an example of a graph representing the plan for the change in the chemical injection rate. The horizontal axis of the graph in Fig. 6 represents time (time), and the vertical axis represents the coagulant injection rate [mg / L] indicating the injection rate of the coagulant.

[0049] In Fig. 6, the chemical injection rate is plotted every hour, and the change in the chemical injection rate is represented by connecting the plots with lines. However, the method of representing the change in the chemical injection rate is not limited to this example. For example, the plots may be represented at intervals shorter than one hour, or the change in the chemical injection rate may be continuously represented only by lines without using plots.

[0050] Figure 6 shows an example of setting a plan for the transition of the flocculant injection rate for the next 24 hours based on the chemical injection rate list shown in Figure 4 and the raw water quality scenario shown in Figure 5.

[0051] As shown in Figure 6, the flocculant injection rate 601 is stable at 16 [mg / L] for the first half (12 hours) of 24 hours and then stable at 20 [mg / L] for the second half (12 hours).

[0052] Specifically, in the first half shown in Figure 5, the raw water turbidity is "2 [NTU]", and the raw water turbidity "2 [NTU]" belongs to the range of raw water turbidity "<6 [NTU]" in Figure 4. Since the corresponding flocculant injection rate is "16 [mg / L]", the flocculant injection rate 601 is set to "16 [mg / L]" in the first half shown in Figure 6.

[0053] Also, in the second half shown in Figure 5, the raw water turbidity is "8 [NTU]", and the raw water turbidity "8 [NTU]" belongs to the range of raw water turbidity "≥6 [NTU] and <12 [NTU]" in Figure 4. Since the corresponding flocculant injection rate is "20 [mg / L]", the flocculant injection rate 601 is set to "20 [mg / L]" in the second half shown in Figure 6.

[0054] The plan for the transition of the chemical injection rate (flocculant injection rate 601) shown in Figure 6 is corrected (optimized) through the processes of the water quality prediction unit 213, cost evaluation unit 214, and optimal injection rate determination unit 215 described later, and the corrected chemical injection rate (flocculant injection rate 601') is generated.

[0055] Figure 7 shows an example of a graph representing the plan for the transition of the corrected chemical injection rate. The horizontal axis of the graph in Figure 6 represents time (time), and the vertical axis represents the flocculant injection rate [mg / L] indicating the injection rate of the flocculant.

[0056] As shown in FIG. 7, the flocculant injection rate 601' is stable at 5 [mg / L] in the first half (12 hours) of 24 hours and then stable at 22 [mg / L] in the second half (12 hours). The reason why the flocculant injection rate 601 shown in FIG. 6 is corrected to the flocculant injection rate 601' as shown in FIG. 7 will become clear from the explanation described later.

[0057] · Water quality prediction unit 213 The water quality prediction unit 213 predicts, for each raw water quality, specifically for each raw water turbidity (for example, for each of the time zones of the raw water turbidity of "2 [NTU]" and the raw water turbidity of "8 [NTU]" shown in FIG. 5), the water quality of the treated water that changes according to the chemical injection rate (for example, the turbidity [NTU] at the outlet of the sedimentation tank that changes according to the flocculant injection rate [mg / L] shown in FIG. 6), using the above-described raw water quality information, raw water flow rate information, process information, and weather information, by a predetermined water quality prediction model. As the water quality prediction model, a model that performs machine learning based on measurement data analysis, a model based on static analysis of a physical / chemical model, etc. may be applied. The raw water quality information, raw water flow rate information, process information, and weather information are used in the learning process in the water quality prediction model. Note that, for water quality prediction, not all of the raw water quality information, raw water flow rate information, process information, and weather information are necessarily used. For example, it is also possible to perform the prediction without using the raw water flow rate information. Specific examples of water quality prediction will be described later.

[0058] In the example of FIG. 5, since the value of the raw water turbidity 501 is in a stable state, it is easy to perform turbidity prediction for each raw water quality. However, when the value of the raw water turbidity 501 is not stable and fluctuates up and down, it may be difficult to perform turbidity prediction for each raw water quality. In such a case, instead of simply dividing the time into a small number of time zones such as two as in FIG. 5, the raw water turbidity 501 can be decomposed into more stable values by dividing the time so that more short time zones are formed in the places where the up and down fluctuations of the raw water turbidity 501 are larger. By doing so, it becomes easier to perform turbidity prediction for each raw water quality.

[0059] · Cost evaluation unit 214 The cost evaluation unit 214 evaluates the cost of the water treatment process 10 based on the water quality prediction result by the water quality prediction unit 213. As described above, the cost includes at least the chemical cost, and may also include the sludge disposal cost and the filtration cleaning cost.

[0060] For each raw water quality, specifically for each raw water turbidity (for example, for each time period of the raw water turbidity of "2 [NTU]" and the raw water turbidity of "8 [NTU]" shown in FIG. 5), the cost evaluation unit 214 predicts the degree of increase or decrease in cost (for example, the cost increase ratio [%] according to the coagulant injection rate [mg / L]) that changes according to the chemical injection rate by a predetermined calculation, and uses the predicted result to evaluate the cost for the water quality prediction result by the water quality prediction unit 213. For the cost evaluation process including the prediction of the cost increase ratio, etc., a model for performing machine learning may be used. Specific examples of cost evaluation will be described later. · Optimal injection rate determination unit 215 The optimal injection rate determination unit 215 determines the chemical injection rate that reduces the cost on the condition that the water quality of the treated water does not exceed the water quality standard for each raw water quality, specifically for each raw water turbidity, using the water quality prediction result of the water quality prediction unit 213 and the cost evaluation result of the cost evaluation unit 214. Specific examples of the optimal injection rate determination will be described later. · Information generation unit 216 The information generation unit 216 generates information indicating the modified plan of the transition of the chemical injection rate so that the cost of the water treatment process 10 is reduced while the water quality of the treated water obtained after the chemical injection into the raw water meets the predetermined water quality standard. For example, when there is a chemical injection rate in the plan of the transition of the chemical injection rate where the water quality of the treated water is below the water quality standard, the information generation unit 216 modifies the chemical injection rate so that the cost is reduced on the condition that the water quality of the treated water does not exceed the water quality standard. Also, when there is a chemical injection rate in the plan of the transition of the chemical injection rate where the water quality of the treated water exceeds the water quality standard, the information generation unit 216 modifies the chemical injection rate so that the water quality of the treated water is below the water quality standard. Specific examples of information generation will be described later.

[0061] (Specific Example of Processing) Hereinafter, specific examples of the processing performed by the water quality prediction unit 213, the cost evaluation unit 214, the optimal injection rate determination unit 215, and the information generation unit 216 will be described.

[0062] The water quality prediction model used by the water quality prediction unit 213 will be described as a model (turbidity prediction model) that predicts the turbidity at the outlet of the sedimentation tank in this example. However, it may be configured as a model that predicts not only the turbidity at the outlet of the sedimentation tank of the treated water but also the turbidity at the outlet of the filter tank of the treated water. Also, as the chemical to be injected, the model may be configured to include not only the flocculant but also the pH adjuster and the like. Further, as a function associated with the prediction model, it may be configured to calculate the chemical cost according to how much chemical such as the flocculant is used. In this case, it may be configured to calculate the cost including not only the chemical cost but also the sludge disposal cost and the filter washing cost.

[0063] The water quality prediction unit 213 predicts, using the raw water quality information, the process information, and the weather information, the turbidity [degree] at the outlet of the sedimentation tank that changes according to the flocculant injection rate [mg / L] for each of the time zones of the raw water turbidity of "2 [degree]" and the time zone of the raw water turbidity of "8 [degree]" shown in FIG. 5 by means of the turbidity prediction model. The cost evaluation unit 214 performs a cost evaluation on the result predicted by the turbidity prediction model (the turbidity [degree] at the outlet of the sedimentation tank that changes according to the flocculant injection rate [mg / L]).

[0064] FIG. 8 shows an example of a graph in which the turbidity [degree] at the outlet of the sedimentation tank and the cost increase ratio [%] that change according to the injection rate (planned injection rate) [mg / L] of the flocculant are obtained for the first half part (the time zone with the raw water turbidity of "2 [degree]") in FIG. 5. Also, FIG. 9 shows an example of a graph in which the turbidity [degree] at the outlet of the sedimentation tank and the cost increase ratio [%] that change according to the injection rate (planned injection rate) [mg / L] of the flocculant are obtained for the second half part (the time zone with the raw water turbidity of "8 [degree]") in FIG. 5.

[0065] In each of the graphs of FIGS. 8 and 9, the horizontal axis represents the injection rate (planned injection rate) of the flocculant [mg / L], and the left vertical axis corresponds to the plots represented by solid circles and represents the turbidity of the sedimentation tank outlet [degree]. The right vertical axis corresponds to the plots represented by triangles and represents the percentage increase in cost with respect to the planned injection rate [%].

[0066] In each of the graphs of FIGS. 8 and 9, for the turbidity of the sedimentation tank outlet 701 and 801 predicted by the turbidity prediction model, from 1 "mg / L" to 60 "mg / L" on the horizontal axis, for each 1 "mg / L", they are represented by plots, and by connecting the plots with lines, the transition of the turbidity of the sedimentation tank outlet is expressed. For the percentage increase in cost 702 and 802 with respect to the planned injection rate, from 1 "mg / L" to 60 "mg / L" on the horizontal axis, for each 1 "mg / L", they are represented by plots, and by connecting the plots with lines, the transition of the percentage increase in cost with respect to the planned injection rate is expressed.

[0067] In the graph of FIG. 8, the origin (0 point) of the percentage increase in cost with respect to the planned injection rate [%] corresponds to the point where the cost increase ratio 702 intersects with the planned injection rate "16 [mg / L]" (the value of the planned injection rate in the "first half" of the graph of FIG. 7). In the graph of FIG. 9, the origin (0 point) of the percentage increase in cost with respect to the planned injection rate [%] corresponds to the point where the cost increase ratio 802 intersects with the planned injection rate "20 [mg / L]" (the value of the planned injection rate in the "second half" of the graph of FIG. 7).

[0068] Also, in each of the graphs of FIGS. 8 and 9, it is assumed that "0.43 [degree]" is given as the control value (upper limit value) for the turbidity of the sedimentation tank outlet 701 and 801.

[0069] In the "first half" of the graph of FIG. 5, the raw water turbidity is 2 [degree] and the value is relatively low. In that case, as shown in the graph of FIG. 8, the turbidity prediction model shows that as the flocculant injection rate increases from zero, the turbidity of the sedimentation tank outlet 701 decreases significantly, and when the flocculant injection rate further increases (when too much flocculant is injected), the turbidity of the sedimentation tank outlet 701 increases due to the influence of the flocculant itself.

[0070] In the "first half" of the graph in Figure 6, the injection rate of the flocculant (planned injection rate) is 16 [mg / L]. In this case, as can be seen from the graph in Figure 8, the turbidity at the sedimentation tank outlet corresponding to 16 [mg / L] has a margin with respect to the control value of "0.43 [NTU]", and even if the flocculant injection rate is further reduced to 5 [mg / L], the control value can be satisfied.

[0071] That is, the response of the turbidity prediction model indicates that the control value of "0.43 [NTU]" can be satisfied even when the flocculant injection rate is 5 [mg / L]. Therefore, by changing the flocculant injection rate in the "first half" of the graph in Figure 6 from 16 [mg / L] to 5 [mg / L] as in the "first half" of the graph in Figure 7, the cost increase ratio 702 in the graph in Figure 8 decreases, and a cost reduction of 16% can be achieved. Thus, the optimal injection rate determination unit 215 determines the flocculant injection rate of "5 [mg / L]" shown in the "first half" of the graph in Figure 7 as the optimal injection rate.

[0072] In the "second half" of the graph in Figure 5, the raw water turbidity is 8 [NTU], which is relatively high. In that case, as shown in the graph in Figure 9, the turbidity prediction model shows that as the flocculant injection rate increases from zero, the turbidity 801 at the sedimentation tank outlet gradually decreases, and even if the flocculant injection rate further increases, it shows a response that it no longer easily decreases.

[0073] In the "second half" of the graph in Figure 6, the injection rate of the flocculant (planned injection rate) is 20 [mg / L]. In this case, as can be seen from the graph in Figure 9, the turbidity at the sedimentation tank outlet corresponding to 20 [mg / L] exceeds the control value of "0.43 [NTU]" and does not satisfy the control value.

[0074] That is, the response of the turbidity prediction model indicates that the turbidity at the outlet of the sedimentation tank corresponding to 20 [mg / L] does not meet the management value of "0.43 [NTU]". Therefore, by changing the coagulant injection rate in the "latter half" of the graph in Fig. 6 from 20 [mg / L] to 22 [mg / L] as in the "latter half" of the graph in Fig. 7, the cost increase ratio 802 in the graph in Fig. 9 increases, resulting in a 1.2% cost increase. However, the turbidity at the outlet of the sedimentation tank becomes a value that meets the management value, and the coagulant injection rate can be set to an appropriate value. Therefore, the optimal injection rate determination unit 215 determines the coagulant injection rate of "22 [mg / L]" shown in the "latter half" of the graph in Fig. 7 as the optimal injection rate.

[0075] In this way, by changing the coagulant injection rate in the "first half" of the graph in Fig. 6 from 16 [mg / L] to 5 [mg / L] as in the "first half" of the graph in Fig. 7, a 16% cost reduction is achieved. On the other hand, by changing the coagulant injection rate in the "latter half" of the graph in Fig. 6 from 20 [mg / L] to 22 [mg / L] as in the "latter half" of the graph in Fig. 7, a 1.2% cost increase occurs.

[0076] Considering that the cost becomes 84% due to a 16% cost reduction and the cost becomes 101.2% due to a 1.2% cost increase, it can be seen from the result of the calculation of "(84 + 101.2) / 2 = 92.6 [%]" that a total cost reduction effect of 7.4% can be obtained.

[0077] Based on the determination result of the optimal injection rate determination unit 215, the information generation unit 216 generates information indicating the transition plan of the coagulant injection rate 601', that is, the optimal injection rate, as shown in the graph in Fig. 7, and presents it to the operation manager through the display unit 220.

[0078] In addition to presenting information indicating the transition plan of the optimal injection rate as shown in the graph in Fig. 7 to the operation manager, a coagulant injection rate that falls within a certain change with respect to the original planned injection rate as shown in the graph in Fig. 6 may be presented to the operation manager as a candidate solution.

[0079] For example, in advance, the operation unit 217 inputs and sets constraint information that the coagulant injection rate is within ±5 [mg / L] with respect to the original planned injection rate. In the "first half" of 24 hours, the coagulant injection rate is 11 [mg / L] and the cost is reduced by 5%. In the "second half" of 24 hours, information showing that the coagulant injection rate is 22 [mg / L] and the cost is increased by 1.2% may be presented.

[0080] Note that the above ±5 [mg / L] is an example. For the purpose of suppressing the deviation with respect to the original planned injection rate, a method such as selecting a solution from among the candidates of solutions within a predetermined percentage from the planned injection rate may be adopted. Further, when the optimal injection rate deviates from the planned injection rate by a certain value or more or a certain number of times or more, a display may be made to notify the operation manager to prompt an update of the chemical injection table.

[0081] (Operation example) Next, with reference to the flowchart of FIG. 10, an example of the main operation by the control unit 201 of the operation support device 101 will be described.

[0082] First, the chemical injection rate table setting unit 210 sets a chemical injection rate list (first information) indicating the chemical injection rate according to the quality of the raw water in response to the operation of the operation unit 217 by the operation manager (step S1).

[0083] Next, the raw water quality scenario setting unit 211 sets a raw water quality scenario (second information) indicating the transition of the raw water quality over a certain period in response to the operation of the operation unit 217 by the operation manager (step S2).

[0084] Next, the chemical injection rate plan setting unit 212 sets a plan for the transition of the chemical injection rate (planned injection rate) based on the chemical injection rate list (first information) set by the chemical injection rate table setting unit 210 and the raw water quality scenario (second information) set by the raw water quality scenario setting unit 211 (step S3).

[0085] The control unit 201 reads a management value (upper limit value) indicating a water quality standard that is a constraint to be observed as a water quality standard for the treatment for each raw water turbidity shown below (steps S5 to S9) (step S4).

[0086] From the start of the treatment for each raw water turbidity (step S5) to the end of the treatment (step S9), water quality prediction (step S6), cost evaluation (step S7), and determination of the optimal injection rate (step S8) are performed using a prediction model.

[0087] The water quality prediction unit 213 predicts, for each turbidity of the raw water, the turbidity of the treated water that changes according to the chemical injection rate (for example, the turbidity [NTU] at the outlet of the sedimentation tank that changes according to the coagulant injection rate [mg / L]) using a predetermined water quality prediction model (step S6).

[0088] Next, the cost evaluation unit 214 predicts, for each turbidity of the raw water, the degree of increase or decrease in cost that changes according to the chemical injection rate (for example, the cost increase ratio [%] that changes according to the coagulant injection rate [mg / L]) by a predetermined calculation, and uses the predicted result to evaluate the cost with respect to the water quality prediction result by the water quality prediction unit 213 (step S7).

[0089] Next, the optimal injection rate determination unit 215 determines, for each turbidity of the raw water, the chemical injection rate that reduces the cost on the condition that the water quality of the treated water does not exceed the water quality standard, using the water quality prediction result of the water quality prediction unit 213 and the cost evaluation result of the cost evaluation unit 214 (step S8).

[0090] Finally, the information generation unit 216 generates information indicating the modified plan of the transition of the chemical injection rate so that the cost of the water treatment process 10 is reduced while the water quality of the treated water obtained after injecting the chemical into the raw water satisfies a predetermined water quality standard (step S10).

[0091] As described in detail above, according to the embodiment, an appropriate chemical injection rate can be presented.

[0092] For example, based on the knowledge and experience of a skilled operation manager, etc., the water quality in the future can be predicted based on the actually applied chemical injection rate table, and further, based on the water quality prediction result, information that can reduce costs and optimize the chemical injection rate can be presented to the operation manager.

[0093] Although several embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the gist of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are included in the invention described in the claims and the equivalent scope thereof.

Description of Reference Numerals

[0094] 1... pipe, 10... water treatment process, 101... operation support device, 102... chemical injection device, 103... raw water quality meter, 104... raw water flow meter, 105... treated water quality meter, 201... control unit, 210... chemical injection rate table setting unit, 211... raw water quality scenario setting unit, 212... chemical injection rate plan setting unit, 213... water quality prediction unit, 214... cost evaluation unit, 215... optimal injection rate determination unit, 216... information generation unit, 217... operation unit, 218... communication unit, 219... storage unit, 220... display unit, 221... water quality management value database, 222... performance value database.

Claims

1. A chemical injection rate planning setting unit that sets a plan for the transition of the chemical injection rate based on first information indicating a chemical injection rate according to the quality of raw water and second information indicating the transition of the quality of the raw water; An information generation unit that generates information indicating a plan for the transition of the corrected chemical injection rate obtained by correcting the plan for the transition of the chemical injection rate so that the quality of the treated water obtained after injecting the chemical into the raw water satisfies a predetermined water quality standard while reducing the cost of the water treatment process; An operation support device comprising:

2. The information generation unit: When there is a chemical injection rate at which the quality of the treated water is below the water quality standard in the plan for the transition of the chemical injection rate, the chemical injection rate is corrected so that the cost is reduced on the condition that the quality of the treated water does not exceed the water quality standard, When there is a chemical injection rate at which the quality of the treated water exceeds the water quality standard in the plan for the transition of the chemical injection rate, the chemical injection rate is corrected so that the quality of the treated water is below the water quality standard. The operation support device according to claim 1.

3. The first information is information based on a chemical injection rate table used at a water purification plant as indicating a chemical injection rate according to the quality of the raw water. The operation support device according to claim 1.

4. The second information is information selected from information input by an operation manager or a plurality of pre-prepared information as indicating the transition of the quality of the raw water. The operation support device according to claim 1.

5. Further comprising a water quality prediction unit that predicts the quality of the treated water that changes according to the chemical injection rate for each quality of the raw water. The operation support device according to claim 1.

6. The water quality prediction unit: Predict the water quality of the treated water with respect to the chemical injection rate using the measured value of the raw water quality, the measured value of the treated water quality, and information indicating the weather. The operation support device according to claim 5.

7. Further comprising a cost evaluation unit that evaluates the cost with respect to the water quality prediction result by the water quality prediction unit. The operation support device according to claim 6.

8. Using the water quality prediction result of the water quality prediction unit and the cost evaluation result of the cost evaluation unit, for each water quality of the raw water, determine the chemical injection rate that reduces the cost on the condition that the water quality of the treated water does not exceed the water quality standard. Further comprising an optimal injection rate determination unit. The operation support device according to claim 7.

9. Set the plan for the transition of the chemical injection rate based on the first information indicating the chemical injection rate corresponding to the water quality of the raw water and the second information indicating the transition of the water quality of the raw water by the chemical injection rate planning and setting unit. Generate information indicating the plan for the transition of the corrected chemical injection rate in which the plan for the transition of the chemical injection rate is corrected so that the water quality of the treated water obtained after injecting the chemical into the raw water satisfies a predetermined water quality standard while reducing the cost of the water treatment process by the information generation unit. Including an operation support method.

10. On one or more computers, Based on the first information indicating the chemical injection rate corresponding to the water quality of the raw water and the second information indicating the transition of the water quality of the raw water, a function of setting the plan for the transition of the chemical injection rate. A function of generating information indicating the plan for the transition of the corrected chemical injection rate in which the plan for the transition of the chemical injection rate is corrected so that the water quality of the treated water obtained after injecting the chemical into the raw water satisfies a predetermined water quality standard while reducing the cost of the water treatment process. A program for realizing.

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